The Experts below are selected from a list of 43173 Experts worldwide ranked by ideXlab platform
Florian Zellweger - One of the best experts on this subject based on the ideXlab platform.
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seasonal drivers of understorey temperature buffering in temperate Deciduous Forests across europe
Global Ecology and Biogeography, 2019Co-Authors: Florian Zellweger, David A Coomes, Jonathan Lenoir, Leen Depauw, Sybryn L Maes, Monika Wulf, K J Kirby, Jorg Brunet, Martin KopeckýAbstract:Aim: Forest understorey microclimates are often buffered against extreme heat or cold, with important implications for the organisms living in these environments. We quantified seasonal effects of understorey microclimate predictors describing canopy structure, canopy composition and topography (i.e., local factors) and the forest patch size and distance to the coast (i.e., landscape factors). Location: Temperate Forests in Europe. Time period: 2017-2018. Major taxa studied: Woody plants. Methods: We combined data from a microclimate sensor network with weather-station records to calculate the difference, or offset, between temperatures measured inside and outside Forests. We used regression analysis to study the effects of local and landscape factors on the seasonal offset of minimum, mean and maximum temperatures. Results: The maximum temperature during the summer was on average cooler by 2.1 degrees C inside than outside Forests, and the minimum temperatures during the winter and spring were 0.4 and 0.9 degrees C warmer. The local canopy cover was a strong nonlinear driver of the maximum temperature offset during summer, and we found increased cooling beneath tree species that cast the deepest shade. Seasonal offsets of minimum temperature were mainly regulated by landscape and topographic features, such as the distance to the coast and topographic position. Main conclusions: Forest organisms experience less severe temperature extremes than suggested by currently available macroclimate data; therefore, climate-species relationships and the responses of species to anthropogenic global warming cannot be modelled accurately in Forests using macroclimate data alone. Changes in canopy cover and composition will strongly modulate the warming of maximum temperatures in forest understories, with important implications for understanding the responses of forest biodiversity and functioning to the combined threats of land-use change and climate change. Our predictive models are generally applicable across lowland temperate Deciduous Forests, providing ecologically important microclimate data for forest understories.
Martin Kopecký - One of the best experts on this subject based on the ideXlab platform.
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seasonal drivers of understorey temperature buffering in temperate Deciduous Forests across europe
Global Ecology and Biogeography, 2019Co-Authors: Florian Zellweger, David A Coomes, Jonathan Lenoir, Leen Depauw, Sybryn L Maes, Monika Wulf, K J Kirby, Jorg Brunet, Martin KopeckýAbstract:Aim: Forest understorey microclimates are often buffered against extreme heat or cold, with important implications for the organisms living in these environments. We quantified seasonal effects of understorey microclimate predictors describing canopy structure, canopy composition and topography (i.e., local factors) and the forest patch size and distance to the coast (i.e., landscape factors). Location: Temperate Forests in Europe. Time period: 2017-2018. Major taxa studied: Woody plants. Methods: We combined data from a microclimate sensor network with weather-station records to calculate the difference, or offset, between temperatures measured inside and outside Forests. We used regression analysis to study the effects of local and landscape factors on the seasonal offset of minimum, mean and maximum temperatures. Results: The maximum temperature during the summer was on average cooler by 2.1 degrees C inside than outside Forests, and the minimum temperatures during the winter and spring were 0.4 and 0.9 degrees C warmer. The local canopy cover was a strong nonlinear driver of the maximum temperature offset during summer, and we found increased cooling beneath tree species that cast the deepest shade. Seasonal offsets of minimum temperature were mainly regulated by landscape and topographic features, such as the distance to the coast and topographic position. Main conclusions: Forest organisms experience less severe temperature extremes than suggested by currently available macroclimate data; therefore, climate-species relationships and the responses of species to anthropogenic global warming cannot be modelled accurately in Forests using macroclimate data alone. Changes in canopy cover and composition will strongly modulate the warming of maximum temperatures in forest understories, with important implications for understanding the responses of forest biodiversity and functioning to the combined threats of land-use change and climate change. Our predictive models are generally applicable across lowland temperate Deciduous Forests, providing ecologically important microclimate data for forest understories.
Sonali Saha - One of the best experts on this subject based on the ideXlab platform.
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Patterns in woody species diversity, richness and partitioning of diversity in forest communities of tropical Deciduous forest biome
Ecography, 2003Co-Authors: Sonali SahaAbstract:The regressive succession model hypothesizes tropical savanna-woodlands to be a degraded stage of primary Deciduous Forests. Species diversity, richness and evenness of woody species in savanna-woodlands, secondary Deciduous Forests and mature Deciduous Forests of central India were compared to test if the regressive succession explained pattern in species richness, diversity, functional diversity and basal area. At the plot scale (0.1 ha) secondary Deciduous Forests and savanna-woodlands had similar species diversity, a pattern not consistent with the regressive model of Deciduous forest succession, and mature Deciduous Forests had greater species diversity and richness (p
Andrew D Richardson - One of the best experts on this subject based on the ideXlab platform.
