Biology subjects

Cazalis, V.

Publications and source records attributed to Cazalis, V..

6 recordsLinked to original sources

bioRxiv2024

Generation length of the world's amphibians and reptiles

Variation in life histories influences demographic processes from adaptive changes to population declines leading to extinction. Among life history traits, generation length offers a critical feature to forecast species demographic trajectories such as population declines (widely used by the IUCN Red List of Threatened Species) and adaptability to environmental change over time. Therefore, estimates of generation length are crucial to monitor demographic stability or future change in highly threatened organisms, particularly ectothermic tetrapods (amphibians and reptiles) - which rank among the most threatened groups - but for which uncertainty in future impacts remains high. Despite its importance, generation length for amphibians and reptiles is largely missing. Here, we aimed to fill-in this gap by modeling generation lengths for amphibians, squamates and testudines as a function of species size, climate, life history, and phylogeny using generalized additive models and phylogenetic generalized least squares. We obtained estimates of generation lengths for 4,543 (52%) amphibians, 8,464 (72%) squamates and 118 (32%) testudines. Our models performed well for most families, for example Bufonidae in amphibians, Lacertidae and Colubridae in squamates and Geoemydidae in testudines, while we found high uncertainty around the prediction of a few families, notably Chamaeleonidae. Species body size and mean temperature were the main predictors of generation length in all groups. Although our estimates are not meant to substitute robust and validated measurements from field studies or natural history museums, they can help reduce existing biases in conservation assessments until field data will be comprehensively available.

zoology↗

bioRxiv2023

Modelling the probability of meeting IUCN Red List criteria to support reassessments.

Comparative extinction risk analysis - which predicts species extinction risk from correlation with traits or geographical characteristics - has gained research attention as a promising tool to support extinction risk assessment in the IUCN Red List of Threatened Species. However, its uptake has been very limited so far, possibly because these models only predict a species Red List category, without indicating which Red List criteria may be triggered by which such approaches cannot easily be used in Red List assessments. We overcome this implementation gap by developing models that predict the probability of species meeting individual Red List criteria. Using data on the worlds birds, we evaluated the predictive performance of our criterion-specific models and compared it with the typical criterion-blind modelling approach. We compiled data on biological traits (e.g., range size, clutch size) and external drivers (e.g., change in canopy cover) often associated with extinction risk. For each specific criterion, we modelled the relationship between extinction risk predictors and species Red List category under that criterion using ordinal regression models. We found criterion-specific models were better at predicting threatened species compared to a criterion-blind model (higher sensitivity), but less good at predicting not threatened species (lower specificity). As expected, different covariates were important for predicting threat status under different criteria, for example change in annual temperature was important to predict criteria related to population trends, while clutch size was important for criteria related to restricted area of occupancy or small population size. Our criteria-specific method can support Red List assessors by producing outputs that identify species likely to meet specific criteria, and which are the most important predictors: these species can be prioritised for re-evaluation. We expect this new approach to increase the uptake of extinction risk models in Red List assessments, bridging a long-standing research-implementation gap.

ecology↗

bioRxiv2023

Testing the predictive performance of comparative extinction risk models to support the global amphibian assessment

Assessing the extinction risk of species through the IUCN Red List is key to guiding conservation policies and reducing biodiversity loss. This process is resource-demanding, however, and requires a continuous update which becomes increasingly difficult as new species are added to the IUCN Red List. The use of automatic methods, such as comparative analyses to predict species extinction risk, can be an efficient alternative to maintaining up to date assessments. Using amphibians as a study group, we predict which species were more likely to change status, in order to suggest species that should be prioritized for reassessment. We used species traits, environmental variables, and proxies of climate and land-use change as predictors of the IUCN Red List category of species. We produced an ensemble prediction of IUCN Red List categories by combining four different model algorithms: Cumulative Link Models (CLM), phylogenetic Generalized Least Squares (PGLS), Random Forests (RF), Neural Networks (NN). By comparing IUCN Red List categories with the ensemble prediction, and accounting for uncertainty among model algorithms, we identified species that should be prioritized for future reassessments due to high prediction versus observation mismatch. We found that CLM and RF performed better than PGLS and NN, but there was not a clear best algorithm. The most important predicting variables across models were species range size, climate change, and landuse change. We propose ensemble modelling of extinction risk as a promising tool for prioritizing species for reassessment while accounting for inherent models uncertainty.

