Climate-Wise Habitat Connectivity Takes Sustained Stakeholder Engagement
Abstract
:1. Introduction
Bridging the Gap through Sustained Engagement
- How did the climate benefits of priority corridors identified by stakeholders at the project outset compare with the final corridors prioritized through the co-production process?
- How did other characteristics of the corridors change throughout the process?
- How does the composition of the participating stakeholders influence the outcomes of the corridors?
2. Materials and Methods
2.1. Project Area
2.2. Project Framework
2.3. The Mayacamas to Berryessa Connectivity Network and Partners
- Partner organization (10): Staff from organizations working to preserve and protect open space and natural resources in the counties of Napa, Lake, and Sonoma. Land trusts (3), open space and park districts (2), non-profit organizations (2), a federal agency (1), and university research reserves (2). With the exception of the federal agency the ongoing efforts of partner organizations were restricted to locations within their county boundary.
- Stakeholders (17): Practitioners at partner organizations who worked in one of the following six primary roles: land and resource management (6), conservation planning (6), data analysis (2), operations (1), research (1), and stewardship (1).
- Researchers (3): Academic and non-profit scientists who served as subject matter experts in landscape ecology and climate-wise connectivity, geospatial modeling, and hydrology.
- Managers (3): Members of the backbone organization, also trained scientists, who facilitated stakeholder engagement and project management.
2.4. Stakeholder Engagement
3. Results
3.1. Ecological Objectives
3.2. Corridor Prioritization
3.3. Cooling Benefits
3.4. Outputs to Support Corridor Implementation
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- United Nations. The Sustainable Development Goals Report; United Nations Publications: New York, NY, USA, 2020.
- Beier, P.; Spencer, W.; Baldwin, R.; Mcrae, B. Toward Best Practices for Developing Regional Connectivity Maps. Conserv. Biol. 2011, 25, 879–892. [Google Scholar] [CrossRef] [PubMed]
- Hilty, J.; Worboys, G.; Keeley, A.; Woodley, S.; Lausche, B.; Locke, H.; Carr, M.; Pulsford, I.; Pittock, J.; White, W.; et al. Guidance for Conserving Connectivity Through Ecological Networks and Corridors; International Union for Conservation of Nature: Gland, Switzerland, 2020. [Google Scholar]
- Olds, A.D.; Connolly, R.M.; Pitt, K.A.; Pittman, S.J.; Maxwell, P.S.; Huijbers, C.M.; Moore, B.R.; Albert, S.; Rissik, D.; Babcock, R.C.; et al. Quantifying the conservation value of seascape connectivity: A global synthesis. Glob. Ecol. Biogeogr. 2016, 25, 3–15. [Google Scholar] [CrossRef]
- Gaüzère, P.; Jiguet, F.; Devictor, V. Can protected areas mitigate the impacts of climate change on bird’s species and communities? Divers. Distrib. 2016, 22, 625–637. [Google Scholar] [CrossRef] [Green Version]
- Thomas, C.D.; Gillingham, P.K. The performance of protected areas for biodiversity under climate change. Biol. J. Linn. Soc. 2015, 115, 718–730. [Google Scholar] [CrossRef]
- Watson, J.E.M.; Dudley, N.; Segan, D.B.; Hockings, M. The performance and potential of protected areas. Nature 2014, 515, 67–73. [Google Scholar] [CrossRef]
