High Resolution Maps
Objective
Provide a robust scientific and analytic framework and evidence base for local, regional, and national conversations and decisions to support an effective biodiversity conservation that sustains species and their many functions for future generations.
Background
Effective conservation decisions rely on detailed geographic data to guide conservation efforts that achieve biodiversity outcomes. This information is vital to support local, regional, and national conversations and decisions, including initiatives to protect 30% of total land and water area by 2030. In collaboration with the Half-Earth Project and in collaboration with national and international partners, Map of Life is producing carefully vetted high resolution maps of species distributions to support this need. In total, these will include thousands of species of diverse taxonomic groups across the U.S. and Canada. Here we demonstrate these draft products and highlight a few taxonomic groups and aggregate species patterns in the forms of richness (i.e., the number of species occurring in each pixel) and geographic rarity. Individual maps for all species of a group in the region allow a quantitative, optimality-based assessment of conservation opportunities that can minimize cost and maximize other benefits while protecting species. One such example priority map is shown for butterflies, where all species conservation targets are achieved within the smallest area possible (See here). These methods can be expanded to include all species and many other environmental and social objectives to ensure policies are maximizing a diversity of needs. Thank you for exploring our maps and your interest in species conservation.
Please check back as we update and finalize these maps. Please contact us at info@mol.org if you have any questions.
Methods
Species Maps
Our species distribution models are produced using a single-species, presence-only point-process model based on an extension of the popular Maxent tool from (Merow, Wilson, and Jetz, 2016). Our approach combines a set of taxon-specific environmental layers with presence records from GBIF (and other taxon-specific sources) and prior estimates of species' ranges from expert range maps or occupied ecoregions to produce a predicted suitability for each 1km2 pixel. Because our pseudo-absences are sampled from the study domain, these raw suitability values are then converted to binary presence/absence predictions according to a threshold calibrated from withheld data.
Richness and Rarity Maps
Richness of each pixel is generated by summing the predicted presence of all study species. Rarity maps are similarly summed, but each species presence in a cell is weighted by the total number of positive cells in the study area for that species. The all-taxa richness and rarity layers are averaged over the normalized richness/rarity of all 7 taxonomic groups.
Priority Maps
Priority maps are drafts that use integer linear programming to identify pixels that best collectively achieve individual species conservation targets (ranging from 15-100% of their total range size) while minimizing land cost and total area.
Contributors (Alphabetical)
Julia Latrza Barbosa, Doug Booher, Kalkidan Chefira, Jeremy Cohen, Bort Edwards, Kate Ingenloff, Walter Jetz, Alexander Killion, Maisha Lucas, Charles Marsh, Stefan Pinkert, Ajay Ranipeta, Mario Ribeiro de Moura, Matt Rogan, Tamara Rudic, Emily Sandall, David Shen, Anna Schuerkmann, Yanina Sica, John Wilshire, Kevin Winner
Further resources
- Merow, C., Wilson, A.M. and Jetz, W. (2017), Integrating occurrence data and expert maps for improved species range predictions. Global Ecol. Biogeogr., 26: 243-258. https://doi.org/10.1111/geb.12539
- Ellis-Soto, D., Merow, C., Amatulli, G., Parra, J.L. and Jetz, W. (2021), Continental-scale 1 km hummingbird diversity derived from fusing point records with lateral and elevational expert information. Ecography, 44: 640-652. https://doi.org/10.1111/ecog.05119
- W. Jetz, M. A. McGeoch, R. Guralnick, S. Ferrier, J. Beck, M. J. Costello, M. Fernandez, G. N. Geller, P. Keil, C. Merow, C. Meyer, F. E. Muller-Karger, H. M. Pereira, E. C. Regan, D. S. Schmeller, E. Turak (2019). Essential biodiversity variables for mapping and monitoring species populations. Nature Ecology & Evolution 3:539-551.
- W. Jetz, J. McGowan, D. S. Rinnan, H. P. Possingham, P. Visconti, B. O’Donnell, M. C. Londoño-Murcia (2021) Include biodiversity representation indicators in area-based conservation targets. Nature Ecology & Evolution. https://doi.org/10.1038/s41559-021-01620-y
Author reprint: Article and Supplementary information
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