Optimal Forest Strategies for Addressing Tradeoffs and Uncertainty in Economic Development under Old-Growth Constraints

In Canada, governments have historically promoted economic development in rural regions by promoting exploitation of natural resources, particularly forests. Forest resources are an economic development driver in many of the more than 80% of native communities located in forest regions. But forests also provide aboriginal people with cultural and spiritual values, and non-timber forest amenities (e.g., biodiversity, wildlife harvests for meat and fur, etc.), that are incompatible with timber exploitation. Some cultural and other amenities can only be satisfied by maintaining a certain amount of timber in an old-growth state. In that case, resource constraints might be too onerous to satisfy development needs. We employ compromise programming and fuzzy programming to identify forest management strategies that best compromise between development and other objectives, applying our models to an aboriginal community in northern Alberta. In addition to describing how mathematical programming techniques can be applied to regional development and forest management, we conclude from the analysis that no management strategy is able to satisfy all of the technical, environmental and social/cultural constraints and, at the same time, offer aboriginal peoples forest-based economic development. Nonetheless, we demonstrate that extant forest management policies can be improved upon.forest-dependent aboriginal communities, boreal forest, compromise and fuzzy programming, sustainability and uncertainty, International Development, Resource /Energy Economics and Policy, R11, Q23, Q01, C61,

Benchmarking impact of nitrogen inputs on grain yield and environmental performance of producer fields in the western US Corn Belt

Benchmarking crop yields against nitrogen (N) input levels can help provide opportunities to improve N ferti-lizer efficiency and reduce N losses on maize in the US Corn Belt by identifying fields most likely to benefit from improved N management practices. Here, we evaluated a large producer database that includes field-level data on yield and applied N inputs from 9280 irrigated and rainfed fields over a 7-year period (2009–2015) in Nebraska (USA). A spatial framework, based on technology extrapolation domains, was used to cluster each field into spatial units with similar climate and soil type that represent 1.3 million ha of US farm land sown annually with maize. Three metrics were employed to evaluate agronomic and environmental performance: partial factor productivity for N inputs (PFPN, ratio between yield and N inputs), N balance (difference between N inputs and grain N removal), and yield-scaled N balance (ratio between N balance and yield). Nitrogen inputs included N from fertilizer and N contained in applied irrigation water. Average yield and N inputs were 40 and 44% higher in irrigated versus rainfed fields. The N balance was ca. 2-fold greater in irrigated versus rainfed fields (81 versus 41 kg N ha−1). Of the total number of field-years, 58% (irrigated) and 15% (rainfed) had N balance ≥ 75 kg N ha−1, which was considered a threshold to identify fields with potentially large N losses. Very large (\u3e 150 kg N ha−1) and negative N balance estimates were not apparent when analysis was based on field averages using a minimum of three years\u27 data instead of individual field-years. Nitrogen balance was smaller for maize crops following soybean compared to continuous maize. Despite the larger N balance (on an area basis), irrigated fields exhibited smaller yield-scaled N balance relative to rainfed fields. The approach proposed here can readily be adopted to benchmark current use of N fertilizer for other cereal-based crop systems, inform policy, and identify opportunities for improvement in N management

Benchmarking impact of nitrogen inputs on grain yield and environmental performance of producer fields in the western US Corn Belt

Benchmarking crop yields against nitrogen (N) input levels can help provide opportunities to improve N ferti-lizer efficiency and reduce N losses on maize in the US Corn Belt by identifying fields most likely to benefit from improved N management practices. Here, we evaluated a large producer database that includes field-level data on yield and applied N inputs from 9280 irrigated and rainfed fields over a 7-year period (2009–2015) in Nebraska (USA). A spatial framework, based on technology extrapolation domains, was used to cluster each field into spatial units with similar climate and soil type that represent 1.3 million ha of US farm land sown annually with maize. Three metrics were employed to evaluate agronomic and environmental performance: partial factor productivity for N inputs (PFPN, ratio between yield and N inputs), N balance (difference between N inputs and grain N removal), and yield-scaled N balance (ratio between N balance and yield). Nitrogen inputs included N from fertilizer and N contained in applied irrigation water. Average yield and N inputs were 40 and 44% higher in irrigated versus rainfed fields. The N balance was ca. 2-fold greater in irrigated versus rainfed fields (81 versus 41 kg N ha−1). Of the total number of field-years, 58% (irrigated) and 15% (rainfed) had N balance ≥ 75 kg N ha−1, which was considered a threshold to identify fields with potentially large N losses. Very large (\u3e 150 kg N ha−1) and negative N balance estimates were not apparent when analysis was based on field averages using a minimum of three years\u27 data instead of individual field-years. Nitrogen balance was smaller for maize crops following soybean compared to continuous maize. Despite the larger N balance (on an area basis), irrigated fields exhibited smaller yield-scaled N balance relative to rainfed fields. The approach proposed here can readily be adopted to benchmark current use of N fertilizer for other cereal-based crop systems, inform policy, and identify opportunities for improvement in N management

