Recipient Organization
UNIV OF MARYLAND
(N/A)
COLLEGE PARK,MD 20742
Performing Department
(N/A)
Non Technical Summary
Pollination is a critically important ecosystem service for agriculture, especially for high value crops whose consumption has been rising over time. Both the natural and commercial provision of pollination services are threatened by wild pollinator habitat loss and climate change. In the face of these challenges, it is important to set priorities among efforts aimed at mitigating or reversing pollinator decline. This project will develop methods for determining (a) the value of pollination services by wild and managed pollinators and (b) efficient levels and locations of wild pollinator habitat preservation and managed pollinator stocking rates. We will draw on economic and ecological sources to develop a conceptual framework for evaluating impacts of landscape management and climate change mitigation strategies on pollination services provided by wild and managed pollinators. We will develop novel methods of identifying land use practices, habitat quality, yield, and use of managed pollinators from a combination of remotely sensed data, primary survey data and government microdata. We will use these novel data in an ecological/econometric analysis that estimates an integrated relationship between land use, habitat, pollination and agricultural productivity. We will combine the theoretical and empirical analyses to study how to set priorities for managing pollinator habitat and how those priorities vary across major production regions. This research will advance "ecological approaches to agriculture that balance production and sustainable resource management", a priority for the Environmental and Natural Resource Economics program (A1651).
Animal Health Component
15%
Research Effort Categories
Basic
75%
Applied
15%
Developmental
10%
Goals / Objectives
The overarching goal of this project is to develop methods for determining (a) the benefits of pollination services by wild pollinators and (b) best practices and costs of providing wild pollination services through habitat preservation. We will address this overall goal through four related specific objectives:1. Develop an economic/ecological theoretical framework for understanding interactions among crop production, surrounding landscapes, pollinator conservation, and the provision of pollination services by wild and managed pollinators.2. Develop and apply innovative data and methods for identifying land use practices, habitat quality, use of managed pollinators, and crop yield from a combination of remotely sensed, primary data and government microdata.3. Develop and apply methods for estimating the effects of surrounding landscapes on pollination services and crop yields.4. Conduct cost-benefit analyses of changes in wild pollinator habitat.
Project Methods
Development and analysis of a theoretical framework that embeds pollination services as an input into a standard economic production model. Pollination services will be characterized as intermediate inputs produced by (i) wild pollinators traveling from nearby habitat and (ii) managed pollinators. Wild pollinator habitat and managed pollinator stocking rates will be chosen to maximize profit, which equals crop revenue minus cost. Cash costs include pollination fees paid as well as expenditures on labor, fertilizers, pesticides, machinery, and other production inputs. Land set aside for wild pollinator habitat incurs an opportunity cost in terms of foregone profit from crop production. We will draw on the ecological literature to examine how growers' choices are influenced by environmental as well as economic factors: characteristics of wild pollinator habitat as they relate to pollinator abundance, diversity, foraging behaviors, etc.; distribution of life history traits within pollinator communities; proximity to crop fields; etc.), land values, crop and input prices, climate, and similar factors. The analysis will also investigate the conditions under which profit maximization implies complete reliance on either wild or managed pollinators.Development of new methods to extract land use practices, landscape features that characterize pollinator habitat, managed pollinator use, and crop yields from remotely sensed imagery combined with ecological science and micro-data from USDA. These data are critical for measuring how pollinator density generates pollinator visitation, pollination (including changes due to interactions among wild and managed pollinators), and crop yield. Data to be used include the Cropland Data Layer, other remote sensing data, county-level acreage and yield data from USDA and state sources, and confidential individual acreage and yield data obtained under agreement with NASS.These data will be used to estimate statistically substitution and complementarities between managed and wild pollinators and thus the value of wild pollinators in crop production, including (1) the degree to which farmers are substituting managed pollinators when wild pollinators are insufficient for their pollination needs, and (2) direct estimation of how wild pollinator habitat affects agricultural yields, as well as calculate the implied effects of wild pollinators on agricultural yields. We will evaluate the provision of wild pollinator habitat by using data on land use practices, remotely sensed data on fragmentation, measures of blossom density, and other landscape characteristics related to wild pollinator abundance, diversity, foraging strategies, and other features related to wild pollinator activity.Scenarios of policy and ecological interest will be investigated numerically using the theoretical model parameterized using the results obtained from the statistical analysis. Possible scenarios inclue reductions in (or complete loss of) pollination services from wild pollinators due to habitat loss, climate change, or other changes in wild pollinator community composition; recurrence of Colony Collapse Disorder; and changes in the spread of pollinator disease and parasite infestation. Equilibrium displacement models will then be used to study the effects of these scenarios on prices of selected insect-pollinated crops, the regional distribution of production of those crops, and the well-being of consumers and growers.