scholarly journals Developing Species-Age Cohorts from Forest Inventory and Analysis Data to Parameterize a Forest Landscape Model

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Richard H. Odom ◽  
W. Mark Ford
Keyword(s):  
Tree Species ◽  
Forest Inventory ◽  
Sugar Maple ◽  
Stand Age ◽  
Forest Landscape ◽  
Landscape Model ◽  
Forest Stands ◽  
Forest Inventory And Analysis ◽  
Fort Drum ◽  
Forest Landscape Model

Simulating long-term, landscape level changes in forest composition requires estimates of stand age to initialize succession models. Detailed stand ages are rarely available, and even general information on stand history often is lacking. We used data from USDA Forest Service Forest Inventory and Analysis (FIA) database to estimate broad age classes for a forested landscape to simulate changes in landscape composition and structure relative to climate change at Fort Drum, a 43,000 ha U.S. Army installation in northwestern New York. Using simple linear regression, we developed relationships between tree diameter and age for FIA site trees from the host and adjacent ecoregions and applied those relationships to forest stands at Fort Drum. We observed that approximately half of the variation in age was explained by diameter breast height (DBH) across all species studied (r2 = 0.42 for sugar maple Acer saccharum to 0.63 for white ash Fraxinus americana). We then used age-diameter relationships from published research on northern hardwood species to calibrate results from the FIA-based analysis. With predicted stand age, we used tree species life histories and environmental conditions represented by ecological site types to parameterize a stochastic forest landscape model (LANDIS-II) to spatially and temporally model successional changes in forest communities at Fort Drum. Forest stands modeled over 100 years without significant disturbance appeared to reflect expected patterns of increasing dominance by shade-tolerant mesophytic tree species such as sugar maple, red maple (Acer rubrum), and eastern hemlock (Tsuga canadensis) where soil moisture was sufficient. On drier sandy soils, eastern white pine (Pinus strobus), red pine (P. resinosa), northern red oak (Quercus rubra), and white oak (Q. alba) continued to be important components throughout the modeling period with no net loss at the landscape scale. Our results suggest that despite abundant precipitation and relatively low evapotranspiration rates for the region, low soil water holding capacity and fertility may be limiting factors for the spread of mesophytic species on excessively drained soils in the region. Increasing atmospheric temperatures projected for the region could alter moisture regimes for many coarse-textured soils providing a possible mechanism for expansion of xerophytic tree species.

scholarly journals A large-scale forest landscape model incorporating multi-scale processes and utilizing forest inventory data

Ecosphere ◽  
2013 ◽  
Vol 4 (9) ◽  
pp. art106 ◽  
Author(s):  
Wen J. Wang ◽  
Hong S. He ◽  
Martin A. Spetich ◽  
Stephen R. Shifley ◽  
Frank R. Thompson III ◽  
...  
Keyword(s):  
Forest Inventory ◽  
Large Scale ◽  
Forest Landscape ◽  
Landscape Model ◽  
Inventory Data ◽  
Multi Scale ◽  
Forest Inventory Data ◽  
Forest Landscape Model

Local and global parameter sensitivity within an ecophysiologically based forest landscape model

2019 ◽  
Vol 117 ◽  
pp. 1-13 ◽  
Author(s):  
Patrick F. McKenzie ◽  
Matthew J. Duveneck ◽  
Luca L. Morreale ◽  
Jonathan R. Thompson
Keyword(s):  
Parameter Sensitivity ◽  
Forest Landscape ◽  
Landscape Model ◽  
Global Parameter ◽  
Forest Landscape Model

scholarly journals Upscaling with the dynamic two-layer classification concept (D2C): TreeMig-2L, an efficient implementation of the forest-landscape model TreeMig

2015 ◽  
Vol 8 (7) ◽  
pp. 5535-5575
Author(s):  
J. E. M. S. Nabel
Keyword(s):  
Vegetation Dynamics ◽  
Climatic Changes ◽  
Discrete Models ◽  
Similarity Criteria ◽  
Forest Landscape ◽  
Two Dimensional ◽  
Landscape Model ◽  
Trade Off ◽  
Forest Landscape Model ◽  
Spatio Temporal

