Forest Ecosystem Model Research Articles

Unravelling the effect of species mixing on water use and drought stress in Mediterranean forests: A modelling approach

Understanding how water use and drought stress in woody plants change in relation to compositional, structural and environmental variability of mixed forests is key to understand their functioning and dynamics. Observational and experimental studies have so far shown a complex array of water use and drought stress responses to species mixing, but progress is hampered by the costs of replicating measurements. A complementary approach consists in using in silico experiments with trait-based forest ecosystem models, which have the advantage of allowing the interpretation of the net mixing effect as the result of specific combinations of trait differences. We explore the potential of such an approach using a novel trait-based forest ecosystem model with a strong focus on plant hydraulics and data from 186 mixed forest inventory plots including holm oak (Quercus ilex L.) and eight co-occurring species. Sensitivity analyses focusing on the effect of differences in individual plant traits indicate that water use and summer drought stress of holm oak trees respond primarily to the variation in competitor's height, root distribution and xylem hydraulic efficiency and safety. Simulations of pure and mixed stands across different combinations of climate aridity and stand leaf area index indicate that differences in traits may compensate for one another, so that the influence of a given trait (e.g. tree height) on water use or drought stress can be decreased or offset by the influence of another one (e.g. hydraulic efficiency). Importantly, we show that species mixing does not always have positive effects at the stand level. Overall, our simulation study shows that the complexity of species- and stand-level mixing effects on water use and drought stress arises primarily as the result of differences in key functional traits of the competitor, although stand structure and climate aridity may modulate mixing effects.

Analysis of the Spatial Differences in Canopy Height Models from UAV LiDAR and Photogrammetry

Forest canopy height is one of the most important spatial characteristics for forest resource inventories and forest ecosystem modeling. Light detection and ranging (LiDAR) can be used to accurately detect canopy surface and terrain information from the backscattering signals of laser pulses, while photogrammetry tends to accurately depict the canopy surface envelope. The spatial differences between the canopy surfaces estimated by LiDAR and photogrammetry have not been investigated in depth. Thus, this study aims to assess LiDAR and photogrammetry point clouds and analyze the spatial differences in canopy heights. The study site is located in the Jigongshan National Nature Reserve of Henan Province, Central China. Six data sets, including one LiDAR data set and five photogrammetry data sets captured from an unmanned aerial vehicle (UAV), were used to estimate the forest canopy heights. Three spatial distribution descriptors, namely, the effective cell ratio (ECR), point cloud homogeneity (PCH) and point cloud redundancy (PCR), were developed to assess the LiDAR and photogrammetry point clouds in the grid. The ordinary neighbor (ON) and constrained neighbor (CN) interpolation algorithms were used to fill void cells in digital surface models (DSMs) and canopy height models (CHMs). The CN algorithm could be used to distinguish small and large holes in the CHMs. The optimal spatial resolution was analyzed according to the ECR changes of DSMs or CHMs resulting from the CN algorithms. Large negative and positive variations were observed between the LiDAR and photogrammetry canopy heights. The stratified mean difference in canopy heights increased gradually from negative to positive when the canopy heights were greater than 3 m, which means that photogrammetry tends to overestimate low canopy heights and underestimate high canopy heights. The CN interpolation algorithm achieved smaller relative root mean square errors than the ON interpolation algorithm. This article provides an operational method for the spatial assessment of point clouds and suggests that the variations between LiDAR and photogrammetry CHMs should be considered when modeling forest parameters.

Radiative forcing of forest biomass production and use under different thinning regimes and initial age structures of a Norway spruce forest landscape

We studied how different thinning regimes and initial age structures of a Norway spruce (Picea abies (L.) Karst.) forest landscape affect the radiative forcing of forest biomass production and use. We considered the effects of forest carbon sequestration, substitution of materials and fossil fuels with forest biomass, and timber use efficiency. The initial age structures of our hypothetical forest landscapes in the middle boreal zone in Finland were young, middle-aged, and mature. Forest landscapes were thinned using either the current thinning recommendations (baseline) or maintaining 20% higher or 20% lower stocking over the 80-year study period. We employed forest ecosystem model simulations together with a life cycle assessment tool. The highest carbon sequestration was obtained by maintaining higher stocking in the landscapes. The initially middle-aged and mature age structures resulted in the strongest cooling of the climate in the first three decades of the simulation, but the highest cooling was found in the young age structure. However, radiative forcing was less sensitive to the thinning than to the substitution or timber use efficiency. Our results indicate that modeled climate impacts are affected by both initial age structure and forest management, which should be considered when generalizing the climate change mitigation potential of forests and forestry.

