A diameter increment model for Crimean pine (Pinus nigra Arnold) and Calabrian pine (Pinus brutia Ten.) stands in Isparta region, Turkey

The purpose of this research was to test the precision of a diameter increment model for the estimation of future periodic diameter increment. Individual trees of Crimean pine (Pinus nigra Arnold) and Calabrian pine (Pinus brutia Ten.) located in both natural and plantation stands were selected. For that reason, normal closed canopy, pure, even-aged and undisturbed stands were examined. In 2002, plots were sampled in three natural and three plantation stands in Isparta region of Turkey. The number of sampling points in sample plots ranged from 19 to 55. In each sampling point, a subject tree and six competitors were selected. In each sampling point, subject tree and competitor trees were stem mapped (x and y coordinate system), and diameter (dbh), total height, age, and 10-yrs radial increment recorded. The predictors of a distance dependent diameter increment model were chosen that included tree level (diameter (d), competition index (CI), and age (t)) and stand level (basal area (G), and site index (SI)) characteristics as well as their transformations. The best fit index of the regression model was pursued in trials with variable combinations. The models explained 65%, 60%, 68% and 50% of the variation in individual tree diameter increment of Crimean pine and Calabrian pine for both natural and plantations stands, respectively. These models can be estimated diameter increment of individual trees at highly significant level (p<0.001).     

Evaluation of some competition indices for the construction of Lebanon cedar (Cedrus libani A. Rich.) stand models

The purpose of this research is to test the precision of some published competition indices of Lebanon cedar (Cedrus libani A. Rich.) for the estimation of future periodic diameter increment of individual trees. Twenty- nine published competition indices were tested, using fifteen separate sets of data and their pooled values, collected from various stand age and site quality classes Lebanon cedar at Antalya. Temporary sample plots were taken in Elmali-Qamkuyusu (9 sample plots) and Finike-Pinarcik (6 sample plots) in 2001. Every plot was stem mapped (x and y coordinate system), diameter (dbh), total height, crown length, crown diameter and 10-year radial increment were recorded for trees greater than 4 cm in dbh. Then, in order to evaluate these competition indices for the prediction of the periodic diameter increment of the individual trees. Three linear models have been constructed for each competition index. It was found that the competition indices (Daniels et al., 1986; Biging and Dobbertin, 1995; Pukkala and Kolstr?m, 1987; Hegyi, 1974) with larger influence-zone areas produce better results.     

Multi-model analysis of tree competition along environmental gradients in southern New England forests.

Robust predictions of competitive interactions among canopy trees and variation in tree growth along environmental gradients represent key challenges for the management of mixed-species, uneven-aged forests. We analyzed the effects of competition on tree growth along environmental gradients for eight of the most common tree species in southern New England and southeastern New York using forest inventory and analysis (FIA) data, information theoretic decision criteria, and multi-model inference to evaluate models. The suite of models estimated growth of individual trees as a species-specific function of average potential diameter growth, tree diameter at breast height, local environmental conditions, and crowding by neighboring trees. We used ordination based on the relative basal area of species to generate a measure of site conditions in each plot. Two ordination axes were consistent with variation in species abundance along moisture and fertility gradients. Estimated potential growth varied along at least one of these axes for six of the eight species; peak relative abundance of less shade-tolerant species was in all cases displaced away from sites where they showed maximum potential growth. Our crowding functions estimate the strength of competitive effects of neighbors; only one species showed support for the hypothesis that all species of competitors have equivalent effects on growth. The relative weight of evidence (Akaike weights) for the best models varied from a low of 0.207 for Fraxinus americana to 0.747 for Quercus rubra. In such cases, model averaging provides a more robust platform for prediction than that based solely on the best model. We show that predictions based on the selected best models dramatically overestimated differences between species relative to predictions based on the averaged set of models.     

