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Causes and Consequences of Species Diversity in Forest Ecosystems

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ISBN: 9783039213092 9783039213108 Year: Pages: 272 DOI: 10.3390/books978-3-03921-310-8 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Geography
Added to DOAB on : 2019-08-28 11:21:27
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Abstract

What are the causes and consequences of species diversity in forested ecosystems, and how is this species diversity being affected by rapid environmental and climatic change, movement of invertebrate and vertebrate herbivores into new biogeographic regions, and expanding human populations and associated shifts in land-use patterns? In this book, we explore these questions for assemblages of forest trees, shrubs, and understory herbs at spatial scales ranging from small plots to large forest dynamics plots, at temporal scales ranging from seasons to centuries, in both temperate and tropical regions, and across rural-to-urban gradients in land use.

Keywords

Ericaceae --- variation partitioning --- climate --- species-area relationship --- mid-domain effect --- spatial patterns --- individual species-area relationship --- tropical evergreen mixed forest --- competition and facilitation --- Vietnam --- microarthropod --- diversity --- seasonal variations --- stand development --- biodiversity --- climate --- human footprint --- productivity --- topography --- USDA Forest Service --- herbaceous layer --- excess nitrogen --- canopy structure --- temperate forests --- Fagus sylvatica --- Pinus sylvestris --- Picea abies --- Pseudotsuga menziesii --- forest management --- tree species diversity --- forest conversion --- gamma diversity --- landscape scale --- Biodiversity Exploratories --- climate change --- temperature --- precipitation --- Hubbard Brook --- elevational shifts --- mountains --- species diversity --- structural complexity --- legacies --- wind damage --- uprooting --- trunk breakage --- understory plant communities --- natural disturbance-based silviculture --- forest management --- species conservation --- northern hardwood forests --- abundance --- Bray-Curtis --- codispersion analysis --- Smithsonian ForestGEO --- Shannon diversity --- Simpson diversity --- spatial analysis --- species richness --- windthrow --- tornado --- tree species --- disturbance severity --- tree regeneration --- salvaging --- salvage logging --- succession --- Climatic change --- species diversity --- potential habitats --- China --- Maxent --- Salicaceae --- herbaceous perennial species --- household respondents --- questionnaire survey --- species richness --- woody species --- temperate forests --- species richness --- assemblage lineage diversity --- phylogenetic diversity --- evolutionary diversity --- United States --- trees --- TILD

Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters

Authors: --- ---
ISBN: 9783039212392 9783039212408 Year: Pages: 334 DOI: 10.3390/books978-3-03921-240-8 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2019-12-09 11:49:15
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Abstract

Monitoring of vegetation structure and functioning is critical to modeling terrestrial ecosystems and energy cycles. In particular, leaf area index (LAI) is an important structural property of vegetation used in many land surface vegetation, climate, and crop production models. Canopy structure (LAI, fCover, plant height, and biomass) and biochemical parameters (leaf pigmentation and water content) directly influence the radiative transfer process of sunlight in vegetation, determining the amount of radiation measured by passive sensors in the visible and infrared portions of the electromagnetic spectrum. Optical remote sensing (RS) methods build relationships exploiting in situ measurements and/or as outputs of physical canopy radiative transfer models. The increased availability of passive (radar and LiDAR) RS data has fostered their use in many applications for the analysis of land surface properties and processes, thanks also to their insensitivity to weather conditions and the capability to exploit rich structural and textural information. Data fusion and multi-sensor integration techniques are pressing topics to fully exploit the information conveyed by both optical and microwave bands.

Keywords

conifer forest --- leaf area index --- smartphone-based method --- canopy gap fraction --- terrestrial laser scanning --- forest inventory --- density-based clustering --- forest aboveground biomass --- root biomass --- tree heights --- GLAS --- artificial neural network --- allometric scaling and resource limitation --- structure from motion (SfM) --- 3D point cloud --- remote sensing --- local maxima --- fixed tree window size --- managed temperate coniferous forests --- point cloud --- spectral information --- structure from motion (SfM) --- unmanned aerial vehicle (UAV) --- chlorophyll fluorescence (ChlF) --- drought --- Mediterranean --- photochemical reflectance index (PRI) --- photosynthesis --- R690/R630 --- recovery --- BAAPA --- remote sensing --- household survey --- forest --- farm types --- automated classification --- sampling design --- adaptive threshold --- over and understory cover --- LAI --- leaf area index --- EPIC --- simulation --- satellite --- MODIS --- biomass --- evaluation --- southern U.S. forests --- VIIRS --- leaf area index (LAI) --- Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) --- MODIS --- consistency --- uncertainty --- evaluation --- downscaling --- Pléiades imagery --- unmanned aerial vehicle --- stem volume estimation --- remote sensing --- clumping index --- leaf area index --- trunk --- terrestrial LiDAR --- HemiView --- forest above ground biomass (AGB) --- polarization coherence tomography (PCT) --- P-band PolInSAR --- tomographic profiles --- canopy closure --- global positioning system --- hemispherical sky-oriented photo --- signal attenuation --- geographic information system --- digital aerial photograph --- aboveground biomass --- leaf area index --- photogrammetric point cloud --- recursive feature elimination --- machine-learning --- forest degradation --- multisource remote sensing --- modelling aboveground biomass --- random forest --- Brazilian Amazon --- validation --- phenology --- NDVI --- LAI --- spectral analyses --- European beech --- altitude --- forests biomass --- remote sensing --- REDD+ --- random forest --- Tanzania --- RapidEye

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MDPI - Multidisciplinary Digital Publishing Institute (2)


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CC by-nc-nd (2)


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english (2)


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2019 (2)