Effects of using certain tree species in forest regeneration on regional wind damage risks in Finnish boreal forests under different CMIP5 projections

We studied how the use of certain tree species in forest regeneration affected the regional wind damage risks to Finnish boreal forests under the current climate (1981–2010) and recent-generation global climate model (GCM) predictions (i.e., 10 GCMs of CMIP5, with wide variations in temperature and precipitation), using the representative concentration pathways RCP4.5 and RCP8.5 over the period 2010–2099. The study employed forest ecosystem and mechanistic wind damage risk model simulations on upland national forest inventory plots throughout Finland. The amount of wind damage was estimated based on the predicted critical wind speeds for uprooting trees and their probabilities. In a baseline management regime, forest regeneration was performed by planting the same tree species that was dominant before the final cut. In other management regimes, either Scots pine, Norway spruce or silver birch was planted on medium-fertility sites. Other management actions were performed as for a baseline management. The calculated amount of wind damage was greatest in southern and central Finland under CNRM-CM5 RCP8.5, and the smallest under HadGEM2-ES RCP8.5. The most severe climate projections (HadGEM2-ES RCP8.5 and GFDL-CM3 RCP8.5) affected the wind damage risk even more than did the tree species preferences in forest regeneration. The situation was the opposite for the less severe climate projections (e.g., MPI-ESM-MR RCP4.5 and MPI-ESM-MR RCP8.5). The calculated amount of wind damage was clearly greater in the south than in the north, due to differences in forest structure. The volume of growing stock is much higher in the south for the more vulnerable Norway spruce (and birch) than in the north, which is opposite for the less vulnerable Scots pine. The increasing risk of wind damage should be taken into account in forest management because it could amplify, or even cancel out, any expected increases in forest productivity due to climate change.

Carbon–nitrogen interactions in European forests and semi-natural vegetation – Part 1: Fluxes and budgets of carbon, nitrogen and greenhouse gases from ecosystem monitoring and modelling

Abstract. The impact of atmospheric reactive nitrogen (Nr) deposition on carbon (C) sequestration in soils and biomass of unfertilized, natural, semi-natural and forest ecosystems has been much debated. Many previous results of this dC∕dN response were based on changes in carbon stocks from periodical soil and ecosystem inventories, associated with estimates of Nr deposition obtained from large-scale chemical transport models. This study and a companion paper (Flechard et al., 2020) strive to reduce uncertainties of N effects on C sequestration by linking multi-annual gross and net ecosystem productivity estimates from 40 eddy covariance flux towers across Europe to local measurement-based estimates of dry and wet Nr deposition from a dedicated collocated monitoring network. To identify possible ecological drivers and processes affecting the interplay between C and Nr inputs and losses, these data were also combined with in situ flux measurements of NO, N2O and CH4 fluxes; soil NO3- leaching sampling; and results of soil incubation experiments for N and greenhouse gas (GHG) emissions, as well as surveys of available data from online databases and from the literature, together with forest ecosystem (BASFOR) modelling. Multi-year averages of net ecosystem productivity (NEP) in forests ranged from −70 to 826 g C m−2 yr−1 at total wet + dry inorganic Nr deposition rates (Ndep) of 0.3 to 4.3 g N m−2 yr−1 and from −4 to 361 g C m−2 yr−1 at Ndep rates of 0.1 to 3.1 g N m−2 yr−1 in short semi-natural vegetation (moorlands, wetlands and unfertilized extensively managed grasslands). The GHG budgets of the forests were strongly dominated by CO2 exchange, while CH4 and N2O exchange comprised a larger proportion of the GHG balance in short semi-natural vegetation. Uncertainties in elemental budgets were much larger for nitrogen than carbon, especially at sites with elevated Ndep where Nr leaching losses were also very large, and compounded by the lack of reliable data on organic nitrogen and N2 losses by denitrification. Nitrogen losses in the form of NO, N2O and especially NO3- were on average 27 % (range 6 %–54 %) of Ndep at sites with Ndep < 1 g N m−2 yr−1 versus 65 % (range 35 %–85 %) for Ndep > 3 g N m−2 yr−1. Such large levels of Nr loss likely indicate that different stages of N saturation occurred at a number of sites. The joint analysis of the C and N budgets provided further hints that N saturation could be detected in altered patterns of forest growth. Net ecosystem productivity increased with Nr deposition up to 2–2.5 g N m−2 yr−1, with large scatter associated with a wide range in carbon sequestration efficiency (CSE, defined as the NEP ∕ GPP ratio). At elevated Ndep levels (> 2.5 g N m−2 yr−1), where inorganic Nr losses were also increasingly large, NEP levelled off and then decreased. The apparent increase in NEP at low to intermediate Ndep levels was partly the result of geographical cross-correlations between Ndep and climate, indicating that the actual mean dC∕dN response at individual sites was significantly lower than would be suggested by a simple, straightforward regression of NEP vs. Ndep.

