Individual Tree Mortality Research Articles

Optimisation of tree mortality models based on growth patterns

Forest succession is often modelled using “gap models” that simulate the establishment, growth and mortality of individual trees. However, many mortality submodels that are currently used in gap models are based on theoretical assumptions and have not been tested with empirical data sets. Except for disturbance-induced mortality, these models predict the time of individual tree death using stress thresholds (ST). They often include a simple stress memory that keeps track of low diameter growth over the recent growth history of each tree, which may lead to increased mortality. In the present study, we optimised the parameter values for a range of commonly used classical ST models. We used the geometric mean of the averages of the correctly classified living and dead trees as our optimisation and model performance criterion. Furthermore, we compared the performance of the ST models with that of recently derived logistic regression models based on growth patterns as predictor variables. Tree-ring data from dead and living Norway spruce ( Picea abies) trees of subalpine forests at three study sites in Switzerland were used to calibrate and validate the ST models. The optimisation increased the performance of the classical ST models by 61–153%. Surprisingly, the model without any stress memory showed the highest performance and thus exceeded the performance of more “realistic” models, i.e., those considering a stress memory. Despite these tremendous improvements, the optimised ST models did not attain the performance of the logistic regression models. Therefore, we conclude that even optimised classical ST models are inferior to regression models with regard to predicting the time of tree death. A considerable change in the simulated forest succession is to be expected if classical ST models that are still used in many gap models are replaced by logistic regression models based on field data.

Prediction of delayed mortality of fire-damaged ponderosa pine following prescribed fires in eastern Oregon, USA

Prescribed burning is a management tool used to reduce fuel loads in western interior forests. Following a burn, managers need the ability to predict the mortality of individual trees based on easily observed characteristics. Astudy was established in six stands of mixed-age ponderosa pine (Pinus ponderosa Dougl. ex Laws.) with scattered western junipers at the south end of the Blue Mountains near Burns, Oregon, USA. Stands were thinned in either 1994 or 1995. Three treatments, a fall burn, a spring burn, and an unburned control, were randomly assigned to 12-ha experimental units within each stand. Prescribed burns occurred during mid-October of 1997 or mid-June of 1998 and were representative of operational burns, given weather and fuel conditions. Within each experimental unit, six 0.2-ha plots were established to evaluate responses to the burns. Ponderosa pine plot trees (n =3415) alive 1 month after the burns were evaluated and observed for four growing seasons. Nine fire damage and tree morphological variables were evaluated by logistic regression. A five-factor full model and a two-factor reduced model are presented for projecting probability of mortality. Significant variables in the full model included measures of crown, bole, and basal damage.

A modeling analysis of the interaction between forest age and forest responsiveness to increasing CO2 concentration

Typically, forests have rotations of 10-200 years. On that time scale, anthropogenic increases in atmospheric carbon dioxide concentration ([CO2]) and the associated changes in climate are expected to be substantial. These changes will, therefore, almost certainly affect the growth of presently established forest stands. Most studies on the effects of increasing [CO2] on tree growth have been made with young plants. However, the growth of trees within a forest stand varies with age. As a consequence, it is difficult to infer from the available experimental data how rising [CO2] will affect forest productivity over a full rotation. In this study, various mechanisms that may account for the slowing of forest growth with age were introduced into the forest growth model CenW, to assess how these processes affect the modeled growth response to increasing [CO2]. Inclusion of allocation shifts with tree height, individual tree mortality, changing respiration load and nutrient dynamics or age-based reductions in photosynthetic capacity had only small effects on the response to increasing [CO2]. However, when photosynthesis of mature trees was decreased as a function of size, then the growth response to increasing [CO2] was reduced because, at the same age, trees were larger in elevated than in ambient [CO2]. No simple and generally valid interactions between increasing [CO2] and forest age were identified because of the large number of interacting processes, all of which are incompletely understood. Important age x climate change interactions on productivity must occur in real forests and need to be considered to understand likely future trends. However, these interactions are complex and difficult to test. It is therefore not yet possible to predict with confidence the modification of the CO2 response by forest age.