ecology↗

bioRxiv2021

Mismatch between bird species sensitivity and the protection of intact habitats across the Americas

Protected areas, the most prevalent international policy mechanism for biodiversity conservation, are highly heterogeneous in their effectiveness at buffering ecosystems and species habitats from human pressure. Protected areas with intense human pressure cannot protect species that are highly sensitive to human activities. Here, we use 60 million bird observations from the eBird citizen science platform to estimate the sensitivity to human pressure of each bird species breeding in the Americas (Nearctic and Neotropical regions). We find that high-sensitivity species, while found in all ecoregions, are concentrated in the tropical biomes. Ecoregions with large proportions of high-sensitivity species do not have more intact protected habitat, resulting in a low coverage of intact protected habitat for many high-sensitivity species. What is more, 139 high-sensitivity species have little or no intact protected habitat within their distributions while being threatened with extinction. Finally, we show that protected area intactness is decreasing faster in ecoregions with many high-sensitivity species. Our results highlight a major mismatch between species conservation needs and the coverage of intact protected habitats, and will likely hamper the long-term effectiveness of protected areas at retaining species. We highlight ecoregions where the protection and management of intact habitats, complemented by the restoration of degraded ones, is urgently needed to avoid extinctions.

ecology↗

bioRxiv2020

Effectiveness of protected areas in conserving tropical forest birds

Protected areas are the cornerstones of global biodiversity conservation efforts1,2, but to fulfil this role they must be effective at conserving the ecosystems and species that occur within their boundaries. This is particularly imperative in tropical forest hotspots, regions that concentrate a major fraction of the worlds biodiversity while also being under intense human pressure3-5. But these areas strongly lack adequate monitoring datasets enabling to contrast biodiversity in protected areas with comparable unprotected sites6,7. Here we take advantage of the worlds largest citizen science biodiversity dataset - eBird8 - to quantify the extent to which protected areas in eight tropical forest biodiversity hotspots are effective at retaining bird diversity, and to understand the underlying mechanisms. We found generally positive effects of protection on the diversity of bird species that are forest-dependent, endemic to the hotspots, or threatened or Near Threatened, but not on overall bird species richness. Furthermore, we show that in most of the hotspots examined this is driven by protected areas preventing both forest loss and degradation. Our results support calls for increasing the extent and strengthening the management efforts within protected areas to reduce global biodiversity loss9-11.

ecology↗

bioRxiv2018

Using a large-scale biodiversity monitoring dataset to test the effectiveness of protected areas in conserving North-American breeding birds

Protected areas currently cover about 15% of the global land area and constitute one of the main tools in biodiversity conservation. Quantifying their effectiveness at protecting species from decline and local extinction involves comparing protected with counterfactual unprotected sites representing \"what would have happened to protected sites if they had not been protected\". Most studies are based on pairwise comparisons, using as counterfactuals neighbour sites to protected areas, but this choice is often subjective and may be prone to biases. An alternative is to use large-scale biodiversity monitoring datasets, which whereby the effect of protected areas is analysed statistically by controlling for landscape differences between protected and unprotected sites, allowing a more targeted and clearly defined measure of protected areas effect. Here we use the North American Breeding Bird Survey dataset as a case study to investigate protected areas effectiveness in conserving bird assemblages. We analysed the effect of protected areas on species richness, assemblage-level abundance and abundance of individual species by modelling how these metrics relate to the proportion of each site that is protected, while controlling for site habitat, altitude, productivity and spatial autocorrelation. At the assemblage level, we found no relationship between protection and species richness or overall abundance. At the species level, we found that species that avoid human activities tend to be favoured by protected areas are the one avoiding human activities. Moreover, we found that forest protected areas presented higher abundances of forest species, making the assemblage more typical of this habitat. We did not find that declining species were particularly favoured by protected areas. Our results highlight the complexity of answering the question of protected areas effectiveness, and the necessity to define clearly metrics measured and the controls used.

ecology↗