ASYMPTOTIC BEHAVIOR OF SOLUTIONS FOR FOREST KINEMATIC MODEL UNDER DIRICHLET CONDITIONS

We continue a study of the forest ecosystem model due to Kuzunetsov et al. (4) in which the Dirichlet conditions are imposed. In this paper, we introduce three kinds of ω-limit sets, namely, ω(U0) ⊂ L 2 -ω(U0) ⊂ w ∗ -ω(U0), for each point U0 of the dynamical system which has been constructed in our preceding paper (7). Using a Lyapunov function, we will then investigate basic properties of the these ω-limit sets. Especially, it shall be shown that L 2 -ω(U0) consists of equilibria alone. These results are then a modification of those obtained in (2) from the Neumann condition case to the Dirichlet condition case. 1 Introduction We continue the study for a forest kinematic model ⎧ ⎪ ⎪ ⎪ u(x, 0) = u0(x) ,v (x, 0) = v0(x) ,w (x, 0) = w0(x )i n Ω

Assessing the response of forest productivity to climate extremes in Switzerland using model-data fusion.

The response of forest productivity to climate extremes strongly depends on ambient environmental and site conditions. To better understand these relationships at a regional scale, we used nearly 800 observation years from 271 permanent long‐term forest monitoring plots across Switzerland, obtained between 1980 and 2017. We assimilated these data into the 3‐PG forest ecosystem model using Bayesian inference, reducing the bias of model predictions from 14% to 5% for forest stem carbon stocks and from 45% to 9% for stem carbon stock changes. We then estimated the productivity of forests dominated by Picea abies and Fagus sylvatica for the period of 1960–2018, and tested for productivity shifts in response to climate along elevational gradient and in extreme years. Simulated net primary productivity (NPP) decreased with elevation (2.86 ± 0.006 Mg C ha−1 year−1 km−1 for P. abies and 0.93 ± 0.010 Mg C ha−1 year−1 km−1 for F. sylvatica). During warm–dry extremes, simulated NPP for both species increased at higher and decreased at lower elevations, with reductions in NPP of more than 25% for up to 21% of the potential species distribution range in Switzerland. Reduced plant water availability had a stronger effect on NPP than temperature during warm‐dry extremes. Importantly, cold–dry extremes had negative impacts on regional forest NPP comparable to warm–dry extremes. Overall, our calibrated model suggests that the response of forest productivity to climate extremes is more complex than simple shift toward higher elevation. Such robust estimates of NPP are key for increasing our understanding of forests ecosystems carbon dynamics under climate extremes.

Improving the modelling and understanding of carbon-nitrogen-water interactions in a semiarid Mediterranean oak forest

Mediterranean drylands are often nutrient poor, but parameter requirements of forest ecosystem models are usually high. Therefore, there is a need for developing parsimonious nutrients models. In that sense, this study aims to contribute to a better understanding and modelling of the hydrological and biogeochemical (carbon and nitrogen) cycles and their interactions in semiarid conditions and to test the capability of a new parsimonious model to satisfactorily reproduce them. The proposed model (TETIS-CN) and two additional widely used models were implemented in a Quercus ilex forest, and no noteworthy differences were found. Results suggest that: (1) it is important to include carbon observations in the calibration process and to consider all the existing vegetation species in the simulation; (2) a fixed daily potential uptake may not be appropriate to reproduce plant nitrogen uptake; and (3) TETIS-CN, with a lower number of parameters, proved an acceptable tool.

