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217 results for “forest model”
Model inputs and outputs for "Modeling boreal forest soil dynamics with the microbially explicit soil model MIMICS+ (v1.0)"
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Agent‐based modeling of the effects of forest dynamics, selective logging, and fragment size on epiphyte communities
<p>Forest canopies play a crucial role in structuring communities of vascular epiphytes by providing substrate for colonization, by locally varying microclimate, and by causing epiphyte mortality due to branch or tree fall. However, as field studies in the three-dimensional habitat of epiphytes are generally challenging, our understanding of how forest structure and dynamics influence the structure and dynamics of epiphyte communities is scarce. Mechanistic models can improve our understanding of epiphyte community dynamics. We present such a model that couples dispersal, growth, and mortality of individual epiphytes with substrate dynamics, obtained from a three-dimensional functional-structural forest model, allowing the study of forest-epiphyte interactions. After validating the epiphyte model with independent field data, we performed several theoretical simulation experiments to assess how (1) differences in natural forest dynamics, (2) selective logging, and (3) forest fragmentation could influence the long-term dynamics of epiphyte communities. The proportion of arboreal substrate occupied by epiphytes (i.e. saturation level) was tightly linked with forest dynamics and increased with decreasing forest turnover rates. While species richness was, in general, negatively correlated with forest turnover rates, low species numbers in forests with very low turnover rates were due to competitive exclusion when epiphyte communities became saturated. Logging had a negative impact on epiphyte communities, potentially leading to a near-complete extirpation of epiphytes when the simulated target diameters fell below a threshold. Fragment size had no effect on epiphyte abundance and saturation level but correlated positively with species numbers. Synthesis: The presented model is a first step towards studying the dynamic forest-epiphyte interactions in an agent-based modelling framework. Our study suggests forest dynamics as key factor in controlling epiphyte communities. Thus, both natural and human-induced changes in forest dynamics, e.g. increased mortality rates or the loss of large trees, pose challenges for epiphyte conservation.</p>
Supplementary material 1 from: Ferreira EM, Valerio F, Medinas D, Fernandes N, Craveiro J, Costa P, Silva JP, Carrapato C, Mira A, Santos SM (2022) Assessing behaviour states of a forest carnivore in a road-dominated landscape using Hidden Markov Models. In: Santos S, Grilo C, Shilling F, Bhardwaj M, Papp CR (Eds) Linear Infrastructure Networks with Ecological Solutions. Nature Conservation 47: 155-175. https://doi.org/10.3897/natureconservation.47.72781
Figures S1–S3
Fig. 3 in Preliminary Biophysical Assessment Of Forest Ecosystem Services: Two Model Area Examples
Fig. 3. Ecosystem service class: wild plants and their outputs, indicator: Potential blueberry yield.
Modeling the Soil Evaporation Loss in Typical Subtropical Secondary Forests-A Changsha Case Study
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Novel representation of leaf phenology improves simulation of Amazonian evergreen forest photosynthesis in a land surface model
<p>This dataset contains the LAI, Litterfall and GPP etc. of the four Amazon FLUX sites (BR-Sa1, BR-Sa3, BR-Ma2 and GF-Guy) simulated using the improved ORCHIDEE model and the corresponding FLUXNET eddy-covariance or ground-measured data. The more detial please the ReadMe.pdf in the zip.</p> <p>Data is organized with netCDF4(.nc).</p> <p><br> If you want to know more detail please contact: chenxzh73@mail.sysu.edu.cn</p>
A global gross primary productivity dataset of sunlit and shaded leaves via combining two-leaf light use efficiency model with random forest from 2002 to 2020
<p><span>The TL-CRF model generated a global </span><span>0.05</span><span><span>´</span></span><span>0.05<span>°</span></span><span> product for eight-day gross primary productivity (GPP) of sunlit and shaded canopies from 2002 to 2020 by embedding the random forest (RF) submodule into the two-leaf light use efficiency (TL-LUE) model while considering the seasonal differences in the clumping index. The RF technique was used to integrate various environmental stress factors including meteorological, hydrological, soil properties, and elevation, thereby improving the overall scale of the complex environmental conditions to the maximum LUE. Eight-day GPP was then aggregated into monthly, seasonal, and annual GPP. This novel GPP product could support further research on spatial and temporal patterns of the carbon cycle and its association with climate change. </span></p>
Future forest flux (e.g., GPP, NPP, NEP) simulated by the optimized InTEC model under four SSP-RCP scenarios
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Data from: Estimation of aboveground net primary productivity in secondary tropical dry forests using the Carnegie–Ames–Stanford approach (CASA) model