- Elsen, P.R.; Monahan, W.B.; Dougherty, E.R.; Merenlender, A.M. Keeping pace with climate change in global terrestrial protected areas. Sci. Adv. 2020, 6, eaay0814. [Google Scholar] [CrossRef]
- Pecl, G.T.; Araujo, M.B.; Bell, J.D.; Blanchard, J.; Bonebrake, T.C.; Chen, I.-C.; Clark, T.D.; Colwell, R.K.; Danielsen, F.; Evengard, B.; et al. Biodiversity redistribution under climate change: Impacts on ecosystems and human well-being. Science 2017, 355, 1–9. [Google Scholar] [CrossRef]
- Chen, I.; Hill, J.K.; Ohlemüller, R.; Roy, D.B.; Thomas, C.D. Rapid Range Shifts of Species Associated with High Levels of Climate Warming. Science 2011, 333, 1024–1026. [Google Scholar] [CrossRef]
- Scheffers, B.R.; De Meester, L.; Bridge, T.C.L.; Hoffmann, A.A.; Pandolfi, J.M.; Corlett, R.T.; Butchart, S.H.M.; Pearce-Kelly, P.; Kovacs, K.M.; Dudgeon, D.; et al. The broad footprint of climate change from genes to biomes to people. Science 2016, 354, aaf7671. [Google Scholar] [CrossRef]
- Holsinger, L.; Parks, S.A.; Parisien, M.; Miller, C.; Batllori, E.; Moritz, M.A. Climate change likely to reshape vegetation in North America’s largest protected areas. Conserv. Sci. Pr. 2019, 1, 1–17. [Google Scholar] [CrossRef]
- Krosby, M.; Tewksbury, J.; Haddad, N.; Hoekstra, J. Ecological Connectivity for a Changing Climate. Conserv. Biol. 2010, 24, 1686–1689. [Google Scholar] [CrossRef] [PubMed]
- Coronato, M.; Prezioso, M. The Network of Protected Areas (NPA) as an Instrument to Implement Cross-Border Public Services. Urban Sci. 2019, 3, 97. [Google Scholar] [CrossRef] [Green Version]
- Heller, N.E.; Zavaleta, E.S. Biodiversity management in the face of climate change: A review of 22 years of recommendations. Biol. Conserv. 2009, 142, 14–32. [Google Scholar] [CrossRef]
- Saura, S.; Bertzky, B.; Bastin, L.; Battistella, L.; Mandrici, A.; Dubois, G. Protected area connectivity: Shortfalls in global targets and country-level priorities. Biol. Conserv. 2018, 219, 53–67. [Google Scholar] [CrossRef] [PubMed]
- Hilty, J.A.; Keeley, A.T.H.; Lidicker, W.Z.; Merenlender, A.M. Corridor Ecology: Linking Landscapes for Biodiversity Conservation and Climate Adaptation, 2nd ed.; Island Press: Washington, DC, USA, 2019. [Google Scholar]
- Keeley, A.; Ackerly, D.; Cameron, D.; Heller, N.; Huber, P.; Schloss, C.; Thorne, J.; Merenlender, A. New concepts, models, and assessments of climate-wise connectivity. Environ. Res. Lett. 2018, 13, 073002. [Google Scholar] [CrossRef]
- Reside, A.E.; Butt, N.; Adams, V.M. Adapting systematic conservation planning for climate change. Biodivers. Conserv. 2018, 27, 1–29. [Google Scholar] [CrossRef]
- Keeley, A.T.H.; Basson, G.; Cameron, D.R.; Heller, N.E.; Huber, P.R.; Schloss, C.A.; Thorne, J.H.; Merenlender, A.M. Making habitat connectivity a reality. Conserv. Biol. 2018, 32, 1221–1232. [Google Scholar] [CrossRef]
- Cash, D.W.; Clark, W.C.; Alcock, F.; Dickson, N.M.; Eckley, N.; Guston, D.H.; Jäger, J.; Mitchell, R.B. Knowledge systems for sustainable development. Proc. Natl. Acad. Sci. USA 2003, 100, 8086–8091. [Google Scholar] [CrossRef] [Green Version]