A multi-species density-dependent matrix growth model for the dry woodlands of Uganda

A density-dependent matrix growth model was constructed for the dry woodlands of Uganda basing on material collected from 42 sample plots with 7904 trees. The model was based on functions for individual tree upgrowth and mortality, and area-based ingrowth, with explicatory variables representing tree size, stand density and stand structure. The trees were pooled into three species groups basing on ecological and morphological criteria. For all groups, parameter estimates for tree size and stand density were found highly significant ( p < 0.001) in predicting diameter increment and mortality except stand density for the upper storey species group ( p = 0.067), while stand structure was found highly significant only for the intermediate storey species group. Ingrowth was modelled by a two-stage approach. Parameter estimates for a logistic function predicting the probability of ingrowth were statistically significant ( p < 0.05) only for the intermediate storey species group, while no conditional ingrowth functions were built for any species group. A visual evaluation of the individual functions was carried out and the matrix model in totality was evaluated by comparing the number of trees ha −1 and basal area ha −1 for each plot at the time of the second inventory with the model predictions. Although the data used for model evaluation was not independent, it was concluded that the model is a reliable and fairly accurate tool for prediction of growth of dry woodland trees in of Uganda. The model may become a useful tool for a sustainable management of these woodlands, which are an important source of bioenergy for consumers in several urban centres.

Predicting the mortality of Pinus sylvestris attacked by Gremmeniella abietina and occurrence of Tomicus piniperda colonization

The fungus Gremmeniella abietina (Lagerb.) Morelet is widely distributed in the northern hemisphere and causes scleroderris canker in several coniferous species. In Sweden, large areas, mainly with 30- to 40-year-old Scots pine (Pinus sylvestris L.) forests, were attacked by the fungus in 2000. The main aim of this study was to investigate the relationship between tree crown transparency (CT) induced by G. abietina and P. sylvestris tree mortality. Furthermore, regeneration–colonization by Tomicus piniperda (L.) was monitored in the investigated stands. Thirty-five permanent sample plots were established in five P. sylvestris stands (38–46 years old) infected by G. abietina and located in the central part of Sweden. During the 2 years following the attack, the total tree mortality accounted for 380 trees·ha–1 and 6.2 m2·ha–1 on average in the five stands, corresponding to 35% of the trees and 27% of the basal area at the time of the attack. Galleries with broods of T. piniperda occurred in trees with a CT value higher than 97%. A model was derived for predicting the probability of P. sylvestris tree mortality. The mortality of individual trees was found to be related to CT, position of needle loss within the crown (CTPOS), and tree diameter at breast height. Furthermore, there was an interaction between CT and CTPOS and a tendency for CT and site to interact. For a P. sylvestris tree with a 0.16-m diameter at breast height and a CT value of 90% spread throughout the crown, the model indicated a mortality probability of 0.03. Above this CT value, the probability of mortality increased substantially. For coniferous species, irrespective of the cause of damage, a CT value of 90%–95% appears to be a critical range; any values greater than this indicate a high probability of mortality.

An Individual-Tree Mortality Model for Complex Stands of Southeastern British Columbia

Abstract An individual-tree mortality model was developed for major tree species in complex stands (multi-cohort, multiaged, and mixed species) of southeastern British Columbia (BC), Canada. Data for 29,773 trees were obtained from permanent sample plots established in BC. Average annual diameter increment and mortality rates ranged from 0.08 to 0.17 cm/year and from 0.3 to 2.6%, respectively. Approximately 70% of the trees were used for model development and 30% for model evaluation. After evaluating the model, all 29,773 trees were used to fit the final model. A generalized logistic model was used to relate mortality to tree size, competition, and relative position of trees in a stand. The evaluation test demonstrated that the model appears to be well behaved and robust for the tree species considered in this study. For the eight tree species, the average deviation between observed and predicted annual mortality rates varied from −0.5 to 0.7% in the test data. West. J. Appl. For. 20(2):101–109.

