Predicting suitable nesting sites for the Black caiman (Melanosuchus niger Spix 1825) in the Central Amazon basin

dc.contributor.authorBanon GPR
dc.contributor.authorBanon GJF
dc.contributor.authorVillamarin F
dc.contributor.authorArraut EM
dc.contributor.authorMoulatlet GM
dc.contributor.authorRenno CD
dc.contributor.authorBanon LC
dc.contributor.authorMarioni B
dc.contributor.authorNovo EMLD
dc.contributor.organizationfi=ekologia ja evoluutiobiologia|en=Ecology and Evolutionary Biology |
dc.contributor.organization-code2606402
dc.converis.publication-id41997112
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/41997112
dc.date.accessioned2022-10-28T13:41:14Z
dc.date.available2022-10-28T13:41:14Z
dc.description.abstractAfter many years of illegal hunting and commercialization, the populations of the Black caiman (Melanosuchus niger) have been recovering during the last four decades due to the enforcement of a legislation that inhibits their international commercialization. Protecting nesting sites, in which vulnerable life forms (as reproductive females, eggs, and neonates) spend considerable time, is one of the most appropriate conservation actions aimed at preserving caiman populations. Thus, identifying priority areas for this activity should be the primary concern of conservationists. As caiman nesting sites are often found across the areas with difficult access, collecting nest information requires extensive and costly fieldwork efforts. In this context, species distribution modeling can be a valuable tool for predicting the locations of caiman nests in the Amazon basin. In this work, the maximum entropy method (MaxEnt) was applied to model the M. niger nest occurrence in the Mamiraua Sustainable Development Reserve (MSDR) using remotely sensed data. By taking into account the M. niger nesting habitat, the following predictor variables were considered: conditional distance to open water, distance to bare soil, expanded contributing area from drainage, flood duration, and vegetation type. The threshold-independent prediction performance and binary prediction based on the threshold value of 0.9 were evaluated by the area under the curve (AUC) and performing a binomial test, respectively. The obtained results (AUC = 0.967 +/- 0.006 and a highly significant binomial test P< 0.01) indicated excellent performance of the proposed model in predicting the M. niger nesting occurrence in the MSDR. The variables related to hydrological regimes (conditional distance to open water, expanded contributing area from drainage, and flood duration) most strongly affected the model performance. MaxEnt can be used for developing community-based sustainable management programs to provide socioeconomic benefits to local communities and promote species conservation in a much larger area within the Amazon basin.
dc.format.pagerange47
dc.format.pagerange59
dc.identifier.jour-issn2376-6808
dc.identifier.olddbid183621
dc.identifier.oldhandle10024/166715
dc.identifier.urihttps://www.utupub.fi/handle/11111/33727
dc.identifier.urnURN:NBN:fi-fe2021042822927
dc.language.isoen
dc.okm.affiliatedauthorMoulatlet, Gabriel
dc.okm.discipline1181 Ecology, evolutionary biologyen_GB
dc.okm.discipline1181 Ekologia, evoluutiobiologiafi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA1 ScientificArticle
dc.publisherTAYLOR & FRANCIS LTD
dc.publisher.countryUnited Kingdomen_GB
dc.publisher.countryBritanniafi_FI
dc.publisher.country-codeGB
dc.relation.doi10.1080/23766808.2019.1646066
dc.relation.ispartofjournalNeotropical Biodiversity
dc.relation.issue1
dc.relation.volume5
dc.source.identifierhttps://www.utupub.fi/handle/10024/166715
dc.titlePredicting suitable nesting sites for the Black caiman (Melanosuchus niger Spix 1825) in the Central Amazon basin
dc.year.issued2019

Tiedostot

Näytetään 1 - 1 / 1
Ladataan...
Name:
Predicting suitable nesting sites for the Black caiman Melanosuchus niger Spix 1825 in the Central Amazon basin.pdf
Size:
3.26 MB
Format:
Adobe Portable Document Format
Description:
Publisher's version