- Tiemann, S.; Siebert, R. Ecological Networks Implemented by Participatory Approaches as a Response to Landscape Fragmentation-A Review of German Literature. In Proceedings of the 8th European IFSA Symposium, Clermont-Ferrand, France, 6–10 July 2008; pp. 529–539. [Google Scholar]
- Hansen, A.J.; Rasker, R.; Maxwell, B.; Rotella, J.J.; Johnson, J.D.; Wright, P.A.; Langner, U.; Cohen, W.B.; Lawrence, R.L.; Kraska, M.P.V. Ecological causes and consequences of demographic change in the new west. Bioscience 2002, 52, 151–162. [Google Scholar] [CrossRef] [Green Version]
- Beunen, R.; Hagens, J. The Use of the Concept of Ecological Networks in Nature Conservation Policies and Planning Practices The implementation of Natura 2000 View project 2020: Published special issue in European Planning Studies View project. Landsc. Res. 2009, 34, 563–580. [Google Scholar] [CrossRef]
- Botts, E.A.; Pence, G.; Holness, S.; Sink, K.; Skowno, A.; Driver, A.; Harris, L.R.; Desmet, P.; Escott, B.; Lötter, M.; et al. Practical actions for applied systematic conservation planning. Conserv. Biol. 2019, 33, 1235–1246. [Google Scholar] [CrossRef] [PubMed]
- Keeley, A.T.H.; Beier, P.; Creech, T.; Jones, K.; Jongman, R.H.G.; Stonecipher, G.; Tabor, G.M. Thirty years of connectivity conservation planning: An assessment of factors influencing plan implementation. Environ. Res. Lett. 2019, 14, 103001. [Google Scholar] [CrossRef]
- Cook, C.N.; Mascia, M.B.; Schwartz, M.W.; Possingham, H.P.; Fuller, R.A. Achieving conservation science that bridges the knowledge-action boundary. Conserv. Biol. 2013, 27, 669–678. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sarewitz, D.; Pielke, R.A. The neglected heart of science policy: Reconciling supply of and demand for science. Environ. Sci. Policy 2007, 10, 5–16. [Google Scholar] [CrossRef]
- Knight, A.T.; Cowling, R.M.; Rouget, M.; Balmford, A.; Lombard, A.T.; Campbell, B.M. Knowing But Not Doing: Selecting Priority Conservation Areas and the Research—Implementation Gap. Conserv. Biol. 2008, 22, 610–617. [Google Scholar] [CrossRef]
- Venter, O.; Sanderson, E.W.; Magrach, A.; Allan, J.R.; Beher, J.; Jones, K.R.; Possingham, H.P.; Laurance, W.F.; Wood, P.; Fekete, B.M.; et al. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nat. Commun. 2016, 7, 1–11. [Google Scholar] [CrossRef] [Green Version]
- Theobald, D.M.; Kennedy, C.; Chen, B.; Oakleaf, J.; Baruch-Mordo, S.; Kiesecker, J. Earth transformed: Detailed mapping of global human modification from 1990 to 2017. Earth Syst. Sci. Data Discuss. 2020, 12, 1953–1972. [Google Scholar] [CrossRef]
- Pressey, R.L.; Bottrill, M. Approaches to landscape-and seascape-scale conservation planning: Convergence, contrasts and challenges. Oryx 2009, 464–475. [Google Scholar] [CrossRef] [Green Version]
- Knight, A.T.; Cowling, R.M.; Boshoff, A.F.; Wilson, S.L.; Pierce, S.M. Walking in STEP: Lessons for linking spatial prioritisations to implementation strategies. Biol. Conserv. 2011, 144, 202–211. [Google Scholar] [CrossRef]
- Fisher, J.R.B.; Dills, B. Do Private Conservation Activities Match Science-Based Conservation Priorities? PLoS ONE 2012, 7, e46429. [Google Scholar] [CrossRef] [Green Version]
- Sinclair, S.P.; Milner-Gulland, E.J.; Smith, R.J.; McIntosh, E.J.; Possingham, H.P.; Vercammen, A.; Knight, A.T. The use, and usefulness, of spatial conservation prioritizations. Conserv. Lett. 2018, 11, e12459. [Google Scholar] [CrossRef]