The forest vegetation simulator: A review of its structure, content, and applications

The Forest Vegetation Simulator (FVS) is a distance-independent, individual-tree forest growth model widely used in the United States to support management decisionmaking. Stands are the basic projection unit, but the spatial scope can be many thousands of stands. The temporal scope is several hundred years at a resolution of 5–10 years. Projections start with a summary of current conditions evident in the input inventory data. FVS contains a self-calibration feature that uses measured growth rates to modify predictions for local conditions. Component models predict the growth and mortality of individual trees, and extensions to the base model represent disturbance agents including insects, pathogens, and fire. The component models differ depending on the geographic region represented by regionally specific model variants. The differences are due to data availability and the applicability of existing models. The model supports specification of management rules in the input, such as thinning if density is too high. The rules can be extended to represent other factors. For example, the effect of climate change on stand development by entering rules that specify how growth and mortality will change in response to changing climate. Applications range from development of silvicultural prescription for single stands to landscape and large regional assessments. Key issues addressed with FVS include forest development, wildlife habitat, pest outbreaks, and fuels management. The predictions are used to gain insights into how forested environments will respond to alternative management actions. Broad-scale forest management policies have been studied with FVS. For the 30 years since the model was initially introduced, the development team has anticipated and provided needed enhancements and maintained a commitment to working with and training users. The existence of an adequate user interface and the continued use of the original programming language are often overlooked factors for the success of this model. Future work will focus on improving FVS by adopting recent biometric techniques and including new information linking geomorphology to mortality and growth. Extending the model to more closely represent biophysical processes and adapting the model so that it is more relevant to management questions related to predicted climate change are also foci. Providing ways to dynamically link FVS to other models is our current strategy for providing major new capabilities.

Are Self-Thinning Constraints Needed in a Tree-Specific Mortality Model?

Abstract Can a tree-specific mortality model elicit expected forest stand density dynamics without imposing stand-level constraints such as Reineke's maximum stand density index (SDImax) or the −3/2 power law of self-thinning? We examine this emergent properties question using the Austrian stand simulator PROGNAUS. This simulator was chosen specifically because it does not use stand density constraints to determine individual tree mortality rates. In addition, it is based on a probability sample of the population that includes the span of the data being used to test the hypothesis. Initial conditions were obtained from 27 permanent research plots that were established in young pure stands of Norway spruce (Picea abies L. Karst.) and Scots pine (Pinus sylvestris L.) in Austria. A growth period of 250 years was simulated. We conduct our test in two parts. First, we compare our simulated results to Reineke's theory of maximum density and stand density index by examining the self-thinning relationship between stem number per hectare and quadratic mean diameter (log-log scale). Second, we compare our results to Sterba's full competition density rule, which incorporates dominant height along with stem number and quadratic mean diameter. From the results for Norway spruce, we conclude that stand-level density constraints are not necessary to obtain Reineke's maximum size-density relations. Norway spruce results confirm that the maximum size-density relationship reflects reasonable and stable stand dynamics and conforms to that expected by Reineke's theory. Results from simulation of Scots pine also display reasonable and stable stand dynamics, except that they greatly exceed Reineke's maximum stand density index determined empirically from the literature. This Scots pine result argues for stand-level constraints (such as specifying SDImax) to ensure that the appropriate intercept for the maximum density line is used. Our second test revealed that the estimated maximum stand density index according to Sterba's theory was too high for both species, but that the relative rankings across plots were correct. Thus, we are left with ambiguous results. First, that a density-dependent individual-tree mortality model, developed on an adequate data set, is sufficient for the desired stand-level behavior of Reineke to emerge. Second, that stand-level constraints on SDImax need to be imposed if the underlying mortality modeling database is not adequate. FOR. SCI. 50(6):848–858.

Bedrock type significantly affects individual tree mortality for various conifers in the inland Northwest, U.S.A.

