Horticulture – Page 30 – Naturehydro Horticulture Grow

The fragile ecosystem in the Loess Plateau is associated with environmental degradation

Prices are not updated to the current year to make these results comparable to Lu et al.’s study in 2003; input and output prices have changed at different rates during the past 10 years and some prices could not be recovered from Lu et al. This assumption does not affect lessons from this study.Three SV matrices for rotation, terrace techniques and land units are created using the estimation results and shown in Tables 8, 9 and 10. These tables can be used to compare the SVs between any pair of rotation types, terracing techniques or land units. Several more detailed tables can be found in Hou for those interested. The SV matrix for the 17 cropping systems is given in Table 8. The rotation types in the first row serve as references. Each value represents a movement from the system on the horizontal axis to the system along the vertical axis. For example, SV is reduced by 465.52 RMB when switching from corn to wheat and improved by 441 RMB if moving from corn to the best system, which is the CSC rotation. A3CM and FA5MC rank second. The cropping systems with PWCM and FWPM create the lowest SV. Wheat is typically low compared to rotations. The SV matrix for three terracing techniques implies that bench terracing contributes most to SV,maceta plastico cuadrada followed by spaced terracing. The cropping systems with no terraces have the least SV when all other practices are held equal.

Not surprisingly, based on the SV matrix for five types of land units , a floodplain is efficient, while very steeply sloped land has the least value. A similar set of SE matrices reinforces the same results, but is not shown here.One of the priorities of this study is to make practical recommendations for improving sustainable agricultural practices in China’s Loess Plateau to balance economic and environmental objectives. SV is computed for different agricultural systems and recorded and organized into comparison matrices. These comparison matrices can be used to compare the relative sustainability of different crops or management practices like rotations and terracing. For example, cropping systems with potatoes or wheat typically were less sustainable than systems with alfalfa and corn. A regression was also used to specify the marginal contribution of cropping system characteristics on SV or SE. Overall, the DEA/SV analysis of Lu et al.’s 2006 potential cropping systems for the region demonstrated that, all things held equal, bench terracing contributes the most to SV. SV is reduced by 465.52 RMB when switching from corn to wheat and improved by 441 RMB if moving from corn to the best system, which is the CSC rotation. On average, SV is −1661 RMB and SE is 69%. Clearly, soil erosion could be reduced without sacrifices in income if producers switched to more efficient systems. However, these results are limited to the present data and the dimensions of sustainability that were considered. Income might be affected, for example, if a change in cropping systems leads to less diversity, and therefore more exposure to the risk of disease. In contrast to other accounting approaches that make adjustments to GDP, the DEA/SV method can be used to inform policy makers, farmers, and farm managers about the sustainability of regional natural resource management decisions.

However, a limitation in the analysis is that the sustainability values are based on simulation, rather than the sustainability of current agricultural practices . Therefore, the results should be viewed in the context of potential, rather than actual, impacts.The region concerns environmentalists, ecologists, economists, agronomists and policy makers alike. As previously stated, much of the agricultural land in the region has already been converted to trees through the Grain for Green program . However, planting land to permanent forests is an extreme conservation measure that generates little economic return to farmers . Perhaps excessive erosion has been traded in for excessive conservation. Policy makers need information and ways to compare systems if they aim to realize both strong economic and social performance with sustainable use of natural resources . Combining the DEA with the SV metric allows for customizable benchmarks that can, at least in theory, facilitate a practical comparison between agricultural land management decisions. This is due, in part, to the fact that this combined DEA/SV approach accounts for the depreciation of natural capital through soil erosion and nitrogen losses, along with human capital. Policy makers can consider trade offs between economic and environmental objectives, as well as extreme solutions that focus on just the environment or just economics. In this comparison of over 2000 possible cropping systems, switching from mono-crop corn to a corn–soybean–corn rotation would generate 441 RMB/ha in SV.

When armed with this knowledge, Chinese policy makers can take steps to educate farmers about the benefits of these trade-offs. In poor areas of China, farmers may lack knowledge about advanced cropping practices. The government also can provide financial incentives to farmers to switch from unsustainable to sustainable cropping systems by subsidizing or offering technological support.Humans have reshaped the biosphere, driving rapid evolution in the species that we exploit. Agriculture stands out as a vast human alteration of biodiversity on Earth: over 12 000 years, humans have molded hundreds of wild plant species into productive crops that cover N35% of the terrestrial habitat. Domestication is a multistaged response to human-imposed selection that progresses from the increase in frequency of desirable alleles in nearly wild populations, to the formation of cultivated populations and deliberate breeding and improvement. Breeding practices have favored crop lineages that produce large, flavorful, and rapidly growing vegetative structures, fruits, and seeds, with improved disease resistance and environmental tolerance traits that manifest primarily in above ground plant tissues. However, below ground traits can be difficult for humans to evaluate during domestication and crop improvement. Thus, the evolutionary disruption of plant–microbe symbioses , that is, a decrease in the interaction of crops with beneficial soil microbiota, can go undetected. Over the past century, research on global staple crops and their associations with microbes has increased considerably. For example, the proportion of papers on agricultural staple crops with symbiosis or inoculation in the topic has nearly doubled since 2000 . Seminal work on wheat and soybean reveals different outcomes of microbial symbiosis between modern cultivars and their less domesticated or wild ancestors, with modern crops being less responsive to symbionts and exerting less robust partner choice. However, measures of symbiotic responsiveness must be viewed cautiously, because data interpreted to indicate that newer cultivars are less able to benefit from symbiosis can be driven by changes in plant performance in the symbiont-free state, as explained in Box 1. New research has expanded to diverse crop lineages, showing that reductions in symbiosis traits can be linked to evolutionary changes in plants that occur during domestication. Symbiosis traits regulate microbial colonization and infection, and can encompass a range of plant phenotypes and mechanisms, from structures in roots and other tissues that host microbes, to the molecular and physiological systems that regulate them .In natural populations, beneficial microbes are defined by their ability to generate fitness benefits for hosts that outweigh investments hosts pay to engage in symbiosis. The net benefit for a plant from a microbial symbiont will decrease if the resource a symbiont provides becomes freely available in the environment,macetero de 7 litros as can occur in agriculture. Many fungal and bacterial plant symbionts, ranging from endophytes to epiphytes, are not well characterized. Thus, here, we focus on model plant symbioses with arbuscular mycorrhizal fungi and root-nodulating bacteria to provide examples for broader and likely more complex phenomena in plant microbiomes. Benefit from costly services, such as phosphorus provisioning or symbiotic nitrogen fixation , can be inhibited or negated under fertilization if these nutrients are freely available to plants in the soil.

Similarly, drought protection offered by rhizosphere microbes can be devalued if irrigation prevents drought stress conditions. Enhanced competitive ability mediated by soil microbiota can be rendered superfluous under herbicide treatments that eliminate weeds, and microbe-mediated resistance to herbivores can be devalued if pesticides remove herbivores at no cost to the plant. Modern intensive agriculture succeeds in protecting crops and enhancing yield, but could cause agricultural plants to evolve to shunt resources away from traits that underlie symbiosis. The consequence of the evolution of symbiosis disruption in crops under fertilized conditions depend upon whether such disruption impedes crop performance under lower, more sustainable anthropogenic inputs in agriculture; thus, symbiotic disruption could be detrimental or adaptive with respect to plant performance, and might depend on local conditions . Moreover, any negative effects of the disruption of crop symbiosis traits will be compounded if agricultural practices drive declines in the overall level of cooperation in symbiont populations, as explained in Box 3. Beneficial soil microbiota have tremendous potential to improve plant health and food security. Microbes can improve plant nutrient acquisition, defense, and stress tolerance without the environmental and socioeconomic costs associated with agrichemical inputs. Understanding microbial services, the plant phenotypes and molecular mechanisms that regulate them, and the evolutionary dynamics of host–microbe interactions, are fundamental goals in evolutionary ecology. As the human population approaches 9.7 billion in 2050, requiring a 1.7- fold increase in crop yields, the vulnerability of microbial services to degradation makes the achievement of these goals an existential challenge for translational research.Distinct evolutionary mechanisms can result in symbiosis trait disruption depending on whether symbiosis traits: trade-off with agricultural traits; accumulate deleterious mutations due to the demographics of the breeding population; or are selectively neutral under agricultural conditions. A significant aspect of the evolutionary models we present later, and a key reason to explore this issue more deeply, is that the changes predicted under these models can remain undetected by growers. For instance, reduced interactions between crops and beneficial microbes during domestication can be masked by practices of growing crops in high-nutrient agricultural fields, and could be invisible to breeders who focus primarily on above ground health.The evolutionary trade-off hypothesis predicts that artificially selected shifts in plant traits, often beyond what was previously shaped by natural selection, can disrupt other plant traits if increases in one trait necessarily result in decreases in another. Physiological constraints can result in a resource allocation trade-off between yield and symbiosis. Here, crops evolve reduced symbiosis because the costs of symbiosis compete with allocation to growth and reproduction. Trade-offs can also be driven by antagonistic pleiotropy, whereby alleles that are selected under domestication express adverse effects on symbiosis functions. Here, artificial selection favoring domestication traits outweighs any selection against the reduction in symbiosis that results from these domestication traits. Irrespective of the trade-off mechanism, artificial selection could result in crops that shunt resources to early and large yield traits and sacrifice allocation to symbiosis traits. Thus, adaptation under artificial selection could increase the frequency of alleles that reduce investment in symbiosis . The devaluation of symbiont services under agriculture that we described earlier can accentuate resource allocation trade-offs between yield and symbiosis. In low-nutrient soils, where many wild crop progenitors thrive, plants benefit from the nutritional services of symbionts. However, symbiotic structures entail costs, and overproducing these structures causes growth deficits. Thus, as macronutrients become more available under fertilization, net plant benefit from symbiosis is reduced or can shift toward net cost . Under fertilization, plants often downregulate investment into symbiosis and multiple plant lineages have independently lost the ability to form symbioses , suggesting that the costs of symbiosis drive its evolutionary loss and that reduced dependence on symbiosis can be adaptive . If trade-offs drive canalized declines in symbiosis function, alleles that underlie high performance in agricultural environments are predicted to result in lower symbiosis function. Thus, alleles that confer symbiosis trait disruption could exhibit signals of positive selection. For example, alleles that alter phytohormone levels to induce earlier flowering have been favored by artificial selection in crops such as maize , but are also predicted to pleiotropically reduce colonization by AMF. Domestication alleles, could be tested for such trade-offs via forward genetics, statistical associations, or quantitative genetics. For instance, certain forms of pathogen resistance are useful under the novel intense disease pressures imposed on high-density crop monocultures.

We develop general conditions and then adapt them for empirical use with available data

Many studies have applied portfolio theory to explain acreage allocation in production agriculture . These applications and many since have been primarily applied to crop acreage decisions assuming linear technology and most are in a static setting. This literature, which grew out of Nerlovian models of supply response , is generally based upon adaptive interpretations of risk, and has evolved into a more rational risk approach . The general finding of this, by now, large literature is that the allocation of total acreage to specific production activities is significantly influenced by risk as generally modeled with variances and covariances. The most common finding is that an increase in the own variance of price or revenue reduces the acreage allocated to that activity. This is generally interpreted as the impact of risk aversion.From the perspective of more recent developments in portfolio theory, two general findings beg application in this empirical agricultural risk literature. First, explicit attempts to measure risk aversion structurally such as those in the equity premium puzzle are preferred . Only this way will researchers be able to distinguish risk aversion from other behaviors. Second, the structural approach provides a way to determine whether estimated risk aversion is credible . Thus, we argue that the structural approach is a sensible way to proceed at least at this stage in the development of risk literature in agriculture.

Specifically,maceta 5 litros this literature suggests advantages for a more integrative examination of the broader portfolio problem in agriculture that includes consumption, investment, and other risk sharing activities as well as production. Modern agriculture is characterized by much off-farm investment . At the very least, reduced form production- or acreage-oriented models may misinterpret the level of risk aversion . Worse, parameters can be biased if relevant variables are omitted. For example, if markets are incomplete, Fisher separation may not hold implying inconsistent estimation of parameters . A third issue concerns the advantages and disadvantages of using typical Euler equation representations of inter temporal arbitrage. Euler equations may yield important information from which to identify parameters, but imply that the dynamics must be properly specified . For example, one must choose between the non-expected utility model of Kreps and Porteus and standard model of discounting with additive preferences . After building a dynamic model of consumption, investment, and production, we obtain fundamental arbitrage equations that govern allocations of wealth to financial assets and agricultural capital as well as the allocation of acreage. This enables econometric choice from a larger set of first-order conditions in order to estimate risk preferences.The crucial variable of interest driving decisions is consumption, which is facilitated by accumulation of net worth .For agricultural households, these are both notoriously difficult to measure.After developing the arbitrage conditions, empirical estimates are obtained by generalized method of moments for eight states in the North Central region of the U.S. using stock market returns, bonds, and agricultural land allocations.

