Planning priority conservation areas for biodiversity under climate change in topographically complex areas: A case study in Sichuan province, China

According to the above hypothesis, the refugia was defined as the temperatures in the target cell were lower than that in a current species cell due to temperature increase in the future, while Eq (1) was used to assess the adaptation index for each cell based on climatically suitable areas of the surroundings. In calculation, the previous studies suggested that the coldest monthly temperature was a major element to change distributions of species and ecosystems [36], which was selected to assess the effects of topography in our study. A ¼ PðWi=NÞ=N � 100% ð1Þ In Eq (1), A is the adaptation index, Wi is the number of cells of similar climatic conditions in a fixed area, and N is the total number of cells in a fixed area. To further linking relationships among topographic diversity, adaptation, and climate change, the topographic complexity was divided into 11 types (Fig 5A) by sliding window algo- rithm [37], while the number of topographic positions was calculated to represent topographic diversity in a fixed area. However, the value of topographic diversity increased with the increase of assessing window area. The mean change-point analysis method could identify the optimal area of the window [38]. Thus, applying the sliding window algorithm and the mean change-point analysis assessed the distributions of topographic diversity for the study area. 2.4.3. Identifying priority conservation areas. Marxan model was developed to deter- mine the spatial distribution of priority conservation areas in terms of the tradeoff between

conservation targets and costs. In the model, a minimum-set algorithm was used to achieve planning scenarios on the limitation of conservation costs, which can set different targets based on the number and types of species. The Systematic Conservation Planning tool (Marxan Model v 2.4.3) was applied to plan priority conservation areas for biodiversity in response to climate change in Sichuan province. Meanwhile, we set quantitative targets for conservation features to identify the priority conservation areas for climate change. The benefit would be the highest in the condition that the protection area accounts for 30% of their habitats [39, 40]. Thus, we set the bottom value of the protection goal to 30% for each species. Meanwhile, the conservation goals of the species were determined by their protection levels. The goals for the percentage of habitat area fall into 3 types: for species belonging to National Protection Grade I is 40%, for species belonging to National Protection Grade II is 30%, and other species is 30%. Additionally, the uncertainties in climate change associated Fig 3. Diagram of the effects of complex topography on climate change adaptation (a represents the topographically complex area, and b represents the flat area). https://doi.org/10.1371/journal.pone.0243425.g003 PLOS ONE Planning priority conservation areas for biodiversity under climate change in topographically complex areas PLOS ONE | https://doi.org/10.1371/journal.pone.0243425 December 23, 2020 6 / 15