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.     

Predicting long-term development of abandoned subalpine conifer forests in the Swiss National Park

In the past 35 years, various kinds of dynamic models have been used to study vegetation development during primary or secondary succession. Typically, one specific model or models with the same conceptual background were employed. It remains largely unknown to what extent such model-based findings, e.g., on the speed of succession, depend on the specific model approach.To address this issue, we estimated the time elapsing during secondary succession in subalpine conifer forests of the Swiss National Park using three models of different conceptual background: (i) a forest gap model, (ii) a Markov chain model, and (iii) a minimum spanning tree model.Starting from a 95- to 125-year-old mountain pine (Pinus montana Miller) forest, all three models predicted a similar successional development. Even though the forest gap model and the Markov chain model are based on totally different approaches and were calibrated using different data sets, they both forecasted that it would take 500–550 years to reach a late-successional forest stage. The minimum spanning tree model, which only reveals a certain number of time steps yielding a minimum time estimate, showed a development of tree density (stems/ha) that was similar to the results of the forest gap model, but a strict quantitative comparison is not feasible.Our study shows that modeling forest development using three different approaches is quite powerful to obtain a robust estimate of the speed of forest succession. In our case, this estimate is higher than what has been suggested in previous studies that investigated secondary forest succession. The use of several approaches allows for a more comprehensive analysis in terms of variables covered (e.g., relative forest cover in the Markov approach vs. stand-scale species composition in the forest gap model). We recommend that in studies focusing on the speed of succession, several models should be employed simultaneously to identify inconsistencies in our knowledge and to increase confidence in the results.     

Accuracy of Short‐Term Demographic Data in Projecting Long‐Term Fate of Populations

Short‐term surveys are useful in conservation of species if they can be used to reliably predict the long‐term fate of populations. However, statistical evaluations of reliability are rare. We studied how well short‐term demographic data (1999–2002) of tartar catchfly (Silene tatarica), a perennial riparian plant, projected the fate and growth of 23 populations of this species up to the year 2010. Surveyed populations occurred along a river with natural flood dynamics and along a regulated river. Riparian plant populations are affected by flooding, which maintains unvegetated shores, while forest succession proceeds in areas with little flooding. Flooding is less severe along the regulated river, and vegetation overgrowth reduces abundance of tartar catchfly on unvegetated shores. We built matrix models to calculate population growth rates and estimated times to population extinction in natural and in regulated rivers, 13 and 10 populations, respectively. Models predicted population survival well (model predictions matched observed survival in 91% of populations) and accurately predicted abundance increases and decreases in 65% of populations. The observed and projected population growth rates differed significantly in all but 3 populations. In most cases, the model overestimated population growth. Model predictions did not improve when data from more years were used (1999–2006). In the regulated river, the poorest model predictions occurred in areas where cover of other plant species changed the fastest. Although vegetation cover increased in most populations, it decreased in 4 populations along the natural river. Our results highlight the need to combine disturbance and succession dynamics in demographic models and the importance of habitat management for species survival along regulated rivers. Precisión de Datos Demográficos de Corto Plazo en la Proyección del Destino de Poblaciones a Largo Plazo     

Forest growth in the light of the thermodynamic theory of ecological systems

The observed growth of a particular forest stand can be described by many models and explained by some of them. The forest growth models are also successfully applied for extrapolating the growth curve. However, the known models of forest growth are not “one-point” models. They are not designed to predict the future growth of a forest stand from its current state: the model parameters either are not directly measurable or cannot be measured with relevant accuracy. This article is an attempt to use Jørgensen–Svirezhev theory as a new clue to the choice of variables that determines forest growth. The postulates of this theory combined with the pipe theory of tree growth lead to conclusion that biomass of a stand should be proportional to the four-fifths power of its age. Empirical validation, however, disclosed that calendar age is rather approximate measure of ecosystem ontogeny. Delayed development or intensive thinning of a forest stand at the early stages leads to rejuvenation bias. Thus derived 4/5-law model approximates well-known Chapman–Richards model in the neighborhood of the inflection point, and is applicable to middle-aged forest stands.     