- Guston, D.H. Boundary Organizations in Environmental Policy and Science: An Introduction. Sci. Technol. Hum. Values 2001, 26, 399–408. [Google Scholar] [CrossRef] [Green Version]
- Wall, T.U.; Meadow, A.M.; Horganic, A. Developing evaluation indicators to improve the process of coproducing usable climate science. Weather. Clim. Soc. 2017, 9, 95–107. [Google Scholar] [CrossRef] [Green Version]
- Buizer, J.; Jacobs, K.; Cash, D. Making short-term climate forecasts useful: Linking science and action. Proc. Natl. Acad. Sci. USA 2016, 113, 4597–4602. [Google Scholar] [CrossRef] [Green Version]
- Cash, D.W.; Borck, J.C.; Patt, A.G. Countering the Loading-Dock Approach to Linking Science and Decision Making: Comparative Analysis of El Niño/Southern Oscillation (ENSO) Forecasting Systems. Sci. Technol. Hum. Values 2006, 31, 465–494. [Google Scholar] [CrossRef]
- Lemos, M.C.; Kirchhoff, C.J.; Ramprasad, V. Narrowing the climate information usability gap. Nat. Clim. Chang. 2012, 2, 789–794. [Google Scholar] [CrossRef]
- Lemos, M.C.; Morehouse, B.J. The co-production of science and policy in integrated climate assessments. Glob. Environ. Chang. 2005, 15, 57–68. [Google Scholar] [CrossRef]
- Meadow, A.M.; Ferguson, D.B.; Guido, Z.; Horangic, A.; Owen, G.; Wall, T. Moving toward the deliberate coproduction of climate science knowledge. Weather. Clim. Soc. 2015, 7, 179–191. [Google Scholar] [CrossRef] [Green Version]
- Latta, S.C. Conservation in Practice Making the Leap from Researcher to Planner: Lessons from Avian Conservation Planning in the Dominican Republic. Conservation Biology 2000, 14, 132–139. [Google Scholar] [CrossRef] [Green Version]
- Susskind, L.; Camacho, A.E.; Schenk, T. A critical assessment of collaborative adaptive management in practice. J. Appl. Ecol. 2012, 49, 47–51. [Google Scholar] [CrossRef]
- Wood, K.A.; Stillman, R.A.; Goss-Custard, J.D. Co-Creation of Individual-Based Models by Practitioners and Modellers to Inform Environmental Decision-Making. J. Appl. Ecol. 2015, 52, 810–815. [Google Scholar] [CrossRef] [Green Version]
- Reed, M.G.; Abernethy, P. Facilitating Co-Production of Transdisciplinary Knowledge for Sustainability: Working with Canadian Biosphere Reserve Practitioners. Soc. Nat. Resour. 2018, 31, 39–56. [Google Scholar] [CrossRef]
- Klempin, S. Establishing the Backbone: An Underexplored Facet of Collective Impact Efforts. CCRC Res. Br. 2016, 60, 1–6. [Google Scholar]
- Wyborn, C.A. Connecting knowledge with action through coproductive capacities: Adaptive governance and connectivity conservation. Ecol. Soc. 2015, 20. [Google Scholar] [CrossRef] [Green Version]
- Kirchhoff, C.J.; Esselman, R.; Brown, D. Boundary organizations to boundary chains: Prospects for advancing climate science application. Clim. Risk Manag. 2015, 9, 20–29. [Google Scholar] [CrossRef] [Green Version]
- Gray, M.; Micheli, E.R.; Comendant, T.; Merenlender, A.M. Quantifying climate-wise connectivity across a topographically diverse landscape. Land 2020, 9, 355. [Google Scholar] [CrossRef]
- U.S. Census Bureau City and Town Population Totals: 2010-2019 (Census 2010 Population). Available online: https://www.census.gov/data.html (accessed on 26 October 2020).