Divergent Growth Responses to Warming between Stand-Grown and Open-Grown Trees in a Dryland Montane Forest in Northwestern China

Dryland montane forests conserve water for people living in the fluvial plains. The fate of these forests under climate warming is strongly affected by local environmental factors. The question remains of how internal factors contribute to climate change impacts on forest growth in these regions. Here, we investigated tree ring records for similar-aged stand-grown trees and their neighboring open-grown trees at elevation in a dryland montane forest (Picea crassifolia Kom.) in northwestern China. The growth rate of open-grown trees is much higher than their neighboring stand-grown trees across the entire elevation gradient, and the lower the altitude, the greater the difference. Open-grown trees at different elevations showed similar growth patterns, as tree growth at all sites was accelerated over time. In contrast, growth patterns of stand-grown trees were divergent at different altitudes, as growth at high elevations (3100–3300 m a.s.l.) was accelerated, whereas growth at low elevations (2700–2900 m a.s.l.) became stable after the year 1990. Analysis of growth–climate relationships indicated that warming promoted open-grown tree growth across the entire altitude gradient, and also stand-grown tree growth at high elevations, but negatively affected the growth of stand-grown trees at low elevations. Water scarcity can be exacerbated by competition within forests, inhibiting the warming-induced benefits on tree growth. Moving window correlation analysis suggested the negative effect of warming on tree growth at low elevations was diminished after the late 1990s, as the drought stress was alleviated. Our research shows the divergent growth responses to warming of stand-grown and open-grown trees along elevation. It reveals effects of internal factors in determining tree growth response to warming and holds the potential to aid forest management and ecosystem models in responding to climate change.

Evaluating k-Nearest Neighbor (kNN) Imputation Models for Species-Level Aboveground Forest Biomass Mapping in Northeast China

Quantifying spatially explicit or pixel-level aboveground forest biomass (AFB) across large regions is critical for measuring forest carbon sequestration capacity, assessing forest carbon balance, and revealing changes in the structure and function of forest ecosystems. When AFB is measured at the species level using widely available remote sensing data, regional changes in forest composition can readily be monitored. In this study, wall-to-wall maps of species-level AFB were generated for forests in Northeast China by integrating forest inventory data with Moderate Resolution Imaging Spectroradiometer (MODIS) images and environmental variables through applying the optimal k-nearest neighbor (kNN) imputation model. By comparing the prediction accuracy of 630 kNN models, we found that the models with random forest (RF) as the distance metric showed the highest accuracy. Compared to the use of single-month MODIS data for September, there was no appreciable improvement for the estimation accuracy of species-level AFB by using multi-month MODIS data. When k > 7, the accuracy improvement of the RF-based kNN models using the single MODIS predictors for September was essentially negligible. Therefore, the kNN model using the RF distance metric, single-month (September) MODIS predictors and k = 7 was the optimal model to impute the species-level AFB for entire Northeast China. Our imputation results showed that average AFB of all species over Northeast China was 101.98 Mg/ha around 2000. Among 17 widespread species, larch was most dominant, with the largest AFB (20.88 Mg/ha), followed by white birch (13.84 Mg/ha). Amur corktree and willow had low AFB (0.91 and 0.96 Mg/ha, respectively). Environmental variables (e.g., climate and topography) had strong relationships with species-level AFB. By integrating forest inventory data and remote sensing data with complete spatial coverage using the optimal kNN model, we successfully mapped the AFB distribution of the 17 tree species over Northeast China. We also evaluated the accuracy of AFB at different spatial scales. The AFB estimation accuracy significantly improved from stand level up to the ecotype level, indicating that the AFB maps generated from this study are more suitable to apply to forest ecosystem models (e.g., LINKAGES) which require species-level attributes at the ecotype scale.

Assimilating spatiotemporal MODIS LAI data with a particle filter algorithm for improving carbon cycle simulations for bamboo forest ecosystems

