*Maytenus senegalensis* subsp. *europaea* communities are unique vegetal formations in Europe. In fact, they are considered Priority Habitat by Directive 92/43/EEC. These are ecologically valuable plant communities found in the southeast of Spain. By combining modeling methods of environmental variables, historical photo-interpretation, and fieldwork, a chronosequence of the evolution of their extent of occurrence (EOO) has been reconstructed in 1957 and 2011. Results showed a strong regression range of *Maytenus senegalensis* subsp. *europaea* populations. More than 26,000 ha of EOO for this species have been lost in the province of Almería. Considering the final number of polygons, this area has been fragmented 18 times since the 1950s. These results reinforce the idea that the alteration and fragmentation of habitat due to human activities is one of the most important drivers of biodiversity loss and global change. These activities are mostly intensive greenhouse agriculture and urbanization without sustainable land planning. Knowledge about the distribution of M. senegalensis subsp. europaea is of great interest for future habitat restoration. Therefore, this would be the key species to recover these damaged ecosystems.
Herein we investigate the distribution and conservation problems of a relict interaction in the Sierra Nevada mountains (southern Europe) between the butterfly *Agriades zullichi* —a rare and threatened butterfly— and its larval foodplant *Androsace vitaliana* subsp. *nevadensis*. We designed an intensive field survey to obtain a comprehensive presence dataset. This was used to calibrate species distribution models with absences taken at local and regional extents, analyze the potential distribution, evaluate the influence of environmental factors in different geographical contexts, and evaluate conservation threats for both organisms.
Many of the best practices concerning the development of ecological models or analytic techniques published in the scientific literature are not fully available to modelers but rather are stored in scientists' digital or biological memories. We propose that it is time to address the problem of storing, documenting, and executing ecological models and analytical procedures. In this paper, we propose a conceptual framework to design and implement a web application that will help to meet this challenge. This tool will foster cooperation among scientists, enhancing the creation of relevant knowledge that could be transferred to environmental managers. We have implemented this conceptual framework in a tool called ModeleR. This is being used to document, share, and execute more than 200 models and analytical processes associated with a global change monitoring program that is being undertaken in the Sierra Nevada Mountains (south Spain). ModeleR uses the concept of scientific workflow to connect and execute different types of models and analytical processes. Finally, we have envisioned the creation of a federation of model repositories where models documented within a local repository could be linked and even executed by other researchers.
The Mediterranean Basin is threatened by climate change, and there is an urgent need for studies to determine the risk of plant range shift and potential extinction. In this study, we simulate potential range shifts of 176 plant species to perform a detailed prognosis of critical range decline and extinction in a transformed mediterranean landscape. Particularly, we seek to answer two pivotal questions: (1) what are the general plant‐extinction patterns we should expect in mediterranean landscapes during the 21st century? and (2) does dispersal ability prevent extinction under climate change?.
We generated 380 S‐SDMs of 1224 tree species in Mesoamerica by combining 19 distribution modelling methods with 20 different thresholds using presence‐only data from the Global Biodiversity Information Facility. We compared the predicted richness and composition with inventory data obtained from the BIOTREE‐NET forest plot database. We designed two indicators of predictive performance that were based on the diversity factors used to measure species turnover: a (shared species between the observed and predicted compositions), b and c (the exclusive species of the predicted and observed compositions respectively) and compared them with the Sorensen and Beta‐Simpson turnover measures. Some modelling methods – especially machine learning and ensemble model forecasting methods performed significantly better than others in minimizing the error in predicted richness and composition. Our results also indicate that restrictive thresholds (with high omission errors) lead to more accurate S‐SDMs in terms of species richness and composition. Here, we demonstrate that particular combinations of modelling methods and thresholds provide results with higher predictive performance.
In this paper, we present the development of ModeleR, a repository of models accessible from the web, which enables the user to design, document, manage, and execute environmental models.
According to the simulations, the suitable habitat for the key species inhabiting the summit area, where most of the endemic and/or rare species are located, may disappear before the middle of the century. The other key species considered show moderate to drastic suitable habitat loss depending on the considered scenario. Climate warming should provoke a strong substitution dynamics between species, increasing spatial competition between both of them. In this study, we introduce the application of differential suitability concept into the analysis of potential impact of climate change, forest management and environmental monitoring, and discuss the limitations and uncertainties of these simulations.