- Myers, N.; Mittermeier, R.A.; Mittermeier, C.G.; da Fonseca, G.A.B.; Kent, J. Biodiversity hotspots for conservation priorities. Nature 2000, 403, 853–858. [Google Scholar] [CrossRef] [PubMed]
- Bay Area Open Space Council. The Conservation Lands Network 2.0 Report; Bay Area Open Space Council: Berkeley, CA, USA, 2019. [Google Scholar]
- Greeninfo Network California Protected Areas Database (Version 2017a). Available online: https://www.lacounts.org/dataset/california-protected-areas-database-2017a (accessed on 25 September 2020).
- Greeninfo Network California Conservation Easement Database (Version 2016). Available online: https://www.greeninfo.org/work/project/cpad-the-california-protected-areas-database (accessed on 25 September 2020).
- Dudley, N.; Shadie, P.; Stolton, S. Guidelines for Applying Protected Area Management Categories; IUCN: Grand, Swiss, 2013. [Google Scholar]
- Critical Linkages: Bay Area & Beyond. Available online: https://www.bayarealands.org/?crb_render_featured_project=yes&crb_popup_index=30. (accessed on 25 July 2020).
- Merenlender, A.M.; Reed, S.E.; Kitzes, J.; Feirer, S. Mayacamas Connectivity Report; Sonoma County Agricultural Preservation and Open Space District: Santa Rosa, CA, USA, 2010. [Google Scholar]
- Kirchhoff, C.J.; Lemos, C.M.; Dessai, S. Actionable Knowledge for Environmental Decision Making: Broadening the Usability of Climate Science. Annu. Rev. Environ. Resour. 2013, 38, 393–414. [Google Scholar] [CrossRef]
- Enquist, C.A.; Jackson, S.T.; Garfin, G.M.; Davis, F.W.; Gerber, L.R.; Littell, J.A.; Tank, J.L.; Terando, A.J.; Wall, T.U.; Halpern, B.; et al. Foundations of translational ecology. Front. Ecol. Environ. 2017, 15, 541–550. [Google Scholar] [CrossRef] [Green Version]
- Data USA County Summary Data. Available online: https://datausa.io/ (accessed on 2 September 2020).
- Flint, L.E.; Flint, A.L.; Thorne, J.H.; Boynton, R. Fine-scale hydrologic modeling for regional landscape applications: The California Basin Characterization Model development and performance. Ecol. Process. 2013, 2, 1–21. [Google Scholar] [CrossRef] [Green Version]
- Jacobs, K. Connecting Science, Policy, and Decision-making: A Handbook for Researchers and Science Agencies; NOAA Office of Global Programs: Silver Springs, MD, USA, 2002.
- Design, Implementation and Cost Elements of Green Infrastructure Projects. Final Report to the European Commission. Available online: https://www.ecologic.eu/3933 (accessed on 26 October 2020).
