Safeguarding Ecosystem Services: A Methodological Framework to Buffer the Joint Effect of Habitat Configuration and Climate Change

<div><p>Ecosystem services provided by mobile agents are increasingly threatened by the loss and modification of natural habitats and by climate change, risking the maintenance of biodiversity, ecosystem functions, and human welfare. Research oriented towards a better understanding of the joint effects of land use and climate change over the provision of specific ecosystem services is therefore essential to safeguard such services. Here we propose a methodological framework, which integrates species distribution forecasts and graph theory to identify key conservation areas, which if protected or restored could improve habitat connectivity and safeguard ecosystem services. We applied the proposed framework to the provision of pollination services by a tropical stingless bee (<i>Melipona quadrifasciata</i>), a key pollinator of native flora from the Brazilian Atlantic Forest and important agricultural crops. Based on the current distribution of this bee and that of the plant species used to feed and nest, we projected the joint distribution of bees and plants in the future, considering a moderate climate change scenario (following IPPC). We then used this information, the bee’s flight range, and the current mapping of Atlantic Forest remnants to infer habitat suitability and quantify local and regional habitat connectivity for 2030, 2050 and 2080. Our results revealed north to south and coastal to inland shifts in the pollinator distribution during the next 70 years. Current and future connectivity maps unraveled the most important corridors, which if protected or restored, could facilitate the dispersal and establishment of bees during distribution shifts. Our results also suggest that coffee plantations from eastern São Paulo and southern Minas Gerais States could suffer a pollinator deficit in the future, whereas pollination services seem to be secured in southern Brazil. Landowners and governmental agencies could use this information to implement new land use schemes. Overall, our proposed methodological framework could help design novel conservational and agricultural practices that can be crucial to conserve ecosystem services by buffering the joint effect of habitat configuration and climate change.</p></div

(a) Bee habitat suitability according to species distribution model outputs for (a1) current conditions and for (a2) 2030, (a3) 2050, and (a4) 2080 scenarios of climate change.

<p>Modeling was executed using climatic variables (abiotic factors) and mutualistic plant species (biotic factors) (see item A on Material and Methods section). (b) Habitat connectivity of each focal landscape (FL) represented by the variation of Integral Index of Connectivity (ΔIIC) through the study area, for (b1) current conditions and for (b2) 2030, (b3) 2050, and (b4) 2080 scenarios. Since the importance of each FL is measured by ΔIIC, the highest the ΔIIC the highest the FL importance (item B on Material and Methods section). (c) Changes in habitat connectivity represented by the variation in ΔIIC considering two climatic subsequent periods: (c1) current to 2030; (c2) 2030 to 2050; (c3) 2050 to 2080; (c4) current to 2080.</p

Methodology workflow: (a) Distribution modeling of <i>Melipona quadrifasciata</i> species included potential distribution of plants used to nest and to collect pollen and nectar (biotic factors) and climatic variables (abiotic factors).

<p>This modeling resulted in one present day and three future models (2030, 2050, 2080) of habitat suitability for the bee species (see item A on Material and Methods section and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0129225#pone.0129225.g003" target="_blank">Fig 3A</a> on <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0129225#sec008" target="_blank">Results</a> section). (b) Local scale analyses estimated the habitat connectivity in each focal landscape (FL, hexagonal cells) through the Probability of Connectivity Index (PC). The PC was based on the bee dispersal capability and also on forest remnant areas that were weighted by habitat suitability obtained with the species distribution modeling (previous step). On regional scale, the importance of each FL to the potential bee flux through the study area was measured based on removal experiments, which estimate the contribution of each FL in changes in the Integral Index of Connectivity (ΔIIC) (item B on Material and Methods section and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0129225#pone.0129225.g003" target="_blank">Fig 3B</a> on Results section). (c) The determination of priority areas for conservation and restoration and for ecosystem services protection and management was based on temporal changes in FL regional importance (item C on Material and Methods section and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0129225#pone.0129225.g003" target="_blank">Fig 3C</a> on Results section).</p

Forest remnants in the studied area, southern region of Brazil (forest remnants map was provided by SOS Mata Atlantica and Instituto Nacional de Pesquisas Espaciais 2008).

<p>Forest remnants in the studied area, southern region of Brazil (forest remnants map was provided by SOS Mata Atlantica and Instituto Nacional de Pesquisas Espaciais 2008).</p