Problems and Countermeasures in Prediction Model of Potential Distribution of Plant Species with Extremely Small Populations
DOI: 10.23977/erej.2022.060501 | Downloads: 9 | Views: 463
Author(s)
Wei Hu 1, Xin Liang 1, Yaqi Zhang 1, Xiansheng Tan 1, Renyan Duan 1
Affiliation(s)
1 College of Agriculture and Biology Technology, Hunan University of Humanities Science and Technology, Loudi, Hunan, 417000, China
Corresponding Author
Renyan DuanABSTRACT
The plant species with extremely small populations (PSESP) is a kind of wild plant population that is on the verge of extinction. It is important to reasonably predict the suitable distribution area of the PSESP for its protection. However, the lack of suitable prediction models, low quality of distribution data and high sensitivity of simulation process can limit the application of species distribution models in the protection of PSESP. It is suggested that a small model niche factor model set should be constructed and optimized according to the different distribution characteristics of PSESP. In order to improve the quality of distribution data, the method of combining real species with virtual species is used to conduct field iterative stratified sampling. Based on the distribution data of iterative stratified sampling lifting and the optimized small model niche factor model, the key factors in the simulation process are optimized to reasonably predict the suitable distribution area of PSESP. Based on the distribution of nature reserves and the potential distribution of PSESP, field investigation and verification, the appropriate in situ or ex situ protection strategies for PSESP can be proposed.
KEYWORDS
Plant species with extremely small populations, Suitable habitat, Species distribution model, Prediction modelCITE THIS PAPER
Wei Hu, Xin Liang, Yaqi Zhang, Xiansheng Tan, Renyan Duan, Problems and Countermeasures in Prediction Model of Potential Distribution of Plant Species with Extremely Small Populations. Environment, Resource and Ecology Journal (2022) Vol. 6: 1-4. DOI: http://dx.doi.org/10.23977/erej.2022.060501.
REFERENCES
[1] Ma, Y.P., Chen, G., Grumbine, R.E., Dao, Z.L., Sun, W.B. and Guo, H.J. (2013) Conserving plant species with extremely small populations (PSESP) in China. Biodiversity and Conservation, 22, 803-809.
[2] Qu, H., Wang, C.J. and Zhang, Z.X. (2018) Planning priority conservation areas under climate change for six plant species with extremely small populations in China. Nature Conservation, 25, 89-106.
[3] Breiner, F.T., Guisan, A., Bergamini, A. and Nobis, M.P. (2015) Overcoming limitations of modelling rare species by using ensembles of small models.Methods in Ecology and Evolution, 6, 1210-1218.
[4] Støa, B., Halvorsen, R., Stokland, J.N. and Gusarov, V.I. (2019) How much is enough? Influence of number of presence observations on the performance of species distribution models.Sommerfeltia, 39, 1-28.
[5] Gábor, L., Moudrý, V., Lecours, V., Malavasi, M., Barták, V., Fogl, M., Šímová, P., Rocchini, D. and Václavík, T. (2020) The effect of positional error on fine scale species distribution models increases for specialist species. Ecography, 43, 256-269.
[6] Burrows, M.T., Schoeman, D.S., Richardson, A.J., Molinos, J.G., Hoffmann, A., Buckley, L.B., Moore, P.J., Brown, C.J., Bruno, J.F., Duarte, C.M., Halpern, B.S., Hoegh-Guldberq, O., Kappel, C.V., Kiessling, W., O’Connor, M.I., Pandolfi, J.M., Parmesan, C., Sydeman, W.J., Ferrier, S., Williams, K.J. and Poloczanska, E.S. (2014) Geographical limits to species-range shifts are suggested by climate velocity. Nature, 507, 492-495.
[7] Komori, O., Eguchi, S., Saigusa, Y., Kusumoto, B. and Kubota, Y. (2020) Sampling bias correction in species distribution models by quasi-linear poisson point process. Ecological Informatics, 55, 101015.
[8] Qiao, H.J., Feng, X., Escobar, L.E., Peterson, A.T., Soberón, J., Zhu, G.P. and Papeş, M. (2019) An evaluation of transferability of ecological niche models. Ecography, 42, 521-534.
[9] Tikhonov, G., Duan, L., Abrego, N., Newell, G., White, M., Dunson, D. and Ovaskainen, O. (2020) Computationally efficient joint species distribution modeling of big spatial data. Ecology, 101, e02929.
[10] Duan, R.Y., Kong, X.Q., Huang, M.Y., Varela, S. and Ji, X. (2016) The potential effects of climate change on amphibian distribution, range fragmentation and turnover in China. PeerJ, 4, e2185.
[11] García-Roselló, E., Guisande, C., González-Vilas, L., González-Dacosta, J., Heine, J., Pérez-Costas, E. and Lobo, J.M. (2019) A simple method to estimate the probable distribution of species. Ecography, 42, 1613-1622.
[12] Engler, R., Guisan, A. and Rechsteiner, L. (2004) An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo‐absence data. Journal of Applied Ecology, 41, 263-274.
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