Model Of Forest Dynamics Research Articles

Quantifying resilience of multiple ecosystem services and biodiversity in a temperate forest landscape.

Resilience is increasingly being considered as a new paradigm of forest management among scientists, practitioners, and policymakers. However, metrics of resilience to environmental change are lacking. Faced with novel disturbances, forests may be able to sustain existing ecosystem services and biodiversity by exhibiting resilience, or alternatively these attributes may undergo either a linear or nonlinear decline. Here we provide a novel quantitative approach for assessing forest resilience that focuses on three components of resilience, namely resistance, recovery, and net change, using a spatially explicit model of forest dynamics. Under the pulse set scenarios, we explored the resilience of nine ecosystem services and four biodiversity measures following a one‐off disturbance applied to an increasing percentage of forest area. Under the pulse + press set scenarios, the six disturbance intensities explored during the pulse set were followed by a continuous disturbance. We detected thresholds in net change under pulse + press scenarios for the majority of the ecosystem services and biodiversity measures, which started to decline sharply when disturbance affected >40% of the landscape. Thresholds in net change were not observed under the pulse scenarios, with the exception of timber volume and ground flora species richness. Thresholds were most pronounced for aboveground biomass, timber volume with respect to the ecosystem services, and ectomycorrhizal fungi and ground flora species richness with respect to the biodiversity measures. Synthesis and applications. The approach presented here illustrates how the multidimensionality of stability research in ecology can be addressed and how forest resilience can be estimated in practice. Managers should adopt specific management actions to support each of the three components of resilience separately, as these may respond differently to disturbance. In addition, management interventions aiming to deliver resilience should incorporate an assessment of both pulse and press disturbances to ensure detection of threshold responses to disturbance, so that appropriate management interventions can be identified.

Overstorey–Understorey Interactions Intensify After Drought-Induced Forest Die-Off: Long-Term Effects for Forest Structure and Composition

Severe drought events increasingly affect forests worldwide, but little is known about their long-term effects at the ecosystem level. Competition between trees and herbs (‘overstorey–understorey competition’) for soil water can reduce tree growth and regeneration success and may thereby alter forest structure and composition. However, these effects are typically ignored in modelling studies. To test the long-term impact of water competition by the herbaceous understorey on forest dynamics, we incorporated this process in the dynamic forest landscape model LandClim. Simulations were performed both with and without understorey under current and future climate scenarios (RCP4.5 and RCP8.5) in a drought-prone inner-Alpine valley in Switzerland. Under current climate, herbaceous understorey reduced tree regeneration biomass by up to 51%, particularly in drought-prone landscape positions (i.e., south-facing, low-elevation slopes), where it also caused a shift in forest composition towards drought-tolerant tree species (for example, Quercus pubescens). For adult trees, the understorey had a minor effect on growth. Under future climate change scenarios, increasing drought frequency and intensity resulted in large-scale mortality of canopy trees, which intensified the competitive interaction between the understorey and tree regeneration. At the driest landscape positions, a complete exclusion of tree regeneration and a shift towards an open, savannah-like vegetation occurred. Overall, our results demonstrate that water competition by the herbaceous understorey can cause long-lasting legacy effects on forest structure and composition across drought-prone landscapes, by affecting the vulnerable recruitment phase. Ignoring herbaceous vegetation may thus lead to a strong underestimation of future drought impacts on forests.

Predicting the abundance of forest types across the eastern United States through inverse modelling of tree demography.

Global environmental change is expected to induce widespread changes in the geographic distribution and biomass of forest communities. Impacts have been projected from both empirical (statistical) and mechanistic (physiology-based) modelling approaches, but there remains an important gap in accurately predicting abundance across species' ranges from spatial variation in individual-level demographic processes. We address this issue by using a cohort-based forest dynamics model (CAIN) to predict spatial variation in the abundance of six plant functional types (PFTs) across the eastern United States. The model simulates tree-level growth, mortality, and recruitment, which we parameterized from data on both individual-level demographic rates and population-level abundance using Bayesian inverse modelling. Across a set of 1° grid cells, we calibrated local growth, mortality, and recruitment rates for each PFT to obtain a close match between predicted age-specific PFT basal area in forest stands and that observed in 46,603 Forest Inventory and Analysis plots. The resulting models produced a strong fit to PFT basal area across the region (R2 =0.66-0.87), captured successional changes in PFT composition with stand age, and predicted the overall stem diameter distribution well. The mortality rates needed to accurately predict basal area were consistently higher than observed mortality, possibly because sampling effects led to biased individual-level mortality estimates across spatially heterogeneous plots. Growth and recruitment rates did not show consistent directional changes from observed values. Relative basal area was most strongly influenced by recruitment processes, but the effects of growth and mortality tended to increase as stands matured. Our study illustrates how both top-down (population-level) and bottom-up (individual-level) data can be combined to predict variation in abundance from size, environmental, and competitive effects on tree demography. Evidence for how demographic processes influence variation in abundance, as provided by our model, can help in understanding how these forests may respond to future environmental change.