For these eight states in the period 1991-2000, reasonably good measurements of wealth are available which are essential for our approach.While this is a relatively short and somewhat anomalous time period compared to typical studies in finance, we suggest this comprehensive approach to arbitrage structure can be beneficial compared to typical incomplete approaches to estimation of risk behavior in agriculture. Using contemporaneous arbitrage equations implied by Euler conditions, an econometric model is specified over future wealth and excess returns conditional on a current information set. In spite of limited data, we find evidence of aggregate risk aversion that is rationalized by a single set of representative consumer preferences using an unconventional but reasonable specification. Although the organizational form of farms varies, a recent report by Hoppe and Banker finds that 98 percent of U.S. farms remained family farms as of 2003. In a family farm, the entrepreneur controls the means of production and makes investment, consumption, and production decisions. We begin by modeling the intertemporal interactions of these decisions. The starting point is a model similar in spirit to Hansen and Singleton’s but generalized to include consumption decisions and farm investments as well as financial investments and production decisions. No carefully-constructed publicly-available panel of agricultural data including farm and off-farm decisions and wealth variables exists. The periodic Survey of Consumer Finances and the Panel Study of Income Dynamics has too little farm information to give a very complete picture of decisions and representation of farm households. The best available data on wealth are found in the Agricultural Resource Management Survey and the U.S. Census of Agriculture, which are conducted by the NASS. For reasons explained above, this survey does not suffice for application of our model at the micro level.

However, data from this survey has been used within ERS to estimate average farm household net worth by state for the period 1991-2001. These data include eight states in the North Central Region of the U.S.: Illinois, Indiana, Iowa, Michigan, Minnesota, Missouri, Ohio, and Wisconsin. These data are not without issues but seem to be the best available source for net worth and are actively used by government personnel in the ERS for research. Alternative data would omit non-farm assets, which are a substantial portion of farm households’ net worth and are intended as a key source of identification for this study. Although the time-period is short and in some ways atypical due to the run up of the stock market in the 1990s, this variation is ideal for identifying the arbitrage effects on agriculture of returns to financial assets. This period also has the advantage that the impact of government policy on crop substitution is relatively reduced and less complicated. For example, the Freedom to Farm Act of 1996 culminated a growing effort to decouple farm subsidies from acreage allocation decisions. A canonical prediction of economic theory is that high wages increase labor productivity. In settings where workers are salaried or paid by the hour, this is the concept of efficiency wages . In settings where workers are paid in proportion to their output , the theoretical connection between wages and productivity is even clearer.1 However, it has proven difficult to empirically estimate the responsiveness of labor productivity to piece rate wages, since much of these wages’ variation is driven by endogenous characteristics of the production process. In this paper, I provide the first quasi experimental estimate of the elasticity of labor productivity with respect to piece rate wages. Specifically, I analyze a high-frequency panel of worker-level production data from over 2,000 California blueberry pickers paid by piece rates. Surprisingly, I find that on average, labor productivity is very inelastic with respect to wages. Piece rate wages are interesting to study because they offer such a direct, clear, and salient link between a worker’s effort and reward. In general, optimal labor contracts can be quite complex, as they must effectively incentivize worker effort while simultaneously accounting for issues like risk aversion, asymmetric information, and moral hazard . However, these complications are less of a concern in settings where a firm can cheaply monitor both worker productivity and product quality. In such cases, theory suggests piece rate wages will outperform other common incentive schemes .2 Understanding how workers respond to changes in a piece rate wage is important in sectors where these wages can vary over time, like in specialty agriculture, the auto repair industry, or the growing ride share market .3 Econometricians face a fundamental challenge when trying to estimate the causal effect of piece rate wages on labor productivity: these wages are inherently endogenous. As an example, consider blueberry picking. When ripe berries are scarce and spread out ,cultivo de la frambuesa average worker productivity is low. When ripe berries are abundant and dense , it is easier for workers to pick berries quickly, and average productivity is markedly higher. Because farmers aim to keep their workers’ average effective hourly pay relatively stable over time, they set piece rate wages higher when picking is more difficult, and lower when picking is easier. In order to account for piece rates wages’ endogeneity, I adopt a two-pronged identification strategy. First, exploiting the richness of my multidimensional panel data, I econometrically control for environmental factors like seasonality and temperature that directly affect the berry picking production function. Second, I use the market price for blueberries as an instrument for piece rate wages.

This price is a valid instrument because it affects a farmer’s willingness to raise piece rates , but is otherwise uncorrelated with picker productivity. Furthermore, the market price for California blueberries is set by global demand and global supply. As a result, individual farms are too small to directly affect the market price, and supply shocks at the farm level can be considered orthogonal to aggregate supply shocks. I find that, on average, labor productivity is very inelastic with respect to piece rate wages, and I can reject even modest elasticities of up to 0.7. This finding contrasts with both canonical economic theory and previous structural estimates: relying on a calibrated structural model of worker effort, Paarsch and Shearer estimate a labor effort elasticity of 2.14 in the British Columbia tree-planting industry, and Haley estimates a labor effort elasticity of 1.51 in the U.S. mid-west logging industry. Why, then, do blueberry pickers not seem to respond to changes in their wage? One explanation of my findings could be that blueberry pickers respond to average effective hourly wages rather than marginal piece rate wages, similar to how electricity consumers respond to average prices rather than marginal prices . This is unlikely, both because piece rate wages are highly salient in the context I study, and because my identification strategy specifically isolates marginal effects from average effects. Instead, I find suggestive evidence that blueberry pickers face some binding constraint on physical effort that is related to temperature. Specifically, I find that at moderate to hot temperatures, I cannot reject that the piece rate wage level has no effect on labor productivity. However, at temperatures below 60 degrees Fahrenheit , a one cent per pound increase in the piece rate wage increases worker productivity by nearly 0.3 pounds per hour, implying a positive and statistically significant productivity elasticity of approximately 1.6. In other words, blueberry pickers respond to the piece rate wage level at cool temperatures, but seem not to respond to changes in their wage at higher temperatures. Temperature also affects productivity directly in economically meaningful ways. Specifically, I find that blueberry pickers’ productivity drops precipitously at very hot temperatures: workers are 12% less productive at temperatures above 100 degrees Fahrenheit than they are at temperatures between 80 and 85 degrees Fahrenheit . However, I also find negative effects at cool temperatures. Workers are nearly 17% less productive at temperatures below 60 degrees Fahrenheit than at temperatures in the low eighties. The most likely explanation of this finding is that berry pickers lose finger dexterity at cool temperatures and find it uncomfortable to maintain high levels of productivity. This hypothesis is supported by evidence from the ergonomics literature , and highlights that temperature’s effects on labor productivity depend on the particularities of the relevant production process. To demonstrate the robustness of my findings, I address several threats to my identification strategy. First, I investigate berry pickers’ labor supply on both the intensive and extensive margins. I show that neither temperature nor wages have a statistically significant effect on these measures. Next, I address the fact that there exists a minimum hourly wage rule in the setting I study. This constraint binds for approximately 15.8% of my observations, raising concerns that workers falling below this threshold have an incentive to shirk or “slack off.” I re-estimate my results using only those observations where workers earn more than the minimum wage and see no qualitative change in my findings. Finally, I confront the possibility of adverse selection in my sample by limiting my sample to only the observations from workers who work more than thirty days in a single season. My results highlight the importance of environmental conditions in outdoor industries. Previous studies have shown, and I confirm, that temperature affects labor productivity directly.However, I am the first to demonstrate that temperature also affects labor productivity indirectly by disrupting the economic relationship between wages and worker effort.

The three catchments have similar precipitation and soil characteristics

The lack of major effects in either season reflect the nature of the modeling scenario: recall that these islands are treated as “pre-flooded”— with salinity levels set the same as the surrounding channels; this corresponds to long-term conditions or near-term flooding under high river-flow conditions within the Delta, not the near-term effect of a “Big Gulp” of saltwater that might occur if the islands flood in the summer or fall or a very dry winter or spring. The contrast between the irrigation and non-irrigation seasons may reflect the effects of the D-1641 regulations , which include requirements to maintain low “X2” salinity standards in the western Delta from February until June. As a result, water exporters responded by increasing pumping in the fall for storage and urban uses, drawing more saline water toward the pumps. Permanent flooding of western islands greatly increases the volume of flood tide inflows and reduces the ability of the out-flowing water to restrain salinity intrusion.Sea level rise leads to limited crop revenue losses in the Delta, both with dual conveyance and through Delta exports . Dual conveyance for Delta exports generally increases total revenue losses somewhat relative to through-Delta exports, but these losses remain well under 1% of total revenues. During dry years, when Delta waters are more saline, dual export conveyance gives the highest revenue losses, slightly above 0.7% ,maceta 30 litros roughly $4.5 million yr-1, with most losses occurring in the western Delta.

Results using the RMA 2-D hydrodynamic modeling for salinity with permanently flooded western islands also show little revenue loss during the irrigation season. Some areas in the north of the Delta may even see slight decreases in water salinity and corresponding increases in crop revenues. Because most salinity changes occur outside the main irrigation season, crop yield and revenue effects are largely confined to acreage planted to winter crops such as wheat; thus the absolute revenue losses are very small because the acreage of winter plantings is itself small . Of course, beyond their effects on water salinity in the Delta, the permanent flooding of the five western islands would also lead to losses from flooded land being taken out of production. Elsewhere, we used DAP to show that farm revenue losses from the permanent flooding of 19 western and central Delta islands would far exceed the salinity-related losses shown here—roughly $66 to $90 million yr-1—10% or more of baseline crop revenues . Changes of this magnitude would also ripple through the regional economy , causing additional losses in revenues and value added. Large conversions of farmland to habitat could also have more substantial local and regional economic effects than the salinity changes modeled here .Because the historical 1981–2000 water year, average export of 5.96 billion m3 yr-1 might not be representative of more recent, higher export levels, we replicated Fleenor et al. WAM hydrodynamic modeling runs using the 1996–2005 water years, when average exports were 7.28 billion m3 yr-1 . We found no major increase in salinity for any of the 52 sampling stations considered during the irrigation season. The largest increase was 2% at the Mokelumne River station near Terminous Tract, and the average electrical conductivity across all stations in the Delta was generally lower than during the 1981–2000 period. This is because the 1996–2005 period was fully covered in the D-1641 requirements in operation from the mid-1990s; under these requirements, the isohaline line of 2ppt must be maintained in the far western Delta from February to June to support delta smelt.

During the non-irrigation season of the 1981–2000 time period, however, dual conveyance may increase salinity in some areas, including those near Old and Middle Rivers, which are intake points to supply Delta water for urban uses in Contra Costa Water District. The change in salinity in these locations is about 15%, which would increase water treatment costs for the Contra Costa Water District service area if the utility were unable to store water during lower salinity periods for later use. To test the sensitivity of the DAP agro-economic model, we also examine cases with uniform values of irrigation water salinity for all islands at 1%, 3%, 5% and 10% of seawater salinity or 33 ppt. DAP responds more abruptly to electrical conductivity levels beyond one percent of seawater. This analysis supports conclusions from earlier modeling : crop revenue losses from salinity increases caused by dual conveyance and sea level rise are relatively low because most higher value crops are not located in parts of the Delta that experience the highest salinity increases. When identical, higher levels of irrigation water salinity are assumed for all Delta islands and sub regions, DAP reports generally higher agricultural revenue losses than those shown in the previous section. This results from two factors: first, the proportional salinity increases are much higher on islands and sub regions in the Delta where salinity is currently low; second, these areas also tend to have greater concentrations of higher-value crops. Thus, increased salinity conditions and losses of higher value crops increase revenue losses substantially . The absolute revenue losses are highest in the northern and southern Delta, where such higher value crops predominate .Human activities associated with food and energy production have greatly elevated nitrogen bio-availability to an extent that exceeds the assimilative capacity in many terrestrial ecosystems, often leading to large increases in N fluxes to waters . Enrichment of N leads to eutrophication of surface waters causing degradation of aquatic ecosystems, such as toxic algal blooms, low dissolved oxygen, depletion of fish populations, and loss of aquatic biodiversity .