Bamboo forests are an important part of the forest ecosystem, which has strong carbon sequestration potential and plays an important role in the global carbon cycle. As a key parameter for simulating the carbon cycle using forest ecosystem models, the quality of leaf area index (LAI) data has a direct influence on the accuracy of modelling results. Here, we used the particle filter (PF) algorithm and PROSAIL model to assimilate MODIS LAI products, which were then used to drive a boreal ecosystem productivity simulator model to simulate the bamboo forest carbon cycle. The results showed that the relationship between the assimilated and observed LAI values was very significant, with an R2 of 0.95 and an RMSE of 0.28, greatly improving the precision of MODIS LAI products. The R2 values for the gross primary productivity (GPP), net ecosystem exchange (NEE), and total ecosystem respiration (TER) simulated by the assimilated LAI values and observed carbon fluxes were 0.65, 0.45 and 0.70, respectively, and the RMSE values were 1.10 g C m−2 day−1, 1.00 g C m−2 day−1 and 0.35 g C m−2 day−1, respectively. Compared with the results of the carbon cycle simulated by non-assimilated LAI, the R2 values of the GPP, NEE and TER values that were simulated by assimilated LAI increased by 27.5%, 45.2% and 6.1%, and the RMSE values decreased by 29.9%, 23.7% and 22.2%, respectively. Therefore, coupling the PF and PROSAIL models can greatly improve the simulation precision for the large-scale bamboo forest carbon cycle. This study laid the foundation for simulating the carbon cycle over a large-scale bamboo forest based on low-resolution data in the future.

Asymmetric Effects of Daytime and Nighttime Warming on Boreal Forest Spring Phenology

Vegetation phenology is the most intuitive and sensitive biological indicator of environmental conditions, and the start of the season (SOS) can reflect the rapid response of terrestrial ecosystems to climate change. At present, the model based on mean temperature neglects the role of the daytime maximum temperature (TMAX) and the nighttime minimum temperature (TMIN) in providing temperature accumulation and cold conditions at leaf onset. This study analyzed the spatiotemporal variations of spring phenology for the boreal forest from 2001 to 2017 based on the moderate-resolution imaging spectro-radiometer (MODIS) enhanced vegetation index (EVI) data (MOD13A2) and investigated the asymmetric effects of daytime and nighttime warming on the boreal forest spring phenology during TMAX and TMIN preseason by partial correlation analysis. The results showed that the spring phenology was delayed with increasing latitude of the boreal forest. Approximately 91.37% of the region showed an advancing trend during the study period, with an average advancement rate of 3.38 ± 0.08 days/decade, and the change rates of different land cover types differed, especially in open shrubland. The length of the TMIN preseason was longer than that of the TMAX preseason and diurnal temperatures showed an asymmetrical increase during different preseasons. The daytime and nighttime warming effects on the boreal forest are asymmetrical. The TMAX has a greater impact on the vegetation spring phenology than TMIN as a whole and the effect also has seasonal differences; the TMAX mainly affects the SOS in spring, while TMIN has a greater impact in winter. The asymmetric effects of daytime and nighttime warming on the SOS in the boreal forest were highlighted in this study, and the results suggest that diurnal temperatures should be added to the forest terrestrial ecosystem model.

Effects of even-aged and uneven-aged management on carbon dynamics and timber yield in boreal Norway spruce stands: a forest ecosystem model approach

Abstract We used a gap-type forest ecosystem model to study how even- and uneven-aged management affected the carbon dynamics and timber production in boreal Norway spruce stands. In business-as-usual management, the intensity of thinnings (from below) and single-tree selective cuttings followed those recommended for even-aged (BT) and uneven-aged management (BSC) in practical forestry in Finland. Moreover, higher or lower basal area thresholds, and shorter or longer production cycles, were used in simulations. We found that, the mean annual carbon uptake, volume growth, and carbon stock in trees and harvested timber, were nearly the same under even-aged (BT) and uneven-aged (BSC) management, when assuming full seed crop in latter one. However, the carbon stock in the soil and ecosystem and the mean annual net ecosystem exchange were slightly smaller under BT. The carbon retention time was longer under BSC. The net present value (NPV with interest rate of 3 per cent) of timber production was clearly lower under BT, when the calculation was initiated at planting on clear-cutting area, in opposite to when initiating calculation a few years before the second thinning. Higher basal area thresholds and longer production cycles increased carbon stocks, carbon retention and timber yield, regardless of management system. On the other hand, the results of uneven-aged management (BSC) were very sensitive to the success of natural regeneration and ingrowth of seedlings, as a reduction of the seed crop by 25–75 per cent from the full seed crop decreases the volume growth by 44–74 per cent and timber yield up to 46 per cent.