Effects of nitrogen deposition on nitrate leaching from forests of the northeastern United States will change with tree species composition

As tree species composition in forests of the northeastern United States changes due to invasive forest pests, climate change, or other stressors, the extent to which forests will retain or release N from atmospheric deposition remains uncertain. We used a species-specific, dynamic forest ecosystem model (Spe-CN) to investigate how nitrate (NO3–) leaching may vary among stands dominated by different species, receiving varied atmospheric N inputs, or undergoing species change due to an invasive forest pest (emerald ash borer; EAB). In model simulations, NO3– leaching varied widely among stands dominated by 12 northeastern North American tree species. Nitrate leaching increased with N deposition or forest age, generally with greater magnitude for deciduous (except red oak) than coniferous species. Species with lowest baseline leaching rates (e.g., red spruce, eastern hemlock, red oak) showed threshold responses to N deposition. EAB effects on leaching depended on the species replacing white ash: after 100 years, predicted leaching increased 73% if sugar maple replaced ash but decreased 55% if red oak replaced ash. This analysis suggests that the effects of tree species change on NO3– leaching over time may be large and variable and should be incorporated into predictions of effects of N deposition on leaching from forested landscapes.

Competition between injunctive social norms and conservation priorities gives rise to complex dynamics in a model of forest growth and opinion dynamics

Human and environmental systems are often treated as existing in isolation from one another, whereas in fact they are often two parts of a single, coupled human-environment system. Developing theoretical models of coupled human-environment systems is a continuing area of research, although relatively few of these models are based on differential equations. Here we develop a simple differential equation coupled human-environment system model of forest growth dynamics and conservationist opinion dynamics in a human population. The model assumes logistic growth and harvesting in the forest. Opinion spread in the human population is based on the interplay between conservation values stimulated by forest rarity, and injunctive social norms that tend to support population conformity. We find that injunctive social norms drive the system to the boundaries of phase space, whereas rarity-based conservation priorities drive the system to the interior. The result is complex dynamics including limit cycles and alternative stable states that do not occur if injunctive social norms are absent. We found that the model with injunctive social norms had five possible observable outcomes, whereas the model without social norms had only two stable states. Thus social norms and have dramatic influence in conservation dynamics. We also find that increasing the conservation value of forests is the best way to boost and stabilize forest cover while also boosting conservationist opinion in the population, although for some parameter regimes it can also give rise to long-term oscillations in opinions and forest cover. We conclude that simple models can provide insights and reveal patterns that might be difficult to see with high-dimensional computational models, and therefore should be used more often in research on coupled human-environment systems.

Predicted long-term effects of group selection on species composition and stand structure in northern hardwood forests

The group selection method can potentially increase the proportion of shade-intolerant and midtolerant tree species in forests dominated by shade-tolerant species, but previous results have been variable, and concerns have been raised about possible effects on forest fragmentation and forest structure. Limited evidence is available on these issues for forests managed beyond the first cutting cycle. We used CANOPY, an individual-tree forest dynamics model, to assess long-term effects of group selection methods on tree species composition, fragmentation of the mature forest matrix, and sustainability of size distributions in northern hardwoods. Results were also compared to reference treatments that included a no-cut control, single-tree selection, and clearcutting. Model simulations predicted that group selection would increase midtolerant tree abundance compared to single-tree selection and controls, but magnitude of response was highly variable depending on habitat type and harvest design. All conventional single-tree and group selection designs greatly increased small-scale fragmentation of the mature forest matrix. Group or small patch cutting with area control (constant percent of stand area cut in openings in each cutting cycle with no cutting between groups) produced residual stands with ‘rings’ of mature and large tree crowns in a ‘chain-link fence’ pattern. All treatments, however, resulted in sustainable populations; size distributions did not deviate substantially from a descending monotonic distribution over the 300-yr period. Results suggest possible tradeoffs between maximizing midtolerant species composition and minimizing fragmentation of the mature forest matrix, and that the potential for increasing the abundance of midtolerant species can be strongly constrained by habitat type.