Potential site productivity influences the rate of forest structural development

Development and maintenance of structurally complex forests in landscapes formerly managed for timber production is an increasingly common management objective. It has been postulated that the rate of forest structural development increases with site productivity. We tested this hypothesis for Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) forests using a network of permanent study plots established following complete timber harvest of the original old-growth forests. Forest structural development was assessed by comparing empirical measures of live tree structure to published values for Douglas-fir forests spanning a range of ages and structural conditions. The rate of forest structural development--resilience--exhibited a positive relationship with site index, a measure of potential site productivity. Density of shade-intolerant conifers declined in all study stands from an initial range of 336-4068 trees/ha to a range of 168-642 trees/ha at the most recent measurement. Angiosperm tree species declined from an initial range of 40-371 trees/ha to zero in seven of the nine plots in which they were present. Trends in shade-tolerant tree density were complex: density ranged from 0 to 575 trees/ha at the first measurement and was still highly variable (25-389 trees/ha) at the most recent measurement. Multivariate analysis identified the abundance of hardwood tree species as the strongest compositional trend apparent over the study period. However, structural variables showed a strong positive association with increasing shade-tolerant basal area and little or no association with abundance of hardwood species. Thus, while tree species succession and forest structural development occur contemporaneously, they are not equivalent processes, and their respective rates are not necessarily linearly related. The results of this study support the idea that silvicultural treatments to accelerate forest structural development should be concentrated on lower productivity sites when the management objective is reserve-wide coverage of structurally complex forests. Alternatively, high-productivity sites should be prioritized for restoration treatments when the management objective is to develop structurally complex forests on a portion of the landscape.     

Rain forest fragmentation and the proliferation of successional trees

The effects of habitat fragmentation on diverse tropical tree communities are poorly understood. Over a 20-year period we monitored the density of 52 tree species in nine predominantly successional genera (Annona, Bellucia, Cecropia, Croton, Goupia, Jacaranda, Miconia, Pourouma, Vismia) in fragmented and continuous Amazonian forests. We also evaluated the relative importance of soil, topographic, forest dynamic, and landscape variables in explaining the abundance and species composition of successional trees. Data were collected within 66 permanent 1-ha plots within a large (approximately 1000 km2) experimental landscape, with forest fragments ranging from 1 to 100 ha in area. Prior to forest fragmentation, successional trees were uncommon, typically comprising 2-3% of all trees (> or =10 cm diameter at breast height [1.3 m above the ground surface]) in each plot. Following fragmentation, the density and basal area of successional trees increased rapidly. By 13-17 years after fragmentation, successional trees had tripled in abundance in fragment and edge plots and constituted more than a quarter of all trees in some plots. Fragment age had strong, positive effects on the density and basal area of successional trees, with no indication of a plateau in these variables, suggesting that successional species could become even more abundant in fragments over time. Nonetheless, the 52 species differed greatly in their responses to fragmentation and forest edges. Some disturbance-favoring pioneers (e.g., Cecropia sciadophylla, Vismia guianensis, V. amazonica, V. bemerguii, Miconia cf. crassinervia) increased by >1000% in density on edge plots, whereas over a third (19 of 52) of all species remained constant or declined in numbers. Species responses to fragmentation were effectively predicted by their median growth rate in nearby intact forest, suggesting that faster-growing species have a strong advantage in forest fragments. An ordination analysis revealed three main gradients in successional-species composition across our study area. Species gradients were most strongly influenced by the standlevel rate of tree mortality on each plot and by the number of nearby forest edges. Species-composition also varied significantly among different cattle ranches, which differed in their surrounding matrices and disturbance histories. These same variables were also the best predictors of total successional-tree abundance and species richness. Successional-tree assemblages in fragment interior plots (>150 m from edge), which are subjected to fragment area effects but not edge effects, did not differ significantly from those in intact forest, indicating that area effects per se had little influence on successional trees. Soils and topography also had little discernable effect on these species. Collectively, our results indicate that successional-tree species proliferate rapidly in fragmented Amazonian forests, largely as a result of chronically elevated tree mortality near forest edges and possibly an increased seed rain from successional plants growing in nearby degraded habitats. The proliferation of fast-growing successional trees and correlated decline of old-growth trees will have important effects on species composition, forest dynamics, carbon storage, and nutrient cycling in fragmented forests.     