Effects of intensified silviculture on timber production and its economic profitability in boreal Norway spruce and Scots pine stands under changing climatic conditions

Abstract The aim of this study was to examine how intensified silviculture affects timber production (sawlogs and pulpwood) and its economic profitability (net present value [NPV], with 2 per cent interest rate) based on forest ecosystem model simulations. The study was conducted on Norway spruce and Scots pine stands located on medium-fertile upland forest sites under middle boreal conditions in Finland, under current climate and minor climate change (the RCP2.6 forcing scenario). In intensified silviculture, improved regeneration materials were used, with 10–20 per cent higher growth than the unimproved materials, and/or nitrogen (N) fertilization of 150 kg ha−1, once or twice during a rotation of 50–70 years. Compared to the baseline management regime, the use of improved seedlings, alone or together with N fertilization, increased timber production by up to 26–28 per cent and the NPV by up to 32–60 per cent over rotation lengths of 60–70 years, regardless of tree species (although more in spruce) or climate applied. The use of improved seedlings affected timber yield and NPV more than N fertilization. Minor climate change also increased these outcomes in Scots pine, but not in Norway spruce.

An integration framework for linking avifauna niche and forest landscape models.

Avian cavity nesters (ACN) are viable indicators of forest structure, composition, and diversity. Utilizing these species responses in multi-disciplinary climate-avian-forest modeling can improve climate adaptive management. We propose a framework for integrating and evaluating climate-avian-forest models by linking two ACN niche models with a forest landscape model (FLM), LANDIS-II. The framework facilitates the selection of available ACN models for integration, evaluation of model transferability, and evaluation of successful integration of ACN models with a FLM. We found selecting a model for integration depended on its transferability to the study area (Northern Rockies Ecoregion of Idaho in the United States), which limited the species and model types available for transfer. However, transfer evaluation of the tested ACN models indicated a good fit for the study area. Several niche model variables (canopy cover, snag density, and forest cover type) were not directly informed by the LANDIS-II model, which required secondary modeling (Random Forest) to derive values from the FLM outputs. In instances where the Random Forest models performed with a moderate classification accuracy, the overall effect on niche predictions was negligible. Predictions based on LANDIS-II simulations performed similarly to predictions based on the niche model’s original training input types. This supported the conclusion that the proposed framework is viable for informing avian niche models with FLM simulations. Even models that poorly approximate habitat suitability, due to the inherent constraints of predicting spatial niche use of irruptive species produced informative results by identifying areas of management focus. This is primarily because LANDIS-II estimates spatially explicit variables that were unavailable over large spatial extents from alternative datasets. Thus, without integration, one of the ACN niche models was not applicable to the study area. The framework will be useful for integrating avifauna niche and forest ecosystem models, which can inform management of contemporary and future landscapes under differing management and climate scenarios.

Assessing the Effects of Climate Change and Air Pollution on Soil Properties and Plant Diversity in Northeastern U.S. Hardwood Forests: Model Setup and Evaluation

The integrated forest ecosystem model ForSAFE-Veg was used to simulate soil processes and understory vegetation composition at three—sugar maple, beech, yellow birch—hardwood forest sites in the Northeastern United States (one at Hubbard Brook, NH, and two at Bear Brook, ME). Input data were pooled from a variety of sources and proved coherent and consistent. While the biogeochemical component ForSAFE was used with limited calibration, the ground vegetation composition module Veg was calibrated to field relevés. Evaluating different simulated ecosystem indicators (soil solution chemistry, tree biomass, ground vegetation composition) showed that the model performed comparably well regardless of the site’s soil condition, climate, and amounts of nitrogen (N) and sulfur (S) deposition, with the exception of failing to capture tree biomass decline at Hubbard Brook. The model performed better when compared with annual observation than monthly data. The results support the assumption that the biogeochemical model ForSAFE can be used with limited calibration and provide reasonable confidence, while the vegetation community composition module Veg requires calibration if the individual plant species are of interest. The study welcomes recent advances in empirically explaining the responses of hardwood forests to nutrient imbalances and points to the need for more research.

Mapping Canopy Heights of Poplar Plantations in Plain Areas Using ZY3-02 Stereo and Multispectral Data

Forest canopy height plays an important role in forest management and ecosystem modeling. There are a variety of techniques employed to map forest height using remote sensing data but it is still necessary to explore the use of new data and methods. In this study, we demonstrate an approach for mapping canopy heights of poplar plantations in plain areas through a combination of stereo and multispectral data from China’s latest civilian stereo mapping satellite ZY3-02. First, a digital surface model (DSM) was extracted using photogrammetry methods. Then, canopy samples and ground samples were selected through manual interpretation. Canopy height samples were obtained by calculating the DSM elevation differences between the canopy samples and ground samples. A regression model was used to correlate the reflectance of a ZY3-02 multispectral image with the canopy height samples, in which the red band and green band reflectance were selected as predictors. Finally, the model was extrapolated to the entire study area and a wall-to-wall forest canopy height map was obtained. The validation of the predicted canopy height map reported a coefficient of determination (R2) of 0.72 and a root mean square error (RMSE) of 1.58 m. This study demonstrates the capacity of ZY3-02 data for mapping the canopy height of pure plantations in plain areas.

