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Quantum inspired community detection for analysis of biodiversity change driven by land-use conversion and climate change.

ABSTRACT: Community detection remains little explored in the analysis of biodiversity change. The challenges linked with global biodiversity change have also multiplied manifold in the past few decades. Moreover, most studies concerning biodiversity change lack the quantitative treatment central to species distribution modeling. Empirical analysis of species distribution and abundance is thus integral to the study of biodiversity loss and biodiversity alterations. Community detection is therefore expected to efficiently model the topological aspect of biodiversity change driven by land-use conversion and climate change; given that it has already proven superior for diverse problems in the domain of social network analysis and subgroup discovery in complex systems. Thus, quantum inspired community detection is proposed as a novel technique to predict biodiversity change considering tiger population in eighteen states of India; leading to benchmarking of two novel datasets. Elements of land-use conversion and climate change are explored to design these datasets viz.-Landscape based distribution and Number of tiger reserves based distribution respectively; for predicting regions expected to maximize Tiger population growth. Furthermore, validation of the proposed framework on the said datasets is performed using standard community detection metrics like-Modularity, Normalized Mutual Information (NMI), Adjusted Rand Index (ARI), Degree distribution, Degree centrality and Edge-betweenness centrality. Quantum inspired community detection has also been successful in demonstrating an association between biodiversity change, land-use conversion and climate change; validated statistically by Pearson's correlation coefficient and p value test. Finally, modularity distribution based on parameter tuning establishes the superiority of the second dataset based on the number of Tiger reserves-in predicting regions maximizing Tiger population growth fostering species distribution and abundance; apart from scripting a stronger correlation of biodiversity change with land-use conversion.

SUBMITTER: Akbar S

PROVIDER: S-EPMC8275618 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Current observed as well as projected changes in biodiversity are the result of multiple interacting factors, with land use and climate change often marked as most important drivers. We aimed to disentangle the separate impacts of these two for sets of vascular plant, bird, butterfly and dragonfly species listed as characteristic for European dry grasslands and wetlands, two habitats of high and threatened biodiversity. We combined articulations of the four frequently used SRES climate scenarios and associated land use change projections for 2030, and assessed their impact on population trends in species (i.e. whether they would probably be declining, stable or increasing). We used the BIOSCORE database tool, which allows assessment of the effects of a range of environmental pressures including climate change as well as land use change. We updated the species lists included in this tool for our two habitat types. We projected species change for two spatial scales: the EU27 covering most of Europe, and the more restricted biogeographic region of 'Continental Europe'. Other environmental pressures modelled for the four scenarios than land use and climate change generally did not explain a significant part of the variance in species richness change. Changes in characteristic bird and dragonfly species were least pronounced. Land use change was the most important driver for vascular plants in both habitats and spatial scales, leading to a decline in 50-100% of the species included, whereas climate change was more important for wetland dragonflies and birds (40-50 %). Patterns of species decline were similar in continental Europe and the EU27 for wetlands but differed for dry grasslands, where a substantially lower proportion of butterflies and birds declined in continental Europe, and 50 % of bird species increased, probably linked to a projected increase in semi-natural vegetation. In line with the literature using climate envelope models, we found little divergence among the four scenarios. Our findings suggest targeted policies depending on habitat and species group. These are, for dry grasslands, to reduce land use change or its effects and to enhance connectivity, and for wetlands to mitigate climate change effects.

Dataset Information

Quantum inspired community detection for analysis of biodiversity change driven by land-use conversion and climate change.

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