To effectively guide watershed management to control N pollution, it is essential to quantify the response of riverine N export to changes in sources and levels of anthropogenic N inputs . Nitrogen budgets are useful for evaluating impacts of human activities on the N cycle by relating anthropogenic N inputs to outputs . Net anthropogenic nitrogen input is a budgeting approach that sums annual N contributions from atmospheric deposition, fertilizer application, agricultural fixation, seed input, and netimport/export in feed and food . The NANI approach has been applied to many watersheds acrossAsia , America , and Europe . It is a simple yet powerful approach to evaluate net N inputsfrom anthropogenic sources to terrestrial ecosystems, as well as an effective toolto explain among-watershed or among-year variations in riverine N exports. However, the relationship between NANI and riverine N export is additionally influenced by variations in hydroclimate and land management activities, as well asprogressive Nsaturation of terrestrial ecosystems . It is commonly observed that years with higher precipitation or river discharge export a higher fraction ofNANI via rivers than drier years . Furthermore, the export fraction of NANI via rivers can be enhanced by improved agricultural drainage systems . Previous studies also demonstrate a larger fractional export of NANI by rivers when NANI exceeds some threshold value , which corresponds to NANI exceeding the N assimilative capacity of terrestrial and aquatic ecosystems . As a result, changes of climate, land management,macetas cuadradas plastico and the degree of N saturation have a strong potential to enhance riverine N export . Importantly, the influence of climate change, land-use change and progressive N saturation is difficult to detect from short-term records, instead requiring a long-term record of NANI and riverine N export dynamics. For a watershed, the NANI components of chemical fertilizer, atmospheric deposition, biological fixation and seed input are the primary N inputs to forest and agricultural systems, while residential systems mainly receive N from human and animal wastes. In terms of N delivery pathways, N exports from forest and agricultural landscapes to the river network are mainly via diffuse runoff and leaching , while a portion of N from residential systems enters the river network via direct sewage discharge . In addition, the greater impervious surface area in residential systems further enhances N delivery efficiency . As a result, residential systems have a higher potential to export NANI than forest/agricultural systems. This is especially true in developing countries where agricultural subsurface drainage and efficient treatment of residential wastewater are both often lacking . Therefore, it is valuable to separate watershed forest/agricultural and residential N budgets to effectively identify their contrasting export fractions and relative contributions to riverine N fluxes. Based on extensive data collection for three adjacent catchments subjected to low, medium and high levels of anthropogenic impacts in eastern China, this study provides a long-term analysis of the response of riverine TN export to changes in forest/agricultural and residentialN budgets,landuse and climate.

Specifically, this study examines temporal and spatial variations of NANI to forest/agricultural and residential systems, addresses temporal and spatial variations of riverine N fluxes; develops empirical models for linking NANIFA and NANIR to riverine TN fluxes, and identifies individual contributions from NANIFA, NANIR and other sources to the riverine TN flux. This study improves the NANI budgeting methodology to separately estimate watershed NANIFA and NANIR budgets andidentifies of their contributions to annual riverine TN flux. Such quantitative knowledge is essential for managers to determine which systems and sources should be targeted for N reduction.The three catchments in this study are located in the rapidly developing Taizhou region of Zhejiang Province, China . The three rivers are tributaries of the Jiaojiang River, which is the third largest river of Zhejiang Province and flows into Taizhou Estuary and the East China Sea, a coastal area that commonly experiences hypoxia . The climate is subtropical monsoon having an average annual temperature of 17.2 C andaverage annual precipitation of 1395 mm. Due to the dominant volcanic, malmstone and mudstone bedrock lithologies, groundwater or base flow contributes 45% of annual river water discharge in the upper Jiaojiang River watershed the investigation made by local Hydrology Bureau. Rainfall mainly occurs in May– September with a typhoon season in July–September, while winter is a major dry season . From 1980 to 2010, there were no significant trends in annual precipitation or river discharge in the three catchments . Considering the availability of relevant long-term data, this study selected three catchments within the Jiaojiang watershed to provide a range of anthropogenic impacts from agricultural activity and urbanization . In terms of managed land area percentage , as well as agricultural drainage, human population and domestic animal density, the three catchments were classified into low , medium and high levels of anthropogenic impacts. Except for catchment HD, catchments LD and MD have comparable slopes and altitudes due to their locations within the watershed .Between 1980 and 2010, average managed land area percentage was 4%, 9% and 26% for catchments LD, MD and HD, respectively. Correspondingly, natural forest and barren lands accounted for 96%, 91% and 74% of the entire catchment area for LD, MD and HD, respectively. Thus, LD may be considered as a reference catchment for examining progressive nitrogen saturation in a dominantly natural ecosystem over the study period. The average percentage of agricultural lands with efficient drainage systems was 12%, 14% and 35% for LD, MD, and HD, respectively . Average population density was 74, 134 and 761 capita km2 , while domestic animal density was 36, 65, and 153 capita km2 for LD, MD, and HD, respectively. Over the 31-year study period, human population within LD, MD, and HD increased by 25%, 32%, and 30%, while managed land area increased by 39%, 43%, and 24%, respectively. The economic role of agriculture has been increasingly replaced by industry since the 1990s, resulting in a remarkable reduction in cropland cultivation as well as N fertilizer use since 2000 . Due to reduction in cropland and increasing availability of chemical fertilizer, recycled animal and human excreta for fertilizing croplands also decreased from 93% in 1980 to 21% in 2010 . The remaining animal wastes were removed via artificial treatments and direct discharge to the environment . Agricultural land area irrigated and drained with improved cement channels and pipes increased by 96–108% since 1980 .Reducing tradeoffs among ecosystem services related to nitrogen cycling in agriculture is a global challenge. One promising strategy to reduce such tradeoffs relies on a stronger role for biological processes to support high yields, such as practiced in organic agriculture, rather than non-renewable inputs like synthetic N fertilizer.

The PEY had comparable increases in the CA categories under the cropping systems

Rice–wheat generated the maximum economic return with CA, which was 29.0% higher than with the conventional practice . Increase in economic return was similar among the maize–wheat, rice–maize and other systems. Crop-based analyses showed higher yields for wheat and maize than for rice under CA practices . Crops in the ‘others’ category exhibited a 3.8% increase in yield. The trend was similar in on-station and on-farm data for maize and wheat crops . However, yield in rice was higher in on-farm studies, but there was no change in on-station studies. Wheat and maize had much higher water use efficiency compared with rice . Other crop systems had 12.7% higher water use efficiency. CA-based practices increased the economic return for all crops, with the highest in wheat and lowest in rice .Meta-analyses of key parameters of on-station and on-farm studies, including all crops and systems in response to the sub-levels of CA , are shown in Table 2. The beneficial effects tend to increase from CA1 to CA2, while the differences between CA2 and CA3 are negligible. Compared with conventional practice, grain yield increased 3.0% in CA1, 5.8% in CA2 and 5.5% in CA3. The increase in PEY followed a similar trend. Likewise,macetas de plástico water use efficiency increased 8.3% in CA1, 12.6% in CA2 and 11.6% in CA3.

The increase in net economic return was, however, the largest in CA3 compared with conventional practices. The increase in net return was higher in CA2 compared with CA1 . In on-station studies, grain yield increase was similar in CA2 and CA3 with no change in CA1; in on-farm studies, all the CA sub-levels had similar yield gains . The PEY showed a similar response as in grain yield . Cropping-system analyses showed the highest yield increase in the maize–wheat system, ranging from 13.7% to 24.2%, which did not differ among three sub-levels of CA. The rice–wheat system had the highest increases in grain yield in CA2 , which was similar to CA3 but higher than CA1 . The rice– maize system, for which data of only CA1 and CA2 were available, showed similar increases of 2.2% in CA1 and 4.5% in CA2.In the rice–wheat and rice–maize systems, the water use efficiencies were similar among CA1, CA2 and CA3. In the maize– wheat system, CA2 and CA3 had comparable increases in water use efficiency of 25.1% and 26.0% . CA3 had the highest increase in economic return in rice–wheat, but in the maize–wheat system, all three CA practices brought similar economic return. In the rice–maize system, greater increase in economic return was achieved in CA2 compared with CA1 . Crop-based analyses showed higher wheat and maize yields in all the CA sub-levels, and water use efficiencies were significantly higher in all three CA sub-levels .As a function of soil texture, yield responses were nominal on sandy soil with increasing responses for fine clayey , medium loamy and moderately coarse loamy soils . The PEY had a trend similar to grain yield.

The moderately fine loam had the highest increase in grain yield and water use efficiency . In maize–wheat, the highest yield gain was obtained from medium loamy soils , which is comparable to the yield increase in moderately fine loamy soils, but moderately fine loamy soils resulted in the highest increase in water use efficiency . In rice–wheat, moderately fine loamy soils contributed to the highest yield gain, but increases in water use efficiency were similar for all the textures. In the rice–maize system, both moderately fine and medium loamy soils showed the largest gains in yield and water use efficiency. Moderately coarse loamy soil appears to be better suited for the ‘others’ category, improving both the yield and water use efficiency compared with conventional practice. The net return was higher in all soil textures except the coarse sandy soils and closely followed the trend in yield gains. Crop-based analysis showed the most significant performance gains in the loamy soils for all the crops while the sandy soils had the poorest response, with marginally positive to negative effect . Clay also did not seem to be favourable under CA. Among the sub-classes of loam, fine loam was the most favourable for all three cereals, with the maximum yield advantage of 16.0% in wheat. Maize performed similarly in all three sub-classes of loam, with grain yield increases ranging from 6.1% to 8.9%. Rice had the maximum yield advantage of 3.6% in fine loam and relatively poor or no responses in other soil texture classes. Increase in water use efficiency in wheat was similar in all textures, except in coarse sandy soil, which was significantly lower.

Maize had comparable increases in water use efficiency in moderately fine and moderately coarse loamy textured soils. In rice, water use efficiency was higher only in medium loamy soils, with no change in other soil texture classes.Our meta-analysis of 1,353 field studies with major cereal-based cropping systems conducted on research stations and farmers’ fields closes a data gap for South Asia that has limited the regional inferences that can be drawn from earlier meta-analyses. Our analysis reveals the positive average effects of full and partially implemented CA on crop yield , water use efficiency and economic return in the cereal-based cropping systems of South Asia. Although all three combinations of CA sub-levels had significant positive effects, the impacts tended to be more positive when both the cereals had ZT with residues retained in one or both the crops across the cropping system. However, the net economic return was 40.5% higher in CA3 compared with around 20% in CA1 and 26% in CA2, suggesting that a full or close to full extent of CA would maximize the economic benefits, which is an important consideration in the farmers’ decision making. Superiority of CA2 and CA3 over CA1 may also indicate cumulative effects of ZT and residue retention resulting from a carryover effect in a system. However, since there were only a limited number of published studies examining long-term effects of CA in South Asia, it was not possible to evaluate the carryover effects in multiple years in the present study. The ZT with surface residue retention has been reported to produce higher crop yield than without residue. In a global meta-analysis, average yield loss of 9.9% was documented with ZT, a decline that was reduced to 5.2% when residue was retained. By contrast, our results show more positive effects on crop yield and other parameters. This could be because South Asia was not well represented in earlier meta-analyses published in 2015. The literature search in the present study revealed 48 new studies after the meta-analysis published in 2015. In addition, our study included data from 1,197 on-farm trials. Earlier meta-analyses had no on-farm data. Our results demonstrate that CA benefits vary among crops, cropping systems and soil textures. The CA practices tend to perform best for upland crops and non-rice cropping systems,cultivo del frambueso a result consistent with earlier findings in South Asia. Higher yield gains with CA in maize–wheat than in the rice-based system provide ample opportunity for much-needed diversification. Diversification is a key to address not only the issues of a faster-declining water table but also the perceived challenges of food and nutrition security. While all the studies included in the meta-analysis had grain yield data, most did not have all the performance parameters, namely, grain and PEYs, water use efficiency and net economic return; hence, analyses may not have captured the relative performance of CA. Research on CA in South Asia is largely focused on rice-based and maize-based systems, resulting in fewer studies in other cropping systems.