Fusing tree‐ring and forest inventory data to infer influences on tree growth

AbstractBetter understanding and prediction of tree growth is important because of the many ecosystem services provided by forests and the uncertainty surrounding how forests will respond to anthropogenic climate change. With the ultimate goal of improving models of forest dynamics, here we construct a statistical model that combines complementary data sources, tree‐ring and forest inventory data. A Bayesian hierarchical model was used to gain inference on the effects of many factors on tree growth—individual tree size, climate, biophysical conditions, stand‐level competitive environment, tree‐level canopy status, and forest management treatments—using both diameter at breast height (dbh) and tree‐ring data. The model consists of two multiple regression models, one each for the two data sources, linked via a constant of proportionality between coefficients that are found in parallel in the two regressions. This model was applied to a data set of ~130 increment cores and ~500 repeat measurements of dbh at a single site in the Jemez Mountains of north‐central New Mexico,USA. The tree‐ring data serve as the only source of information on how annual growth responds to climate variation, whereas both data types inform non‐climatic effects on growth. Inferences from the model included positive effects on growth of seasonal precipitation, wetness index, and height ratio, and negative effects of dbh, seasonal temperature, southerly aspect and radiation, and plot basal area. Climatic effects inferred by the model were confirmed by a dendroclimatic analysis. Combining the two data sources substantially reduced uncertainty about non‐climate fixed effects on radial increments. This demonstrates that forest inventory data measured on many trees, combined with tree‐ring data developed for a small number of trees, can be used to quantify and parse multiple influences on absolute tree growth. We highlight the kinds of research questions that can be addressed by combining the high‐resolution information on climate effects contained in tree rings with the rich tree‐ and stand‐level information found in forest inventories, including projection of tree growth under future climate scenarios, carbon accounting, and investigation of management actions aimed at increasing forest resilience.

Multispecies Coexistence without Diffuse Competition; or, Why Phylogenetic Signal and Trait Clustering Weaken Coexistence.

Related and phenotypically similar species often compete more strongly than unrelated and dissimilar species. Much is unknown about the community-level implications of such complex interactions. Here, we study how they affect community dynamics differently from diffuse interactions (competing equally with all heterospecifics). We derive results for a model that applies to many forms of density dependence and also examine specific cases using a site-occupancy model of forest dynamics. The results indicate that nondiffuse competition produces three effects that will not occur under diffuse competition: first, the central niche effect-if a species has high niche overlap with several competitors, then its average fitness is reduced; second, the common competitor effect-if a species has high niche overlap with more common species, then its average fitness is reduced (these two effects are usually equalizing, because more favorable niches are likely to contain more species and more abundant species); and, finally, the community redistribution effect-when a species falls to low density, the relative abundance of its competitors will change, altering its ability to recover. The community redistribution effect usually undermines coexistence, because the community will usually become dominated by an invader's closest competitors. This study provides both instructions for measuring these effects in the field and a framework for analyzing how phylogenetic signal, trait-based niche axes, and other forms of nondiffuse competition affect coexistence.

The past and future of modeling forest dynamics: from growth and yield curves to forest landscape models

Quantitative models of forest dynamics have followed a progression toward methods with increased detail, complexity, and spatial extent. We highlight milestones in the development of forest dynamics models and identify future research and application opportunities. We reviewed milestones in the evolution of forest dynamics models from the 1930s to the present with emphasis on forest growth and yield models and forest landscape models We combined past trends with emerging issues to identify future needs. Historically, capacity to model forest dynamics at tree, stand, and landscape scales was constrained by available data for model calibration and validation; computing capacity; model applicability to real-world problems; and ability to integrate biological, social, and economic drivers of change. As computing and data resources improved, a new class of spatially explicit forest landscape models emerged. We are at a point of great opportunity in development and application of forest dynamics models. Past limitations in computing capacity and in data suitable for model calibration or evaluation are becoming less restrictive. Forest landscape models, in particular, are ready to transition to a central role supporting forest management, planning, and policy decisions. Transitioning forest landscape models to a central role in applied decision making will require greater attention to evaluating performance; building application support staffs; expanding the included drivers of change, and incorporating metrics for social and economic inputs and outputs.