The impact of fragmentation and density regulation on forest succession in the Atlantic rain forest

The Atlantic Rain Forest, an important biodiversity hot spot, has faced severe habitat loss since the last century which has resulted in a highly fragmented landscape with a large number of small forest patches (<100 ha). For conservation planning it is essential to understand how current and future forest regeneration depends on ecological processes, fragment size and the connection to the regional seed pool. We have investigated the following questions by applying the forest growth simulation model FORMIND to the situation of the Atlantic Forest in the state of São Paulo, SE Brazil: (1) which set of parameters describing the local regeneration and level of density regulation can reproduce the biomass distribution and stem density of an old growth forest in a reserve? (2) Which additional processes apart from those describing the dynamics of an old growth forest, drive forest succession of small isolated fragments? (3) Which role does external seed input play during succession? Therefore, more than 300 tree species have been classified into nine plant functional types (PFTs), which are characterized by maximum potential height and shade tolerance. We differentiate between two seed dispersal modes: (i) local dispersal, i.e. all seedlings originated from fertile trees within the simulated area and (ii) external seed rain. Local seed dispersal has been parameterized following the pattern oriented approach, using biomass estimates of old growth forest. We have found that moderate density regulation is essential to achieve coexistence for a broad range of regeneration parameters. Considering the expected uncertainty and variability in the regeneration processes it is important that the forest dynamics are robust to variations in the regeneration parameters. Furthermore, edge effects such as increased mortality at the border and external seed rain have been necessary to reproduce the patterns for small isolated fragments. Overall, simulated biomass is much lower in the fragments compared to the continuous forest, whereas shade tolerant species are affected most strongly by fragmentation. Our simulations can supplement empirical studies by extrapolating local knowledge on edge effects of fragments to larger temporal and spatial scales. In particular our results show the importance of external seed rain and therefore highlight the importance of structural connectivity between regenerating fragments and mature forest stands.     

Temporal turnover in the composition of tropical tree communities: functional determinism and phylogenetic stochasticity

The degree to which turnover in biological communities is structured by deterministic or stochastic factors and the identities of influential deterministic factors are fundamental, yet unresolved, questions in ecology. Answers to these questions are particularly important for projecting the fate of forests with diverse disturbance histories worldwide. To uncover the processes governing turnover we use species-level molecular phylogenies and functional trait data sets for two long-term tropical forest plots with contrasting disturbance histories: one forest is older-growth, and one was recently disturbed. Having both phylogenetic and functional information further allows us to parse out the deterministic influences of different ecological filters. With the use of null models we find that compositional turnover was random with respect to phylogeny on average, but highly nonrandom with respect to measured functional traits. Furthermore, as predicted by a deterministic assembly process, the older-growth and disturbed forests were characterized by less than and greater than expected functional turnover, respectively. These results suggest that the abiotic environment, which changes due to succession in the disturbed forest, strongly governs the temporal dynamics of disturbed and undisturbed tropical forests. Predicting future changes in the composition of disturbed and undisturbed forests may therefore be tractable when using a functional-trait-based approach.     

Simulating dynamics of managed monsoon evergreen broad-leaved forest in south China

