A B S T R A C TTo examine management options for biodiversity in agricultural landscapes, eight research regions were classified into social-ecological domains, using a dataset of indicators of livelihood resources, i.e., capital assets. Potential interventions for biodiversity-based agriculture were then compared among landscapes and domains. The approach combined literature review with expert judgment by researchers working in each landscape. Each landscape was described for land use, rural livelihoods and attitudes of social actors toward biodiversity and intensification of agriculture. Principal components analysis of 40 indicators of natural, human, social, financial and physical capital for the eight landscapes showed a loss of biodiversity associated with high-input agricultural intensification. High levels of natural capital (e.g. indicators of wildland biodiversity conservation and agrobiodiversity for human needs) were positively associated with indicators of human capital, including knowledge of the flora and fauna and knowledge sharing among farmers. Three social-ecological domains were identified across the eight landscapes (Tropical Agriculture-Forest Matrix, Tropical Degrading Agroecosystem, and Temperate High-Input Commodity Agriculture) using hierarchical clustering of the indicator values. Each domain shared a set of interventions for biodiversity-based agriculture and ecological intensification that could also increase food security in the impoverished landscapes. Implementation of interventions differed greatly among the landscapes, e.g. financial capital for new farming practices in the Intensive Agriculture domain vs. developing market value chains in the other domains. This exploratory study suggests that indicators of knowledge systems should receive greater emphasis in the monitoring of biodiversity and ecosystem services, and that inventories of assets at the landscape level can inform adaptive management of agrobiodiversity-based interventions.ß
895Nitrogen (N) use in intensive agriculture can degrade groundwater resources. However, considerable time lags between groundwater recharge and extraction complicate source attribution and remedial responses. We construct a historic N mass balance of two agricultural regions of California to understand trends and drivers of past and present N loading to groundwater . Changes in groundwater N loading result from historic changes in three factors: the extent of agriculture (cropland area and livestock herd increased 120 and 800%, respectively), the intensity of agriculture (synthetic and manure waste effluent N input rates increased by 525 and 1500%, respectively), and the efficiency of agriculture (crop and milk production per unit of N input increased by 25 and 19%, respectively). The net consequence has been a greater-than-order-of-magnitude increase in nitrate (NO 3 -) loading over the time period, with 163 Gg N yr -1 now being leached to groundwater from approximately 1.3 million ha of farmland (not including alfalfa [Medicago sativa L.]). Meeting safe drinking water standards would require NO 3 -leaching reductions of over 70% from current levels through reductions in excess manure applications, which accounts for nearly half of all groundwater N loading, and through synthetic N management improvements. This represents a broad challenge given current economic and technical conditions of California farming if farm productivity is to be maintained. The findings illustrate the growing tension-characteristic of agricultural regions globally-between intensifying food, feed, fiber, and biofuel production and preserving clean water.
BackgroundQuantification of ecosystem services, such as carbon (C) storage, can demonstrate the benefits of managing for both production and habitat conservation in agricultural landscapes. In this study, we evaluated C stocks and woody plant diversity across vineyard blocks and adjoining woodland ecosystems (wildlands) for an organic vineyard in northern California. Carbon was measured in soil from 44 one m deep pits, and in aboveground woody biomass from 93 vegetation plots. These data were combined with physical landscape variables to model C stocks using a geographic information system and multivariate linear regression.ResultsField data showed wildlands to be heterogeneous in both C stocks and woody tree diversity, reflecting the mosaic of several different vegetation types, and storing on average 36.8 Mg C/ha in aboveground woody biomass and 89.3 Mg C/ha in soil. Not surprisingly, vineyard blocks showed less variation in above- and belowground C, with an average of 3.0 and 84.1 Mg C/ha, respectively.ConclusionsThis research demonstrates that vineyards managed with practices that conserve some fraction of adjoining wildlands yield benefits for increasing overall C stocks and species and habitat diversity in integrated agricultural landscapes. For such complex landscapes, high resolution spatial modeling is challenging and requires accurate characterization of the landscape by vegetation type, physical structure, sufficient sampling, and allometric equations that relate tree species to each landscape. Geographic information systems and remote sensing techniques are useful for integrating the above variables into an analysis platform to estimate C stocks in these working landscapes, thereby helping land managers qualify for greenhouse gas mitigation credits. Carbon policy in California, however, shows a lack of focus on C stocks compared to emissions, and on agriculture compared to other sectors. Correcting these policy shortcomings could create incentives for ecosystem service provision, including C storage, as well as encourage better farm stewardship and habitat conservation.
Agriculture in the Central Valley of California, one of the USA's main sources of fruits, nuts, and vegetables, is highly vulnerable to climate change impacts in the next 50 years. This interdisciplinary case study in Yolo County shows the urgency for building adaptation strategies to climate change. Climate change and the effects of greenhouse gas emissions are complex, and several of the county's current crops will be less viable in 2050. The study uses a variety of methods to assemble information relevant to Yolo County's agriculture, including literature reviews, models, geographic information system analysis, interviews with agency personnel, and a survey of farmers. Potential adaptation and mitigation responses by growers include changes in crop taxa, irrigation methods, fertilization practices, tillage practices, and land use. On a regional basis, planning must consider the vulnerability of agricultural production and the tradeoffs associated with diversified farmlands, drought, flooding of cropland, loss of habitat for wild species of concern, and urbanization.
How farming systems supply sufficient nitrogen (N) for high yields but with reduced N losses is a central challenge for reducing the tradeoffs often associated with N cycling in agriculture. Variability in soil organic matter and management of organic farms across an agricultural landscape may yield insights for improving N cycling and for evaluating novel indicators of N availability. We assessed yields, plant-soil N cycling, and root expression of N metabolism genes across a representative set of organic fields growing Roma-type tomatoes (Solanum lycopersicum L.) in an intensively-managed agricultural landscape in California, USA. The fields spanned a three-fold range of soil carbon (C) and N but had similar soil types, texture, and pH. Organic tomato yields ranged from 22.9 to 120.1 Mg ha-1 with a mean similar to the county average (86.1 Mg ha-1), which included mostly conventionally-grown tomatoes. Substantial variability in soil inorganic N concentrations, tomato N, and root gene expression indicated a range of possible tradeoffs between yields and potential for N losses across the fields. Fields showing evidence of tightly-coupled plant-soil N cycling, a desirable scenario in which high crop yields are supported by adequate N availability but low potential for N loss, had the highest total and labile soil C and N and received organic matter inputs with a range of N availability. In these fields, elevated expression of a key gene involved in root N assimilation, cytosolic glutamine synthetase GS1, confirmed that plant N assimilation was high even when inorganic N pools were low. Thus tightly-coupled N cycling occurred on several working organic farms. Novel combinations of N cycling indicators (i.e. inorganic N along with soil microbial activity and root gene expression for N assimilation) would support adaptive management for improved N cycling on organic as well as conventional farms, especially when plant-soil N cycling is rapid.
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