Combining satellite and field data reveals Congo's forest types structure, functioning and composition

IF 3.9 2区 环境科学与生态学 Q1 ECOLOGY Remote Sensing in Ecology and Conservation Pub Date : 2024-10-12 DOI:10.1002/rse2.419
Juliette Picard, Maïalicah M. Nungi‐Pambu Dembi, Nicolas Barbier, Guillaume Cornu, Pierre Couteron, Eric Forni, Gwili Gibbon, Felix Lim, Pierre Ploton, Robin Pouteau, Paul Tresson, Tom van Loon, Gaëlle Viennois, Maxime Réjou‐Méchain
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Abstract

Tropical moist forests are not the homogeneous green carpet often illustrated in maps or considered by global models. They harbour a complex mixture of forest types organized at different spatial scales that can now be more accurately mapped thanks to remote sensing products and artificial intelligence. In this study, we built a large‐scale vegetation map of the North of Congo and assessed the environmental drivers of the main forest types, their forest structure, their floristic and functional compositions and their faunistic composition. To build the map, we used Sentinel‐2 satellite images and recent deep learning architectures. We tested the effect of topographically determined water availability on vegetation type distribution by linking the map with a water drainage depth proxy (HAND, height above the nearest drainage index). We also described vegetation type structure and composition (floristic, functional and associated fauna) by linking the map with data from large inventories and derived from satellite images. We found that water drainage depth is a major driver of forest type distribution and that the different forest types are characterized by different structure, composition and functions, bringing new insights about their origins and successional dynamics. We discuss not only the crucial role of soil–water depth, but also the importance of consistently reproducing such maps through time to develop an accurate monitoring of tropical forest types and functions, and we provide insights on peculiar forest types (Marantaceae forests and monodominant Gilbertiodendron forests) on which future studies should focus more. Under the current context of global change, expected to trigger major forest structural and compositional changes in the tropics, an appropriate monitoring strategy of the spatio‐temporal dynamics of forest types and their associated floristic and faunistic composition would considerably help anticipate detrimental shifts.
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结合卫星和实地数据揭示刚果森林类型的结构、功能和组成
热带潮湿森林并不是地图上经常标示的或全球模型所认为的均匀的绿色地毯。在遥感产品和人工智能的帮助下,现在可以更精确地绘制出不同空间尺度的森林类型。在这项研究中,我们绘制了刚果北部大尺度植被图,并评估了主要森林类型的环境驱动因素、森林结构、花卉和功能组成以及动物组成。为了绘制该地图,我们使用了 Sentinel-2 卫星图像和最新的深度学习架构。我们通过将地图与排水深度代用指标(HAND,最近排水指数以上的高度)相连接,测试了由地形确定的水源对植被类型分布的影响。我们还通过将地图与来自大型清单和卫星图像的数据相连接,描述了植被类型的结构和组成(植物学、功能和相关动物群)。我们发现,排水深度是森林类型分布的主要驱动因素,不同的森林类型具有不同的结构、组成和功能,这为我们了解其起源和演替动态提供了新的视角。我们不仅讨论了土壤水深度的关键作用,还讨论了随着时间的推移不断复制此类地图对准确监测热带森林类型和功能的重要性,并就未来研究应更加关注的特殊森林类型(马缨丹科森林和单优势吉尔伯特碘龙森林)提出了见解。在当前全球变化的背景下,预计热带地区的森林结构和组成将发生重大变化,对森林类型的时空动态及其相关的花卉和动物组成进行适当的监测战略将大大有助于预测有害的变化。
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来源期刊
Remote Sensing in Ecology and Conservation
Remote Sensing in Ecology and Conservation Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
9.80
自引率
5.50%
发文量
69
审稿时长
18 weeks
期刊介绍: emote Sensing in Ecology and Conservation provides a forum for rapid, peer-reviewed publication of novel, multidisciplinary research at the interface between remote sensing science and ecology and conservation. The journal prioritizes findings that advance the scientific basis of ecology and conservation, promoting the development of remote-sensing based methods relevant to the management of land use and biological systems at all levels, from populations and species to ecosystems and biomes. The journal defines remote sensing in its broadest sense, including data acquisition by hand-held and fixed ground-based sensors, such as camera traps and acoustic recorders, and sensors on airplanes and satellites. The intended journal’s audience includes ecologists, conservation scientists, policy makers, managers of terrestrial and aquatic systems, remote sensing scientists, and students. Remote Sensing in Ecology and Conservation is a fully open access journal from Wiley and the Zoological Society of London. Remote sensing has enormous potential as to provide information on the state of, and pressures on, biological diversity and ecosystem services, at multiple spatial and temporal scales. This new publication provides a forum for multidisciplinary research in remote sensing science, ecological research and conservation science.
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