five

Indirect Impacts of Fire on Vertebrates

收藏
DataCite Commons2025-04-09 更新2025-04-16 收录
下载链接:
https://data.mendeley.com/datasets/rgg4538296/1
下载链接
链接失效反馈
官方服务:
资源简介:
The information in this CSV file represents the identification of vertebrate animals indirectly impacted by fire in Brazil. We built a database of images received by firefighters, managers and people directly involved in fighting fires and implementing prescribed burns. Additionally, databases provided by the non-governmental organization (NGO) Onçafari and the Wild Animal Rehabilitation Center (CRAS) of the State of Mato Grosso do Sul (MS) were included, and photographs collected from online news sources displayed such information. This database is supported by the citizen science initiative and is part of the first collaborator's master's research. Each line corresponds to an animal impacted by the fire. We compiled: i) biome, ii) state, iii) location or name of the Protected Area, iv) fire event (prescribed burn or wildfire), v) class, vi) order, vii) family, viii) genus, ix) species, and x) body size. Animals were classified into three body size categories: small (less than 1 kg), medium (between 1 kg and 7 kg), and large (greater than 7 kg) (Emmons & Feer, 1997; Chiarello, 2000), based on the average weight of the species. The type of impact was classified as: i) indirect negative, for cases in which the animals were present alive in the burned areas, but did not show signs of burns, smoke inhalation, desiccation and physiological stress, and ii) indirect positive, for situations in which the recorded individuals were foraging in the burned areas. Chiarello, A. G. (2000). Density and population size of mammals in remnants of Brazilian Atlantic Forest. Conservation Biology, 14(6), 1649-1657. https://doi.org/10.1111/j.1523-1739.2000.99071.x Emmons, L. H. & Feer, F. (1997). Neotropical Rainforest Mammals: A Field Guide. University of Chicago Press, Chicago and London.
提供机构:
Mendeley Data
创建时间:
2025-04-09
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作