The forest succession model FORDYN is developed based on TREEDEV model. TREEDEV is a process-based tree growth model, that calculates tree growth based on carbon and nitrogen balance, and is calculated using on the photo-production of leaves, respiration, nitrogen content of all organisms and that in soil, and other losses due to respiration, litter and renewal of stems, branches, leaves and roots. In the FORDYN model succession is divided into three phases called early, middle and late succession, and the transition between these three succession phases is distinguished by a difference in leaf area index. As a verification of the model we used the characteristics and available data of a monsoon evergreen broad-leaved forest in Dinghushan Biosphere Reserve (DHS-BR). The model was validated with natural forest data. In addition, a sensitivity analysis was performed in which 30 independent variables were varied and analyzed in connection with their influence on 16 dependent variables describing forest conditions. The simulation results describe the changes in total biomass, carbon and nitrogen change in plant–litter–soil system of an undisturbed monsoon evergreen broad-leaved forest during succession. We compared these findings with simulation in which different logging management strategies were used. The results show that having a longer logging cycle, delaying the first logging time and a smaller logging fraction the scenario can contribute to a sustainable forest development, while still having a positive economic yield.     

Individual-based modeling of flooding and salinity effects on a coastal swamp forest

Coastal swamps are among the rapidly vanishing wetland habitats in Louisiana. Increased flooding, nutrient and sediment deprivation, and salt-water intrusion have been implicated as probable causes of the decline of coastal swamps. We developed a two-species individual-based forest succession model to compare the growth and composition of a cypress-tupelo swamp under various combinations of flooding intensity and salinity levels, using historical time-series of stage and salinity data as inputs. Our model simulates forest succession over 500 years by representing the growth, mortality, and reproduction of individual Taxodium distichum (baldcypress) and Nyssa aquatica (water tupelo) trees in a 1-km² spatial grid of 10 m × 10 m cells that vary in water levels and salinity through differences in elevation. We independently adjusted the elevations of each cell to obtain different grid-wide mean elevations and standard deviations of elevation; this affected the temporal and spatial pattern of flooding. We calibrated the model by adjusting selected parameters until averaged basal area, stem density and wood production rates under two different mean elevations (partially versus highly flooded) were qualitatively similar to comparable values reported for swamps in the literature. Corroboration involved comparing model predictions to four well-monitored contrasting habitat sites within the Maurepas Basin, Louisiana, USA. Model predictions of both species combined showed the same patterns among sites as the data, but the model overestimated wood production and the dominance of T. distichum. Exploratory simulations predicted that increased flooding leads to swamps with reduced basal areas and stem densities, while increased salinity resulted in lower basal areas at low salinity concentration (∼1-3 psu) and complete tree mortality at higher salinity concentrations (∼2-6 psu). Our model can provide insight into the succession dynamics of coastal swamps and information for the effective design of restoration actions.     

Spatio-temporal modelling of ground vegetation development in mountain spruce forests

More complex models of forest ecosystems are required to understand how land-cover changes can impact vegetation dynamics and spatial pattern. In order to document spatio-temporal modelling abilities, the observations conducted in the declined climax mountain Norway spruce forest during the recovery period (1995-2006) are used for simulation and spatial analysis in the GIS environment. The developed spatio-temporal model is used for simulation of forest vegetation dynamics in a mountain spruce forest in the framework of regeneration processes after stress from air pollution. In order to explore the spatial and temporal phenomena of regeneration processes, the spatio-temporal model is based on a large set of ordinary differential equations that solve dynamic processes in sets of microsites arranged in grids for each ground vegetation species and each age group of Norway spruce seedlings. The spatial extent of the explored site is composed of a set of 50 × 50 microsites. Each microsite is represented by a square with dimensions of 1 m × 1 m. The presented simulation studies are mainly focused on seedlings from the seed year 1992, in order to explore the longest monitored time series of survival. It is based on exponential growth models that are related to the environmental conditions for each microsite. The canopy gaps based on estimates of the local crown projected area, the soil type layer, and the dominant grass density are used to provide case simulation studies. The first case study simulates the influence of microsite positions in relation to the local tree crown projections on the survival of spruce seedlings. It is assumed that the density of the trees is the main factor that determines the light and heat supply to the ground level of the Norway spruce seedlings. The second case study extends the previous study to include terms that determine the growth ratio in dependence on the crown projection area. The third case study provides further extensions in order to simulate growth ratio relations to the local soil type. The fourth case study demonstrates the local influence of the dominant grasses, such as Avenella flexuosa and Calamagrostis villosa, on the natural regeneration of Norway spruce. Starting from the conditions at the sites before the recovery period, the case simulation studies are able to project the short-term succession for a regeneration decade and the approximate long-term development. In addition to the standard simulation procedures based on solution of ordinary differential equations, spatio-temporal modelling in the GIS environment is able to provide spatial data management, analysis and visualization of the data.     

