Sobral-Souza Thadeu, Stropp Juliana, Santos Jessie Pereira, Prasniewski Victor Mateus, Szinwelski Neucir, Vilela Bruno, Freitas André Victor Lucci, Ribeiro Milton Cezar, Hortal Joaquín
Departamento de Botânica e Ecologia, Universidade Federal de Mato Grosso, Cuiaba, Mato Grosso, Brazil.
Department of Biogeography and Global Change, Museo Nacional de Ciencias Naturales (MNCN-CSIC), Madrid, Spain.
PeerJ. 2021 Jun 25;9:e11673. doi: 10.7717/peerj.11673. eCollection 2021.
A key challenge for conservation biology in the Neotropics is to understand how deforestation affects biodiversity at various levels of landscape fragmentation. Addressing this challenge requires expanding the coverage of known biodiversity data, which remain to date restricted to a few well-surveyed regions. Here, we assess the sampling coverage and biases in biodiversity data on fruit-feeding butterflies at the Brazilian Atlantic Forest, discussing their effect on our understanding of the relationship between forest fragmentation and biodiversity at a large-scale. We hypothesize that sampling effort is biased towards large and connected fragments, which occur jointly in space at the Atlantic forest.
We used a comprehensive dataset of Atlantic Forest fruit-feeding butterfly communities to test for sampling biases towards specific geographical areas, climate conditions and landscape configurations.
We found a pattern of geographical aggregation of sampling sites, independently of scale, and a strong sampling bias towards large and connected forest fragments, located near cities and roads. Sampling gaps are particularly acute in small and disconnected forest fragments and rare climate conditions. In contrast, currently available data can provide a fair picture of fruit-feeding butterfly communities in large and connected Atlantic Forest remnants.
Biased data hamper the inference of the functional relationship between deforestation and biodiversity at a large-scale, since they are geographically clustered and have sampling gaps in small and disconnected fragments. These data are useful to inform decision-makers regarding conservation efforts to curb biodiversity loss in the Atlantic Forest. Thus, we suggest to expand sampling effort to small and disconnected forest fragments, which would allow more accurate evaluations of the effects of landscape modification.
新热带地区保护生物学面临的一个关键挑战是了解森林砍伐如何在不同程度的景观破碎化情况下影响生物多样性。应对这一挑战需要扩大已知生物多样性数据的覆盖范围，而迄今为止这些数据仍局限于少数几个经过充分调查的地区。在此，我们评估了巴西大西洋森林中以果实为食的蝴蝶的生物多样性数据的采样覆盖范围和偏差，讨论了它们对我们在大规模层面理解森林破碎化与生物多样性之间关系的影响。我们假设采样工作偏向于大西洋森林中在空间上共同出现的大型且相连的片段。
我们使用了一个关于大西洋森林以果实为食的蝴蝶群落的综合数据集，来测试针对特定地理区域、气候条件和景观配置的采样偏差。
我们发现采样地点存在地理聚集模式，与尺度无关，并且对位于城市和道路附近的大型且相连的森林片段存在强烈的采样偏差。在小型且不相连的森林片段以及罕见气候条件下，采样空白尤为严重。相比之下，目前可用的数据能够较为准确地呈现大型且相连的大西洋森林残余地中以果实为食的蝴蝶群落情况。
有偏差的数据阻碍了对森林砍伐与生物多样性之间功能关系的大规模推断，因为它们在地理上聚集，且在小型且不相连的片段中存在采样空白。这些数据有助于为决策者提供有关遏制大西洋森林生物多样性丧失的保护工作的信息。因此，我们建议将采样工作扩展到小型且不相连的森林片段，这将有助于更准确地评估景观改变的影响。