Quantification and identification of lightning damage in tropical forests.

Accurate estimates of tree mortality are essential for the development of mechanistic forest dynamics models, and for estimating carbon storage and cycling. However, identifying agents of tree mortality is difficult and imprecise. Although lightning kills thousands of trees each year and is an important agent of mortality in some forests, the frequency and distribution of lightning‐caused tree death remain unknown for most forests. Moreover, because all evidence regarding the effects of lightning on trees is necessarily anecdotal and post hoc, rigorous tests of hypotheses regarding the ecological effects of lightning are impossible. We developed a combined electronic sensor/camera‐based system for the location and characterization of lightning strikes to the forest canopy in near real time and tested the system in the forest of Barro Colorado Island, Panama. Cameras mounted on towers provided continuous video recordings of the forest canopy that were analyzed to determine the locations of lightning strikes. We used a preliminary version of this system to record and locate 18 lightning strikes to the forest over a 3‐year period. Data from field surveys of known lightning strike locations (obtained from the camera system) enabled us to develop a protocol for reliable, ground‐based identification of suspected lightning damage to tropical trees. In all cases, lightning damage was relatively inconspicuous; it would have been overlooked by ground‐based observers having no knowledge of the event. We identified three types of evidence that can be used to consistently identify lightning strike damage in tropical forests: (1) localized and directionally biased branch mortality associated with flashover among tree and sapling crowns, (2) mortality of lianas or saplings near lianas, and (3) scorched or wilting epiphytic and hemiepiphytic plants. The longitudinal trunk scars that are typical of lightning‐damaged temperate trees were never observed in this study. Given the prevalence of communications towers worldwide, the lightning detection system described here could be implemented in diverse forest types. Data from multiple systems would provide an outstanding opportunity for comparative research on the ecological effects of lightning. Such comparative data are increasingly important given expected increases in lightning frequency with climatic change.

Managing stand density to enhance the adaptability of Scots pine stands to climate change: A modelling approach

In the Mediterranean region most climatic forecasts predict longer and more intense drought periods that can affect tree growth and mortality over broad geographic regions. One of the silvicultural treatments that has gained currency to lessen the impacts of climatic change is the reduction of stand density by thinning. However, we lack information on how the response of forest stands to different thinning treatments will be affected by climate change, and on the post-thinning temporal dynamics of water balance, specifically blue and green water. We adopted a modelling approach to explore the long-term effects of different thinning intensities on forest dynamics and water balance under climate change scenarios, coupling an individual-based model of forest dynamics (SORTIE-ND) with a mechanistic model of soil moisture dynamics and plant drought stress. We used as a case study three Scots pine plots across a gradient of climatic conditions, and we assessed the effect of site, three climatic scenarios and eight thinning intensities on tree growth, stand productivity, tree drought stress and blue water. The best thinning intensity in terms of stand productivity was obtained when between 20 and 40% of the basal area was removed, whereas the final stand stock rapidly decreased at higher thinning intensities. Moreover, the decrease in final basal area occurred at lower thinning intensities the drier the site conditions. Moderate and heavy thinnings (>30%) doubled basal area increment (BAI) of the following years in all the plots, although the effect vanished after 30–40 years, independently of the site and climate scenario. As expected, thinning was simulated to have an overall positive effect on the blue water yield and tree water status, which increased and also tended to last longer for higher thinning intensities. However, the magnitude of this effect on tree water status was most dependent on the site and climatic scenario, as drier conditions generally raised stronger and longer lasting reductions in drought stress for a given thinning intensity. Furthermore, our results highlight the existence of a site- and climate-dependent trade-off between the gain in stand productivity and the improvement in tree water status obtained by thinning, particularly for moderate or heavy thinning intensities. Our simulations suggest that thinning is a useful management tool to mitigate climate change but strongly argue against the application of general recipes across sites and appeals for carefully taking into consideration local climatic trajectories for management planning.

