Mapping connectivity and conservation opportunity on agricultural lands across the conterminous United States
(2023) In Biological Conservation 278.- Abstract
Depending on management practices, agricultural lands can either pose substantial barriers to species movement or can support landscape connectivity by linking areas of high-quality habitat. Balancing connectivity and sustainable food production on agricultural lands is critical to conservation in the conterminous United States (CONUS) where agriculture makes up close to half of total land area. However, limited guidance exists on where to target conservation resources to maximize benefits for native species and food security. To quantify the potential contribution of agricultural lands to the movement of organisms, we developed a novel method for estimating agricultural management intensity (based on remotely sensed temporal variation... (More)
Depending on management practices, agricultural lands can either pose substantial barriers to species movement or can support landscape connectivity by linking areas of high-quality habitat. Balancing connectivity and sustainable food production on agricultural lands is critical to conservation in the conterminous United States (CONUS) where agriculture makes up close to half of total land area. However, limited guidance exists on where to target conservation resources to maximize benefits for native species and food security. To quantify the potential contribution of agricultural lands to the movement of organisms, we developed a novel method for estimating agricultural management intensity (based on remotely sensed temporal variation in vegetation cover) and incorporated these estimates into a CONUS-wide model of ecological flow connectivity. We combined our connectivity results with data on the productivity, versatility, and resilience of agricultural lands (PVR) to identify conservation opportunities that support both biodiversity and food production. The highest levels of connectivity on agricultural lands occurred on relatively unmodified rangelands and on cropland and pasture surrounded by large amounts of natural land cover. Mapping connectivity and PVR across CONUS revealed 10.2 Mha of agricultural lands (2.7 %) with high value for both connectivity and food production, as well as large amounts of agricultural land (>140 Mha in total) with high value for either cultivation or supporting biodiversity. Drawing on these findings, we provide recommendations on the types of conservation approaches most suitable for a given agricultural system and link these recommendations to specific government incentive programs.
(Less)
- author
- Suraci, Justin P. ; Littlefield, Caitlin E. ; Nicholson, Charlie C. LU ; Hunter, Mitchell C. ; Sorensen, Ann and Dickson, Brett G.
- organization
- publishing date
- 2023-02
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Agroecology, Circuit theory, Conservation planning, Ecological flow, Landscape resistance, Spatial ecology
- in
- Biological Conservation
- volume
- 278
- article number
- 109896
- publisher
- Elsevier
- external identifiers
-
- scopus:85146078898
- ISSN
- 0006-3207
- DOI
- 10.1016/j.biocon.2022.109896
- language
- English
- LU publication?
- yes
- additional info
- Funding Information: This work was supported by Microsoft AI for Earth and by the United States Department of Agriculture's Natural Resources Conservation Service (NRCS) via American Farmland Trust-NRCS Contribution Agreement # 68-3A75-18-005 . Publisher Copyright: © 2023 Elsevier Ltd
- id
- 98d491b7-3399-4be7-804b-8ad79c06c532
- date added to LUP
- 2023-02-09 16:38:39
- date last changed
- 2023-02-21 17:01:29
@article{98d491b7-3399-4be7-804b-8ad79c06c532, abstract = {{<p>Depending on management practices, agricultural lands can either pose substantial barriers to species movement or can support landscape connectivity by linking areas of high-quality habitat. Balancing connectivity and sustainable food production on agricultural lands is critical to conservation in the conterminous United States (CONUS) where agriculture makes up close to half of total land area. However, limited guidance exists on where to target conservation resources to maximize benefits for native species and food security. To quantify the potential contribution of agricultural lands to the movement of organisms, we developed a novel method for estimating agricultural management intensity (based on remotely sensed temporal variation in vegetation cover) and incorporated these estimates into a CONUS-wide model of ecological flow connectivity. We combined our connectivity results with data on the productivity, versatility, and resilience of agricultural lands (PVR) to identify conservation opportunities that support both biodiversity and food production. The highest levels of connectivity on agricultural lands occurred on relatively unmodified rangelands and on cropland and pasture surrounded by large amounts of natural land cover. Mapping connectivity and PVR across CONUS revealed 10.2 Mha of agricultural lands (2.7 %) with high value for both connectivity and food production, as well as large amounts of agricultural land (>140 Mha in total) with high value for either cultivation or supporting biodiversity. Drawing on these findings, we provide recommendations on the types of conservation approaches most suitable for a given agricultural system and link these recommendations to specific government incentive programs.</p>}}, author = {{Suraci, Justin P. and Littlefield, Caitlin E. and Nicholson, Charlie C. and Hunter, Mitchell C. and Sorensen, Ann and Dickson, Brett G.}}, issn = {{0006-3207}}, keywords = {{Agroecology; Circuit theory; Conservation planning; Ecological flow; Landscape resistance; Spatial ecology}}, language = {{eng}}, publisher = {{Elsevier}}, series = {{Biological Conservation}}, title = {{Mapping connectivity and conservation opportunity on agricultural lands across the conterminous United States}}, url = {{http://dx.doi.org/10.1016/j.biocon.2022.109896}}, doi = {{10.1016/j.biocon.2022.109896}}, volume = {{278}}, year = {{2023}}, }