First national assessment of wildlife mortality in Ecuador: An effort from citizens and academia to collect roadkill data at country scale

Abstract

Ecuador has both high richness and high endemism, which are increasingly threatened by anthropic pressures, including roads. Research evaluating the effects of roads remains scarce, making it difficult to develop mitigation plans. Here, we present the first national assessment of wildlife mortality on roads that allow us to (1) estimate roadkill rates per species, (2) identify affected species and areas, and (3) reveal knowledge gaps. We bring together data from systematic surveys and citizen science efforts to present a dataset with 5010 wildlife roadkill records from 392 species, and we also provide 333 standardized corrected roadkill rates calculated on 242 species. Systematic surveys were reported by ten studies from five Ecuadorian provinces, revealing 242 species with corrected roadkill rates ranging from 0.03 to 171.72 ind./km/year. The highest rates were for the yellow warbler Setophaga petechia in Galapagos (171.72 ind./km/year), the cane toad Rhinella marina in Manabi (110.70 ind./km/year), and the Galapagos lava lizard Microlophus albemarlensis (47.17 ind./km/year). Citizen science and other nonsystematic monitoring provided 1705 roadkill records representing all 24 provinces in Ecuador and 262 identified species. The common opossum Didelphis marsupialis, the Andean white-eared opossum Didelphis pernigra, and the yellow warbler Setophaga petechia were more commonly reported (250, 104, and 81 individuals, respectively). Across all sources, we found 15 species listed as "Threatened" and six as "Data Deficient" by the IUCN. We recommend stronger research efforts in areas where the mortality of endemic or threatened species could be critical for populations, such as in Galapagos. This first country-wide assessment of wildlife mortality on Ecuadorian roads represents contributions from academia, members of the public, and government, underlining the value of wider engagement and collaboration. We hope these findings and the compiled dataset will guide sensible driving and sustainable planning of infrastructure in Ecuador and, ultimately, contribute to reduce wildlife mortality on roads.

Assessing Brazilian reptiles' road‐kill risks using trait‐based models

“…Our road‐kills dataset comprises approximately 20.6% of the Brazilian reptile species (see Costa et al, 2021), representing a diverse range of habits and species ecology. This proportion is similar to the one found by Medrano‐Vizcaíno et al (2023) in Ecuador, where approximately 21.2% of the species recognized for the country have been recorded as road‐kills, although they also counted citizen science data, which could make their sample more diverse. No other studies have analysed reptile road‐kill patterns at this large scale, limiting direct comparisons of our results with road‐kill data from other countries.…”

Road Infrastructure and Primate Conservation: Introducing the Global Primate Roadkill Database

“…In creating our database, we were inspired by other freely available databases that were created as a result of collaborative efforts by often large numbers of research teams, including the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) database, GrassPlot (a database of scale-dependent phytodiversity patterns in Palaearctic grasslands), TRY (a global database of plant traits) and the national assessment of wildlife mortality in Ecuador [38][39][40][41][42]. Our database (GPRD) includes, where available, the following information for each entry: the data source (e.g., database, anecdote, research paper, social media, or donated private data), the primate species' scientific and common names and Red List status, the year and month of the incident observation, the location (e.g., country, state, district, National Park, town/city, road), GIS coordinates (i.e., latitude and longitude), demographic details (e.g., number of individuals killed, including the age and sex).…”

Evaluating Road Hazard Maintenance Efficiency Using Citizen Science Data to Improve Road Safety

“…Collisions between wildlife and vehicles pose a potential threat to both wildlife populations and road user safety. Data collection methods for wildlife-vehicle collisions (WVCs) include accident reports by the police [22]; historical data from hunters, citizen scientists, or volunteers [23][24][25][26][27][28]; sensor-driven data collection such as lidar [29] and smartphone [30]. The study by [4] is unique, given the fact that they utilized a YOLO v3 computer vision algorithm to detect two road hazards (potholes and roadkill) at the same time.…”