Mast seeding under increasing drought: results from a long-term data set and from a rainfall exclusion experiment

Mast seeding, the synchronous, highly variable seed production among years, is very common in tree species, but there is no consensus about its main causes and the main environmental factors affecting it. In this study, we first analyze a long-term data set on reproductive and vegetative growth of Quercus ilex in a mediterranean woodland in order to identify the main environmental drivers of interannual variation in flower and seed production and contrast the impact of climate vs. adaptive factors as main causes of masting. Second, we conducted an experiment of rainfall exclusion to evaluate the effects of an increasing drought (simulating predictions of global change models) on both reproductive processes. The annual seed crop was always affected by environmental factors related to the precipitation pattern, these abiotic factors disrupting the fruiting process at different periods of time. Seed production was strongly dependent upon water availability for the plant at initial (spring) and advanced (summer) stages of the acorn maturation cycle, whereas the final step of seed development was negatively affected by the frequency of torrential-rain events. We also found clear evidence that seed masting in the study species is not only regulated by selective endogenous rhythms, but is mainly a physiological response to the variable environment. Our results from the rainfall exclusion experiment corroborated the conclusions obtained from the 26-year fruiting record and demonstrated that the high interannual variation in seed crop was mainly determined by the success in seed development rather than by the flowering effort. Under a global change scenario, it could be expected that the drier conditions predicted by climate models reinforce the negative effects of summer drought on seed production, leading to negative consequences for tree recruitment and forest dynamics.     

Neutral theory and the evolution of ecological equivalence

Since the publication of the unified neutral theory in 2001, there has been much discussion of the theory, pro and con. The hypothesis of ecological equivalence is the fundamental yet controversial idea behind neutral theory. Assuming trophically similar species are demographically alike (symmetric) on a per capita basis is only an approximation, but it is equivalent to asking: How many of the patterns of ecological communities are the result of species similarities, rather than of species differences? The strategy behind neutral theory is to see how far one can get with the simplification of assuming ecological equivalence before introducing more complexity. In another paper, I review the empirical evidence that led me to hypothesize ecological equivalence among many of the tree species in the species-rich tropical forest on Barro Colorado Island (BCI). In this paper, I develop a simple model for the evolution of ecological equivalence or niche convergence, using as an example evolution of the suite of life history traits characteristic of shade tolerant tropical tree species. Although the model is simple, the conclusions from it seem likely to be robust. I conclude that ecological equivalence for resource use are likely to evolve easily and often, especially in species-rich communities that are dispersal and recruitment limited. In the case of the BCI forest, tree species are strongly dispersal- and recruitment-limited, not only because of restricted seed dispersal, but also because of low recruitment success due to heavy losses of the seedling stages to predators and pathogens and other abiotic stresses such as drought. These factors and the high species richness of the community strongly reduce the potential for competitive exclusion of functionally equivalent or nearly equivalent species.     

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.     

Analysis of neighborhood dynamics of forest ecosystems using likelihood methods and modeling.

