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巴西河口海马定位:红树林结构是分布和生境偏好的关键预测因子。

Mapping seahorses in a Brazilian estuary: mangrove structures as key predictors for distribution and habitat preference.

机构信息

Programa de Pós-Graduação em Etnobiologia e Conservação da Natureza, Universidade Federal Rural de Pernambuco, Recife, Pernambuco, Brazil.

LAPEC-Laboratório de Peixes e Conservação Marinha, Universidade Estadual da Paraíba, João Pessoa, Paraíba, Brazil.

出版信息

PeerJ. 2023 Jul 20;11:e15730. doi: 10.7717/peerj.15730. eCollection 2023.

Abstract

Planning for effective conservation demands an accurate understanding of the ecological aspects of species, particularly their distribution and habitat preferences. This is even more critical in the case of data-poor, rare, and threatened species, such as seahorses, mainly when they inhabit vulnerable ecosystems like estuaries. Given the importance of better understanding these parameters to design seahorse conservation strategies, we mapped the distribution and assessed habitat preferences of longsnout seahorses ( in a mangrove estuary in a Brazilian protected area. Using generalised linear mixed-effects models we found that dense mangrove cover macro-habitats and shallow depths predicted seahorse sightings and higher densities. Furthermore, the selective index of micro-habitats used by seahorses showed that seahorses exhibited a preference for mangrove structures as holdfasts (, fallen branches). Due to the significant importance of mangroves in providing suitable habitats for in estuaries, it is crucial to enforce the protection of these ecosystems in conservation and management strategies for the species.

摘要

规划有效的保护措施需要准确了解物种的生态方面,特别是它们的分布和栖息地偏好。对于数据匮乏、稀有和受威胁的物种,如海马,情况更是如此,尤其是当它们栖息在脆弱的生态系统,如河口时。鉴于更好地了解这些参数对于设计海马保护策略的重要性,我们绘制了长吻海马的分布情况,并评估了它们在巴西保护区的红树林河口的栖息地偏好。使用广义线性混合效应模型,我们发现茂密的红树林覆盖的宏观生境和较浅的水深预测了海马的出现和更高的密度。此外,海马使用的微生境的选择指数表明,海马更喜欢作为固着器(,倒下的树枝)的红树林结构。由于红树林在河口为 提供合适栖息地方面具有重要意义,因此在保护和管理该物种的策略中,强制保护这些生态系统至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/933a/10363342/385bc62eb8df/peerj-11-15730-g001.jpg

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