32Species distribution maps are essential for assessing extinction risk and guiding conservation efforts. Here, 33we developed a data-driven, reproducible geospatial workflow to map species distributions and evaluate 34 their conservation status consistent with the guidelines and criteria of the IUCN Red List. Our workflow 35 follows five automated steps to refine the distribution of a species starting from its Extent of Occurrence 36(EOO) to Area of Habitat (AOH) within the species range. The ranges are produced with an Inverse 37 Distance Weighted (IDW) interpolation procedure, using presence and absence points derived from primary 38 biodiversity data. As a case-study, we mapped the distribution of 2,273 bird species in the Americas, 55% 39 of all terrestrial birds found in the region. We then compared our produced species ranges to the expert-40 drawn IUCN/BirdLife range maps and conducted a preliminary IUCN extinction risk assessment based on 41 criterion B (Geographic Range). We found that our workflow generated ranges with fewer errors of 42 omission, commission, and a better overall accuracy within each species EOO. The spatial overlap between 43 both datasets was low (28%) and the expert-drawn range maps were consistently larger due to errors of 44 commission. Their estimated Area of Habitat (AOH) was also larger for a subset of 741 forest-dependent 45 birds. We also found that incorporating geospatial data increased the number of threatened species by 52% 46 in comparison to the 2019 IUCN Red List, and 103 species could be placed in threatened categories (VU, 47 EN, CR) pending further assessment. The implementation of our geospatial workflow provides a valuable 48 alternative to increase the transparency and reliability of species risk assessments and improve mapping 49 species distributions for conservation planning and decision-making.50 51
Tropical forests support immense biodiversity and provide essential ecosystem services for billions of people. Despite this value, tropical deforestation continues at a high rate. Emerging evidence suggests that elections can play an important role in shaping deforestation, for instance by incentivising politicians to allow increased utilisation of tropical forests in return for political support and votes. Nevertheless, the role of elections as a driver of deforestation has not been comprehensively tested at broad geographic scales. Here, we created an annual database from 2001 to 2018 on political elections and forest loss for 55 tropical nations and modelled the effect of elections on deforestation. In total, 1.5 million km2 of forest was lost during this time period, and the rate of deforestation increased in 37 (67%) of the analysed countries. Deforestation was significantly lower in years with presidential or lower chamber elections compared to non-election years, which is in contrast to previous local-scale studies. Moreover, deforestation was significantly higher in presidential or lower chamber elections that are competitive (i.e. when the opposition can participate in elections and has a legitimate chance to gain governmental power) compared to uncompetitive elections. Our results document a pervasive loss of tropical forests and suggest that competitive elections are potential drivers of deforestation. We recommned that organisations monitoring election transparency and fairness should also monitor environmental impacts such as forest loss, habitat destruction and resource exploitation. This would benefit the tracking of potential illegal vote buying with natural resources.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.