Look Down to See What’s Up: A Systematic Overview of Treefall Dynamics in Forests

The study of treefall and its after-effects is a common theme in studies of forest structure and local dynamics, yet its value as descriptor of broader-scale ecological dynamics is rarely explored. Here we synthesize the most highly cited literature on treefalls, from 1985 to 2016 (in three-year blocks), highlighting the importance of the causes, characteristics and consequences of such events. We then ask how this knowledge might contribute to the broader conceptual model of forest dynamics, and develop two conceptual models, which we use to illustrate both the classic and alternative views of how forests ‘work’. Treefalls are one of the few ‘integrating’ attributes of forests, because of their ubiquity and longevity, and therefore can inform a variety of processes (e.g., tree mortality, turnover rates, structural impacts, recruitment, and fire frequency) due to their impacts occurring simultaneously over space (patterns), and time (legacy effects). The substantial knowledge that already exists on localized treefall dynamics should be combined with more integrative approaches to studying forest ecosystems, to investigate landscape-scale patterns of treefall and reconstruct past disturbance events.

Two centuries of masting data for European beech and Norway spruce across the European continent.

Tree masting is one of the most intensively studied ecological processes. It affects nutrient fluxes of trees, regeneration dynamics in forests, animal population densities, and ultimately influences ecosystem services. Despite a large volume of research focused on masting, its evolutionary ecology, spatial and temporal variability, and environmental drivers are still matter of debate. Understanding the proximate and ultimate causes of masting at broad spatial and temporal scales will enable us to predict tree reproductive strategies and their response to changing environment. Here we provide broad spatial (distribution range-wide) and temporal (century) masting data for the two main masting tree species in Europe, European beech (Fagus sylvatica L.) and Norway spruce (Picea abies (L.) H. Karst.). We collected masting data from a total of 359 sources through an extensive literature review and from unpublished surveys. The data set has a total of 1,747 series and 18,348 yearly observations from 28 countries and covering a time span of years 1677-2016 and 1791-2016 for beech and spruce, respectively. For each record, the following information is available: identification code; species; year of observation; proxy of masting (flower, pollen, fruit, seed, dendrochronological reconstructions); statistical data type (ordinal, continuous); data value; unit of measurement (only in case of continuous data); geographical location (country, Nomenclature of Units for Territorial Statistics NUTS-1 level, municipality, coordinates); first and last record year and related length; type of data source (field survey, peer reviewed scientific literature, gray literature, personal observation); source identification code; date when data were added to the database; comments. To provide a ready-to-use masting index we harmonized ordinal data into five classes. Furthermore, we computed an additional field where continuous series with length >4yr where converted into a five classes ordinal index. To our knowledge, this is the most comprehensive published database on species-specific masting behavior. It is useful to study spatial and temporal patterns of masting and its proximate and ultimate causes, to refine studies based on tree-ring chronologies, to understand dynamics of animal species and pests vectored by these animals affecting human health, and it may serve as calibration-validation data for dynamic forest models.

Model-based analyses reveal insular population diversification and cryptic frog species in the Ischnocnema parva complex in the Atlantic forest of Brazil

The Atlantic Forest (AF) of Brazil has long been recognized as a biodiversity conservation hotspot. Despite decades of studies the species inventory of this biome continues to increase with the discovery of cryptic diversity and the description of new species. Different diversification mechanisms have been proposed to explain the diversity in the region, including models of forest dynamics, barriers to gene flow and dispersal. Also, sea level change is thought to have influenced coastal diversification and isolated populations on continental islands. However, the timing and mode of diversification of insular populations in the AF region were rarely investigated. Here, we analyze the phylogeography and species diversity of the small-sized direct-developing frog Ischnocnema parva. These frogs are independent from water bodies but dependent on forest cover and high humidity, and provide good models to understand forest dynamics and insular diversification. Our analysis was based on DNA sequences for one mitochondrial and four nuclear genes of 71 samples from 18 localities including two islands, São Sebastião, municipality of Ilhabela, and Mar Virado, municipality of Ubatuba, both in the state of São Paulo. We use molecular taxonomic methods to show that I. parva is composed of six independently evolving lineages, with the nominal I. parva likely endemic to the type locality. The time-calibrated species tree shows that these lineages have diverged in the Pliocene and Pleistocene, suggesting the persistence of micro-refuges of forest in the AF. For the two insular populations we used approximate Bayesian computation to test different diversification hypotheses. Our findings support isolation with migration for São Sebastião population, with ∼1Mya divergence time, and isolation without migration for Mar Virado population, with ∼13Kya divergence time, suggesting a combination of different processes for diversification on AF islands.