Although tropical dry forests (TDFs) cover roughly 42% of all tropical ecosystems, extensive deforestation and habitat fragmentation pose important limitations for their conservation and restoration worldwide. In order to develop conservation policies for this endangered ecosystem, it is necessary to quantify their provision of ecosystems services such as carbon sequestration and primary production. In this paper we explore the potential of the Carnegie–Ames–Stanford approach (CASA) for estimating aboveground net primary productivity (ANPP) in a secondary TDF located at the Santa Rosa National Park (SRNP), Costa Rica. We calculated ANPP using the CASA model (ANPPCASA) in three successional stages (early, intermediate, and late). Each stage has a stand age of 21 years, 32 years, and 50+ years, respectively, estimated as the age since land abandonment. Our results showed that the ANPPCASA for early, intermediate, and late successional stages were 3.22 Mg C ha−1 yr−1, 8.90 Mg C ha−1 yr−1, and 7.59 Mg C ha−1 yr−1, respectively, which are comparable with rates of carbon uptake in other TDFs. Our results indicate that key variables that influence ANPP in our dry forest site were stand age and precipitation seasonality. Incident photosynthetically active radiation and temperature were not dominant in the ANPPCASA. The results of this study highlight the potential of the use of remote sensing techniques and the importance of incorporating successional stage in accurate regional TDF ANPP estimation.
Projected shifts in deadwood bryophytes in Sweden, data used for species distribution modelling and for climate and forest scenario analysis
<p>Climate change and habitat loss are main threats to forest biodiversity. We fitted ensembles of single species distribution models for 23 deadwood-living bryophyte species in Sweden, based on species records from the Swedish Lifewatch website. This data set comprises the species and environmental data used for species distribution modelling, and coefficients of the fitted single species distribution models (GLM, Poisson point-process, MaxEnt).</p> <p>Based on the fitted species distribution models, we conducted simulations of future species distributions given realistic climate and forest projection scenarios at the national scale of Sweden. The data used for the scenario analysis are stored here.</p>
The data and code for "Gap-Filling of Turbulent Heat Fluxes over Rice–Wheat-Rotation Croplands Using the Random Forest Model""
<p>This file contains the dataset and code for the paper "Gap-Filling of Turbulent Heat Fluxes over Rice–Wheat-Rotation Croplands Using the Random Forest Model".</p>
Supplementary material 1 from: Nunes P, Robinet C, Branco M, Franco JC (2023) Modelling the invasion dynamics of the African citrus psyllid: The role of human-mediated dispersal and urban and peri-urban citrus trees. In: Jactel H, Orazio C, Robinet C, Douma JC, Santini A, Battisti A, Branco M, Seehausen L, Kenis M (Eds) Conceptual and technical innovations to better manage invasions of alien pests and pathogens in forests. NeoBiota 84: 369-396. https://doi.org/10.3897/neobiota.84.91540
Supplementary tables
Data from: Estimation of aboveground net primary productivity in secondary tropical dry forests using the Carnegie–Ames–Stanford approach (CASA) model
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Agent‐based modeling of the effects of forest dynamics, selective logging, and fragment size on epiphyte communities
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Projected shifts in deadwood bryophytes in Sweden, data used for species distribution modelling and for climate and forest scenario analysis
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Data from: Using a forest dynamics model to link community assembly processes and traits structure
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GEDI-FIA Fusion: Training Lidar Models to Estimate Forest Attributes
This dataset includes interpolated cumulative waveforms, with uncertainties, over national forest inventory (FIA) field plots across the contiguous United States. The predicted waveforms are for the Global Ecosystem Dynamics Investigation (GEDI) instrument, which produces high resolution laser ranging observations of the 3D structure of the Earth. GEDI's data provides precise measurements of forest canopy height, canopy vertical structure, and surface elevation. This dataset also provides R scripts to extract information from user-selected plots and for training linear regression models between GEDI lidar metrics and target forest attributes. The interpolated waveforms are provided in RData and JSON formats. A table of Forest Inventory and Analysis (FIA) plot information is included in comma separated values format
PnET Models: Carbon, Nitrogen, Water Dynamics in Forest Ecosystems (Vers. 4 and 5)
PnET (Photosynthetic / EvapoTranspiration model) is a nested series of models of carbon, water, and nitrogen dynamics in forest ecosystems. The models can be used to predict transient responses in net primary production (NPP), carbon and water balances, net nitrogen (N) mineralization and nitrification and N leaching losses, resulting from changes in climate, N deposition, tropospheric ozone and land use as well as variation in species composition. The models have been developed and validated in the Northeastern U.S. at both the site and grid level (to 1-km resolution) at the Complex Systems Research Center, University of New Hampshire, by John Aber and colleagues.