Characterization of soil erosion and its implication to forest management

Forests have traditionally been managed to maximize timber production or economic profit, completely neglecting other forest values. Nowadays, however, forests are being managed for multiple uses. The basic requirement of multiple use forestry is to identify and quantify forest values and to determine management objectives. The priorities of management objectives, however, must be decided. In this study, a model predicting the soil loss for multi objective forest management was developed. The model was based on data from remeasurement of permanent sample plots. The data were gathered from 132 sample plots. Approximately 80% of the observations were used for model development and 20% for validation. The model was designed for even aged and uneven aged forests, as well as for forests with mixed and pure species composition. The explicatory variables in the model were mean diameter and number of trees. All parameter estimates were found highly significant (p < 0.001) in predicting soil loss. The model fit and validation tests were fairly good. The soil loss model presented in this paper was considered to have an appropriate level of reliability. It can be used in the overall multi-objective forest management planning, but, it should be limited to the conditions for which the data were gathered.     

Pre-growth mortality of Abies cilicica trees and mortality models performance

In this study, we compared tree-growth rates (basal area increment) from recently dead and living Taurus fir (Abies cilicica Carr.) trees in the Kovada lake Forest of Isparta, Turkey. For each dead tree, tree-growth rates were analyzed for the presence of pre-death growth depressions in the study area (number of sample plots = 11) in 2006. However, we compared both the magnitude and rate of growth prior to death to a control (living) group of trees. Basal area increment (BAI) averaged substantially less during the last 10 years before death than for control trees. Trees that died started diverging in growth, on average, 50-60 years before death. About 18% of trees that died had chronically slow growth, 46% had pronounced declines in growth, whereas 36% had good growth up to death. However, tree-ring-based growth patterns of dead and living Taurus fir trees were compared and used 12 mortality models that were derived using logistic regression from growth patterns of tree-ring series as predictor variables. The four models with the highest overall performance correctly classified 43.8-56.3% of all dead trees and 75.0-87.5% of all living trees, and they predicted 25.0-43.8% of all dead trees to die within 0-15 years prior to the actual year of death.     

Growth response of Lebanon cedar (Cedrus libani) plantations to thinning intensity in Western Turkey

This paper presents the growth response of 25 yr old Lebanon cedar (Cedrus libani A. Rich.) plantation to thinnings of different intensities in Isparta in western Turkey. The thinning intensity was measured by using the residual basal area (%) as parameter. In spring of 2005, three treatments were tested; light, moderate and heavy thinning with respectively 10, 25 and 35% of basal area removed. The statistical design of the experiment was a randomized incomplete block with two blocks and three treatments. Variables such as diameter at breast height (diameter) and height were measured. Growth rate ratios of diameter in moderately thinned and heavily thinned stands were 1.02 and 1.03, respectively. Basal area growth rates in moderately thinned and heavily thinned plots were 0.93 and 1.05, respectively. The largest values for the mean tree were observed with the heaviest thinning treatment. Absolute diameter increment was positively correlated with initial diameter in all plots. Relative diameter growth was negatively correlated with initial diameter. Growth rate interpretations were supported by analysis of variance using Duncan's test of range multiple. The results obtained show significant differences between treatments for tree height growth, for the two inventories carried out (2005, 2008). However diameter basal area and volume were no found between treatments for tree.     

A geospatial model of forest dynamics with controlled trend surface

This paper proposes a method of controlled trend surface to simultaneously account for large-scale spatial trends and non-spatial local effects. With this method, a geospatial model of forest dynamics was developed for the Alaska boreal forest from 446 constantly monitored permanent sample plots. The geospatial component of this model represented large-scale spatial trends in recruitment, diameter growth, and mortality. The model was tested on two sets of validation plots which represented temporal and spatial extensions of the current sample coverage. The results suggest that the controlled trend surface model was generally more accurate than both the non-spatial and conventional trend surface models. With this model, we mapped the forest dynamics of the entire Alaska boreal region by aggregating predicted stand states across the region. It was predicted that under current conditions of climate and natural disturbances, most of the Alaska boreal forest region may undergo a major shift from deciduous-dominant to conifer-dominant, with an average increase of 0.33 m² ha year⁻¹ in basal area over the Twenty-First Century.     

