DOI: 10.5061/dryad.m0cfxpp8s
title: A global map of species at risk of extinction due to natural hazards

description: An often-overlooked question of the biodiversity crisis is how natural
 hazards contribute to species extinction risk. To address this issue, we
 explored how four natural hazards: earthquakes, hurricanes, tsunamis, and
 volcanoes, overlapped with the distribution ranges of amphibians, birds,
 mammals, and reptiles that have either narrow distributions or populations
 with few mature individuals. To assess which species are at risk from
 these natural hazards, we combined the frequency and magnitude of each
 natural hazard to estimate a probability of impact. We considered species
 at risk if they overlapped with regions where any of the four natural
 hazards historically occurred (n = 3,722). Those species with at least a
 quarter of their range subjected to a high probability of impact were
 considered at high risk (n = 2,001) of extinction due to natural hazards.
 In total, 834 reptiles, 617 amphibians, 302 birds, and 248 mammals were at
 high risk and they were mainly distributed on islands and in the tropics.
 Hurricanes (n = 983) and earthquakes (n = 868) affected the most species,
 while tsunamis (n = 272), and volcanoes (n = 171) affected considerably
 fewer. The region with the highest number of species at high risk was the
 Pacific Ring of Fire, especially due to volcanoes, earthquakes and
 tsunamis, while hurricane-related high-risk species were concentrated in
 the Caribbean Sea, Gulf of Mexico, and northwestern Pacific Ocean. Our
 study provides important information regarding the species at risk due to
 natural hazards and can help guide conservation attention and efforts to
 safeguard their survival.
description: To address this knowledge gap, we provide an evaluation of the
 risk posed by natural hazards to terrestrial vertebrate species worldwide,
 focusing especially on those species that have limited distributions
 and/or occur at low numbers. First, we selected all amphibian, bird,
 mammal, and reptile species with a maximum population size of 1,100 mature
 individuals and/or those with a range size less than or equal to 2,500 km²
 based on the IUCN Red List of Threatened Species. Second, we constructed
 an estimate for the likelihood of impact from four natural hazards
 (earthquakes, hurricanes, tsunamis, and volcanoes) by analysing
 approximately 50 years of historical data concerning the frequency and
 magnitude of events. We then identified all species whose ranges overlap
 with known occurrences of hurricanes, earthquakes, tsunamis, and
 volcanoes. Finally, we classified the species at ‘high-risk’ as those for
 which at least a quarter of their range overlapped with areas of high
 probability of impact from at least one natural hazard.
  
description: # A global map of species at risk of extinction due to natural hazards
 [https://doi.org/10.5061/dryad.m0cfxpp8s](https://doi.org/10.5061/dryad.m0cfxpp8s) To account for potential errors of commission and omission in the IUCN range maps, we tested two approaches: (1) estimating the percentage of the ranges intersecting with each cell (Datasets S1-S4). Then we conducted binary pixel-based analyses, using the entire cell area is a species range intersected it (Datasets S5-S20). *Dataset S1: Information about reptile species at risk and high risk due to natural hazards.* *Dataset S2: Information about amphibian species at risk and high risk due to natural* *hazards.* *Dataset S3: Information about bird species at risk and high risk due to natural hazards.* *Dataset S4: Information about mammal species at risk and high risk due to natural* *hazards.* *Dataset S5: Information about reptile species at risk and high risk due to earthquakes* *calculated using six different transformations.* *Dataset S6: Information about reptile species at risk and high risk due to hurricanes* *calculated using six different transformations.* *Dataset S7: Information about reptile species at risk and high risk due to tsunamis* *calculated using six different transformations.* *Dataset S8: Information about reptile species at risk and high risk due to volcanoes* *calculated using six different transformations.* *Dataset S9: Information about amphibian species at risk and high risk due to earthquakes* *calculated using six different transformations.* *Dataset S10: Information about amphibian species at risk and high risk due to hurricanes* *calculated using six different transformations.* *Dataset S11: Information about amphibian species at risk and high risk due to tsunamis* *calculated using six different transformations.* *Dataset S12: Information about amphibian species at risk and high risk due to volcanoes* *calculated using six different transformations.* *Dataset S13: Information about bird species at risk and high risk due to earthquakes* *calculated using six different transformations.* *Dataset S14: Information about bird species at risk and high risk due to hurricanes* *calculated using six different transformations.* *Dataset S15: Information about bird species at risk and high risk due to tsunamis* *calculated using six different transformations.* *Dataset S16: Information about bird species at risk and high risk due to volcanoes* *calculated using six different transformations.* *Dataset S17: Information about mammal species at risk and high risk due to earthquakes* *calculated using six different transformations.* *Dataset S18: Information about mammal species at risk and high risk due to hurricanes* *calculated using six different transformations.* *Dataset S19: Information about mammal species at risk and high risk due to tsunamis* *calculated using six different transformations.* *Dataset S20: Information about mammal species at risk and high risk due to volcanoes* *calculated using six different transformations.* ## Description of the data and file structure We calculate the probability of occurrence of an event for each natural hazard in a given year within a specific 2,500 km2 grid cell, we used a binomial regression with a logit link function. In this analysis, the dependent variable was the presence or absence of a hazard in a given year, with this 347 event weighted by its magnitude. After exploring alternative weighting schemes 348 (*Appendix S1*), we adjusted the models to accommodate the assumption that a single and strong event should have a higher magnitude as well as account for years with multiple events. Furthermore, as observations with no weight (e.g. years during which no hazards were observed) were discarded by our model, we assigned the lowest magnitude (a value  of 1 after standardisation) between 1970 and 2016 for these observations.  We calculated the weighted impact for each grid cell using the following equation:   I = glm(F ~ 1, weights = M, family = “binomial”),  Where I is the relative impact, F is the binary variable of occurrence or not of a specific hazard in a given year (between 1970 and 2016) and M are the scaled magnitudes of the hazards in each year. To give higher weight to events with higher magnitudes in relation to events with lower magnitudes, we squared the magnitude values. To account for years where there were multiple events, we summed the magnitudes before squaring them. The relative impact of natural hazards varies between 0 (indicating a low impact) and 1 (indicating a high impact). Further details about the calculation of the relative impact of 363 natural hazards and the exploration of alternative weighting schemes can be found in *Appendix S1*.  We identified species exposed to natural hazards by intersecting the range of each species with the occurrences of natural hazards. To account for potential errors of commission and omission in the IUCN range maps, we tested two approaches: (1) estimating the percentage of the ranges intersecting with each cell and (2) conducting binary pixel-based analyses, using the entire cell area is a species range intersected it. Here we provide the results of the former approach and in the supplementary materials we provide the latter. Species were classified as “high risk” if at least 25% of their geographic range overlapped with areas subjected to at least 0.25 of relative impact of natural hazards. The relative impact of each threat was estimated by calculating the median impact across the cells with hazards that overlapped with the range of a species. We used this threshold value to categorise species at high risk by natural hazard because they have been previously used in spatial ecology and conservation prioritization of terrestrial vertebrates at different scales. ##### Code/Software R code is available at [https://github.com/harithmorgadinho/natural_hazards](https://github.com/harithmorgadinho/natural_hazards)