Abstract. Models used to investigate impacts of climatic changes on spatio-temporal vegetation dynamics need to balance required accuracy with computational feasibility. To enhance the computational efficiency of these models, upscaling methods are required that maintain key fine-scale processes influencing vegetation dynamics. In this paper, an adjustable method – the dynamic two-layer classification concept (D2C) – for the upscaling of time- and space-discrete models is presented. D2C aims to separate potentially repetitive calculations from those specific to single grid cells. The underlying idea is to extract processes that do not require information about a grid cell's neighbourhood to a reduced-size non-spatial layer, which is dynamically coupled to the original two-dimensional layer. The size of the non-spatial layer is thereby adaptive and depends on dynamic classifications according to pre-specified similarity criteria. I present how D2C can be used in a model implementation on the example of TreeMig-2L, a new, efficient version of the intermediate-complexity forest-landscape model TreeMig. To discuss the trade-off between computational expenses and accuracy, as well as the applicability of D2C, I compare different model stages of TreeMig-2L via simulations of two different application scenarios. This comparison of different model stages demonstrates that applying D2C can strongly reduce computational expenses of processes calculated on the new non-spatial layer. D2C is thus a valuable upscaling method for models and applications in which processes requiring information about the neighbourhood constitute the minor share of the overall computational expenses.

Analyzing fine-scale spatiotemporal drivers of wildfire in a forest landscape model

2018 ◽  
Vol 384 ◽  
pp. 87-102 ◽  
Author(s):  
Alan A. Ager ◽  
Ana M.G. Barros ◽  
Michelle A. Day ◽  
Haiganoush K. Preisler ◽  
Thomas A. Spies ◽  
...  
Keyword(s):  
Forest Landscape ◽  
Fine Scale ◽  
Landscape Model ◽  
Forest Landscape Model

Population dynamics of sugar maple through the southern portion of its range: implications for range migration

Botany ◽  
2014 ◽  
Vol 92 (8) ◽  
pp. 563-569 ◽  
Author(s):  
Justin L. Hart ◽  
Christopher M. Oswalt ◽  
Craig M. Turberville
Keyword(s):  
Forest Inventory ◽  
Acer Saccharum ◽  
Sugar Maple ◽  
Basal Area ◽  
Usda Forest Service ◽  
Forest Inventory And Analysis ◽  
Southern Boundary ◽  
Range Boundary ◽  
The Stability ◽  
Biophysical Changes

The range of sugar maple (Acer saccharum Marsh.) is expected to shift northward in accord with changing climate. However, a pattern of increased sugar maple abundance has been reported from sites throughout the eastern US. The goal of our study was to examine the stability of the sugar maple southern range boundary by analyzing its demography through the southern extent of its distribution. We analyzed changes in sugar maple basal area, relative frequency, relative density, relative importance values, diameter distributions, and the ratio of sapling biomass to total sugar maple biomass at three spatial positions near the southern boundary of the species’ range using forest inventory data from the USDA Forest Service Forest Inventory and Analysis program over a 20 year observation period (1990–2010). We contend that the southern range boundary of sugar maple neither contracted nor expanded during this period. We speculated that biophysical changes caused by succession may provide a short-lived ameliorative barrier to a rapid southern range contraction for some species. The eclipse of some greater climate change threshold may therefore be required to realize significant range movement for mesophytic tree species.

scholarly journals Large-scale forest landscape model, design, validation, and application in management of oak decline

2012 ◽  
Author(s):  
◽  
Wenjuan Wang
Keyword(s):  
Forest Inventory ◽  
Large Scale ◽  
Basal Area ◽  
Model Parameters ◽  
Forest Landscape ◽  
Oak Decline ◽  
Model Predictions ◽  
Forest Landscape Model ◽  
Landis Pro

