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

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.

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

Ecological Modelling ◽

10.1016/j.ecolmodel.2018.06.018 ◽

2018 ◽

Vol 384 ◽

pp. 87-102 ◽

Cited By ~ 13

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

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

International Journal of Forestry Research ◽

10.1155/2021/6650821 ◽

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.

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

Geoscientific Model Development ◽

10.5194/gmd-13-537-2020 ◽

2020 ◽

Vol 13 (2) ◽

pp. 537-564 ◽

Cited By ~ 2

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.

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

10.5194/gmd-2019-117 ◽

2019 ◽

Cited By ~ 1

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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TreeMig: A forest-landscape model for simulating spatio-temporal patterns from stand to landscape scale

Ecological Modelling ◽

10.1016/j.ecolmodel.2005.11.046 ◽

2006 ◽

Vol 199 (4) ◽

pp. 409-420 ◽

Cited By ~ 134

Author(s):

Heike Lischke ◽

Niklaus E. Zimmermann ◽

Janine Bolliger ◽

Sophie Rickebusch ◽

Thomas J. Löffler

Keyword(s):

Temporal Patterns ◽

Landscape Scale ◽

Forest Landscape ◽

Landscape Model ◽

Forest Landscape Model ◽

Spatio Temporal

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Simulating Growth and Competition on Wet and Waterlogged Soils in a Forest Landscape Model

Frontiers in Ecology and Evolution ◽

10.3389/fevo.2020.598775 ◽

2020 ◽

Vol 8 ◽

Author(s):

Eric J. Gustafson ◽

Brian R. Miranda ◽

Anatoly Z. Shvidenko ◽

Brian R. Sturtevant

Keyword(s):

Climate Change ◽

Tree Growth ◽

Climate Impacts ◽

Species Range ◽

Range Shifts ◽

Forest Landscape ◽

Landscape Model ◽

Time Step ◽

Forest Landscape Model ◽

Waterlogged Soils

Changes in CO2 concentration and climate are likely to alter disturbance regimes and competitive outcomes among tree species, which ultimately can result in shifts of species and biome boundaries. Such changes are already evident in high latitude forests, where waterlogged soils produced by topography, surficial geology, and permafrost are an important driver of forest dynamics. Predicting such effects under the novel conditions of the future requires models with direct and mechanistic links of abiotic drivers to growth and competition. We enhanced such a forest landscape model (PnET-Succession in LANDIS-II) to allow simulation of waterlogged soils and their effects on tree growth and competition. We formally tested how these modifications alter water balance on wetland and permafrost sites, and their effect on tree growth and competition. We applied the model to evaluate its promise for mechanistically simulating species range expansion and contraction under climate change across a latitudinal gradient in Siberian Russia. We found that higher emissions scenarios permitted range expansions that were quicker and allowed a greater diversity of invading species, especially at the highest latitudes, and that disturbance hastened range shifts by overcoming the natural inertia of established ecological communities. The primary driver of range advances to the north was altered hydrology related to thawing permafrost, followed by temperature effects on growth. Range contractions from the south (extirpations) were slower and less tied to emissions or latitude, and were driven by inability to compete with invaders, or disturbance. An important non-intuitive result was that some extant species were killed off by extreme cold events projected under climate change as greater weather extremes occurred over the next 30 years, and this had important effects on subsequent successional trajectories. The mechanistic linkages between climate and soil water dynamics in this forest landscape model produced tight links between climate inputs, physiology of vegetation, and soils at a monthly time step. The updated modeling system can produce high quality projections of climate impacts on forest species range shifts by accounting for the interacting effects of CO2 concentration, climate (including longer growing seasons), seed dispersal, disturbance, and soil hydrologic properties.

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