Parameterization of Productivity Model for the Most Common Trees Species in European Part of Russia for Simulation of Forest Ecosystem Dynamics

The proposed model is the version of well-known biomass production model 3-PG (Physiological Principles Predicting Growth), which allows for calculation of biomass production in dependence of consumed soil nitrogen and available solar radiation. The model utilizes the concept of modifiers, i.e. functions describing the effect of tree age and environmental factors (air temperature and humidity, soil moisture, carbon dioxide concentration) on productivity. To make the model applicable to mixed forests of European Russia, the substantial modifications were implemented. In particular, more detailed response functions to air temperature, soil moisture and absorbed nitrogen were introduced. We also implemented new procedure of calculation of light use efficiency taking into account the difference between shade-tolerant and shade-intolerant tree species. The rank distribution equation was used for the description of an increment allocation to different tree biomass compartments. Model parameters were estimated for the 12 most common tree species of European Russia. The model was implemented as sub-routine for calculation of biomass production in forest ecosystem model EFIMOD 2. The model performance was tested against the wide range of environmental conditions.

Climate change, woodpeckers, and forests: Current trends and future modeling needs.

The structure and composition of forest ecosystems are expected to shift with climate‐induced changes in precipitation, temperature, fire, carbon mitigation strategies, and biological disturbance. These factors are likely to have biodiversity implications. However, climate‐driven forest ecosystem models used to predict changes to forest structure and composition are not coupled to models used to predict changes to biodiversity. We proposed integrating woodpecker response (biodiversity indicator) with forest ecosystem models. Woodpeckers are a good indicator species of forest ecosystem dynamics, because they are ecologically constrained by landscape‐scale forest components, such as composition, structure, disturbance regimes, and management activities. In addition, they are correlated with forest avifauna community diversity. In this study, we explore integrating woodpecker and forest ecosystem climate models. We review climate–woodpecker models and compare the predicted responses to observed climate‐induced changes. We identify inconsistencies between observed and predicted responses, explore the modeling causes, and identify the models pertinent to integration that address the inconsistencies. We found that predictions in the short term are not in agreement with observed trends for 7 of 15 evaluated species. Because niche constraints associated with woodpeckers are a result of complex interactions between climate, vegetation, and disturbance, we hypothesize that the lack of adequate representation of these processes in the current broad‐scale climate–woodpecker models results in model–data mismatch. As a first step toward improvement, we suggest a conceptual model of climate–woodpecker–forest modeling for integration. The integration model provides climate‐driven forest ecosystem modeling with a measure of biodiversity while retaining the feedback between climate and vegetation in woodpecker climate change modeling.

Water limitation can negate the effect of higher temperatures on forest carbon sequestration

Climate change will bring about a consistent increase in temperatures. Annual precipitation rates are also expected to increase in boreal countries, but the seasonal distribution will be uneven, and several areas in the boreal zone will experience wetter winters and drier summers. This study uses the dynamic forest ecosystem model ForSAFE to estimate the combined effect of changes in temperature and precipitation on forest carbon stocks in Sweden. The model is used to simulate carbon stock changes in 544 productive forest sites from the Swedish National Forest Inventory. Forest carbon stocks under two alternative climate scenarios are compared to stocks under a hypothetical scenario of no climate change (baseline). Results show that lower water availability in the future can cause a significant reduction in tree carbon compared to a baseline scenario, particularly expressed in the southern and eastern parts of Sweden. In contrast, the north-western parts will experience an increase in tree carbon stocks. Results show also that summer precipitation is a better predictor of tree carbon reduction than annual precipitation. Finally, the change in soil carbon stock is less conspicuous than in tree carbon stock, showing no significant change in the north and a relatively small but consistent decline in the south. The study indicates that the prospect of higher water deficit caused by climate change cannot be ignored in future forest management planning.