Forest landscape models (FLMs) have increasingly become important tools for exploring forest landscape changes by predicting forest vegetation dynamics over large spatial scales. However, two challenges confronting FLMs have persisted: how to simulate fine, site-scale processes while making large-scale (landscape and regional) simulation feasible, and how to fully take advantage of extensive U.S. Forest Service Inventory and Analysis (FIA) data to initialize and constraint model parameters. In this dissertation, first, a new FLM, LANDIS PRO was developed. In LANDIS PRO, forest succession and dynamics are simulated by incorporating species-, stand-, and landscape-scale processes by tracking number of trees by species age cohort. Because stand-scale resource competition is achieved by implementing rather than simulating the emergent properties of stand development, LANDIS PRO is computationally efficient, which makes large-scale simulation feasible. Since model parameters and simulation results are comparatively straightforward to forest inventory data, current intensive forest inventory data can be directly applied for model initialization and to constrain model parameters. Validation of FLMs is essential to ensure users’ confidence in model predictions and achieve reliable management decision making. To date, validation of FLMs has been limited due to lack of suitable data. However, recent advances in FLMs, together with increasingly available spatiotemporal data make FLM validation feasible. In this dissertation, second, I proposed a framework for validating forest landscape projections from LANDIS PRO using Forest Inventory Analysis (FIA) data. The proposed framework incorporated data assimilation techniques to constrain model parameters and the initial state of the landscape by verifying the initialized landscape and iteratively calibrating the model parameters. The model predictions were rigorously validated against independent FIA data at multiple scales, and the long-term natural successional pattern was also verified against empirical studies. Results showed model predictions were able to capture much of the variation overtime in species basal area and tree density at stand-, landtype- , and landscape-scales. Subsequent long-term predictions of natural succession patterns were consistent with expected changes in tree species density of oak-dominated forests in the absence of disturbance. Lastly, I used LANDIS PRO, a forest landscape model that includes stand-scale species density and basal area to evaluate the potential landscape-scale effects of alternative harvest methods (thinning, clearcutting and group selection) on oak decline mitigation. Projections indicated that forest harvesting can be effective in mitigating oak decline. Group selection and clearcutting were the most effective methods in the management of oak decline in the short-term (20 years) and mid-term (50 years), respectively. However, in the long-run (100 years), there was no significant difference predicted among the three methods.

scholarly journals FORests and HYdrology under Climate Change in Switzerland v1.0: a spatially distributed model combining hydrology and forest dynamics

2020 ◽  
Vol 13 (2) ◽  
pp. 537-564 ◽  
Author(s):  
Matthias J. R. Speich ◽  
Massimiliano Zappa ◽  
Marc Scherstjanoi ◽  
Heike Lischke
Keyword(s):  
Climate Change ◽  
Vegetation Structure ◽  
Drought Index ◽  
Canopy Structure ◽  
Climate Change Scenarios ◽  
Forest Landscape ◽  
Landscape Model ◽  
Forest Landscape Model ◽  
The Impact

