Abstract
Here we develop a framework to design multi-species monitoring networks using species distribution models and conservation planning tools to optimize the location of monitoring stations to detect potential range shifts driven by climate change. For this study, we focused on seven bat species in Northern Portugal (Western Europe). Maximum entropy modelling was used to predict the likely occurrence of those species under present and future climatic conditions. By comparing present and future predicted distributions, we identified areas where each species is likely to gain, lose or maintain suitable climatic space. We then used a decision support tool (the Marxan software) to design three optimized monitoring networks considering: a) changes in species likely occurrence, b) species conservation status, and c) level of volunteer commitment. For present climatic conditions, species distribution models revealed that areas suitable for most species occur in the north-eastern part of the region. However, areas predicted to become climatically suitable in the future shifted towards west. The three simulated monitoring networks, adaptable for an unpredictable volunteer commitment, included 28, 54 and 110 sampling locations respectively, distributed across the study area and covering the potential full range of conditions where species range shifts may occur. Our results show that our framework outperforms the traditional approach that only considers current species ranges, in allocating monitoring stations distributed across different categories of predicted shifts in species distributions. This study presents a straightforward framework to design monitoring schemes aimed specifically at testing hypotheses about where and when species ranges may shift with climatic changes, while also ensuring surveillance of general population trends.
Highlights
Ecosystems and global biodiversity are facing a decline as a direct and indirect consequence of human actions [1,2], and we are yet to experience the full impacts of anthropogenic climate change [3,4,5]
Performance of optimized vs. non-optimized networks Three additional networks were designed to test whether our proposed framework has potentially increased performance in detecting species range shifts derived by climate change than the commonly used approach which only considers the current distribution of the species
Designing and implementing optimal monitoring schemes under climate change We presented an innovative approach representing an improvement in the design of monitoring networks that goes beyond the conventional surveillance schemes in the sense that it allows testing hypotheses about how environmental change will drive species distributions
Summary
Ecosystems and global biodiversity are facing a decline as a direct and indirect consequence of human actions [1,2], and we are yet to experience the full impacts of anthropogenic climate change [3,4,5]. Effective conservation depends on our ability to define, measure, and monitor biodiversity change. Biodiversity monitoring programs usually aim at determining population trends and changes in the structure of biotic communities, often in response to environmental change, anthropogenic disturbance, or targeted management actions [6,7]. The importance of monitoring biodiversity is becoming increasingly recognized, many ongoing monitoring schemes have been criticized for not being underpinned by clear objectives, designed to test specific scientific hypotheses or to evaluate the success of conservation actions Untargeted monitoring can result in years of wasted effort and money [11] and may even fail in acquiring the critical information to improve management options, one of the major purposes of monitoring [9]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
