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Combining occurrence and abundance distribution models for the conservation of the Great Bustard
Mi, Chunrong1; Huettrnann, Falk2; Suns, Rui3; Guo, Yumin1
2017-12-13
Source PublicationPEERJ
ISSN2167-8359
Volume5Pages:20
Corresponding AuthorGuo, Yumin(guoyumin@bjfu.edu.cn)
AbstractSpecies distribution models (SDMs) have become important and essential tools in conservation and management. However, SDMs built with count data, referred to as species abundance models (SAMs), are still less commonly used to date, but increasingly receiving attention. Species occurrence and abundance do not frequently display similar patterns, and often they are not even well correlated. Therefore, only using information based on SDMs or SAMs leads to an insufficient or misleading conservation efforts. How to combine information from SDMs and SAMs and how to apply the combined information to achieve unified conservation remains a challenge. In this study, we introduce and propose a priority protection index (PI). The PI combines the prediction results of the occurrence and abundance models. As a case study, we used the best available presence and count records for an endangered farmland species, the Great Bustard (Otis tarda dybowskii), in Bohai Bay,'China.l We then applied the Random Forest algorithm (Salford Systems Ltd. Implementation) with eleven 1predictor variables to forecast the spatial occurrence as we las the abundance distribution. The results show that the occurrence model had a decent performance (ROC:(0.77) and the abundance model had a RMSE of 26.54. It is noteworthy that environmental variables influenced bustard occurrence and abundance differently. The area of farmland, and the distance to residential areas were the top important variables influencing bustard occurrence. While the distance to national roads and to expressways were the most important influencing abundance. In addition, the occurrence and abundance models displayed different spatial distribution patterns. The regions with a high index of occurrence were concentrated in the south-central part of the study area; and the abundance distribution showed high populations Species occurrence in the central and northwestern parts of the study area. However, combining occurrence and abundance indices to produce a priority protection index (PI) to be used for conservation could guide the protection of the areas with high occurrence and high abundance (e.g., in Strategic Conservation Planning). Due to the widespread use of SDMs and the easy subsequent employment of SAMs, these findings have a wide relevance and applicability than just those only based on SDMs or SAMs and tiladate the We promote and strongly encourage researchers to further test, apply priority protection inde) (PI) elsewhere to explore the generality of rid methods that are now readil available.
KeywordConservation decision Occurrence model Abundance model Great Bustard (Otis tarda dybowskii) Machine learning method Random Forest
DOI10.7717/peerj.4160
WOS KeywordSPECIES DISTRIBUTION MODELS ; HABITAT SELECTION ; RANDOM FORESTS ; PREDICTION ; ECOLOGY ; CANADA ; METAPOPULATION ; SCENARIOS ; ABSENCE ; GUIDE
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[31570532] ; State Forestry Administration of China ; Scientific Research Committee of the China Wildlife Conservation Association[kkw-2017-005]
Funding OrganizationNational Natural Science Foundation of China ; State Forestry Administration of China ; Scientific Research Committee of the China Wildlife Conservation Association
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000417862700006
PublisherPEERJ INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/56817
Collection中国科学院地理科学与资源研究所
Corresponding AuthorGuo, Yumin
Affiliation1.Beijing Forestry Univ, Coll Nat Conservat, Beijing, Peoples R China
2.Univ Alaska Fairbanks, Inst Arctic Biol, Dept Biol & Wildlife, EWHALE Lab, Fairbanks, AK USA
3.Univ Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Mi, Chunrong,Huettrnann, Falk,Suns, Rui,et al. Combining occurrence and abundance distribution models for the conservation of the Great Bustard[J]. PEERJ,2017,5:20.
APA Mi, Chunrong,Huettrnann, Falk,Suns, Rui,&Guo, Yumin.(2017).Combining occurrence and abundance distribution models for the conservation of the Great Bustard.PEERJ,5,20.
MLA Mi, Chunrong,et al."Combining occurrence and abundance distribution models for the conservation of the Great Bustard".PEERJ 5(2017):20.
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