J Plant Ecol ›› 2023, Vol. 16 ›› Issue (3): rtac099.DOI: 10.1093/jpe/rtac099

• Research Articles •    

Community-level predictions in a megadiverse hotspot:comparison of stacked species distribution models to forest inventory data

Victor Pereira Zwiener*,†, Valéria Andressa Alves   

  1. Laboratório de Ecologia e Biogeografia de plantas, Departamento de Biodiversidade, Setor Palotina, Universidade Federal do Paraná, Rua Pioneiro, 2153, Jardim Dallas, 85950-000 Palotina, PR, Brazil
  • Received:2021-09-03 Revised:2022-02-13 Accepted:2022-10-26 Online:2022-12-08 Published:2023-06-01
  • Contact: E-mail: vzwiener@gmail.com
  • About author:†These authors contributed equally to this work.

生物多样性热点地区内的群落预测:堆叠物种分布模型与森林清查数据对比

Abstract: Given the current scenario of climate change and anthropogenic impacts, spatial predictions of biodiversity are fundamental to support conservation and restoration actions. Here, we compared different stacked species distribution models (S-SDMs) to forest inventories to assess if S-SDMs capture emerging properties and geographic patterns of species richness and composition of local communities in a biodiversity hotspot. We generated SDMs for 1499 tree species sampled in 151 sites across the Atlantic Forest. We applied four model stacking approaches to reconstruct the plant communities: binary SDMs (bS-SDMs), binary SDMs cropped by minimum convex polygons (bS-SDMs-CROP), stacked SDMs constrained by the observed species richness (cS-SDMs) and minimum convex polygons of species occurrences (MCPs). We compared the stacking methods with local communities in terms of species richness, composition, community prediction metrics and components of beta diversity—nestedness and turnover. S-SDMs captured general patterns, with bS-SDMs-CROP being the most parsimonious approach. Species composition differed between local communities and all stacking methods, in which bS-SDMs, bS-SDMs-CROP and MCPs followed a nested pattern, whereas species turnover was most important in cS-SDMs. S-SDMs varied in terms of performance, omission and commission errors, leading to a misprediction of some vulnerable, endangered and critically endangered species. Despite differing from forest inventory data, S-SDMs captured part of the variation from local communities, representing the potential species pool. Our results support the use of S-SDMs to endorse biodiversity synthesis and conservation planning at coarse scales and warn of potential misprediction at local scales in megadiverse regions.

Key words: Atlantic Forest, species richness, species composition, nestedness, turnover, ecological niche modeling

摘要:
鉴于当前气候变化和人类活动的影响,生物多样性的空间预测对其保护和修复至关重要。本文将不同堆叠物种分布模型(stacked species distribution models, S-SDMs)的预测结果与森林清查数据进行了比较,以评估这些S-SDMs模型能否捕获生物多样性热点地区物种丰富度的新特性和地理分布及局部群落的组成。我们选取大西洋沿岸森林151处地点的1499个树种进行SDM模型构建,并利用4种模型堆叠方法重建植物群落。这43种方法分别为二进制SDM模型(bS-SDM)、由最小凸多边形裁剪得到的二进制SDM模型(bS-SDM-CROP)、受物种丰富度观测结果约束的堆叠SDM模型(cS-SDM)以及物种出现点的最小凸多边形(MCP)。我们从物种丰富度、组成、群落预测指标以及β多样性组分(物种嵌套和物种周转)等方面将各堆叠方法与局部群落进行对比。研究结果表明,所有S-SDM模型均捕获到了一般分布格局,其中bS-SDM-CROP模型最为简约。各堆叠模型预测得到的物种组成与局部群落的实际情况存在一定的差异,其中bS-SDM、bS-SDM-CROP和MCP模型呈现出嵌套格局,而物种周转在cS-SDM模型中最为显著。这些S-SDM模型在性能、遗漏率和记账错率方面的表现各不相同,对一些脆弱、濒危和极度濒危物种给出了错误预测。尽管与森林清查数据有差别,但这些S-SDM模型均捕获了与局部群落数据的部分差异,可以表征物种的潜在分布区。本研究的结论有助于S-SDM模型在粗尺度生物多样性整合与保护规划中的应用,但在生物高度多样性地区局部尺度上可能会得出错误的预测结果。

关键词: 大西洋森林, 物种丰富度, 物种组成, 嵌套, 周转, 生态位建模