A Research Road Map for Responsible Use of Agricultural Nitrogen

Nitrogen (N) is an essential but generally limiting nutrient for biological systems. Development of the Haber-Bosch industrial process for ammonia synthesis helped to relieve N limitation of agricultural production, fueling the Green Revolution and reducing hunger. However, the massive use of industrial N fertilizer has doubled the N moving through the global N cycle with dramatic environmental consequences that threaten planetary health. Thus, there is an urgent need to reduce losses of reactive N from agriculture, while ensuring sufficient N inputs for food security. Here we review current knowledge related to N use efficiency (NUE) in agriculture and identify research opportunities in the areas of agronomy, plant breeding, biological N fixation (BNF), soil N cycling, and modeling to achieve responsible, sustainable use of N in agriculture. Amongst these opportunities, improved agricultural practices that synchronize crop N demand with soil N availability are low-hanging fruit. Crop breeding that targets root and shoot physiological processes will likely increase N uptake and utilization of soil N, while breeding for BNF effectiveness in legumes will enhance overall system NUE. Likewise, engineering of novel N-fixing symbioses in non-legumes could reduce the need for chemical fertilizers in agroecosystems but is a much longer-term goal. The use of simulation modeling to conceptualize the complex, interwoven processes that affect agroecosystem NUE, along with multi-objective optimization, will also accelerate NUE gains

Upstream Solutions to Downstream Problems: Investing in Rural Natural Infrastructure for Water Quality Improvement and Flood Risk Mitigation

Communities across the globe are experiencing degraded water quality as well as inland flooding, and these problems are anticipated to worsen with climate change. We review the evidence that implementing natural infrastructure in upstream agricultural landscapes could improve water quality and reduce flood risk for downstream communities. Based on our analysis, we identify a suite of natural infrastructure measures that provide the greatest benefits, and which could be prioritized for investment by downstream communities and regional leadership, with an emphasis on systems that minimize loss of productive agricultural land. Our results suggest that the restoration of wetlands and floodplains are likely to provide the greatest benefits for both water quality improvement and flood risk reduction

Optimal Forest Strategies for Addressing Tradeoffs and Uncertainty in Economic Development under Old-Growth Constraints

In Canada, governments have historically promoted economic development in rural regions by promoting exploitation of natural resources, particularly forests. Forest resources are an economic development driver in many of the more than 80% of native communities located in forest regions. But forests also provide aboriginal people with cultural and spiritual values, and non-timber forest amenities (e.g., biodiversity, wildlife harvests for meat and fur, etc.), that are incompatible with timber exploitation. Some cultural and other amenities can only be satisfied by maintaining a certain amount of timber in an old-growth state. In that case, resource constraints might be too onerous to satisfy development needs. We employ compromise programming and fuzzy programming to identify forest management strategies that best compromise between development and other objectives, applying our models to an aboriginal community in northern Alberta. In addition to describing how mathematical programming techniques can be applied to regional development and forest management, we conclude from the analysis that no management strategy is able to satisfy all of the technical, environmental and social/cultural constraints and, at the same time, offer aboriginal peoples forest-based economic development. Nonetheless, we demonstrate that extant forest management policies can be improved upon

Hobby Farms and British Columbia'a Agricultural Land Reserve

Agricultural land protection near the urban-rural fringe is a goal of many jurisdictions, including British Columbia, Canada, which uses a provincial-wide zoning scheme to prevent subdivisions and non-agricultural uses of the land. Preferential taxes are also used to encourage agricultural use of the land. Small scale hobby farmers are present at the urban fringe near Victoria (the capital), both inside and outside of the Agricultural Land Reserve (ALR). The goal of this paper is to investigate whether hobby farms create problems for agricultural land preservation. We make use of a GIS (geographic information system) model to construct detailed spatial variables and analyse our parcel-level data set using an hedonic pricing model and a limited dependent variable model. The results show that hobby farmers tend to select small parcels that are near open space and relatively close to the city and they tend to support horses and other livestock. In terms of price, farmland is worth more per ha the smaller the parcel is and the closer it is to the city. In general farmland is worth more when it is less fragmented but this appears to be reversed for hobby farms – indicating that hobby farmers may be better adapted to surviving in the urban fringe than conventional farmers. The conclusions drawn from the results in this paper would likely apply to other jurisdictions which seek to protect agricultural land in the urban fringe