Satellite-derived vegetation indices contribute significantly to the prediction of epiphyllous liverworts

• Published in: Ecological indicators 2014-03, Vol.38, p.72-80
• Main Authors: Jiang, Yanbin, Wang, Tiejun, de Bie, C.A.J.M., Skidmore, A.K., Liu, Xuehua, Song, Shanshan, Zhang, Li, Wang, Jian, Shao, Xiaoming
• Format: Article
• Language: English
• Subjects: Animal and plant ecology; Animal, plant and microbial ecology; Applied ecology; Biological and medical sciences; China; Climate; Conservation, protection and management of environment and wildlife; Fundamental and applied biological sciences. Psychology; General aspects; Macro-habitat; MaxEnt; Parks, reserves, wildlife conservation. Endangered species: population survey and restocking; Species distribution model; Synecology; Vegetation
• ISSN: 1470-160X; 1872-7034
• DOI: 10.1016/j.ecolind.2013.10.024

•The spatial distribution of epiphyllous liverworts in China is predicted.•Six core distribution areas of epiphyllous liverworts across China are found.•The macro-habitat factors that affect epiphyllous liverwort distribution are identified.•Satellite vegetation indices are the most important predictors of epiphyllous liverworts.•Epiphyllous liverworts may be used as indicator for forest degradation. Epiphyllous liverworts form a special group of bryophytes that primarily grow on leaves of understory vascular plants, occurring in constantly moist and warm evergreen forest in tropical and subtropical regions. They are very sensitive to climate change and environmental pollution. Previous studies have focused largely on microhabitat preferences of epiphyllous liverworts and demonstrated the importance of climate factors such as humidity, temperature and light. However, little is known about the relationship between distribution of epiphyllous liverworts and macro-habitat factors at broad spatial scales. Here, we predicated the distribution of epiphyllous liverworts in China based on topographic and bioclimatic variables, as well as satellite-derived vegetation indices at a 1km spatial resolution using presence-only ecological niche models. We used the Area Under the receiver operating characteristic Curve (AUC) and True Skill Statistic (TSS) to validate the models, and then used the Wilcoxon paired test to compare model performances. Furthermore, we applied the jackknife test to identify the important factors affecting predictions. Our results showed that the highest accuracy (i.e., AUC=0.98 and TSS=0.93) in predicting epiphyllous liverworts was achieved by the model that combined climatic and remotely sensed vegetation variables. The satellite-derived annual mean and minimum Normalized Difference Vegetation Index (NDVI) as well as the annual mean and minimum Normalized Difference Water Index (NDWI) emerged as the most important predictors of distribution patterns of epiphyllous liverworts, while climatic variables such as precipitation in the wettest quarter and temperature of the coldest quarter were of ancillary importance. The significant contributions of NDVI and NDWI in defining the distribution range and spatial patterns of epiphyllous liverworts, and the strong relationship between this species and evergreen forest implies that epiphyllous liverworts may be a useful indicator for forest degradation or integrity at broad spatial scales.