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 existing models only predict a species' Red List category, without indicating which Red List criteria may be triggered. This prevents such approaches to be integrated into 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 world's 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 identifying threatened species compared to a criterion-blind model (higher sensitivity), but less good at identifying not threatened species (lower specificity). As expected, different covariates were important for predicting extinction risk under different criteria. Change in annual temperature was important for criteria related to population trends, while high forest dependency 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 then 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

Modelling range dynamics under global change: which framework and why?

1. To conserve future biodiversity, a better understanding of the likely effects of climate and land-use change on the geographical distributions of species and the persistence of ecological communities is needed. Recent advances have integrated population dynamic processes into species distribution models (SDMs), to reduce potential biases in predictions and to better reflect the demographic nuances of incremental range shifts. However, there is no clear framework for selecting the most appropriate demographic-based model for a given data set or scientific question. 2. We review the computer-based modelling platforms currently used for the development of either population- or individual-based species range dynamics models. We describe the features and requirements of 20 software platforms commonly used to generate simulations of species ranges and abundances. We classify the platforms according to particular capabilities or features that account for user requirements and constraints, such as (i) ability to simulate simple to complex population dynamics, (ii) organism specificity or (iii) their computational capacities. 3. Using this classification, we develop a protocol for choosing the most appropriate framework for modelling species range dynamics based in data availability and research requirements. We find that the main differences between modelling platforms are related to the way in which they simulate population dynamics, the type of organisms they are able to model and the ecological processes they incorporate. We show that some platforms can be used as generic modelling software to investigate a broad range of ecological questions related to the range dynamics of most species, and how these are likely to change in the future in response to forecast climate and land-use change. We argue that model predictions will be improved by reducing usage to a smaller number of highly flexible freeware platforms. 4. Our approach provides ecologists and conservation biologists with a clear method for selecting the most appropriate software platform that meets their needs when developing SDMs coupled with population-dynamic processes. We argue that informed tool choice will translate to better predictions of species responses to climate and land-use change and improved conservation management.Miguel Lurgi, Barry W. Brook, Frédérik Saltré and Damien A. Fordha

Pollution, stochasticité at hétérogénéité spatiale dans la dynamique d'une population de truites présentatnt une structure d'âge et vivant dans un réseau de rivières

International audienceWe report the strategy adopted for the modeling of a resident brown trout population living in a theoretical river network. We consider chronic cadmium pollution occurring in one stretch of river. Using RAMAS Metapop, spatial modeling allows us to integrate spatial heterogeneity influencing the population dynamics and also influenced by the heterogeneity of the environmental contamination. We show how to perform the assessment of global impact of pollution from local perturbations using this modeling step: we build for instance population level dose-response curves linking population features with pollutant concentrations. We take advantage of the flexibility of RAMAS Metapop to deal with demographic stochasticity in order to discuss the use of deterministic models or stochastic models (extinction risk concepts) to provide population endpoints for decision-making. Besides, we confirm the conclusion of a previous contribution focused on the potential effect of migratory disruptions due to pollution: random variations in the dispersal pattern during the breeding event expand the extinction risk of the trout population. So increasing efforts are necessary to develop knowledge relative to toxicant-induced spatial behaviors and to integrate such effects in the definition of environmental quality criteria

Unsustainable harvest of water frogs in southern Turkey for the European market

Frogs have been harvested from the wild for the last 40 years in Turkey. We analysed the population dynamics of Anatolian water frogs (Pelophylax spp.) in the Seyhan and Ceyhan Deltas during 2013-2015. We marked a total of 13,811 individuals during 3 years, estimated population sizes, simulated the dynamics of a harvested population over 50 years, and collated frog harvest and export statistics from the region and for Turkey as a whole. Our capture estimates indicated a population reduction of c. 20% per year, and our population modelling showed that, if overharvesting continues at current rates, the harvested populations will decline rapidly. Simulations with a model of harvested population dynamics resulted in a risk of extinction of > 90% within 50 years, with extinction likely in c. 2032. Our interviews with harvesters revealed their economic dependence on the frog harvest. However, our results also showed that reducing harvest rates would not only ensure the viability of these frog populations but would also provide a source of income that is sustainable in the long term. Our study provides insights into the position of Turkey in the 'extinction domino' line, in which harvest pressure shifts among countries as frog populations are depleted and harvest bans are effected. We recommend that harvesting of wild frogs should be banned during the mating season, hunting and exporting of frogs < 30 g should be banned, and harvesters should be trained on species knowledge and awareness of regulations. Copyright © Fauna & Flora International 2020