Nevertheless, it is notable that rice-based and maize-based are the most dominant cropping systems in South Asia. Published data on GHG emissions under CA were limited, and only emissions from on-station studies in the rice–wheat system were available. Most studies also lacked soil information . Another notable limitation was that there were not many long-term studies to assess the residual effects of CA on succeeding crops. All the crops, including rice, had higher average yields in loam than in clay or sand. These results may explain the variable performance of CA reported by those that did not consider soil texture as a factor. These findings highlight the need for a better environmental characterization for targeting CA by appropriately defining recommendation domains. Greater benefits in the field studies carried out by the researchers compared with those implemented by farmers are probably attributable to knowledge gaps that influence appropriate implementation of CA practices. The use of CA not only provides significant private benefits but can contribute to several ecosystem services. In our data, GWP was reduced by 12.4% in CA1 and 33.5% in CA2 in rice–wheat systems, values that are consistent with others. Moreover, public benefits are not limited to GHG emissions. Residue burning is a serious public health threat in South Asia, and approximately 23 million tons of rice residues are burned every year in Northwest India. The CA-based practices provide an economically feasible alternative to burning, which has been made possible with the development of ‘next generation’ seeders that permit ZT into heavy residues. Beyond the potential benefits that our study directly assessed, CA is largely mechanized and hence provides opportunity for timeliness of operations, reducing risks, increasing use efficiency of fertilizers through precise placement and reducing drudgery and hence attracting youth and women to remain engaged in agriculture. Our extensive literature examination of published studies on CA and a large number of on-farm trials revealed the need for a pragmatic approach to scaling CA practices. Few farmers in South Asia are able to adopt all three elements of CA at once, but benefits of partial adoption are clear. Some of the impediments to full adoption include the conflicting edaphic requirements of crops in a system; for example, rice grown in a rainy or wet season gets flooded before planting, which makes residue retention difficult. However, our analysis suggests that the classical definition of CA should not limit the smallholder farmers from adopting CA elements as their application separately or in tandem has potential benefits. Most farmers in South Asia follow ZT in only one crop, and few farmers retain complete residue cover at the soil surface throughout the annual cropping cycle. This situation has been observed and discussed by others but has not been resolved in terms of characterizing CA. According to our findings, if 50% of the area under the dominant cereal-based cropping systems of South Asia is brought under CA by 2030, there will be additional outputs of 3.6 million metric tons of grain and 0.5 million metric tons of grain protein on an annual basis . In addition, water used for irrigation will be reduced by 14,100 millionm3 , GWP will be reduced by 2.9 million tons and farmer income will increase by US$1,771 million. A concerted effort involving public and private stakeholders supported by an effective enabling environment for technology scaling is required. A renewed eco-regional initiative like the Rice–Wheat Consortium for the Indo-Gangetic Plains is perhaps part of the answer, with the provision that market-led approaches must be at the centre of the approach16. It is noteworthy that the Rice–Wheat Consortium pioneered and led much of the strategic and adaptive research on CA in South Asia, resulting in an accumulation of knowledge, which largely made this meta-analysis possible. Our results clearly show that while adoption of full CA is often superior on the basis of multi-criteria assessment, it is not always necessary to achieve meaningful benefits in the South Asian context. Since the benefits of partial adoption of CA practices are consistently observed in the cereal-based cropping systems in South Asia, rigid adherence to an ‘all or nothing’ approach to scaling CA does not seem warranted. More fundamentally, our results suggest that conclusions regarding the potential of CA derived from global meta-analyses or those reported from Africa do not hold true for the cereal-based cropping systems of South Asia. It is important to note that agriculture in South Asia is different from that in the rest of the world. The cropping system in South Asia is predominantly under irrigated management and is very intensive, with two or more crops in a year.

A short lasting fall or spring frost lasts a few hours and can cause substantial damages

Part of the modeled gains in consumer surplus are enjoyed elsewhere, as the majority of pistachio output is currently exported. However, export demand is usually considered more elastic than domestic demand, making the share of local consumer surplus gains disproportionate to the share of local consumption. At a share of 1/3 of total consumption, let us assume that Californians still enjoy half of the consumer surplus gains from MCE . Adjusting Table 4.1, the total welfare gains in California are strictly negative when the demand is unrealistically inelastic, εD = −0.5, and strictly positive for more realistic demand assumptions . The scope of consumer surplus gains brings us to the potential gains from public investment in R&D for MCE solutions. With social returns from investments largely exceeding private ones, this type of research is a good candidate for prioritizing in public research fund allocation . The case for public research is made stronger by the fact that there seems to be little private incentive to invest in MCE, at least in this case. I see MCE technologies mostly as an adaptation of existing ones to solve a climate problem. Therefore, innovations in the field would be hard to make proprietary by the innovator. Moreover,growing pot innovators are likely to come from the industry: a large growing firm would have the resources and access to enough pistachio acreage to run experiments and develop new MCE solutions. But if this firm sees that a world with MCE is worse, why invest in innovation?

Adding market power to the equation makes an even stronger potential case for public R&D: the total welfare gains are higher, and the incentives for innovation could be even lower. What might be the implications of MCE technologies in a broader sense? One could imagine, with further agronomic research, other MCE technologies applied to other fruit and nut crops, and even for annuals such as corn or soybeans. Of course, these are less profitable than pistachios, but they face similar challenges, and MCE solutions are not necessarily very expensive. Other implications could be with the distribution of climate change damage incidence. Technologies might only be available to growers in countries better off financially, further exacerbating international income disparities. An interesting potential for MCE technologies could be in accelerating the transition of agricultural practices closer to the poles, sometimes referred to as the “crop migration” . For example, MCE solutions for frost could accelerate the expansion of viticulture to higher latitudes. The simulation based valuation methodology in this chapter has its caveats. Modeling supply and demand as linear is obviously a simplification. The assumptions on growth and distribution of acreage are based on past growth patterns, and might not reflect unexpected future changes in market conditions. The future chill predictions are in line with other predictions by climatologists, yet might fail to materialize. Nevertheless, by choosing various scenarios, basing the parameter ranges in the literature, and choosing conservatively when possible, I believe to have gotten a reasonable range for the potential gains from MCE in California pistachios. They are in the low billions for a crop of secondary importance to California agriculture. I believe this shows a great potential of MCE technologies for climate change adaptation in general.Weather is a key input for agricultural production.

A vast economic literature is dedicated to the role of weather information in grower decision making, market outcomes, and commodity futures. On one hand, better information about the weather can help growers optimize their use of other inputs, increasing efficiency in production and avoiding costs related with uncertainty. On the other hand, some economic models can show—under some assumptions—that more precise weather information might not be welfare increasing, as ex-ante uncertainty about the weather can lead to extra investment in other inputs. That is, when growers have better forecast of adverse weather, output would be further reduced from its level under uncertainty . There is also some concern about weather forecasts acting as signals for collusion among growers, but simple price mechanisms can technically reduce output and welfare with better weather prediction even in a competitive market . Notwithstanding these warnings by economists, the economic gains from weather information are usually deemed positive, even if their magnitude is sometimes contested . Much of the seminal economic literature on the value of weather information was written between the 1960’s and the 1990’s, when significant improvements in forecasting was achieved with the advance of computing power and complex meteorology models . This literature is based on the agricultural practices and available data of that time. While literature about the value of weather information seems to have plateaued in the 2000’s, perhaps as forecasting technologies matured and stabilized, the surge of precision agriculture could re-ignite interest in this topic. Heterogeneity within fields and precise growing strategies, based on exact measurement of weather variables , is increasingly the subject of research and technological application . Uncertainty regarding real-time weather on micro scales poses conceptually similar questions to those dealt with by the weather forecast literature in the past.

At the same time, new discussions on the value of weather information and the government’s role in providing it have been revived with advances in remote sensing and satellite technology . The technical and scientific capabilities required to gather and analyze weather data, as well as the non-rival nature of weather information as a product, meant that much of the development of weather services has been done by governments. Johnson and Holt point out that this led to a significant economic literature, assessing the potential gains from better weather information given the public expenditures. Their survey of the relevant literature mostly includes econometric studies, where the output gains from improved forecasting are estimated and the economic gains from providing them are then calculated per hectare. Other methodologies include survey based valuation, paired with economic data and modeling. Anaman and Lellyett assess the gains from a weather information system for cotton growers in Australia, finding the benefit-cost ratio of the system at 12.6 . Klockow, McPherson, and Sutter conduct a survey based study of the value of the Mesonet network in Oklahoma. Less than 4% of Oklahoma’s cropland is irrigated, and the modest value they find for Mesonet information mostly comes from risk management. Interestingly, there are few such examples of an economic study about a specific weather information system in the published literature,square pot as opposed to numerous studies on the value of information for growers. Johnson and Holt do mention, for example, that weather forecast services in Sweden and New Zealand have gone through “extensive privatization”, but do not cite any articles analyzing these decisions. The first part of this dissertation is an analysis of economic gains from the California Irrigation Management Information System , a network of weather stations and data center run by the California Department of Water Resources. For over 30 years, this system has been used by growers, consultants, and other users in California agriculture. This chapter presents the preliminary findings from a thorough report on the value of CIMIS, showing substantial gains not only in agriculture but also in landscape management, regulation, research, and industry. Climate change poses a major challenge for agriculture, as predicted shifts in temperature and precipitation patterns around the world affect agricultural productivity . Early studies on climate change in agriculture first focused on the impacts of changing mean temperatures, and more recent empirical literature emphasizes the importance of temperature variance and extreme heat on yields, especially during the growing season . For example, Schlenker and Roberts show sharp drops in the yields of corn, soybean, and cotton, when exposed to degree days above 28–300C. Similar findings have been replicated in various crops and locations around the world. Climate scientists affirm that heat waves will increase in frequency and duration as the process of climate change advances . Researching yield responses to high temperatures, especially when the relationship seems non-linear orthreshold like, is therefore essential for prediction of climate change effects on agriculture. This can only be done with adequate weather information. Chapter 3 presents an analysis of the yield response of pistachios to hot winters.

This is also a temperature distribution tail problem, at least when looking at temperatures between November and March. Daytime temperatures in California winters have been rising in the past 20 years, and are predicted to rise further in the future. This can have detrimental implications for pistachios, a major California crop, but estimating the yield response function has been a challenge so far. I use CIMIS data and innovative techniques to recover this relationship and predict the potential threat of climate change to California pistachios. It turns out that Pistachios, a billion dollar crop in California, could be threatened by warming winter within the next 20 years. While the scope and magnitude of our current climate crisis might be unprecedented in human history, this is not the first time that humans are facing climatic challenges in agriculture. Olmstead and Rhode show how, through the 19th and 20th centuries in North America, wheat growers managed “…to push wheat cultivation repeatedly into environments once thought too arid, too variable, and too harsh to farm”. The transition was made possible mostly by the development of new varieties. Plant breeding toward that end required information on the climate both in the progenitor native areas and the areas where the eventual new varieties would be planted . Adaptation to climate can be on the physical dimension as well. Specific interventions can be designed to change the physical environment surrounding plants. The most obvious intervention is building irrigation systems, to compensate for lack of adequate rainfall and soil moisture. But examples of adaptation to temperature by physical means exist as well. This type of intervention is common for a left tail effect: frost. To avoid it, only a slight increase in temperature is required, and growers know how to do that. Some examples for dealing with frost are hundreds of years old. The Tiwanaku civilization formed a system of raised fields on the shores of lake Titikaka in the 7–12 centuries C.E. Fields in select locations were raised with extra soil, up to a few feet above the ground level. Water from nearby springs was diverted and run through canals dug in these raised fields. This provided not only moisture for the plants, but also converted the top soil level into a large heat storage unit. On frost nights, which are common in this high area, the heat stored in the soil kept the near-surface temperatures on raised fields higher than the normal air temperatures, preventing plants from freezing . Without modern weather instruments, the Tiwanaku realized that slight differences in ambient temperatures can have crucial consequences, and planned their fields according to their understanding of the climate. This system yielded far better than regular dry farming practiced before in this area, and supported a larger population than the one residing on the lake shores in the 1990’s. Eventually, as climate became drier, the water level of lake Titikaka dropped and the springs dried up, resulting in the collapse of the Tiwanaku culture . Despite its eventual failure, this technology was successful in abating frost damage for centuries, maintaining a population of hundreds of thousands and showing the power of human intervention on the field level to tackle a temperature distribution tail challenge. In Europe, traditional methods of dealing with frosts in vineyards include lighting small fires or “frost candles”. A more modern approach uses big fans, circulating the cold air in the inverted layer with the warmer air on top of it. Farmers have been using “air disturbance technology” in the US since the 1950’s . Wind generators are used around the world to protect wine grapes, fruits, and even tea from spring frosts. In some cases, a similar effect can be achieved with sprinklers . Interestingly, little economic literature has focused on air disturbance technologies. Stewart, Katz, and Murphy assess the value of weather information in the Yakima Valley of central Washington, in the context of frost prediction and air disturbance technologies. This descriptive study was published in the Bulletin of the American Meteorological Society.