- Wilson, K.; Pressey, R.L.; Newton, A.; Burgman, M.; Possingham, H.; Weston, C. Measuring and incorporating vulnerability into conservation planning. Environ. Manag. 2005, 35, 527–543. [Google Scholar] [CrossRef]
- Lemos, M.C.; Wolske, K.S.; Rasmussen, L.V.; Arnott, J.C.; Kalcic, M.; Kirchhoff, C.J. The closer, the better? Untangling scientist–practitioner engagement, interaction, and knowledge use. Weather. Clim. Soc. 2019, 11, 535–548. [Google Scholar] [CrossRef]
- Haywood, B.K. Beyond Data Points and Research Contributions: The Personal Meaning and Value Associated with Public Participation in Scientific Research. Int. J. Sci. Educ. Part B Commun. Public Engagem. 2016, 6, 239–262. [Google Scholar] [CrossRef]
- Owen, G.; Ferguson, D.B.; McMahan, B. Contextualizing climate science: Applying social learning systems theory to knowledge production, climate services, and use-inspired research. Clim. Chang. 2019, 157, 151–170. [Google Scholar] [CrossRef]
Category | Indicator | Examples |
---|---|---|
Conservation priorities | Geological complexity | Serpentine soils and/or habitats |
Volcanic soils | ||
Hydrologic integrity | Water supply and quality | |
Wetlands | ||
Riparian ecosystems | ||
Geysers and springs | ||
Vernal pools | ||
Headwaters | ||
Animal species | Mesocarnivores and large mammals | |
Threatened and endangered species | ||
Endemic and/or freshwater fish | ||
Rare aquatic and terrestrial invertebrates | ||
Amphibians | ||
Plant species | Rare serpentine endemics | |
Old-growth forest | ||
Native vegetation (e.g., grasslands) | ||
Prominent landscape features | Clear Lake—A large water body in Lake County that provides irreplaceable economic, recreation, and hydrologic services. | |
Mount Saint Helena—A large, centrally located mountain protected by a mosaic of numerous protected areas. | ||
Concerns and challenges | Habitat fragmentation | Land conversion for vineyards and/or cannabis |
Rural subdivision | ||
Roads that impede wildlife movement | ||
Fences that are not wildlife-friendly | ||
Renewable energy development | ||
Ongoing human impacts | Recreation on protected lands | |
Agriculture, viticulture, and grazing | ||
Wildlife-vehicle collisions | ||
Climate change | Species loss and mortality | |
Shifts in habitable climate space | ||
Invasive species | ||
Impacts on water resources (e.g., drought, flooding) | ||
Sea level rise | ||
Increased wildfire threat | ||
Socio-economic constraints | Lack of resources (e.g., funding, capacity, data) | |
Social and/or political priorities |
Potential Challenge | Example | Our Approach |
---|---|---|
Methods used for the regional linkage assessment may be inadequate for identifying corridors at the parcel-scale. | Stakeholders identified a locally known habitat linkage that was not predicted by the regional linkage assessment. The threshold value used for the maximum number of connections per node in the regional linkage mapping was inadequate for a local-scale assessment when more than 3 protected areas are close together. | We conducted a second linkage assessment for the region of interest that used a larger threshold for the number of potential connections between nodes. |
A parcel with high-quality habitat may have ownership and/or management practices that are incompatible with conservation goals. | Stakeholder knowledge of parcels with conservation-friendly landowners and/or used for higher-intensity agriculture or grazing within a potential corridor. Local parcel ownership and use unaccounted for in the input data used for the regional linkage assessment. | We revised the parcels included within the initial corridor boundary to (1) include those with permeable land and conservation-friendly landowners, and (2) exclude those with land use known to be incompatible with conservation goals. |
Conducting a parcel-scale assessment for a large corridor composed of numerous potential linkages is computationally and technically demanding. | Stakeholders prioritized a large, county-spanning corridor (139.7 km2) that spanned the Mayacamas and Vaca Mountains. Most of the land within the corridor had high permeability, and initially encompassed 53 least cost paths that connected 221 protected lands. | We developed a nested approach to prioritize the expanse of highly permeable land within the large corridor based on potential threat of land conversion. Regions with higher threat were designated as priority corridors and underwent a parcel-scale climate-wise connectivity assessment. Large swaths of undeveloped habitat (i.e., no agriculture, roads, or development) were designated as landscape linkages, and evaluated at a regional scale. |