Advances in computing power in the past 20 years have led to a proliferation of spatially explicit, individual-based models of population and ecosystem dynamics. In forest ecosystems, the individual-based models encapsulate an emerging theory of "neighborhood" dynamics, in which fine-scale spatial interactions regulate the demography of component tree species. The spatial distribution of component species, in turn, regulates spatial variation in a whole host of community and ecosystem properties, with subsequent feedbacks on component species. The development of these models has been facilitated by development of new methods of analysis of field data, in which critical demographic rates and ecosystem processes are analyzed in terms of the spatial distributions of neighboring trees and physical environmental factors. The analyses are based on likelihood methods and information theory, and they allow a tight linkage between the models and explicit parameterization of the models from field data. Maximum likelihood methods have a long history of use for point and interval estimation in statistics. In contrast, likelihood principles have only more gradually emerged in ecology as the foundation for an alternative to traditional hypothesis testing. The alternative framework stresses the process of identifying and selecting among competing models, or in the simplest case, among competing point estimates of a parameter of a model. There are four general steps involved in a likelihood analysis: (1) model specification, (2) parameter estimation using maximum likelihood methods, (3) model comparison, and (4) model evaluation. Our goal in this paper is to review recent developments in the use of likelihood methods and modeling for the analysis of neighborhood processes in forest ecosystems. We will focus on a single class of processes, seed dispersal and seedling dispersion, because recent papers provide compelling evidence of the potential power of the approach, and illustrate some of the statistical challenges in applying the methods.     

An innovative computer design for modeling forest landscape change in very large spatial extents with fine resolutions

Although forest landscape models (FLMs) have benefited greatly from ongoing advances of computer technology and software engineering, computing capacity remains a bottleneck in the design and development of FLMs. Computer memory overhead and run time efficiency are primary limiting factors when applying forest landscape models to simulate large landscapes with fine spatial resolutions and great vegetation detail. We introduce LANDIS PRO 6.0, a landscape model that simulates forest succession and disturbances on a wide range of spatial and temporal scales. LANDIS PRO 6.0 improves on existing forest landscape models with two new data structures and algorithms (hash table and run-length compression). The innovative computer design enables LANDIS PRO 6.0 to simulate very large (>10⁸ ha) landscapes with a 30-m spatial resolution, which to our knowledge no other raster forest landscape models can do. We demonstrate model behavior and performance through application to five nested forest landscapes with varying sizes (from 1 million to 100 million 0.09-ha cells) in the southern Missouri Ozarks. The simulation results showed significant and variable effects of changing spatial extent on simulated forest succession patterns. Results highlighted the utility of a model like LANDIS PRO 6.0 that is capable of efficiently simulating large landscapes and scaling up forest landscape processes to a common regional scale of analysis. The programming methodology presented here may significantly advance the development of next generation of forest landscape models.     

Using the ECLPSS software environment to build a spatially explicit component-based model of ozone effects on forest ecosystems

We have developed a modeling framework to support grid-based simulation of ecosystems at multiple spatial scales, the Ecological Component Library for Parallel Spatial Simulation (ECLPSS). ECLPSS helps ecologists to build robust spatially explicit simulations of ecological processes by providing a growing library of reusable interchangeable components and automating many modeling tasks. To build a model, a user selects components from the library, and then writes new components as needed. Some of these components represent specific ecological processes, such as how environmental factors influence the growth of individual trees. Other components provide simulation support such as reading and writing files in various formats to allow inter-operability with other software. The framework manages components and variables, the order of operations, and spatial interactions. The framework provides only simulation support; it does not include ecological functions or assumptions. This separation allows biologists to build models without becoming computer scientists, while computer scientists can improve the framework without becoming ecologists. The framework is designed to operate on multiple platforms and be used across networks via a World Wide Web-based user interface. ECLPSS is designed for use with both single processor computers for small models, and multiple processors in order to simulate large regions with complex interactions among many individuals or ecological compartments. To test Version 1.0 of ECLPSS, we created a model to evaluate the effect of tropospheric ozone on forest ecosystem dynamics. This model is a reduced-form version of two existing models: , which represents an individual tree, and , which represents forest stand growth and succession. This model demonstrates key features of ECLPSS, such as the ability to examine the effects of cell size and model structure on model predictions.     