Integrating models across temporal and spatial scales to simulate landscape patterns and dynamics in mountain pasture-woodlands

Pasture-woodlands are semi-natural landscapes that result from the combined influences of climate, management, and intrinsic vegetation dynamics. These landscapes are sensitive to future changes in land use and climate, but our ability to predict the impact on ecosystem service provisioning is limited due to the disparate scales in time and space that govern their dynamics. To develop a process-based model to simulate pasture-woodland landscapes and the provisioning of ecosystem services (i.e., livestock forage, woody biomass and landscape heterogeneity). We modified a dynamic forest landscape model to simulate pasture-woodland landscapes in Switzerland. This involved including an annual herbaceous layer, selective grazing from cattle, and interactions between grazing and tree recruitment. Results were evaluated within a particular pasture, and then the model was used to simulate regional vegetation patterns and livestock suitability for a ~198,000 ha landscape in the Jura Vaudois region. The proportion of vegetation cover types at the pasture level (i.e., open, semi-open and closed forests) was well represented, but the spatial distribution of trees was only broadly similar. The entire Jura Vaudois region was simulated to be highly suitable for livestock, with only a small proportion being unsuitable due to steep slopes and high tree cover. High and low elevation pastures were equally suitable for livestock, as lower forage production at higher elevations was compensated by reduced tree cover. The modified model is valuable for assessing landscape to regional patterns in vegetation and livestock, and offers a platform to evaluate how climate and management impact ecosystem services.

Trade-offs and synergies between ecosystem services in uneven-aged mountain forests: evidences using Pareto fronts

Uneven-aged mountain forests are considered favourable for the continuous provisioning of multiple ecosystem services (ES). These ES may however exhibit trade-offs or synergies that can be modulated by forest management. Yet, our knowledge remains poor on both the relationships between ES and the way management practices can optimise and reconcile them. In this study, we aimed at (1) characterising trade-offs and synergies between timber production, biodiversity conservation and protection against natural hazards; (2) identifying efficient (i.e. Pareto-optimal) management scenarios for the joint provisioning of these ES; and (3) comparing them to “reference” management scenarios. Using a simulation framework that couples a forest dynamics model, a silviculture algorithm and linker functions relating ES indicators to stand structure, we predicted the response of different ES indicators to various uneven-aged management practices in the Western Alps. With a metamodeling approach and Pareto front techniques, we intensively explored and analysed relationships between ES indicators and found trade-offs between timber production and other ES, but synergies between protection and biodiversity. “Pareto-optimal” management scenarios were characterised by low thinning and harvesting intensities but exhibited gradients of total removals and deadwood and large tree retention along the Pareto front. They greatly differed from our set of production and biodiversity oriented reference scenarios, thus emphasising the strong impact of considering additional ES in scenario optimisation processes. This study highlighted the strengths and weaknesses of Pareto front techniques for both the analysis of trade-offs and synergies between ES and the identification of efficient management practices.

Modelling the integrated effects of land use and climate change scenarios on forest ecosystem aboveground biomass, a case study in Taihe County of China

Global and regional environmental changes such as land use and climate change have significantly integrated and interactive effects on forest. These integrated effects will undoubtedly alter the distribution, function and succession processes of forest ecosystems. In order to adapt to these changes, it is necessary to understand their individual and integrated effects. In this study, we proposed a framework by using coupling models to gain a better understanding of the complex ecological processes. We combined an agent-based model for land use and land cover change (ABM/LUCC), an ecosystem process model (PnET-II), and a forest dynamic landscape model (LANDIS-II) to simulate the change of forest aboveground biomass (AGB) which was driven by land use and climate change factors for the period of 2010–2050 in Taihe County of southern China, where subtropical coniferous plantations dominate. We conducted a series of land use and climate change scenarios to compare the differences in forest AGB. The results show that: (1) land use, including town expansion, deforestation and forest conversion and climate change are likely to influence forest AGB in the near future in Taihe County. (2) Though climate change will make a good contribution to an increase in forest AGB, land use change can result in a rapid decrease in the forest AGB and play a vital role in the integrated simulation. The forest AGB under the integrated scenario decreased by 53.7% (RCP2.6 + land use), 57.2% (RCP4.5 + land use), and 56.9% (RCP8.5 + land use) by 2050, which is in comparison to the results under separate RCPs without land use disturbance. (3) The framework can offer a coupled method to better understand the complex and interactive ecological processes, which may provide some supports for adapting to land use and climate change, improving and optimizing plantation structure and function, and developing measures for sustainable forest management.