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multiscale modeling of spring phenology across Deciduous Forests in the eastern united states
Global Change Biology, 2016Co-Authors: Eli K Melaas, Mark A Friedl, Andrew D RichardsonAbstract:: Phenological events, such as bud burst, are strongly linked to ecosystem processes in temperate Deciduous Forests. However, the exact nature and magnitude of how seasonal and interannual variation in air temperatures influence phenology is poorly understood, and model-based phenology representations fail to capture local- to regional-scale variability arising from differences in species composition. In this paper, we use a combination of surface meteorological data, species composition maps, remote sensing, and ground-based observations to estimate models that better represent how community-level species composition affects the phenological response of Deciduous broadleaf Forests to climate forcing at spatial scales that are typically used in ecosystem models. Using time series of canopy greenness from repeat digital photography, citizen science data from the USA National Phenology Network, and satellite remote sensing-based observations of phenology, we estimated and tested models that predict the timing of spring leaf emergence across five different Deciduous broadleaf forest types in the eastern United States. Specifically, we evaluated two different approaches: (i) using species-specific models in combination with species composition information to 'upscale' model predictions and (ii) using repeat digital photography of forest canopies that observe and integrate the phenological behavior of multiple representative species at each camera site to calibrate a single model for all Deciduous broadleaf Forests. Our results demonstrate variability in cumulative forcing requirements and photoperiod cues across species and forest types, and show how community composition influences phenological dynamics over large areas. At the same time, the response of different species to spatial and interannual variation in weather is, under the current climate regime, sufficiently similar that the generic Deciduous forest model based on repeat digital photography performed comparably to the upscaled species-specific models. More generally, results from this analysis demonstrate how in situ observation networks and remote sensing data can be used to synergistically calibrate and assess regional parameterizations of phenology in models.
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influence of physiological phenology on the seasonal pattern of ecosystem respiration in Deciduous Forests
Global Change Biology, 2015Co-Authors: Mirco Migliavacca, Markus Reichstein, Andrew D Richardson, Miguel D Mahecha, Edoardo Cremonese, Nicolas Delpierre, Marta Galvagno, Beverly E Law, Georg WohlfahrtAbstract:Understanding the environmental and biotic drivers of respiration at the ecosystem level is a prerequisite to further improve scenarios of the global carbon cycle. In this study we investigated the relevance of physiological phenology, defined as seasonal changes in plant physiological properties, for explaining the temporal dynamics of ecosystem respiration (RECO) in Deciduous Forests. Previous studies showed that empirical RECO models can be substantially improved by considering the biotic dependency of RECO on the short-term productivity (e.g., daily gross primary production, GPP) in addition to the well-known environmental controls of temperature and water availability. Here, we use a model-data integration approach to investigate the added value of physiological phenology, represented by the first temporal derivative of GPP, or alternatively of the fraction of absorbed photosynthetically active radiation, for modeling RECO at 19 Deciduous broadleaved Forests in the FLUXNET La Thuile database. The new data-oriented semiempirical model leads to an 8% decrease in root mean square error (RMSE) and a 6% increase in the modeling efficiency (EF) of modeled RECO when compared to a version of the model that does not consider the physiological phenology. The reduction of the model-observation bias occurred mainly at the monthly time scale, and in spring and summer, while a smaller reduction was observed at the annual time scale. The proposed approach did not improve the model performance at several sites, and we identified as potential causes the plant canopy heterogeneity and the use of air temperature as a driver of ecosystem respiration instead of soil temperature. However, in the majority of sites the model-error remained unchanged regardless of the driving temperature. Overall, our results point toward the potential for improving current approaches for modeling RECO in Deciduous Forests by including the phenological cycle of the canopy.
Chandra Shekhar Jha - One of the best experts on this subject based on the ideXlab platform.
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Estimation of LAI and above-ground biomass in Deciduous Forests: Western Ghats of Karnataka, India
International Journal of Applied Earth Observation and Geoinformation, 2008Co-Authors: Rangaswamy Madugundu, Vyjayanthi Nizalapur, Chandra Shekhar JhaAbstract:Abstract This study demonstrates the potentials of IRS P6 LISS-IV high-resolution multispectral sensor (IGFOV ∼ 6 m)-based estimation of biomass in the Deciduous Forests in the Western Ghats of Karnataka, India. Regression equations describing the relationship between IRS P6 LISS-IV data-based vegetation index (NDVI) and field measured leaf area index (ELAI) and estimated above-ground biomass (EAGB) were derived. Remote sensing (RS) data-based leaf area index (PLAI) image is generated using regression equation based on NDVI and ELAI (r2 = 0.68, p ≤ 0.05). RS-based above-ground biomass (PAGB) image was generated based on regression equation developed between PLAI and EAGB (r2 = 0.63, p ≤ 0.05). The mean value of estimated above-ground biomass and RS-based above-ground biomass in the study area are 280(±72.5) and 297.6(±55.2) Mg ha−1, respectively. The regression models generated in the study between NDVI and LAI; LAI and biomass can also help in generating spatial biomass map using RS data alone. LISS-IV-based estimation of biophysical parameters can also be used for the validation of various coarse resolution satellite products derived from the ground-based measurements alone.