LINKAGES: An Individual-based Forest Ecosystem Biogeochemistry Model
This model product contains the source codes for version 1 of the individual-based forest ecosystem biogeochemistry model LINKAGES and two subsequent versions as well as example input and output data. LINKAGES predicts long-term structure and dynamics of forest ecosystems as constrained by nitrogen availability, climate, and soil moisture. Model simulations compare favorably to field data from different geographic areas worldwide. LINKAGES, written in FORTRAN and provided in ASCII format, simulates birth, growth, and death of all trees greater than 1.43-cm dbh. Litter fall and decomposition are also simulated. Sunlight is the driving variable. Growing season degree days, soil water availability, and AET are calculated from precipitation, temperature, soil field moisture capacity, and wilting point. Decomposition and soil N availability are calculated from organic matter quantity and carbon chemistry, evapotranspiration, and degree of canopy closure. Light availability to each tree is a function of leaf biomass of taller trees. Degree days and availabilities of light and water constrain species reproduction. These variables plus soil N constrain tree growth and carbon accumulation in biomass. Tree death probability increases with age and slow growth. Leaf, root, and woody litter are returned to the soil at the end of each year to decay the following year. Climatic and forest data for eastern North America and New South Wales are provided as example model inputs. Modelers may use their own site data within any version of LINKAGES. Example model output is also provided.
PnET-BGC: Modeling Biogeochemical Processes in a Northern Hardwood Forest Ecosystem
This archived model product contains the directions, executables, and procedures for running PnET-BGC to recreate the results of Gbondo-Tugbawa, S.S., C.T. Driscoll , J.D. Aber and G.E. Likens. 2001. The evaluation of an integrated biogeochemical model (PnET-BGC) at a northern hardwood forest ecosystem. Water Resources Research 37:1057-1070. Gbondo-Tugbawa et al,. 2001 Excerptfrom Abstract: An integrated biogeochemical model (PnET-BGC) was formulated to simulate chemical transformations of vegetation, soil, and drainage water in northern forest ecosystems. The model operates on a monthly time step and depicts the major biogeochemical processes, such as forest canopy element transformations, hydrology, soil organic matter dynamics, nitrogen cycling, geochemical weathering, and chemical equilibrium reactions involving solid and solution phases. The model was evaluated against soil and stream data at the Hubbard Brook Experimental Forest, New Hampshire. Model predictions of concentrations and fluxes of major elements generally agreed reasonably well with measured values, as estimated by normalized mean error and normalized mean absolute error. Model output of soil base saturation and stream acid neutralizing capacity were sensitive to parameter values of soil partial pressure of carbon dioxide, soil mass, soil cation exchange capacity, and soil selectivity coefficients of calcium and aluminum. PnET-BGC can be used as a tool to evaluate the response of soil and water chemistry of forest ecosystems to disturbances such as clear-cutting, climatic events, and atmospheric deposition.PnET-BGC, was used to investigate inputs and dynamics of S in a northern hardwood forest at the Hubbard Brook Experimental Forest (HBEF) (Gbondo-Tugbawa et al., 2002). The changes in soil S pools and stream-water were simulated to assess the response 22 SO4 to both atmospheric S deposition and forest clear-cutting disturbances. Watershed studies across the northeastern United States have shown that stream losses of exceed atmospheric sulfur (S) deposition. Understanding the processes responsible for this additional source of S is critical to quantifying ecosystem response to ongoing and potential future controls on SO2 emission.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.