Forest cover classification and geoinformation modeling of forest regeneration dynamics (Based on the example of the southern part of near-Yenisei Siberia)

An automated conjugate classification of forest growing conditions and forest vegetation has been developed based on the example of the southern part of Yenisei Siberia; maps of potential forest growing conditions and forest-cover regeneration dynamics have been constructed on the basis of the automated recognition of remote sensing data and a system of conjugate analysis of dissimilar data in GIS. The proposed approach makes it possible to promptly create and update forest cover maps, which is particularly important for the vast taiga regions of Siberia.

Simulation study on the effects of climate change on aboveground biomass of plantation in southern China: Taking Moshao forest farm in Huitong Ecological Station as an example

Global climate warming has significant effect on territorial ecosystem, especially on forest ecosystem. The increase in temperature and radiative forcing will significantly alter the structure and function of forest ecosystem. The southern plantation is an important part of forests in China, its response to climate change is getting more and more intense. In order to explore the responses of southern plantation to climate change under future climate scenarios and to reduce the losses that might be caused by climate change, we used climatic estimated data under three new emission scenarios, representative concentration pathways (RCPs) scenarios (RCP2.6 scenario, RCP4.5 scenario, and RCP8.5 scenario). We used the spatially dynamic forest landscape model LANDIS-2, coupled with a forest ecosystem process model PnET-2, to simulate the impact of climate change on aboveground net primary production (ANPP), species' establishment probability (SEP) and aboveground biomass of Moshao forest farm in Huitong Ecological Station, which located in Hunan Province during the period of 2014-2094. The results showed that there were obvious differences in SEP and ANPP among different forest types under changing climate. The degrees of response of SEP to climate change for different forest types were shown as: under RCP2.6 and RCP4.5, artificial coniferous forest>natural broadleaved forest>artificial broadleaved forest. Under RCP8.5, natural broadleaved forest>artificial broadleaved forest>artificial coniferous forest. The degrees of response of ANPP to climate change for different forest types were shown as: under RCP2.6, artificial broadleaved forest> natural broadleaved forest>artificial coniferous forest. Under RCP4.5 and RCP8.5, natural broadleaved forest>artificial broadleaved forest>artificial coniferous forest. The aboveground biomass of the artificial coniferous forest would decline at about 2050, but the natural broadleaved forest and artificial broadleaved forest showed a rising trend in general. During the period of 2014-2094, the total aboveground biomass under RCP2.6, RCP4.5 and RCP8.5 scenarios increased by 68.2%, 79.3% and 72.6%, respectively. The total aboveground biomass under various climatic scenarios sort as: RCP4.5>RCP8.5>RCP2.6. We thought that an appropriate temperature might be beneficial to the biomass accumulation in this study area. However, overextended temperature might hinder the sustainable development of forest production and ecological function.

Future ecosystem services from European mountain forests under climate change

Summary Ecosystem services (ES) from mountain forests are highly relevant for human societies. ES with a direct economic support function (e.g. timber production), regulatory services (e.g. protection from natural hazards) and cultural services (e.g. recreation) are likely to be affected strongly by a rapidly changing climate. To evaluate whether adverse climate change effects on ES can be counteracted by adapting management, dynamic models and indicator‐based assessments are needed. We applied a forest dynamic model in case study areas of four European mountain regions and evaluated the future supply of four ES – timber production, carbon sequestration, biodiversity and protection against natural hazards – using state‐of‐the‐art ES indicators. Forest dynamics were simulated under three management scenarios (no management, business‐as‐usual and alternative management) and five climate change projections for selected representative stand types in each region. We analysed potential trade‐offs and synergies between ES and evaluated future changes among regions, forest stands, climate and management scenarios. Impacts of climate change on the provision of multiple ES were found to be highly heterogeneous and to depend on the region, site and future climate. In the absence of large‐scale natural disturbance (not considered), protection services, carbon stock and deadwood abundance (proxy for biodiversity) benefitted from no management in all regions. Negative impacts of climate change were evident for the provision of multiple ES but limited to the most severe climate scenarios and low‐elevation stands. Synergies and trade‐offs between the majority of ES were found to be sensitive to the choice of management strategy and – in some regions – to climate change. Synthesis and applications. Management regimes in European mountain forests should be regionally adapted to stand and site conditions. Although in some cases alternative management regimes may be more suitable than current management for supporting multiple ecosystem services, adaptation options should be evaluated carefully at the local scale due to the highly different magnitude of the impacts of climate change in different regions and along elevation gradients.