Ecological dissimilarity among land-use/land-cover types improves a heterogeneity index for predicting biodiversity in agricultural landscapes
- 495 Downloads
Land-use/land-cover heterogeneity is among the most important factors influencing biodiversity in agricultural landscapes and is the key to the conservation of multi-habitat dwellers that use both terrestrial and aquatic habitats. Heterogeneity indices based on land-use/land-cover maps typically do not integrate ecological dissimilarity between land-use/land-cover types. Here, we applied the concept of functional diversity to an existing land-use/land-cover diversity index (Satoyama index) to incorporate ecological dissimilarity and proposed a new index called the dissimilarity-based Satoyama index (DSI). Using Japan as a case study, we calculated the DSI for three land-use/land-cover maps with different spatial resolutions and derived similarity information from normalized difference vegetation index values. The DSI showed better performance in the prediction of Japanese damselfly species richness than that of the existing index, and a higher correlation between the index and species richness was obtained for higher resolution maps. Thus, our approach to improve the land-use/land-cover diversity index holds promise for future development and can be effective for conservation and monitoring efforts.
KeywordsDamselfly NDVI Proper conditional autoregressive model Remote sensing Satoyama
We would like to thank Dr. Ogawa M, Dr. Ishihama F, and Ms. Matsuzaki S for providing data and information on the land-use/land-cover map in Ogawa et al. (2013). We also appreciate two anonymous reviewers for thoughtful comments, which greatly improved this manuscript. The GLCNMO2003 and GLCNMO2008 maps were retrieved from International Steering Committee for Global Mapping at http://www.iscgm.org/gm/glcnmo.html (accessed August 3, 2015). The MODIS 13Q1 data products were retrieved from the online Data Pool, courtesy of the NASA Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota, https://lpdaac.usgs.gov/data_access/data_pool (accessed August 3, 2015). This study was funded by Japan Society for the Promotion of Science (grant ID: 25740047 and 26292181).
- Akasaka, M., A. Takenaka, F. Ishihama, T. Kadoya, M. Ogawa, T. Osawa, T. Yamakita, S. Tagane, et al. 2014. Development of a national land-use/cover dataset to estimate biodiversity and ecosystem services. In Integrative observations and assessments: Ecological Research monograph, ed. S. Nakano, T. Yahara, and T. Nakashizuka, 209–229. Tokyo: Springer Japan.Google Scholar
- Bivand, R.S., V. Gomez-Rubio, and H. Rue. 2015. Spatial data analysis with R-INLA with some extensions. Journal of Statistical Software 63: 20. http://hdl.handle.net/11250/276910.
- Environment Agency, Japan and Asia Air Survey Co., Ltd. 1999. The 5th national survey on the natural environment: Report of vegetation survey. Retrieved August 21, 2015, from http://www.biodic.go.jp/reports2/5th/vgtmesh/vgtmesh/5_vgtmesh.pdf (in Japanese with English summary).
- Huete, A., C. Justice, and W. van Leeuwen. 1999. MODIS Vegetation Index (MOD 13): Algorithm Theoretical Basis Document (version 3). Retrieved August 3, 2015, from http://modis.gsfc.nasa.gov/data/atbd/atbd_mod13.pdf.
- Imai, J., T. Kadoya, and I. Washitani. 2013. A land-cover heterogeneity index for the state of biodiversity in the Satoyama landscape: Assessment of spatial scale and resolution using participatory monitoring data in Fukui Prefecture. Japanese Journal of Conservation Ecology 18: 19–31 (in Japanese with English abstract).Google Scholar
- Japan Wildlife Research Center (JWRC). 2010. Biodiversity of Japan: A harmonious coexistence between nature and humankind. Fujiyoshida: Biodiversity Center of Japan, Nature Conservation Bureau, Ministry of the Environment.Google Scholar
- Jones, H.G., and R.A. Vaughan. 2010. Remote sensing of vegetation. New York: Oxford University Press.Google Scholar
- Land Processes Distributed Active Archive Center (LP DAAC). 2013. MODIS 13Q1. Retrieved August 3, 2015, from https://lpdaac.usgs.gov/data_access/data_pool.
- Millennium Ecosystem Assessment. 2005. Ecosystems and human well being: Our human planet summary for decision-makers. Washington, DC: Island Press.Google Scholar
- Ministry of the Environment, Japan, 2009. Japan Integrated Biodiversity Information System (J-IBIS). Retrieved August 3, 2015, from http://www.biodic.go.jp/english/J-IBIS.html.
- Ogawa, M., A. Takenaka, T. Kadoya, F. Ishihama, H. Yamano, and M. Akasaka. 2013. Land-use classification and mapping at a whole scale of Japan based on a national vegetation map. Japanese Journal of Conservation Ecology 18: 69–76 (in Japanese with English abstract).Google Scholar
- R Core Team. 2014. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. Retrieved August 3, 2015, from http://www.R-project.org/.
- Sugimura, M., S. Ishida, K. Kojima, K. Ishida, and T. Aoki. 1999. Dragonflies of the Japanese Archipelago in color. Sapporo, Japan: Sapporo University Press (in Japanese).Google Scholar
- Yoshioka, A., T. Kadoya, J. Imai, and I. Washitani. 2013. Overview of land-use pattern of Japanese Archipelago with biodiversity-conscious land-use classification and Satoyama Index. Japanese Journal of Conservation Ecology 18: 141–156 (in Japanese with English summary).Google Scholar
- Zhang, Z.D., and R.G. Zang. 2011. Relationship between species richness of plant functional groups and landscape patterns in a tropical forest of Hainan Island, China. Journal of Tropical Forest Science 23: 289–298.Google Scholar