Soil at both sites was fumigated once a year in summer over a two-year period

Enzyme activities can be used as an index of microbial functional diversity, although accumulated enzymes may contribute considerably to the overall enzyme activity of a soil. A semi-quantitative method to determine enzyme protein contents in soil based on the specific activities of reference enzymes and enzyme activity values of soils was reported by Klose and Tabatabai in order to prove whether there is a direct correlation between the activity of any enzyme and its protein concentration in soil. This approach is based on the assumption that the compositions of the reference enzymes are similar to those in soils. Protein concentrations were suggested to serve as a suitable measure to quantify the effects of environmental changes, for example after application of pesticides, on soil biological properties . The understanding of the impacts of pesticide fumigants on key biochemical reactions involved in organic matter degradation and soil nutrient dynamics is important in order to evaluate the ecological significance of fumigation on the soil system. The toxicity of fumigants is related to their interference with respiratory enzymes, including pyruvate dehydrogenase, their ability to chelate metal cations such as Cu, the inhibition by the unchelated ion,blueberry grow bag and toxic degradation products such as methyl isothiocyanate . MeBr can be degraded in soils by the following three pathways : a) chemical hydrolysis to form methanol and bromide, b) methylation to soil organic matter and release of bromide ion, and c) microbial oxidation to form formaldehyde and bromide ion.

Biological hydrolysis and other microbial processes involving enzymatic processes are also likely to contribute to the degradation of MeBr in soil . Microbial respiration, nitrification potential, and dehydrogenase and arylsulfatase activities were inhibited by MeBr + CP and the alternatives PrBr, InLine, Midas and CPEC one week after soil fumigation . After 30 weeks, there was no difference in microbial biomass and activities between the treatments studied, with the exception of lower acid phosphatase and arylsulfatase activities in fumigated soils. These results indicate that there are short- and long-term differences in the response of various microbial and enzymatic processes to MeBr + CP and alternative fumigants and thus, of the various functions of the soil biota in ecosystems. A limitation of this study is that it was conducted for a maximum of 37 weeks; it remains unknown if MeBr + CP and alternative fumigants have longer-term impacts on soil biochemical processes under field conditions after multiple applications. The objective of this study was to evaluate the effect of repeated soil fumigation with MeBr + CP and two registered and two non-registered alternative fumigants on microbial biomass and respiration, the activities of dehydrogenase, acid phosphatase, β-glucosidase and arylsulfatase, and enzyme protein concentrations in soils. Furthermore, the effect of these fumigants was evaluated on dry proteins containing β-glucosidase, acid phosphatase and arylsulfatase in the absence of immobilizing or protecting constituents of soil .

The selected alternative fumigants represent the actual formulations that likely will be used by growers for strawberry production. Dehydrogenase activities were selected because they reflect the total oxidative activities of soil microorganisms and are important in oxidizing soil organic matter. Acid phosphatase catalyzes the hydrolysis of a variety of organic phosphomonoesters and is therefore important in soil organic P mineralization and plant nutrition. The enzyme β-glucosidase catalyzes the hydrolysis of cellobiose, and thus plays a major role in the initial phases of the decomposition of organic C compounds. Arylsulfatase is believed to be partly responsible for S cycling in soils as it participates in the process whereby organic sulfate esters are mineralized and made available for plants. The first aim of the present study was to test whether soil fumigation with these four potential pesticides will alter important soil functions that, in turn, will affect the long-term productivity of agricultural soils. The second aim of this study was to evaluate the effects of soil fumigation on the activities of enzyme proteins, which may be present in the soil as free enzymes and not protected by clay-humus complexes. Free enzymes are likely to be more sensitive to environmental factors as intracellular or adsorbed enzymes, which are protected by the cell envelope or by clay-humic complexes. Field studies were conducted in California, USA, in the central region in Watsonville and in the southern region in Oxnard in 2000 and 2001. Both sites are located in intensive strawberry production areas of California. Soil at both locations had not been fumigated for the past 2 and 3 years prior to this experiment for Watsonville and Oxnard site, respectively. However, before that soil at both sites had been fumigated routinely with MeBr + CP for the past 10 years. The soil in Watsonville is classified as an Elder sandy loam . The soil in Oxnard is classified as a Hueneme sandy loam .

The past 50-year average annual precipitation is 582 mm and 385 mm at Watsonville and Oxnard, respectively. The average annual maximum and minimum temperature at Watsonville is 19.5ºC and 10.7ºC, respectively. Corresponding values for Oxnard are 21.2ºC and 10.7ºC. Commercial agricultural practices for the area were followed . The soil was tilled and beds were formed in Watsonville at 132 cm center-to-center and in Oxnard at 173 cm center-to-center . Slow release fertilizer was applied to the beds at the rate of 400 kg ha-1 y -1. A drip irrigation system was used consisting of two drip tapes , with emitters spaced 30 cm apart and an emitter flow rate of 0.87 l min-1 at 70 kPa, placed 10 cm and 30 cm from the bed center at a soil depth ranging from 2 to 5 cm. Fumigation treatments were randomized in a complete block design with four replicates per treatment at each site. Fumigants used, fumigant rates and application methods are summarized in Table 1. Each replicate consisted of three neighboring 15-m long beds.Soil in Watsonville was fumigated on August 10, 2000 and September 27, 2001, the soil in Oxnard was fumigated on September 1, 2000 and August 24, 2001. At the time of fumigation, the average daily soil temperature within the raised bed ranged between 16 to 20ºC, and the average soil water content was less than 85% of field capacity . About 4 weeks after fumigation bareroot strawberry [Fragaria X ananassa Duchesne, variety “Diamante” and “Camarosa” ] was transplanted in 2000 and 2001. Pesticide effects on soil microorganisms are difficult to evaluate because of the heterogeneous physical-chemical nature of soil, resulting in uncertainties about their distribution and fate within soil microsites. Previous studies on the effects of potential MeBr alternatives on the size,blueberry grow bag size composition and activity of soil microorganisms are limited to one or a few fumigants, a relative short time period, and/or the laboratory . Recovery of microbial processes in the laboratory compared to the field may be reduced due to the absence of re-colonization by nonfumigated soils . Furthermore, the effect of alternative fumigants on soil microbial processes was studied on soils with a 10-year history of fumigation with MeBr + CP combinations followed by a 2 to 3 year break prior to the initiation of these field experiments at Watsonville and Oxnard, respectively. Consequently, results obtained from these soils with a long-term fumigation history may not apply to soils previously not fumigated . The results presented in this work are part of a longer study to evaluate application methods and efficacy of chemical MeBr alternatives to control weeds and pathogens in strawberry production systems in California, USA. The response of microbial performance to soil fumigation with InLine, CP, PrBr and Midas relative to the standard MeBr + CP application and a control soil was determined at 1, 4, and 30 weeks after fumigation in 2000, the first year of the study. Fumigation initially inhibited microbial respiration, nitrification potential, and activities of dehydrogenase, acid phosphatase and arylsulfatase . After 30 weeks, microbial activities in fumigated and control soils were similar at both sites, with exception of acid phosphatase and arylsulfatase activities in selected treatments that remained lower in the fumigated soils. Soil microbial biomass C and β-glucosidase activity were not affected by fumigation with MeBr + CP and alternatives throughout the whole study period in the first year .

This paper focused on the effects of repeated soil fumigation with MeBr + CP, PrBr, InLine, Midas, and CP on the size and activity of soil microorganisms and hydrolytic enzymes, which control the degradation of organic substances and the rate at which nutrient elements become available for plants . Microbial respiration was significantly decreased in Oxnard soils fumigated with MeBr + CP, but not affected by the four selected alternative fumigants at both sites. In this study, microbial respiration showed a low sensitivity to detect changes in soil microbial activity due to repeated application of the standard MeBr + CP combination and alternative fumigants. This finding is in contrast with the high sensitivity of respiration measurements to treatment of soils with heavy metals and pesticides . Significant lower respiration rates in Oxnard soils fumigated with MeBr + CP compared to recently not fumigated control soils however, may indicate a decreased biological activity. Soil fumigation had no significant effect on microbial biomass C, and the results for microbial biomass N were inconsistent over the two experimental locations. Therefore, the effects of soil fumigation on total microbial biomass content provided little information on possible changes in the size of microbial populations. The overall low response of microbial biomass and respiration to repeated soil fumigation may be related to selected effect on sensitive microbial populations and the growth of resistant species. The latter may feed on cell debris, leading to restructuring of soil microbial populations as indicated elsewhere . Selected specialized bacteria may also use the fumigants as a source of carbon and energy, as documented for agricultural soils repeatedly subjected to MeBr fumigation . The effect of soil fumigation on the activities of dehydrogenase, β-glucosidase, acid phosphatase and arylsulfatase varied among the soil enzymes and within the two study sites. At the Watsonville site, soil fumigation with alternative fumigants generally had no significant effect on the activities of the four soil enzymes studied over the two year study period. Fumigation with MeBr + CP however severely affected the activities of β-glucosidase and acid phosphatase . These results suggest that biochemical reactions involved in organic matter degradation and P mineralization were affected by fumigation to a greater extent than were those reactions reflecting the general oxidative capabilities of microbial communities or involved in S mineralization in soils. In contrast, at the Oxnard site, β- glucosidase and acid phosphatase activities were relatively stable towards repeated soil fumigation, but dehydrogenase activity was significantly decreased by MeBr + CP. The reasons for these site-related variations in the response of soil enzyme activities to soil fumigants remain unclear. The two study sites showed very similar soil physical and chemical properties, such as clay and organic C contents. Variations may have occurred in the actual soil moisture content and temperature at the time of fumigation, which were proved to be crucial for the efficacy of pesticide applications . The results also suggest that the four alternative fumigants had no longer-term impact on enzyme reactions involved in organic matter turnover and nutrient cycling in soil. The inhibitory and/or activation effects of any compound in a soil matrix on enzyme activity are largely controlled by the reactivity of clay and humic colloids . The finding that MeBr + CP and the alternative fumigants led to a greater inhibition of the activities of the reference enzymes than that of soils suggests that free enzymes are more sensitive to soil fumigation than enzymes that are associated with the microbial biomass or enzymes adsorbed to clay or humic colloids. Ladd and Butler hypothesized that some enzymes are stabilized in the soil environment by complexes of organic and mineral colloids and therefore are partially protected from denaturation by fumigation. Similar results were observed for acid phosphatase, β-glucosidase and arylsulfatase in chloroform fumigated soils . Furthermore, reference enzymes were purified from one source for each protein, whereas soil enzymes derive from various sources leading to a set of isoenzymes [i.e., enzymes that catalyze the same reaction but may differ in origin, kinetic properties or amino acid sequencing ].

We estimated nitrogen input from biological fixation for soybean

To reflect the trend of farm energy efficiency gains, we adopted the estimates from the widely used GREET model , which shows an efficiency increase of about 30% for corn and soybean growth over the last decade. Few studies exist on cotton and wheat on-farm energy change, thus we assumed a similar 30% efficiency gain for them over the timescale investigated. Note that we did not consider nitrogen from manure considering that it is small relative to other nitrogen sources .Building on our previous studies , we estimated a large number of emissions from all the agricultural inputs applied based on emission factors from various models and references . Most of the emissions are pesticides and speciated Volatile Organic Compounds . Estimation of pesticide emissions was slightly more complicated than that of other emissions, thus a detailed explanation is in order. Several approaches to pesticides emissions have been applied in literature and LCA databases. For example, the Ecoinvent database assumes that all pesticides remain in soil after application . The PestLCI model, on the other hand,plastic grow bag treats agricultural soil as part of the technosphere and excludes the impacts of pesticides on ecosystems in the soil .

And yet there is another approach that estimates pesticide emissions to different compartments . We adopted the third approach here. Following Berthoud et al. , we used a pesticide’s vapor pressure to approximate its air emissions, assumed a generic factor of 0.5% of the total applied for pesticides lost to water systems through runoff and leaching, and assumed the remaining fraction, capped at 85% of the total applied, for pesticides emitted to soil.Last, the data we compiled are at the state level, but given our emphasis on the change of environmental impacts of U.S. agriculture on average we aggregated the state-level results to present totals. We also aggregated the three different types of wheat into one “wheat” by adding up their annual agricultural inputs and outputs. In deriving the impacts per ton of crop produced, we followed previous studies and used 3-year average yield data to reduce annual variation caused by possible extreme weathers such as droughts and floods. For example, 2001 impact per ton for corn was calculated by dividing 2001 impact per ha by the average corn yield of 2000, 2001, and 2002. As Fig. 4.2 reflects, changes in the average irrigation water use from 2002 to 2012 were also moderate for corn, cotton, and wheat, with variations <20% between 2002 and 2007 or between 2002 and 2012. In contrast, a noticeable upward trend can be observed for soybean. Average irrigation water use per ha soybean produced increased by around 50%, from 180 m3 in 2002 to 270 m3 in 2012. On a per ton basis, the percentage increase is 30%, from 4300 to 5600 m3 , due to yield increase over the period. Behind this upward trend are several factors, including the slightly increasing irrigation intensity for irrigated area, but the major contributor is the growth in area irrigated and its share in the total area harvested .