Standard node-based linkage assessment methods fail to account for the dominance of a single large node within a region. | Stakeholders sought to identify areas important for climate-wise connectivity within a single, large protected area with differing land management types. Protected lands with multiple management types may have highly variable interior permeability (e.g., within a single protected area some locations are managed for motorized recreation and others are designated for conservation). | We created a subset of nodes within a large protected area based on management type. The resulting nodes were used as input for a linkage assessment for the region of interest to generate potential linkages that were the basis for the final corridor. |
Corridor Type | A Priori Corridor | Candidate Corridor | Final Corridor |
---|---|---|---|
Prioritization Phase | Phase 1 | Phase 2 | Phase 3 |
Description | A region identified by an individual stakeholder at the project outset as a potentially important area for long-term connectivity and climate resilience. | A spatially explicit polygon delimiting a region prioritized by individual stakeholders for implementation. | A region of adjacent parcels collectively prioritized by the stakeholders and research team for climate corridor implementation. |
Purpose | An initial inventory of local areas of a priori concern to stakeholders. | A subset of potential terrestrial linkages for consideration by the project team for parcel-scale corridor analysis. | Spatially explicit corridor extents for use in parcel-scale climate and connectivity assessments and summary reports. |
When Delimited | At the project outset before the connectivity and climate assessments. | During 1:1 guided data exploration in which each stakeholder reviewed the connectivity and climate results with the research team. | Over a 9-month period using an iterative process to reach consensus among stakeholders. |
Scale | Very coarse | Intermediate resolution | Parcel-scale |
Size | Relatively small; narrow geographic extent | Larger than a priori corridors; wide geographic extent. | Similar in size to a priori corridors. |
Area (km2) | |||
Mean | 81.9 | 530.9 | 38 |
Minimum | 51.2 | 92.3 | 5 |
Maximum | 92.3 | 2133.3 | 139.7 |
Range | 41.1 | 2041 | 134.7 |
Variable | Statistic | In Corridor | All Linkages | Not in Corridors | 90th Percentile | ||
---|---|---|---|---|---|---|---|
A priori | Candidate | Final | |||||
Phase 1 | Phase 2 | Phase 3 | |||||
Least cost path (count) | Total | 84 | 233 | 32 | 666 | 634 | 66 |
Mean | 6 | 36 | 5 | — | — | — | |
Minimum | 0 | 1 | 1 | — | — | — | |
Maximum | 19 | 96 | 13 | — | — | — | |
Summer cooling benefit (°C) | Mean | 0.99 | 1.47 | 1.80 | 1.13 | 1.09 | 4.12 |
Minimum | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 2.90 | |
Maximum | 6.92 | 6.94 | 6.92 | 7.00 | 7.00 | 7.00 | |
Range | 6.92 | 6.94 | 6.92 | 7.00 | 7.00 | 4.10 | |
Winter cooling benefit (°C) | Mean | 0.53 | 0.71 | 1.02 | 0.68 | 0.66 | 3.17 |
Minimum | 0.00 | 0.00 | 0.01 | 0.00 | 0.00 | 1.55 | |
Maximum | 3.37 | 3.37 | 4.91 | 9.29 | 9.29 | 9.29 | |
Range | 3.37 | 3.37 | 4.90 | 9.29 | 9.29 | 7.74 |
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Gray, M.; Micheli, E.; Comendant, T.; Merenlender, A. Climate-Wise Habitat Connectivity Takes Sustained Stakeholder Engagement. Land 2020, 9, 413. https://doi.org/10.3390/land9110413
Gray M, Micheli E, Comendant T, Merenlender A. Climate-Wise Habitat Connectivity Takes Sustained Stakeholder Engagement. Land. 2020; 9(11):413. https://doi.org/10.3390/land9110413
Chicago/Turabian StyleGray, Morgan, Elisabeth Micheli, Tosha Comendant, and Adina Merenlender. 2020. "Climate-Wise Habitat Connectivity Takes Sustained Stakeholder Engagement" Land 9, no. 11: 413. https://doi.org/10.3390/land9110413
APA StyleGray, M., Micheli, E., Comendant, T., & Merenlender, A. (2020). Climate-Wise Habitat Connectivity Takes Sustained Stakeholder Engagement. Land, 9(11), 413. https://doi.org/10.3390/land9110413