Biology subjects

Lucas, P. M.

Publications and source records attributed to Lucas, P. M..

4 recordsLinked to original sources

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

Including biotic interactions in species distribution models improves the understanding of species niche: a case of study with the brown bear in Europe

Biotic interactions are expected to influence species responses to climate change, but they are usually not included when predicting future range shifts. We assessed the importance of biotic interactions to understand future consequences of climate and land use change for biodiversity using as a model system the brown bear (Ursus arctos) in Europe. By including biotic interactions using the spatial variation of energy contribution and habitat models of each food species, we showed that the use of biotic factors considerably improves our understanding of the distribution of brown bears. Predicted future range shifts, which included changes in the distribution of food species, varied greatly when considering various scenarios of change in biotic factors, warning about future indirect climate change effects. Our study confirmed that advancing our understanding of ecological networks of species interactions will improve future scenarios of biodiversity change, which is key for conserving biodiversity and ecosystem services.

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↗

bioRxiv2018

Human activity is altering the world’s zoogeographical regions

Human activity leading to both species introductions and extinctions is widely known to influence diversity patterns on local and regional scales. Yet, it is largely unknown whether the intensity of this activity is enough to affect the configuration of biodiversity at broader levels of spatial organization. Zoogeographical regions, or zooregions, are surfaces of the Earth defined by characteristic pools of species, which reflect ecological, historical, and evolutionary processes acting over millions of years. Consequently, it is widely assumed that zooregions are robust and unlikely to change on a human timescale. Here, however, we show that human-mediated introductions and extinctions can indeed reconfigure the currently recognized zooregions of amphibians, mammals, and birds. In particular, introductions homogenize the African and Eurasian zooregions in mammals; reshape boundaries with the reallocation of Oceania to the New World zooregion in amphibians; and divide bird zooregions by increasing biotic heterogeneity. Furthermore, the combined effect of amphibian introductions and extinctions has the potential to divide two zooregions largely representing the Old and the New World. Interestingly, the robustness of zooregions against changes in species composition may largely explain such zoogeographical changes. Altogether, our results demonstrate that human activities can erode the higher-level organization of biodiversity formed over millions of years. Comparable reconfigurations have previously been detectable in Earths history only after glaciations and mass extinction events, highlighting the profound and far-reaching impact of ongoing human activity and the need to protect the uniqueness of biotic assemblages from the effects of future species introductions and extinctions.

ecology↗