Simulation of wetlands forest vegetation dynamics

A computer program, SWAMP, was designed to simulate the effects of flood frequency and depth to water table on southern wetlands forest vegetation dynamics. By incorporating these hydrologic characteristics into the model, forest vegetation and vegetation dynamics can be simulated. The model, based on data from the White River National Wildlife Refuge near De Witt, Arkansas, “grows” individual trees on a 20 x 20-m plot taking into account effects on the tree growth of flooding, depth to water table, shade tolerance, overtopping and crowding, and probability of death and reproduction. A potential application of the model is illustrated with simulations of tree fruit production following flood-control implementation and lumbering.     

Simulation of NO and N2O emissions from a spruce forest during a freeze/thaw event using an N-flux submodel from the PnET-N-DNDC model integrated to CoupModel

The amount of nitrogen gases (N₂O, NO and N₂) emitted from forest soils depends on interactions between soil properties, climatic factors and soil management. To increase the understanding of nitrogen processes in soil ecosystems, two dynamic models, CoupModel (coupled heat and mass transfer model for soil–plant–atmosphere systems) and the denitrification–decomposition (DNDC) model were selected. Both are dynamic models with different submodels for soil, vegetation, hydrology and climate system. CoupModel has a higher degree of detail on soil physical and abiotic components, whereas the DNDC model contains details of microbiological processes involved in production of nitrogen gases. To improve the previous simple submodel of nitrogen emission in CoupModel, we included a submodel corresponding to the forest version of DNDC containing photosynthesis/evapotranspiration-nitrogen (PnET-N-DNDC model).     

Species richness in a riparian plant community along the banks of the Xiangxi River,the Three Gorges region

The distribution of vascular plant species richness along an altitudinal gradient and their relationships with environmental variables, including slope, aspect, bank (flooding) height, and river width of the Xiangxi River, Hubei Province, were examined. Total vascular plant species richness changed with elevation: it increased at lower elevations, reached a maximum in the midreaches and decreased thereafter. In particular, tree and herbaceous species richness were related to altitude. Correlation analysis (Kendall's τ) between species richness and environmental variables indicated that the change in species richness in the riparian zone was determined by riparian environmental factors and characteristics of regional vegetation distribution along the altitudinal gradient. The low species richness at lower elevations resulted from seasonal flooding and human activities – agriculture and fuel collection – and the higher species richness in the midreaches reflected transitional zones in natural vegetation types that had had little disturbance. These results on species distribution in the riparian community could be utilized as a reference for restoration efforts to improve water quality of the emerging reservoir resulting from the Three Gorges Hydroelectric Dam project.     

Assessing the performance of theoretical and empirical tree mortality models using tree-ring series of Norway spruce

Successional dynamics of forests under current and changed climate are often investigated using gap models, a subset of forest succession models that simulate establishment, growth, and mortality of trees. However, the mortality submodels of gap models are largely based on theoretical assumptions, and have not been tested in detail.In the present study, we compared the performance of a range of theoretical mortality functions (TMFs) that are commonly used in gap models with several empirical mortality functions (EMFs) that were derived using logistic regression from growth patterns of tree-ring series as predictor variables. Data from dead and living Norway spruce (Picea abies (L.) Karst.) trees from subalpine forests at three study sites in Switzerland were used to this end.Three of the four EMFs consistently performed better at all three sites, while three of the four TMFs performed worse than the remaining mortality functions. At one site, these three EMFs correctly classified 71–78% of the dead trees (48–72% for the three TMFs) and 73% (49–64%) of the living trees. 44–54% (21–25%) of the dead trees were predicted to die within 15 years prior to death. 0–2% (7–10%) of the dead trees and 5% (19–31%) of the living trees were predicted to die more than 60 years prior to the last measured year.We conclude that, unless the parameters of the TMFs are optimized for individual species, the TMFs are not appropriate to predict the time of tree death, in spite of their widespread use. A substantial change in simulated forest succession is to be expected if the currently implemented TMFs in gap models are replaced by species-specific EMFs.