Development of the gap model ZELIG-CFS to predict the dynamics of North American mixed forest types with complex structures

When the development of gap models began about three decades ago, they became a new category of forest productivity models. Compared with traditional growth and yield models, which aim at deriving empirical relationships that best fit data, gap models use semi-theoretical relationships to simulate biotic and abiotic processes in forest stands, including the effects of photosynthetic active radiation interception, site fertility, temperature and soil moisture on tree growth and seedling establishment. While growth and yield models are appropriate to predict short-term stemwood production, gap models may be used to predict the natural course of species replacement for several generations. Because of the poor availability of historical data and knowledge on species-specific allometric relationships, species replacement and death rate, it has seldom been possible to develop and evaluate the most representative algorithms to predict growth and mortality with a high degree of accuracy. For this reason, the developers of gap models focused more on developing simulation tools to improve the understanding of forest succession than predicting growth and yield accurately.In a previous study, the predictions of simulations in two southeastern Canadian mixed ecosystem types using the ZELIG gap model were compared with long-term historical data. This exercise highlighted model components that needed modifications to improve the predictive capacity of ZELIG. The updated version of the model, ZELIG-CFS, includes modifications in the modelling of crown interaction effects, survival rate and regeneration. Different algorithms representing crown interactive effects between crowns were evaluated and species-specific model components that compute individual-tree mortality probability rate were derived. The results of the simulations were compared using long-term remeasurement data obtained from sample plots located in La Mauricie National Park of Canada in Quebec. In the present study, three forest types were studied: (1) red spruce-balsam fir-yellow birch, (2) yellow birch-sugar maple-balsam fir, and (3) red spruce-balsam fir-white birch mixed ecosystems. Among the seven algorithms that represented individual crown interactions, two better predicted the changes in basal area and individual-tree growth: (1) the mean available light growing factor (ALGF), which is computed from the proportion of light intercepted at different levels of individual crowns adjusted by the species-specific shade tolerance index, and (2) the ratio of mean ALGF to crown width. The long-term predicted patterns of change in basal area were consistent with the life history of the different species.     

Tree species diversity and its relationship to stand parameters and geomorphology features in the eastern Black Sea region forests of Turkey

We studied the effects of stand parameters (crown closure, basal area, stand volume, age, mean stand diameter number of trees, and heterogeneity index) and geomorphology features (elevation, aspect and slope) on tree species diversity in an example of untreated natural mixed forest stands in the eastern Black Sea region of Turkey. Tree species diversity and basal area heterogeneity in forest ecosystems are quantified using the Shannon-Weaver and Simpson indices. The relationship between tree species diversity basal area heterogeneity stand parameters and geomorphology features are examined using regression analysis. Our work revealed that the relationship between tree species diversity and stand parameters is loose with a correlation coefficient between 0.02 and 0.70. The correlation of basal area heterogeneity with stand parameters fluctuated between 0.004 and 0.77 (R2). According to our results, stands with higher tree species diversity are characterised by higher mean stand diameter number of diameter classes, basal area and lower homogeneity index value. Considering the effect of geomorphology features on tree species or basal area heterogeneity we found that all investigated relationships are loose with R < or = 0.24. A significant correlation was detected only between tree species diversity and aspect. Future work is required to verify the detected trends in behaviour of tree species diversity if it is to estimate from the usual forest stand parameters and topography characteristics.     

Using forest inventory data to assess fisher resting habitat suitability in California.

