ORCID Profile
0000-0001-5069-8900
Current Organisation
University of Reading
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Publisher: Elsevier BV
Date: 04-2022
DOI: 10.1016/J.TREE.2021.12.002
Abstract: The International Union for Conservation of Nature (IUCN) Red List of Threatened Species is central in bio ersity conservation, but insufficient resources h er its long-term growth, updating, and consistency. Models or automated calculations can alleviate those challenges by providing standardised estimates required for assessments, or prioritising species for (re-)assessments. However, while numerous scientific papers have proposed such methods, few have been integrated into assessment practice, highlighting a critical research-implementation gap. We believe this gap can be bridged by fostering communication and collaboration between academic researchers and Red List practitioners, and by developing and maintaining user-friendly platforms to automate application of the methods. We propose that developing methods better encompassing Red List criteria, systems, and drivers is the next priority to support the Red List.
Publisher: Wiley
Date: 10-09-2021
DOI: 10.1111/GEB.13375
Abstract: The road network is increasing globally but the consequences of roadkill on the viability of wildlife populations are largely unknown. We provide a framework that allows us to estimate how risk of extinction of local populations increases due to roadkill and to generate a global assessment that identifies which mammalian species are most vulnerable to roadkill and the areas where they occur. Global. 1995–2015. Terrestrial mammals. We introduce a framework to quantify the effect of roadkill on terrestrial mammals worldwide that includes three steps: (a) compilation of roadkill rates to estimate the fraction of a local population killed on the roads, (b) prediction of population risk of extinction based on observed roadkill rates (for a target group of species of conservation concern and non‐threatened species with high roadkill rates), and (c) global assessment of vulnerability to roadkill for 4,677 terrestrial mammalian species estimated using phylogenetic regression models that link extinction risk to demographic parameters. We identified four populations among the 70 species in the target group that could become extinct in 50 years if observed roadkill levels persist in the study areas: maned wolf Chrysocyon brachyurus (Brazil), little spotted cat Leopardus tigrinus (Brazil), brown hyena Hyaena brunnea (Southern Africa) and leopard Panthera pardus (North India). The global assessment revealed roadkill as an added risk for 2.7% ( n = 124) terrestrial mammals, including 83 species Threatened or Near Threatened. We identified regions of concern that have species vulnerable to roadkill with high road densities in areas of South Africa, central and Southeast Asia, and the Andes. Our framework revealed populations of threatened species that require special attention and can be incorporated into management and planning strategies informing road managers and conservation agencies.
Publisher: Wiley
Date: 19-02-2019
DOI: 10.1111/COBI.13296
Abstract: Every 2 years, the conservation community comes together at The Society for Conservation Biology's International Congress for Conservation Biology (ICCB) to share new developments in conservation science and practice. Publication of findings presented at conferences in scientific journals adds to the permanent record and helps increase the potential impact of the work presented. However, quantitative research on publication rates for meetings relevant to conservation is lacking. For the 25th ICCB, (Auckland, New Zealand in 2011), we examined study publication rates and presenter demographics, recorded titles, number of authors, presenter affiliations, gender, country of the study region, publication status, and elapsed time between presentation and publication. Of the 980 contributions (782 talks and 198 posters), 587 (60%) were published as peer-reviewed journal articles or book chapters. Mean time to publication was 13.7 months for all presentation abstracts and 21.3 months excluding abstracts with corresponding articles that were published before the meeting. The gender breakdown of presenters was almost even (53% male, 47% female), but representation of the countries where the presenting authors were based was skewed. The political units with the most contributions were by far the United States, Australia, New Zealand, and the United Kingdom. Presenters based in 16 different English-speaking countries made up 74% of the total s le, but this did not influence the likelihood of their abstract leading to a publication. Examination of conference presenters and publication of their presentations is useful to identify biases and potential challenges that need to be addressed to make conference communications permanent and increase their reach beyond conference attendees.
Publisher: Wiley
Date: 29-09-2023
Publisher: Cold Spring Harbor Laboratory
Date: 09-11-2022
DOI: 10.1101/2022.11.08.515633
Abstract: Characterizing changes in trait ersity at large spatial scales provides insight into the impact of human activity on ecosystem structure and function. However, the approach is often based on trait datasets that are incomplete and unrepresentative, with uncertain impacts on trait ersity estimates. To address this knowledge gap, we simulated random and biased removal of data from a near complete avian trait dataset (9579 species) and assessed whether trait ersity metrics were robust to data incompleteness with and without using imputation to fill data gaps. Specifically, we compared two commonly used metrics each calculated with two methods: trait richness (calculated with convex hulls and trait probabilities densities) and trait ergence (calculated with distance-based Rao and trait probability densities). Without imputation, estimates of global avian trait ersity (richness and ergence) were robust when 30-70% of species had missing data for four out of 11 continuous traits, depending on severity of bias and the method used. However, when missing traits were imputed based on present morphological trait data and phylogeny, trait ersity metrics consistently remained representative of the true value, even when 70% of species were missing data for four out of 11 traits and data were not missing at random (biased with respect to body mass). Trait probability densities and distance-based Rao were particularly robust to missingness and bias when combined with imputation, with convex hull-based trait richness being less reliable. Expanding global morphometric datasets to represent more taxa and traits, and to quantify intraspecific variation, remains a priority. In the meantime, our results show that widely used methods can successfully quantify large-scale trait ersity even when data are missing for two-thirds of species, so long as missing traits are estimated using imputation.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Manuela Gonzalez Suarez.