Abstract. We present FORHYCS (FORests and HYdrology under Climate Change in Switzerland), a distributed ecohydrological model to assess the impact of climate change on water resources and forest dynamics. FORHYCS is based on the coupling of the hydrological model PREVAH and the forest landscape model TreeMig. In a coupled simulation, both original models are executed simultaneously and exchange information through shared variables. The simulated canopy structure is summarized by the leaf area index (LAI), which affects local water balance calculations. On the other hand, an annual drought index is obtained from daily simulated potential and actual transpiration. This drought index affects tree growth and mortality, as well as a species-specific tree height limitation. The effective rooting depth is simulated as a function of climate, soil, and simulated above-ground vegetation structure. Other interface variables include stomatal resistance and leaf phenology. Case study simulations with the model were performed in the Navizence catchment in the Swiss Central Alps, with a sharp elevational gradient and climatic conditions ranging from dry inner-alpine to high alpine. In a first experiment, the model was run for 500 years with different configurations. The results were compared against observations of vegetation properties from national forest inventories, remotely sensed LAI, and high-resolution canopy height maps from stereo aerial images. Two new metrics are proposed for a quantitative comparison of observed and simulated canopy structure. In a second experiment, the model was run for 130 years under climate change scenarios using both idealized temperature and precipitation change and meteorological forcing from downscaled GCM-RCM model chains. The first experiment showed that model configuration greatly influences simulated vegetation structure. In particular, simulations where height limitation was dependent on environmental stress showed a much better fit to canopy height observations. Spatial patterns of simulated LAI were more realistic than for uncoupled simulations of the forest landscape model, although some model deficiencies are still evident. Under idealized climate change scenarios, the effect of the coupling varied regionally, with the greatest effects on simulated streamflow (up to 60 mm yr−1 difference with respect to a simulation with static vegetation parameters) seen at the valley bottom and in regions currently above the treeline. This case study shows the importance of coupling hydrology and vegetation dynamics to simulate the impact of climate change on ecosystems. Nevertheless, it also highlights some challenges of ecohydrological modeling, such as the need to realistically simulate the plant response to increased CO2 concentrations and process uncertainty regarding future land cover changes.

scholarly journals FORHYCS v1.0: A spatially distributed model combining hydrology and forest dynamics

2019 ◽  
Author(s):  
Matthias J. R. Speich ◽  
Massimiliano Zappa ◽  
Marc Scherstjanoi ◽  
Heike Lischke
Keyword(s):  
Climate Change ◽  
Vegetation Structure ◽  
Drought Index ◽  
Canopy Structure ◽  
Climate Change Scenarios ◽  
Forest Landscape ◽  
Landscape Model ◽  
Forest Landscape Model ◽  
The Impact

Abstract. We present FORHYCS (FORests and HYdrology under Climate Change in Switzerland), a distributed ecohydrological model to assess the impact of climate change on water resources and forest dynamics. FORHYCS is based on the coupling of the hydrological model PREVAH and the forest landscape model TreeMig. In a coupled simulation, both original models are executed simultaneously and exchange information through shared variables. The simulated canopy structure is summarized by the leaf area index (LAI), which affects local water balance calculations. On the other hand, an annual drought index is obtained from daily simulated potential and actual transpiration. This drought index affects tree growth and mortality, as well as a species-specific tree height limitation. The effective rooting depth is simulated as a function of climate, soil and simulated above-ground vegetation structure. Other interface variables include stomatal resistance and leaf phenology. Case study simulations with the model were performed in the Navizence catchment in the Central Swiss Alps, with a sharp elevational gradient and climatic conditions ranging from dry inneralpine to high alpine. In a first experiment, the model was run for 500 years with different configurations. The results were compared against observations of vegetation properties from national forest inventories, remotely sensed LAI and high-resolution canopy height maps from stereo aerial images. Two new metrics are proposed for a quantitative comparison of observed and simulated canopy structure. In a second experiment, the model was run for 130 years under idealized climate change scenarios: daily temperature was increased by up to 6 K, and precipitation altered by 10 %, with a gradual change over 35 years. The first experiment showed that model configuration greatly influences simulated vegetation structure. In particular, simulations where height limitation was dependent on environmental stress showed a much better fit to canopy height observations. Spatial patterns of simulated LAI were more realistic than for uncoupled simulations of the forest landscape model, although some model deficiencies are still evident. Under idealized climate change scenarios, the effect of the coupling varied regionally, with the greatest effects on simulated streamflow (up to 40 mm y−1 difference with respect to a simulation with static vegetation parameters) seen at the valley bottom and in regions currently above the treeline. This case study shows the importance of coupling hydrology and vegetation dynamics to simulate the impact of climate change on ecosystems. Nevertheless, it also highlights some challenges of ecohydrological modelling, such as the need to realistically simulate plant response to increased CO2 concentrations, and process uncertainty regarding future land cover changes.

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