The fisher (Martes pennanti) is a forest-dwelling carnivore whose current distribution and association with late-seral forest conditions make it vulnerable to stand-altering human activities or natural disturbances. Fishers select a variety of structures for daily resting bouts. These habitat elements, together with foraging and reproductive (denning) habitat, constitute the habitat requirements of fishers. We develop a model capable of predicting the suitability of fisher resting habitat using standard forest vegetation inventory data. The inventory data were derived from Forest Inventory and Analysis (FIA), a nationwide probability-based sample used to estimate forest characteristics. We developed the model by comparing vegetation and topographic data at 75 randomly selected fisher resting structures in the southern Sierra Nevada with 232 forest inventory plots. We collected vegetation data at fisher resting locations using the FIA vegetation sampling protocol and centering the 1-ha FIA plot on the resting structure. To distinguish used and available inventory plots, we used nonparametric logistic regression to evaluate a set of a priori biological models. The top model represented a dominant portion of the Akaike weights (0.87), explained 31.5% of the deviance, and included the following variables: average canopy closure, basal area of trees <51 cm diameter breast height (dbh), average hardwood dbh, maximum tree dbh, percentage slope, and the dbh of the largest conifer snag. Our use of routinely collected forest inventory data allows the assessment and monitoring of change in fisher resting habitat suitability over large regions with no additional sampling effort. Although models were constrained to include only variables available from the list of those measured using the FIA protocol, we did not find this to be a shortcoming. The model makes it possible to compare average resting habitat suitability values before and after forest management treatments, among administrative units, across regions and over time. Considering hundreds of plot estimates as a sample of habitat conditions over large spatial scales can bring a broad perspective, at high resolution, and efficiency to the assessment and monitoring of wildlife habitat.     

Validation of a multispecies forest dynamics model using 50-year growth from Eucalyptus forests in eastern Australia

One of the key problems confronting ecological forecasting is the validation of computer models. Here we report successful validation of a forest dynamics model Ecosystem Dynamics Simulator (EDS), adapted from the JABOWA-II forest succession model. This model and many variants derived from it have successfully simulated growth dynamics of uneven-aged mixed forests under changing environment with a moderate amount of input data. But rarely are adequate time-series data available for quantitative model validation. This study tested the performance of EDS in projecting the tree density, tree diameter at breast height (dbh), tree height, basal area and aboveground biomass of uneven-aged, mixed species sclerophyll forests in St. Mary state forests of eastern Australia. The test data were collected between 1951 and 2005. Every tree was uniquely numbered, tagged and measured in consecutive re-measurements. Projected growth attributes were compared with those observed in an independent validation dataset. The model produced satisfactory projections of tree density (91.7%), dbh (92.3%), total tree height (82.8%), basal area (89.3%) and aboveground biomass (87.6%) compared to the observed attributes. These results suggest that the EDS model can provide reasonable capability in projecting growth dynamics of uneven-aged, mixed species sclerophyll forests.     

Two neighborhood-free plot designs for adaptive sampling of forests

Adaptive cluster sampling (ACS) has the potential of being superior for sampling rare and geographically clustered populations. However, setting up an efficient ACS design is challenging. In this study, two adaptive plot designs are proposed as alternatives: one for fixed-area plot sampling and the other for relascope sampling (also known as variable radius plot sampling). Neither includes a neighborhood search which makes them much easier to execute. They do, however, include a conditional plot expansion: at a sample point where a predefined condition is satisfied, sampling is extended to a predefined larger cluster-plot or a larger relascope plot. Design-unbiased estimators of population total and its variance are derived for each proposed design, and they are applied to ten artificial and one real tree position maps to estimate density (number of trees per ha) and basal area (the cross-sectional area of a tree stem at breast height) per hectare. The performances—in terms of relative standard error (SE%)—of the proposed designs and their non-adaptive alternatives are compared. The adaptive plot designs were superior for the clustered populations in all cases of equal sample sizes and in some cases of equal area of sample plots. However, the improvement depends on: (1) the plot size factor; (2) the critical value (the minimum number of trees triggering an expansion); (3) the subplot distance for the adapted cluster-plots, and (4) the spatial arrangement of the sampled population. For some spatial arrangements, the improvement is relatively small. The adaptive designs may be particularly attractive for sampling in rare and compactly clustered populations with critical value of 1, subplot distance equal to the diameter of initial circular plots, or plot size factor of 2.5 for an initial basal area factor of 2.     