What led to the growth in soybean area irrigated is unclear, however, and further research is needed. Here, we offer a possible explanation. In the past “ethanol decade,” soybean and corn areas substantially expanded, into other cropland and also grassland . Because such marginal land as grassland is on average not as fertile as existing corn or soybean land , irrigation might have been applied to boost or maintain yield. Consequently, as total soybean and corn areas expanded, so also did the area irrigated. In the case of corn, however, although area irrigated grew from 4.0 to 5.4 million ha between 2002 and 2012, its share in the total area harvested only slightly increased . Additionally, irrigation intensity for area irrigated decreased from 1480 to 1234 m3 ha-1 . As a result, average irrigation use per ha or per ton corn produced barely changed from 2002 to 2012. Major contributors include reduced use of herbicides atrazine and acetochlor, and of insecticides terbfos, dimethenamid, and, especially, chlorpyrifos . The downward trend is likely due to the continuous expansion of herbicide resistant and insect-resistant corn, particularly glyphosate tolerant and Btcorn. Since its introduction in 1996, HR corn has now expanded to over 70%of cornfield , resulting in increasing use of glyphosate compounds in place of conventional herbicides like atrazine and acetocholor. In fact, glyphosate and related compounds had gradually surpassed atrazine and other herbicides over the past decade to become the most commonly applied pesticide . As glyphosate compounds are relatively less toxic to ecosystems compared with the replaced herbicides like atrazine and acetochlor , the overall ecotoxicity impact of corn attributable to herbicides decreased moderately between 2001 and 2010. Meanwhile, Bt corn has also dominated U.S. cornfield now , offering both economic and environmental benefits by protecting yield and reducing handling and use of insecticides .

This likely further contributed to the downward trend of corn’s freshwater ecotoxicity impact. Similar to corn, the freshwater ecotoxicity impact of cotton decreased by 60% from 2000 to 2007, due to the reduced use of herbicides chlorpyrifos, lambda–cyhalothrin, and particularly cyfluthrin . Application of cyfluthrin reduced from 11 g ha-1 in 2000 to 4 g ha-1 in 2007. Similar to corn, the downward trend in cotton’s freshwater ecotoxicity impact was attributable to the expansion of HR and Bt varieties, which are now planted 95% and 75% of U.S. cotton field respectively . Our result on decreasing freshwater ecotoxicity impact of corn and cotton due to changes in pesticide use and patterns reinforces previous findings . Unlike corn and cotton, soybean’s freshwater ecotoxicity impact quintupled between 2002 and 2012. HR soybean has also expanded dramatically in the US, now planted on 95% of soybean field . Along with the expansion, application of glyphosatecompounds per ha has increased by over 60% between 2002 and 2012, and now they account for 80% of total pesticides applied in soybean growth. However, the benefits of HR soybean seem to have been entirely offset by the increasing use of insecticides lambdacyhalothrin, cyfluthrin, and chlorpyrifos . This is due to the invasion of soybean aphid, a species native to eastern Asia and first detected in North America in 2000, and application of insecticides has been the primary means of pest management . Since its first detection, soybean aphid had rapidly spread to 30 states in the U.S. by 2009 and become a major source of economic loss in soybean production . As a result, the total quantity of insecticides applied to soybean quadrupled between 2002 and 2012, resulting in a 3-fold increase in soybean’s freshwater ecotoxicity impact. The freshwater ecotoxicity impact of wheat increased by about 40% from 2000 to 2009, attributable partly to increased use of several insecticides including chlorpyrifos, cyfluthrin, beta–cyfluthrin, and lambda–cyhalothrin. Also, pesticide application rate in general increased from 0.45 kg ha-1 in 2000 to 0.88 kg ha-1 in 2009. Unlike the other major crops, however,PE grow bag there is not a clear explanation for the upward trend. One possible reason may be the growing resistance of pests as a result of increasing pesticide use. Further research is needed in this area. We conducted sensitivity analysis to test the robustness of the changes in freshwater ecotoxicity impact, considering that it is our major finding and that large uncertain is involved in the estimation of pesticide emissions and assessment of their ecotoxicity impact . First, the proportion in which pesticides are emitted to water systems was identified as the major contributor to crops’ freshwater ecotoxicity. Literature also shows it may vary greatly, from 5% to 0.1% or even less . We thus built 3 scenarios to test the sensitivity of the ecotoxicity result to different leaching and runoff rates. Additionally, we also tested the sensitivity of the trends to other analytical approaches to pesticide emissions , with one assuming all pesticides to remain in soils and the other excluding the impact of pesticides on agricultural soils. All 5 scenarios are presented in Fig. 4.4, which reinforces the trends identified of freshwater ecotoxicity impact regardless of different runoff and leaching rates and analytical approaches to pesticide emissions. Second, impact assessment of freshwater ecotoxicity is also highly uncertain, with the uncertainty range for TRACI 2.0 being likely 1-2 orders of magnitude . However, detailed information on the distribution of each characterization factor is not available yet, thus a full uncertainty analysis is not feasible at this stage. To further test the robustness of the ecotoxicity results, we applied two other characterization models to evaluate the aquatic ecotoxicity impact of pesticide emissions.

For corn, cotton, and soybean, the other two models confirm the directionality of the changes but generally show a lower magnitude of change . This is due in part to differences in the number of pesticides covered by the three models and in part to differences in the relative ecotoxicity potential they assign to each pesticide. Generally, IMPACT 2002+ and CML 2001 cover a smaller number of pesticides than TRACI 2.0, thus they may not capture all the changes in pesticide use and patterns that are captured by TRACI 2.0. For wheat, however, the three characterization models seem to disagree on the directionality as well as the magnitude of changes. A detailed comparison, together with contribution analysis, is provided in the Appendix C. In this study, we evaluated several non-global environmental impacts of U.S. corn, cotton, soybean, and wheat, and analyzed how they changed in the past decade. Due likely to the increasing adoption of genetically modified varieties, freshwater ecotoxicity impact per ha corn produced declined by around 50% from 2001 to 2010 and per ha cotton produced declined by 60% from 2000 to 2007. Due to the invasion of alien species and increasing use of insecticides, freshwater ecotoxicity impact per ha soybean produced increased by 3-fold from 2002 to 2012. In the meantime, on-farm irrigation water use per ha soybean harvested increased by about 50%. In comparison, other non-global impacts were relatively stable. The major implication of our study is that identifying the underlying drivers of the dynamical mechanisms in agricultural systems would be essential for making informed agricultural decisions and policies, prioritizing LCA data update needs, and interpreting LCA results. By evaluating the relative ecotoxicity potential of a large number of pesticides, we found that the use of GM crops have contributed to substantial declines in corn and cotton’s freshwater ecotoxicity impact. This finding provides an opportunity for better assessing the trade offs between the potential impacts of GM and conventional crops, as opposed to comparisons based mainly on the total quantity of pesticides applied . Additionally, our results suggest that updates on agricultural inventory data can be done selectively, with regular updates needed for impact categories that are highly dynamic, such as pesticide related ecotoxicity. Studies relying on single-year and outdated data may inaccurately portray a crop’s ecotoxicity impact; even just a few years of data age may under or overestimate the ecotoxicity impact. This also implies that we should exercise caution when interpreting an LCA study in which ecotoxicity impact of agricultural processes plays an important role in the overall conclusion. Broadly, our study highlights the importance of understanding the dynamics in the input and output structure of a process or a technology in LCA . The focus of our study was to evaluate how environmental impacts of agriculture might have changed in the past decade. Our results that show decreasing freshwater ecotoxicity impacts for corn and cotton are not intended to prove that GM crops are overall more ecologically friendly than conventional crops. Other impacts of GM crops that could not have been evaluated due to the limitations of the current LCIA methods should also be taken into consideration in such comparisons. Current LCIA methods, for example, are not able to properly evaluate potential adverse effects of Bt toxin on populations of non-target species and elevated risk of species invasiveness through genetic modifications . In addition, it should be noted that the trend of decreasing ecotoxicity impact is unlikely to continue for cotton and corn.

Agricultural imports grew at an average rate of 5.9 percent over the same time period

However, the real value of China’s agricultural trade grew at only 2 percent per year, on average, from 1980 to 1996. The overall composition of China’s agricultural trade is presented in Tables 1 through 3. Tables 1 and 2 report exports and imports, respectively, over the five year 1992-96 time period. For the purposes of summarizing these extensive trade data, we have broken the agricultural trade figures in Tables 1 and 2 into four categories: grains, horticultural products, animal products, and other.China’s total agricultural exports were valued at $10.6 billion in 1996. Exports of grains were valued at $1.4 billion in 1996 and edible oil seeds and oils accounted for most of these grain exports. Maize exports were near zero in 1995 and 1996 . Earlier, in 1992 and 1993, maize exports were much more important and maize alone accounted for 13 percent of total agricultural exports in each of those two years. Prior to the export blockade, grains accounted for over 27 percent of total agricultural exports. In 1996, China’s horticultural exports totaled $5.1 billion, up from $3.5 billion in 1992. As a share of total agricultural exports, horticultural products increased from 39 percent in 1992 to 48 percent in 1996. Fruit and vegetable products are by far the most important component of horticultural exports, followed by “other crops” and vegetables . Exports of animal products also grew over this 1992 to 1996 time period,plastic square flower bucket from $2.0 to $3.4 billion, and from 22 to 33 percent of total agricultural exports. Unlike, grains and horticultural products, no one commodity has dominated animal product exports.

Processed poultry, processed swine, and raw wool were the most valuable exports in 1996 but in total these three commodities accounted for less than 15 percent of animal product exports.Turning to Table 2, we find that China’s agricultural imports grew from $4.9 billion in 1992 to $9.9 billion in 1996. Grains typically make up over one-half the value of imports, with wheat and vegetable oils and fats the major imports. In 1992, wheat plus vegetable oils and fats made up over 40 percent of total agricultural exports, with wheat at 30 percent and vegetable oils/fats at 10 percent. In 1996, these two commodity groups still had a 40 percent share of imports, but wheat’s share fell to 19 percent and vegetable oils/fats increased to 21 percent. From 1992 to 1996, the value of horticultural imports increased from $0.8 to $1.4 billion, but horticultural’s share in total agricultural imports fell from 18 percent to 14 percent over this period. Fruits tend to be the most important horticultural import, but imports are diversified across this product grouping. The share of animal products in total imports also fell over this period from 22 percent to 17 percent . Raw wool is by far the most important item in this group, accounting for over one-half of animal product imports. The data in Table 2 are the official imports and for some commodities they significantly under report the value of trade due to smuggling from Hong Kong. This is especially true for horticultural and animal products and this issue is discussed below.

We can utilize Table 3 to comment on Wang’s finding that China’s pattern of agricultural trade is consistent with its resource endowment, importing land intensive bulk commodities and exporting labor intensive horticultural and consumer ready products. For this purpose, we have aggregated China’s agricultural trade into the same categories defined by Wang : bulk commodities, consumer ready products, horticultural and other food products, and processed intermediary products. The make-up of these four categories is explained in the notes to Table 3.Our database for Table 3 covers the 1992 to 1996 time period, whereas Wang’s analysis was based on 1995 and 1996 data alone. Because of the export blockade, we believe the 1992 to 1994 time period gives a clearer picture of the economic forces within China that are influencing trade patterns, but of course it is still a very short time period. With the information revealed by these additional years, the conclusions by Wang are found to be questionable. Consider the top panel of Table 3. This panel shows that from 1992 to 1994, bulk commodities were indeed an important component of exports, accounting for anywhere from 25% to 29% of China’s exports. As expected, there was a sharp decline in the share of bulk commodity exports in 1995 during the blockade. In 1995 and 1996, China became a net exporter of rice and maize, shifting away from a net exporter position in the 1992-1994 time period. From 1992 to 1996 there was little change in the percentage of exports explained by two of the categories; horticultural and other food products, and processed intermediary products. The pattern of imports over the 1992 to 1996 time period is shown in the bottom panel of Table 3. The most striking result associated with these data is the lack of any trend, measured by the relative import percentages shown in the bottom one-half of the panel. Either bulk commodities or processed intermediary products account for around 90% of China’s official imports of agricultural products. The bulk imports are heavily concentrated in grains, vegetable oils, and cotton. In 1996, these commodities accounted for over 50% of the value of imports. In recent years, China has been the world’s largest importer of cotton, with annual imports average about 800,000 mt.

