Abstract

Many studies have explored the dynamic change of wetlands distribution which play an important role in wetlands conservation and its sustainable management. However, given an uneven distribution of natural wetland resources in the context of global change, little is known about the spatial relationship between natural wetlands changes and associated influencing factors in mainland China. In this study, Moran-based spatial statistics are an effective methodology to examine the spatial patterns of natural wetlands and associated influencing factors at the province level, and GIS mapping is applied to help visualize spatial patterns. Results show that 1) significant spatial agglomeration and regional differences of natural wetlands distribution have been captured by Moran’s I statistics, and the agglomeration level has increased over the past ten years; 2) Seven of the eight factors show significantly strong and positive spatial autocorrelation except for water consumption, and spatial patterns of them show significant spatial clusters or spatial outliers; 3) Spatial coordination between natural wetlands distribution and the associated influencing factors is higher in the western region than in east China and northeast China. Moreover, spatial coordination between a cultivated area or water consumption and natural wetlands distribution is weaker than that of other factors. Finally, the influences generated by neighboring provinces should not be neglected in the implementation of wetlands conservation. This study could provide a scientific basis for the policy making of wetlands conservation and sustainable management systems.

Highlights

  • Wetlands have value owing to their useful functions to humans [1]

  • The dynamic change of wetlands directly reflects on the change of wetland area and landscape pattern and indirectly on the wetland structure and functions [8,9]

  • This study explored the spatial pattern of natural wetlands dynamics and the associated influencing factors based on data of the natural wetlands area in 31 provinces, by applying Moran’s I statistics

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Summary

Introduction

Wetlands have value owing to their useful functions to humans [1] They provide goods and ecosystem services for humanity and habitats for flora and fauna [2,3]. With their fragility and sensitivity to climatic change and anthropogenic activities, wetlands are among the most vulnerable ecosystems around the world [4]. Understanding the dynamics of wetlands is significant for the conservation of wetland biodiversity and its sustainable management [5] Wetlands changes and their causes have been paid more attention by global environmental change research [6,7]. Landscape metrics or models at national, regional or local scales can make the long-term monitoring of wetland changes feasible and build a significant foundation for wetland resources protection and management [15,16,20,27,28,29,30,31]

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