长白山暗针叶林建群种竞争关系的研究

根据野外调查数据,利用Hegyi单木竞争指数模型,定量地研究了长白山暗针叶内主要建群种（以鱼鳞云杉为例）的种内、种间竞争关系,结果表明：暗针叶林中鱼鳞云杉种内竞争强度随着林木径级的增大而迅速减小,也就是说,在暗叶叶林内,鱼鳞云杉种群由于自然调节的作用,随着林木径级的增大,林木因自然稀疏过程导致部分个体死亡,加大了株间距离,因此对光、温、水等生态条件及资源的竞争强度降低,暗针叶林内鱼鳞云杉种内种间竞争强度的顺序为：鱼鳞云杉－鱼鳞云杉＞鱼鳞云杉－臭冷杉＞鱼鳞云杉－红松＞鱼鳞云杉－长白落叶松＞鱼鳞云杉－岳桦＞鱼鳞云杉－杂木,鱼鳞云杉种内种间竞争强度可用幂函数关系CI＝AD－B（其中CI为竞争强度：D为对象木胸径;A、B为参数）表示,并可模拟和预测鱼鳞云杉种内种间竞争强度,从预测结果中发现：当鱼鳞云杉胸径达到35cm后,竞争强度变得小,且变化幅度不大,说明此时该生态系统已基本上达到稳定状态,这可为暗叶林的经营管理提供依据,即在鱼鳞云杉胸径达到35cm之间辅以必要的人工管理措施,以期使得该生态系统尽快达到稳定状态,图2表4参10     

Comparison and ranking of different modelling techniques for prediction of site index in Mediterranean mountain forests

Forestry science has a long tradition of studying the relationship between stand productivity and abiotic and biotic site characteristics, such as climate, topography, soil and vegetation. Many of the early site quality modelling studies related site index to environmental variables using basic statistical methods such as linear regression. Because most ecological variables show a typical non-linear course and a non-constant variance distribution, a large fraction of the variation remained unexplained by these linear models. More recently, the development of more advanced non-parametric and machine learning methods provided opportunities to overcome these limitations. Nevertheless, these methods also have drawbacks. Due to their increasing complexity they are not only more difficult to implement and interpret, but also more vulnerable to overfitting. Especially in a context of regionalisation, this may prove to be problematic. Although many non-parametric and machine learning methods are increasingly used in applications related to forest site quality assessment, their predictive performance has only been assessed for a limited number of methods and ecosystems.In this study, five different modelling techniques are compared and evaluated, i.e. multiple linear regression (MLR), classification and regression trees (CART), boosted regression trees (BRT), generalized additive models (GAM), and artificial neural networks (ANN). Each method is used to model site index of homogeneous stands of three important tree species of the Taurus Mountains (Turkey): Pinus brutia, Pinus nigra and Cedrus libani. Site index is related to soil, vegetation and topographical variables, which are available for 167 sample plots covering all important environmental gradients in the research area. The five techniques are compared in a multi-criteria decision analysis in which different model performance measures, ecological interpretability and user-friendliness are considered as criteria.When combining these criteria, in most cases GAM is found to outperform all other techniques for modelling site index for the three species. BRT is a good alternative in case the ecological interpretability of the technique is of higher importance. When user-friendliness is more important MLR and CART are the preferred alternatives. Despite its good predictive performance, ANN is penalized for its complex, non-transparent models and big training effort.     

