Allan Hollander

Assessment of carbon in woody plants and soil across a vineyard-woodland landscape

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's Contribution to Nitrate Contamination of Californian Groundwater (1945-2005).

Nitrogen (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 (1945-2005). 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) loading over the time period, with 163 Gg N yr now being leached to groundwater from approximately 1.3 million ha of farmland (not including alfalfa [ L.]). Meeting safe drinking water standards would require NO 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.

Tightly-Coupled Plant-Soil Nitrogen Cycling: Comparison of Organic Farms across an Agricultural Landscape.

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.

Integrating ecoinformatics resources on the semantic web

We describe ELVIS (the Ecosystem Location Visualization and Information System), a suite of tools for constructing food webs for a given location. We express both ELVIS input and output data in OWL, thereby enabling its integration with other semantic web resources. In particular, we describe using a Triple Shop application to answer SPARQL queries from a collection of semantic web documents. This is an end-to-end case study of the semantic webs utility for ecological and environmental research.

Sustainable Sourcing of Global Agricultural Raw Materials: Assessing Gaps in Key Impact and Vulnerability Issues and Indicators.

Understanding how to source agricultural raw materials sustainably is challenging in today’s globalized food system given the variety of issues to be considered and the multitude of suggested indicators for representing these issues. Furthermore, stakeholders in the global food system both impact these issues and are themselves vulnerable to these issues, an important duality that is often implied but not explicitly described. The attention given to these issues and conceptual frameworks varies greatly—depending largely on the stakeholder perspective—as does the set of indicators developed to measure them. To better structure these complex relationships and assess any gaps, we collate a comprehensive list of sustainability issues and a database of sustainability indicators to represent them. To assure a breadth of inclusion, the issues are pulled from the following three perspectives: major global sustainability assessments, sustainability communications from global food companies, and conceptual frameworks of sustainable livelihoods from academic publications. These terms are integrated across perspectives using a common vocabulary, classified by their relevance to impacts and vulnerabilities, and categorized into groups by economic, environmental, physical, human, social, and political characteristics. These issues are then associated with over 2,000 sustainability indicators gathered from existing sources. A gap analysis is then performed to determine if particular issues and issue groups are over or underrepresented. This process results in 44 “integrated” issues—24 impact issues and 36 vulnerability issues —that are composed of 318 “component” issues. The gap analysis shows that although every integrated issue is mentioned at least 40% of the time across perspectives, no issue is mentioned more than 70% of the time. A few issues infrequently mentioned across perspectives also have relatively few indicators available to fully represent them. Issues in the impact framework generally have fewer gaps than those in the vulnerability framework.

Potential to assess nitrate leaching vulnerability of irrigated cropland

Irrigated cropland represents the largest source of groundwater nitrate (NO3) pollution in the Central Valley (CV) of California. Mitigation, through the use of best management practices that maximize crop nitrogen use efficiency (NUE), will be most effective in reducing pollution if used where the risk of NO3 leaching loss is greatest. The University of Californias Nitrate Groundwater Pollution Hazard Index (HI) tool was used to map the risk of NO3 leaching below the rootzone in irrigated fields in a portion of the CV. The HI is an expert system that calculates an index value based on soil properties, crop characteristics, and type of irrigation system in use. Depth to groundwater, aquifer recharge rate, and actual farm management practices (e.g., rate of nitrogen [N] fertilizer applied) are not considered in the calculation. Application of the HI to 1,318,000 ha (3,256,848 ac) of irrigated cropland in the four southernmost counties of the CV revealed that 31% of the area is at high risk of NO3 leaching loss if not managed carefully. Adoption of drip or microsprinkler irrigation on all orchards, vineyards, and vegetable fields would decrease the area rated as most vulnerable from 31% to 20% of the area analyzed. Crop fields on permeable soils and/or irrigated by surface gravity methods contributed the most to the area at high risk. The HI can help the USDA, regulatory agencies, and Cooperative Extension target regulatory, research, and education efforts.

Indicators of global sustainable sourcing as a set covering problem: an integrated approach to sustainability

Abstract Sustainability describes a broad set of themes centered on current human uses of the planet’s resources. The multiple uses and users of the term have led to a proliferation of salient issues and associated indicators. We present a new method to systematically link these issues and indicators under two conceptual frameworks of sustainability in order to enable quantitative analyses. We demonstrate this approach with a specific use case focused on the global sourcing of agricultural products. We use the optimization software Marxan in a novel way to develop minimum sets of indicators that provide maximum coverage of sustainability issues. Minimum covering sets were identified and accumulation curves were developed to measure the contribution of each indicator in each set to overall issues coverage. While greater detail in the assessment of each indicator would likely provide more effective sets of indicators, those that were generated provide optimism that this approach can bring better focus to sustainability assessments.

Managing biodiversity under climate change: challenges, frameworks, and tools for adaptation

The myriad challenges facing biodiversity under climate change are reflected in the challenges facing managers planning for these impacts. An ever-expanding number of recommendations and tools for climate change adaptation exist to aid managers in these efforts, yet navigating these various resources can lead to information overload and paralysis in decision-making. Here we provide a synthesis of the key considerations, approaches, and available tools for integrating climate change adaptation into management plans. We discuss principal elements in climate change adaptation—incorporating uncertainty through scenario planning and adaptive management—and review three leading frameworks for incorporating climate change adaptation into place-based biodiversity conservation planning. Finally, we identify the following key questions needed for long-term conservation planning and review the associated tools and techniques needed to address them: (1) How is the climate projected to change in my study area?; (2) How are non-climatic stressors projected to change?; (3) How vulnerable are species to climate change impacts?; (4) How are species ranges likely to respond?; and (5) How are management strategies expected to affect outcomes? In doing so, we aim to aid natural resource managers in navigating the burgeoning field of climate change adaptation planning and provide managers a roadmap for managing biodiversity under climate change.

The Butterfly Effect: An Approach to Web-Based Scientific Data Distribution and Management with Linkages to Climate Data and the Semantic Web

Environmental scientists generating longitudinal data that reliably track changes in biodiversity face additional challenges of data management and dissemination. An open source web framework can be used effectively to manage datasets while making research available at different levels of expertise, including for public environmental education. This chapter discusses the development of a web framework which links long-term butterfly presence/absence data with regional weather data, allowing researchers to investigate the relationship between butterfly populations and climate change, over time. The chapter concludes with a discussion of the semantic web, and how observational and monitoring data can become part of the growing Linked Data project.