However, in 1998/99 China will revert to becoming a net cotton exporter. China also has excessive stockpiles of grain and cotton. For instance, for 1998/99, China’s cotton stockpile is estimated to be 3.3 mmt, or 40 percent of the world’s stocks.It is somewhat puzzling that the share of land-intensive agricultural exports such as grain and cotton has not declined, because China does not have a comparative advantage in land-intensive commodities. One possible explanation to this puzzle could lie with the domestic “two-tier” pricing system. The “two-tier” price system may cause trade patterns to diverge from what might be expected from domestic resource endowments and this possibility has not been adequately examined in the literature. The potential trade distortions caused by the domestic pricing policy also has important implications for future trade policy reform. More than 95% of China’s marketed cotton and 50% of the marketed grain6 is procured by the government. Under the “two-tier” pricing system, COFCO in the case of grain, and China’s National Textiles Import and Export Corporation in the case of cotton,plastic plant pot could earn profits from exporting even when the domestic free market price is lower than the world price. COFCO and CHINATEX will have an incentive of export grain and cotton whenever the world price PW > PP + marketing costs + taxes. This is the case even if the domestic free market price PF > PW . This was true in 1993-94 when the domestic free market prices rose significantly as the slowdown in domestic production created excess domestic demand, and at the same time, China’s grain exports reached historical records. In 1993-94, domestic grain prices increased dramatically and the State Grain Bureau could have sold grain into the domestic market to stabilize prices, but instead they increased exports and reduced imports. Partly to override these perverse incentives, the central government eventually imposed a grain export embargo in 1995. More recently,COFCO has exported corn to world markets, even though world prices were below domestic free market prices.7 Figure 1 displays China’s net agricultural exports for four aggregate groups: grains, animal products, horticultural products and “other.” Although there are erratic swings in the value of exports, China continues to be a net exporter of grains . The data in Figure 1 show exports of horticultural products have grown, and these are products where China probably does have a comparative advantage. However, China’s official trade data do not account for smuggling. If net exports of horticultural products were adjusted for imports smuggled into China, the rise in horticultural exports on the part of China would not be so strong. To help illustrate this point with regard to smuggling, Figure 2 shows net exports of fruits and vegetables from China, Hong Kong, and the two combined. We see from Figure 2 that both Hong Kong’s imports and China’s exports of fruits and vegetables have risen significantly in the past ten years. However, China’s exports did drop off in 1996 and 1997.

If we combine the two, we find that the 1997 value of net exports into the region was not much different from that of the late 1980s. China tends to directly import bulk agricultural commodities, whereas a large share of the processed food and consumer ready products are first imported into Hong Kong and then re-exported to mainland China. For example, almost all of the U.S. meat, fruit, and vegetable exports to China are routed through Hong Kong. Despite a relatively small population of only 6 million, Hong Kong imported over $14.2 billion in agricultural products in 1996 more than official imports into mainland China. Hong Kong ranks as one of the top Asian markets for farm products, and it is the second largest Asian market for U.S. horticultural products. As an additional measure of its importance, Hong Kong imports 20 percent of U.S. fruit and vegetable exports and it has been a growing market. However, these imports are not all for domestic consumption purposes and, in fact, Hong Kong officially re-exports about 55 percent of its agricultural imports. There is a large two way trade in agricultural products between Hong Kong and China. Hong Kong’s imports from China include poultry, fruits, vegetables, rice, and nuts. At the same time, Hong Kong exports substantial amounts of poultry, fruits, vegetables, nuts, oil seeds, and cotton to China. In addition to the legal shipments from Hong Kong to China, there is a large illegal trade . Undocumented shipments of fresh fruit may account for up to 70 percent of Hong Kong’s imports . For example, the value of chicken parts smuggled into China alone could amount to over $300 million per year . It is difficult to estimate the total dollar value of undocumented agricultural exports from Hong Kong to China, but it could exceed $1 billion per year. For “other” primary products, the subgroups that were in surplus in 1980-82 accounted for 40.34% of the value of normalized agricultural trade in 1994-96. Of these goods, 15.74% of trade moved to balance by 1994-96 and 10.34% moved to a deficit. Adding up the diagonal elements in Table 5, we find that 44.4% of the trade in manufacturing was persistent, from 1980 to 1996. These results suggest less persistence in “other” primary products trade compared to agricultural trade. Turning to manufacturing, in Table 6, the subgroups that were in surplus in 1980-82 accounted for 31.82% of the value of normalized agricultural trade in 1994-96. Of these goods, 4.93% of trade moved to balance by 1994-96 and 0.81% moved to deficit. Adding up the diagonal elements in Table 6, we find that 65.5% of the trade in manufacturing was persistent, from 1980 to 1996. These results suggest almost as much persistence in manufacturing trade compared to agricultural trade. As a statistical measure of trade persistence, we can use a transformation of the standard chisquared test, Cramer’s C-statistic, suggested by Carolan et. al.. The C-statistic lies between zero and one, with one representing complete association between the beginning and the ending trade balance. From Tables 7, 8 and 9 we find the C-statistic is 0.66 for agriculture, 0.39 for other primary products, and 0.54 for manufactures. These results suggest there was the least change in the trade balances over the 1980-1996 time period for agriculture, because the C-statistic is relatively high. For manufacturing and other primary products the results suggest there was relatively more change in the trade balances over the time period studied, because the C-statistics are lower.Rather than just comparing the beginning and ending time periods, we can construct histograms for agriculture and manufacturing, based on the number of years each subgroup runs a surplus .

We focus on responses from landscape managers and golf course managers

About 60% of respondents are aged 45 and above, and only about 17% are aged 25-35. While this might be the result of the age distribution in the major fields of occupation which are potential CIMIS users, it could also be that the current interface of CIMIS caters less to younger potential users who might seek the data elsewhere. About a quarter of respondents are women, and their share decreases at higher age groups. This probably reflects the changing labor force characteristics in CIMIS related professions over the past few decades. In terms of geographic location, most respondents report only one area of activity, with the San Joaquin Valley leading the count. Figure 2.1 below shows the shares of respondents in each region. Note that we allowed more than one response for location. We ask all respondents to rank each type of data, offered by CIMIS, according to the frequency they search for it. Figure 2.2 shows the breakdown of answers for each of the frequency choices. ET and precipitation are large shares of the “often” column. These shares decrease when moving in the “never” direction. On the other hand, one can observe an opposite trend for insolation , soil temperature, and relative humidity, which seem to be of less interest for respondents. Interestingly, air temperature seems less correlated with the frequency response, with response rate for “often” lower than “sometimes”. This could stem from the use of air temperature data: while irrigation requires using ET data often,flower harvest buckets air temperature data applications might require less frequent data pulls. Respondents seem satisfied with CIMIS services. About 72% of respondents reported using CIMIS at least occasionally.

The user types reporting “often” using CIMIS the most were Agriculture, followed by Golf Course Management and Water Districts. These user types are indeed likely to use CIMIS on a day to day basis, at least for some part of the year. In research and planning, on the other hand, one might use CIMIS to draw data only at an initial stage of a given task. In general terms, of the respondents who report using CIMIS to some extent, 77% say it is at least “moderately important” for their operations, with 22% reporting CIMIS as “extremely important”. The frequency of use and importance scores are positively correlated: frequent users also report high importance of CIMIS to their operations, which makes sense. The correlations between frequency and satisfaction, and between importance and satisfaction, seem less pronounced. There might be users who use CIMIS infrequently, perhaps because only a smaller part of their tasks involve the weather or climate information provided. Nevertheless, they seem satisfied with CIMIS services, as the satisfaction scores are relatively high. We also asked respondents to rank factors which hinder further use of CIMIS. Various answers were provided, given the results of initial surveys, and there was also room to specify other answers. Two main concerns exist, especially for users in agriculture: how reliable is the data and how to integrate it into existing systems and practices. Many growers and consultants in agriculture complement CIMIS with other data sources, such as soil moisture sensors, irrigation logs, and flow meters. Integrating information from multiple sources into decision making is a challenge faced by virtually all growers. 599 respondents, about a quarter of our survey, reported agriculture to be their primary business. Out of these, about half work on one farm, and the rest are consultants of sorts . 89% of respondents in agriculture report using CIMIS to some extent. Growers and consultants were asked to report their total acreage, selecting into pre-determined ranges. Summing these, we have 318,156 acres covered by growers, and almost 3 million acres covered by consultants. Many of the questions for growers and consultants were similar. One notable exception is regarding water use. The team decided not to ask growers how much water they use, fearing that growers would not want to share this information and would not finish the survey. However, consultants were asked how much water their clients use on average. This question was presented in the online survey as a slider bar, with a default at the lower bar , and an option to check a “Not applicable” box.

This box was not checked very often. Instead, it seems like many consultants who did not want to answer this questions left the slider bar at the default value of 0.5 AF/acre. This is a very low value for irrigated crops, and we assume that all these responses are basically non-answers. Ignoring them, the average reported water use is 2.96 AF/acre per year . This seems like a very reasonable distribution for water use in irrigated crops. Indeed, the USDA’s most recent Farm and Ranch Irrigation Survey reports a total of 7,543,928 irrigated acres in California, with a total of 23,488,939 AF of water applied, and a resulting average water use of 3.11 AF/acre, only a minor deviation of the reported average. Given the responses from agricultural consultants, we seem to have captured a very large portion of the drip irrigated acres in California. As a baseline for valuation, we will use the total 2013 drip irrigated acreage from the USDA survey, 2.8 million acres. While some growers might use CIMIS with gravitational or sprinkler systems as well, our understanding of the qualitative and quantitative responses is that CIMIS is mostly important for drip. We exclude the potential of CIMIS values on non-drip acreage, noting that our estimates would therefore be conservative in that sense.Growers in our survey reported an average CIMIS water saving effect of 24.2%. The reported saving rates seem to be distributed evenly among crops and grower acreage. The average water saving rates reported for consultants is 21.5%, a slightly lower rate than the growers, but this difference is not meaningful in an economic or statistical way. Figure 2.3 plots the distributions of reported savings by growers and consultants, with very similar means and medians. Regressing the reported savings rate on all user types, one cannot reject the null hypothesis that the mean water saving effect is equal between growers and consultants with 95% confidence . Since each group deals with different acreages, we interpret this result as lack of substantial economies of scale in water saving by CIMIS. The monetary cost of water saved can be viewed as savings on the intensive margin. One can also consider gains on an extensive margin. The water saved by use of CIMIS is likely to be used in agriculture as well. This means more acres can be grown with the same initial amount of water. The “full” economic value of the water saved by CIMIS in agriculture is the value of agricultural output that can be produced with it on acres not irrigated before. This following analysis includes the economic value of growing alone, without the added values of post-harvest and economic multiplier effects, and probably a safe lower bound. We do not, however, include a counter-factual productivity of non-irrigated land. In California,round flower buckets this is probably range land or acreage that is too sloped for traditional irrigation methods, and therefore of very low economic productivity.