Spatial elements of mortality risk in old-growth forests

For many species of long-lived organisms, such as trees, survival appears to be the most critical vital rate affecting population persistence. However, methods commonly used to quantify tree death, such as relating tree mortality risk solely to diameter growth, almost certainly do not account for important spatial processes. Our goal in this study was to detect and, if present, to quantify the relevance of such processes. For this purpose, we examined purely spatial aspects of mortality for four species, Abies concolor, Abies magnifica, Calocedrus decurrens, and Pinus lambertiana, in an old-growth conifer forest in the Sierra Nevada of California, USA. The analysis was performed using data from nine fully mapped long-term monitoring plots. In three cases, the results unequivocally supported the inclusion of spatial information in models used to predict mortality. For Abies concolor, our results suggested that growth rate may not always adequately capture increased mortality risk due to competition. We also found evidence of a facilitative effect for this species, with mortality risk decreasing with proximity to conspecific neighbors. For Pinus lambertiana, mortality risk increased with density of conspecific neighbors, in keeping with a mechanism of increased pathogen or insect pressure (i.e., a Janzen-Connell type effect). Finally, we found that models estimating risk of being crushed were strongly improved by the inclusion of a simple index of spatial proximity. Not only did spatial indices improve models, those improvements were relevant for mortality prediction. For P. lambertiana, spatial factors were important for estimation of mortality risk regardless of growth rate. For A. concolor, although most of the population fell within spatial conditions in which mortality risk was well described by growth, trees that died occurred outside those conditions in a disproportionate fashion. Furthermore, as stands of A. concolor become increasingly dense, such spatial factors are likely to become increasingly important. In general, models that fail to account for spatial pattern are at risk of failure as conditions change.     

A model of surface fire,climate and forest pattern in the Sierra Nevada,California

A spatially explicit forest gap model was developed for the Sierra Nevada, California, and is the first of its kind because it integrates climate, fire and forest pattern. The model simulates a forest stand as a grid of 15×15 m forest plots and simulates the growth of individual trees within each plot. Fuel inputs are generated from each individual tree according to tree size and species. Fuel moisture varies both temporally and spatially with the local site water balance and forest condition, thus linking climate with the fire regime. Fires occur as a function of the simulated fuel loads and fuel moisture, and the burnable area is simulated as a result of the spatially heterogeneous fuel bed conditions. We demonstrate the model’s ability to couple the fire regime to both climate and forest pattern. In addition, we use the model to investigate the importance of climate and forest pattern as controls on the fire regime. Comparison of model results with independent data indicate that the model performs well in several areas. Patterns of fuel accumulation, climatic control of fire frequency and the influence of fuel loads on the spatial extent of fires in the model are particularly well-supported by data. This model can be used to examine the complex interactions among climate, fire and forest pattern across a wide range of environmental conditions and vegetation types. Our results suggest that, in the Sierra Nevada, fuel moisture can exert an important control on fire frequency and this control is especially pronounced at sites where most of the annual precipitation is in the form of snow. Fuel loads, on the other hand, may limit the spatial extent of fire, especially at elevations below 1500 m. Above this elevation, fuel moisture may play an increasingly important role in limiting the area burned.     

Modelling forest management within a global vegetation model—Part 2: Model validation from a tree to a continental scale

The construction of a new forest management module (FMM) within the ORCHIDEE global vegetation model (GVM) allows a realistic simulation of biomass changes during the life cycle of a forest, which makes many biomass datasets suitable as validation data for the coupled ORCHIDEE-FM GVM. This study uses three datasets to validate ORCHIDEE-FM at different temporal and spatial scales: permanent monitoring plots, yield tables, and the French national inventory data. The last dataset has sufficient geospatial coverage to allow a novel type of validation: inventory plots can be used to produce continuous maps that can be compared to continuous simulations for regional trends in standing volumes and volume increments. ORCHIDEE-FM performs better than simple statistical models for stand-level variables, which include tree density, basal area, standing volume, average circumference and height, when management intensity and initial conditions are known: model efficiency is improved by an average of 0.11, and its average bias does not exceed 25%. The performance of the model is less satisfying for tree-level variables, including extreme circumferences, tree circumference distribution and competition indices, or when management and initial conditions are unknown. At the regional level, when climate forcing is accurate for precipitation, ORCHIDEE-FM is able to reproduce most productivity patterns in France, such as the local lows of needleleaves in the Parisian basin and of broadleaves in south-central France. The simulation of water stress effects on biomass in the Mediterranean region, however, remains problematic, as does the simulation of the wood increment for coniferous trees. These pitfalls pertain to the general ORCHIDEE model rather than to the FMM. Overall, with an average bias seldom exceeding 40%, the performance of ORCHIDEE-FM is deemed reliable to use it as a new modelling tool in the study of the effects of interactions between forest management and climate on biomass stocks of forests across a range of scales from plot to country.