Development of a framework for landscape assessment of Taiwanese wetlands

Abstract

Wetlands harbor rich biodiversity and biomass and provide a variety of ecosystem services. Therefore, environmental assessment of wetlands is critical for those seeking to manage these pivotal ecosystems. While the landscape development intensity (LDI) index is commonly used for wetlands assessment, it is, unfortunately, limited in scope and, in some regions, efficacy. The objectives of this study were to improve and modify methods for wetlands assessment using a multi-metric approach that incorporated both the LDI index and landscape metrics. We calculated the LDI index values for 10 test wetlands across both the area of each wetland and within a 0–600m wide area (in 100-m intervals). The results showed that the LDI index values varied significantly as the buffer distance increased, and specifically, the wetlands plus a 300-m wide swath was found to encompass the most appropriate area of inclusion for assessment. Furthermore, based on the metrics selective criteria, only LDI index and area metrics were incorporated into the assessment schematic. Due to two types of wetlands identified significantly different in the scatter plots of the LDI index and area, the assessment system was built to accommodate appropriate cut-off points. Four levels were then designated; the coastal wetland had an overall accuracy of 70.0% (kappa coefficient of 0.61), while that of the inland wetlands, which included natural and artificial wetlands, was only 41.7% (kappa coefficient of 0.22). This study confirmed that the extent of assessment had an effect on the LDI value, and there were significant differences in the assessment schematics across wetland types. In addition, LDI and/or area indices could be incorporated into landscape assessments. The assessment methods of this study can be applied in regions with high population density and consequently altered terrain, though the metric, scoring ranges, and levels should be adjusted to local conditions.