生命积分:通过参数Rao’s Q指数曲线下的面积从空间上跟踪生态系统的空间异质性

IF 3.1 3区 环境科学与生态学 Q2 ECOLOGY Ecological Complexity Pub Date : 2022-12-01 DOI:10.1016/j.ecocom.2023.101029
Elisa Thouverai , Matteo Marcantonio , Jonathan Lenoir , Mariasole Galfré , Elisa Marchetto , Giovanni Bacaro , Roberto Cazzolla Gatti , Daniele Da Re , Michele Di Musciano , Reinhard Furrer , Marco Malavasi , Vítězslav Moudrý , Jakub Nowosad , Franco Pedrotti , Raffaele Pelorosso , Giovanna Pezzi , Petra Šímová , Carlo Ricotta , Sonia Silvestri , Enrico Tordoni , Duccio Rocchini
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引用次数: 4

摘要

空间生态异质性与许多生态过程和功能密切相关,如植物物种多样性格局和变化、超种群动态和基因流动。遥感对测量大区域生态系统的空间异质性特别有用,需要在空间和时间上进行重复测量。此外,为空间生态建模开发免费和开源算法对于证明分析工作流程的可重复性至关重要。从这个角度来看,美国国家航空航天局开发了诸如表面生物学和地质学(SBG)之类的项目,以支持开发利用星载遥感数据的算法,以提供相对快速但准确的大面积生态特性估计。大多数测量空间异质性的指数都是点描述符:它们只捕获了整个异质性谱的一部分。在SBG的框架下,本文提供了栅格R包的一个新的R函数部分,它允许通过考虑其所有可能的方面来计算空间生态异质性及其随时间的变化。新功能在两个不同的案例研究中进行了测试,分别是多光谱和高光谱图像,证明了它是测量异质性和检测其随时间变化的有效工具。
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Integrals of life: Tracking ecosystem spatial heterogeneity from space through the area under the curve of the parametric Rao’s Q index

Spatio-ecological heterogeneity is strongly linked to many ecological processes and functions such as plant species diversity patterns and change, metapopulation dynamics, and gene flow. Remote sensing is particularly useful for measuring spatial heterogeneity of ecosystems over wide regions with repeated measurements in space and time. Besides, developing free and open source algorithms for ecological modelling from space is vital to allow to prove workflows of analysis reproducible. From this point of view, NASA developed programs like the Surface Biology and Geology (SBG) to support the development of algorithms for exploiting spaceborne remotely sensed data to provide a relatively fast but accurate estimate of ecological properties in vast areas over time. Most of the indices to measure heterogeneity from space are point descriptors : they catch only part of the whole heterogeneity spectrum. Under the SBG umbrella, in this paper we provide a new R function part of the rasterdiv R package which allows to calculate spatio-ecological heterogeneity and its variation over time by considering all its possible facets. The new function was tested on two different case studies, on multi- and hyperspectral images, proving to be an effective tool to measure heterogeneity and detect its changes over time.

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来源期刊
Ecological Complexity
Ecological Complexity 环境科学-生态学
CiteScore
7.10
自引率
0.00%
发文量
24
审稿时长
3 months
期刊介绍: Ecological Complexity is an international journal devoted to the publication of high quality, peer-reviewed articles on all aspects of biocomplexity in the environment, theoretical ecology, and special issues on topics of current interest. The scope of the journal is wide and interdisciplinary with an integrated and quantitative approach. The journal particularly encourages submission of papers that integrate natural and social processes at appropriately broad spatio-temporal scales. Ecological Complexity will publish research into the following areas: • All aspects of biocomplexity in the environment and theoretical ecology • Ecosystems and biospheres as complex adaptive systems • Self-organization of spatially extended ecosystems • Emergent properties and structures of complex ecosystems • Ecological pattern formation in space and time • The role of biophysical constraints and evolutionary attractors on species assemblages • Ecological scaling (scale invariance, scale covariance and across scale dynamics), allometry, and hierarchy theory • Ecological topology and networks • Studies towards an ecology of complex systems • Complex systems approaches for the study of dynamic human-environment interactions • Using knowledge of nonlinear phenomena to better guide policy development for adaptation strategies and mitigation to environmental change • New tools and methods for studying ecological complexity
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