With 1.92 million AF of water saved by CIMIS, and an average use of 2.5 AF/acre by growers , the savings from CIMIS can water an extra 768,000 acres in California. To put this in context, this is about double the total walnut acreage in 2016. Because of economic and technical constraints of water transport, it is hard to determine which crops would be planted in these extra acres. A conservative approximation assumes that the water saved by CIMIS serves to replicate the existing distribution of crops , taking the average value of productivity of an acre as the benchmark. The weighted average of grower revenue per acre in 2016 was $3,757 per acre1 . Multiplying by 768,000 acres, a conservative approximation for the contribution from CIMIS to California’s GDP via agriculture is about $2.89 billion. This number may appear very high, yet this calculation took various conservative assumptions:in the calculation of the water saved, in assuming the value of extra acreage, and in not including post-harvest added value and multiplier effects. To be even more conservative, let us assume that the elasticity of demand for the products grown on these extra acres is -2. That is, an increase of 1% in quantity would drop the price by about 0.5%. This is a reasonable estimate for elasticities of high value crops . The resulting extra income for growers is then about $1.44 billion dollars. CIMIS allows for more precise irrigation, which means not only saving water but also increasing yields: water application can be adjusted to the plant requirements, which might depend on the weather and growing phase. We ask growers and consultants how does CIMIS contribute in increasing yields, ranking from 1 to 5 . How should we quantify these ranked contributions? Taylor, Parker, and Zilberman mention average yield effects of drip irrigation, ranging between 5% and 25% increase in output. This extra yield effect is explained by allowing for more consistent soil humidity and the precision of the irrigation. This aspect of drip depends on weather and ET information, such as the one provided by CIMIS, to assess the water intake by plants and the appropriate amount of water required. We calculate an average yield effect of CIMIS by reconciling the respondent rankings with a portion of the yield effects from drip irrigation. For a lower estimate, rankings between 1 and 3 are attributed 0% yield effect, and the rankings of 4 and 5 get 5%. For a higher estimate, ranking of 1 gets 0% yield increase, ranking of 2 and 3 get 5% yield increase, and the rankings of 4 and 5 get a 10% yield increase. These percent yield effects are then averaged among the respondents. We aggregate growers and consultants with equal weights. 41% of respondents rank the importance of CIMIS for yield effects at 4-5. The low estimate for yield contribution of CIMIS results in 2% output increase, and the higher estimate at 5.9% increase. At a conservative estimate of per-acre income of $3,757 for growers, this represents an extra yearly income of $76 – $222 per acre. For the 2.8 million acres using drip irrigation, this would account for $213 – $622 million yearly from the contribution of CIMIS to yields. Assuming again the demand is elastic with a coefficient of -2, these estimates would halve to $107 – $311 million. Weather data can have quality effects on crops. For example, using ET data and drip irrigation, the quality of tomatoes can be increased by controlled irrigation deficit in proper timing. For tomatoes grown under a contract, reaching threshold quality levels raises the price received by the grower . Another potential use of weather data is in pest control, avoiding not only yield loss but quality degradation as well. These two examples reflect a relationship between quality and price that has long been established in the literature . To assess the contribution of CIMIS to quality, we also asked respondents to rank it from 1 to 5 . We assume that a score of 4-5 represents a quality index resulting in a price increase of 5%. About 45% of all respondents report a score of 4-5. The average price increase due to quality is therefore 2.2%, or $83 per acre. For 2.8 million acres, this results in a total increased revenue of $231 million. Note that this price increase is due to quality improvement, and thus not accompanied by a quantity reduction in our analysis. These are gains from water saving in parks, golf courses, and gardens. They were assessed as a small portion of the total gains from CIMIS in the 1996 report by Parker et al., totaling about $2.3 million . Our current estimate for these gains is much higher. The discrepancy from the 1996 report is due to several factors. First, we believe to have reached out to more respondents in this sector. Second, water prices in California have gone up substantially. Third, there might be more use of CIMIS and smart irrigation planning in the sector compared to 20 years ago.

Farmers need to know that they won’t suffer economically to implement these measures

Future work could explore the genomes of these ASVs to discern why they are important in their respective agricultural systems and test the hypothesis that they serve as keystone species using synthetic communities. Concluding whether adaptive plant-microbe feed backs result in an M × R interaction leading to shifts in other rhizosphere processes is complicated by the importance of poorly understood fungal communities and methodological limitations of this study. Numerous fungal taxa respond to the M × R interaction according to our differential abundance analysis , yet knowledge of these taxa remains limited due in part to the constraints of culture-dependent methods prevalent in the past. Nonetheless, fungi influence inter-kingdom interactions and agriculturally relevant processes in the rhizosphere, and novel molecular biology tools could be used to improve our understanding of key fungal regulators identified in these analyses. Metagenomics and -transcriptomics would facilitate a much more comprehensive analysis of potential functional shifts. A highly useful starting point would be to delve into dynamic variation in microbial genes involved in carbon metabolism and nitrogen cycling in the rhizosphere,30 litre plant pots in combination with root exudate metabolomics and measurements of root N uptake.

Stable isotope labeling and in situ visualization methods could further complement our understanding of how management, plant roots, and their interactive effects shape rhizosphere processes. The scope of this study was intentionally restricted to a single genotype of one crop in two management systems to limit the main sources of variation to the management and rhizosphere effects that were of primary interest, but the limits to inference of this small-scale study must be considered. Other studies in maize have found that strong legacy effects of soil managementhistory are generally acted upon in a similar manner by two maize cultivars and that rhizosphere bacterial community composition varies only slightly among hybrids from different decades of release.Testing whether these limited effects of plant selection hold true for additional contrasting genotypes and genetic groups of maize would further complement this work. Furthermore, variation in root system architecture across crop genotypes might interact with tillage and soil properties responsive to management effects. Management practices such as the inclusion of forage or cover crops planted in stands rather than rows might affect the differentiation of bulk and rhizosphere soil uniquely from systems based on perennial crops, successive plantings of row crops in the same locations, and/or minimal tillage. Study designs incorporating more genotypes, management systems, and cultivation environments would therefore be highly useful to test how results of this study may be extrapolated to other settings. Future studies should also identify functional genes that are upregulated or downregulated in the rhizosphere under specific agricultural management practices.

Whether such functional shifts are adaptive will provide insight into the relationship between agroecology and ecology. Positive eco-evolutionary feed backs resulting in adaptive microbial communities have been described in unmanaged ecosystems, for example, habitat-adapted symbiosis in saline or arid environments. If similar adaptive recruitment can occur with annual crops in the context of agroecosystems, maximizing this process should be added to the list of rhizosphere engineering strategies and targets for G × E breeding screens. Finally, while our results provide evidence that management and plant influence interact to shape microbial communities at one sampling point, we highlight the need to reframe the M × R interaction as a dynamic process. Rhizosphere communities may be more different from one another than bulk soil communities because roots develop right after tillage and fertilization, when management systems are most distinct . Plants are not static entities, but active participants in the ongoing process of rhizosphere recruitment. As an alternative to the “rhizosphere snapshot,” we propose a “rhizosphere symphony” model that acknowledges the active role of root exudates in orchestrating the composition and function of microbial communities. Altered root exudation during development and in response to water and nutrient limitation can upregulate or downregulate microbial taxa and functions, as a conductor brings together different sections of instruments in turn during a symphony.

Although it is unknown whether this plasticity in exudate composition occurs in response to agricultural management, observations of changed exudate quantity and quality in response to soil type and long-term N fertilization suggest that it is possible. Differences in the timing of nutrient availability between management systems, such as delayed N release from cover crop mineralization compared to mineral fertilizer, could thus result in management-system-specific exudate dynamics and rhizosphere microbial communities, i.e., an M × R interaction. If true, this mechanism suggests that we may be able to manipulate the sound of the symphony by talking to the conductor: plant-driven strategies may be instrumental in maximizing beneficial rhizosphere interactions throughout the season.The Elkhorn Slough is located in the Central Monterey Bay area and feeds into the head of the Monterey Submarine Canyon in the newly designated Monterey Bay National Marine Sanctuary. The slough is described by the Department of Fish and Game as “one of the most ecologically important estuarine systems in California” . Elkhorn Slough was designated as an environmentally sensitive habitat in the 1976 California Coastal Plan and over 1400 acres of the slough are in the National Estuarine Research Reserve System. Water quality in the Elkhorn Slough is heavily influenced by both past and present human activities on the land surrounding the slough. This is especially true of agriculture. Non-point source pollutants from farm use of chemical fertilizers and pesticides have been identified as a primary cause of water quality degradation in the Elkhorn Slough. Agriculture is one of the main land uses in the slough watershed with about 26% of the local watershed in agricultural production. Of this land, strawberry production accounts for the greatest area under production . Field testing and monitoring of alternative farming practices that decrease dependence on synthetic chemical inputs has been extremely limited. What is needed is the development of farming systems that are economically as well as environmentally sustainable. The Azevedo Ranch site encompasses 137 acres, approximately 120 of which are currently in strawberry cultivation. The land is jointly owned by The Nature Conservancy and the Monterey County Agricultural and Historical Land Conservancy, whose stated goal is to keep this property in open space in perpetuity. The property will be divided into a wetlands buffer zone surrounding three “pocket marshes,” and an upland agricultural zone. The marshes are separated from the main channel of the slough by a railroad berm. They are connected to tidal water by culverts through the berm,25 liter pot plastic making each independent. The buffer zone, which is currently in cultivation, will be restored with native vegetative cover including native bunch grasses, Coast Live Oaks, and maritime chaparral. The upper agricultural zone will encompass 83 acres and will eventually be converted to low-input sustainable agriculture. The management of the agricultural lands will be guided by an advisory committee, but the overall goal is to develop models, for the greater watershed, of ecologically and economically sustainable methods for crop production.

An additional research site is located on the Elkhorn Slough National Estuarine Research Reserve. The site includes a small pond drained by sloping uplands. It is very similar to the three drainages on the Azevedo ranch, with the important exception that it has never been cultivated. Although the pond is larger than any of the Azevedo marshes and is subject to greater flushing, it provides the opportunity to obtain background data on soils, sediments, and biota in the absence of agricultural disturbances. During the first two years of the study we established critical measurements, protocols, and characterizations of these watersheds under standard cultivation practices. These data will serve as a baseline for comparison once the property is converted to low-input sustainable agricultural management and habitat restoration is completed in the wetland buffer. Conversion and restoration will occur in 2 to 4 years, once the land has been fully paid for. The project is guided by a Technical Advisory Committee which meets monthly. Although this report marks the end of Project Number UCAL-WRC-W-801, the project is ongoing. Our long term goal is the investigation oflinkages between different farm management practices and health of the adjacent slough, as monitored by sedimentation, input of anthropogenic chemicals, water quality, and the response of wetlands flora and fauna. In the future, we will implement and test alternative farming practices that lessen or eliminate the dependence on synthetic chemical inputs. We will also be able to assess the influence of border zones at the land-water margin as buffers between agricultural uplands and estuarine receiving waters. The lead author recently submitted a proposal to the UC Water Resources Center entitled, “Evaluating Vegetated Buffer Zones Between Commercial Strawberry Fields and the Elkhorn Slough Estuary.” Erosion of soils from strawberry fields is a major mechanism of transport of agricultural chemical residues into slough surface waters. About 75% of the anthropogenic erosion in the Eu.horn Slough watershed is attributed to strawberry production . While a background rate of erosion for most soils is about 1 ton/acre/year, erosion from these strawberry lands ranges from 8 to 145 tons/acre/year, with the highest rates occurring during heavy rains. Costs of erosion and sediment damages are estimated at over $3 million/year, or $7911acre of strawberry land . These estimates do not include any factor for environmental damage to the estuary. The Soil Conservation Service has recommended a variety of management practices designed specifically to address the problem of erosion from strawberry fields in the Elkhorn Slough watershed . Unfortunately, many local growers have not yet implemented these practices. A demonstration project can test and report on these and other practices to convince reluctant growers that these techniques work. A recent report on farming practices in the Elkhorn Slough watershed showed that growing practices are strongly correlated with grower ethnicity, and that outreach programs must be targeted for specific under served groups to be effective . Growers apply synthetically and naturally compounded forms of nitrogen, potassium, phosphorous, and other plant nutrients to soils. Some portion of these minerals is taken up by the crop, some is retained in the soil, and some is subject to export from the system through downward leaching, surface runoff, or erosion. Nitrogen, in the form of nitrate, is especially prone to leaching and is a significant problem in groundwater in the Elkhorn Slough watershed. A significant percentage of wells in the Elkhorn Slough watershed are contaminated with unacceptable levels of nitrate . High levels of nitrate in groundwater are associated with agricultural activities, especially strawberry production around the slough. Other nutrients, such as phosphorous, tend to associate closely with soil colloids, and are prone to transport on eroded sediments. There are little or no data to address the potential of fertilizer nutrients being transported into the slough. Research by Broenkow and Smith suggests that tidal water may be the major source of nitrogen in the slough, as local nitrogen concentrations seem to be controlled mainly by the tide. Strong pulses of nitrogen enter the slough after winter rains, but they are soon flushed by the tide. Past measurements have shown low nitrate and phosphate levels in slough water, though no new measurements of slough channel surface water have been made since 1980. Soil water and nitrate movement through the surface soil were studied using porous cup lysimeters. In the first year, twelve lysimeters were installed in the Central Field and six in the grassland control site at the Elkhorn Slough NERR. Lysimeters were place in pairs at one foot and two foot depths to sample the root zone and below the principal root zone. In the crop field, three pairs were placed low on the slope, and three pairs higher up on the slope. In the grassland all three pairs were placed at a similar slope position. First year results showed a great deal of variation in nitrate-nitrogen levels in strawberry bed soil-water. It was not possible to determine the direction of movement or any strong response to seasonality. Furthermore, we found that surface runoff was extremely significant in nutrient loading into the pocket marshes.