Individual tree mortality models for western white pine (Pinus monticola Dougl. ex D. Don), Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), grand fir (Abies grandis (Dougl. ex D. Don) Lindl.), western redcedar (Thuja plicata Donn ex. D. Don), western hemlock (Tsuga heterophylla (Raf.) Sarg.), and western larch (Larix occidentalis Nutt.) were developed using data from permanent research plots located throughout the inland Northwest. The proposed linear logistic models included the following independent variables: diameter at breast height, basal area in larger trees, basal area per hectare, individual tree diameter increment, and a set of dummy variables for the six bedrock types, which were granite, basalt, metasedimentary, sedimentary, mixed – glacial till, and deep deposit. The results show that rock type significantly affects individual tree mortality for western white pine, Douglas-fir, and western redcedar, while grand fir, western hemlock, and western larch were not affected. Western white pine and Douglas-fir growing on meta sedimentary rocks exhibited greater mortality probabilities than on other rocks. Mortality probabilities for western hemlock were low across all rock types, including "nutrient-poor" rocks like metasedimentary types.

Non‐linear matrix modeling of forest growth with permanent plot data: The case of uneven‐aged Douglas‐fir stands

AbstractUneven‐aged forest management is acquiring increasing importance throughout the world as an alternative to clear cutting. Simple stage‐structured matrix models can be used to predict the growth of uneven‐aged stands, and they are easily incorporated in optimization analysis. Parameters of these models can be estimated from readily available permanent plot data. Such a growth and yield model is presented for mixed, uneven‐aged Douglas‐fir and hardwood stands. The model was calibrated with data from 66 permanent plots in Oregon and Washington. The density‐dependent matrix model predicts the number of trees by diameter class and species type, softwood or hardwood. The parameters are based on individual tree growth equations, individual tree mortality equations, and stand ingrowth equations. The individual tree equations are a function of tree diameter, stand density, species, and site index. The stand‐level ingrowth equations are a function of stand density. The model was validated in the short term by comparing the number of trees in each diameter and species class at the time of the second inventory with the number predicted by the model, given conditions at the first inventory. A long‐term validation of the model was also done by comparing the steady‐state stand structure and stand volume with those observed for old‐growth stands. The model was applied to show the effects of different cutting cycles on productivity, diversity of tree species and size, and financial returns. The results suggest that uneven‐aged management of the Douglas‐fir forest type in the Pacific Northwest can be as productive as even‐aged management, with the added benefits of continuous cover forestry.

Landscape patterns of change in coarse woody debris accumulation in an old-growth deciduous forest on the Cumberland Plateau, southeastern Kentucky

Forest disturbance was evaluated in an old-growth forest on the Cumberland Plateau in southeastern Kentucky using a 10-year history of coarse woody debris (CWD) accumulation. CWD averaged 21.8 Mg/ha in 1989 and 29.6 Mg/ha (36% increase) in 1999. In both years, Quercus montana Willd. and Fagus grandifolia Ehrh. were the two dominant components of CWD; however, over the 10-year interval, Tilia heterophylla Vent., Carya glabra (Mill.) Sweet, and Acer saccharum Marsh. increased significantly, while Quercus alba L. declined. CWD occurrence had a highly skewed frequency, which is consistent with the idea that gap dynamics dominate the disturbance patterns of temperate old-growth forests. However, CWD composition bore limited relationship to overstory species composition or to the dynamics of gap creation. Further, while CWD showed no relationship to forest community (i.e., landscape position) in 1989, it was strongly related to community in 1999. The increase in CWD mass and changing importance of landscape position appear to have occurred in the absence of extrinsic disturbance factors. Thus, in old-growth deciduous forests of the temperate region, autogenic disturbance appears to occur at two scales: (i) the patch dynamics of individual tree mortality and (ii) landscape-scale patterns of mortality that are determined by species composition and differing patterns of mortality among species.

Modeling individual tree mortality for white spruce in Alberta

An individual tree mortality model, based on the provincial PSP data, was developed for white spruce ( Picea glauca (Moench) Voss), an important tree species in Alberta, Canada. Annual probability of survival was modeled by a generalized logistic function with the measurement interval length as a predictor variable to overcome the problem of unequal measurement intervals. Potential predictor variables were selected based on their ecological importance to tree mortality and unknown parameters were estimated using the maximum likelihood method. A U-shaped mortality trend was captured by diameter and diameter squared. Annual diameter increment was used to indicate tree vigor. Basal area of larger trees and a ratio of basal area of larger broadleaf trees to stand total basal area were both used to capture competition from neighboring trees. The newly developed mortality function outperformed the old one previously used in the Mixedwood Growth Model (MGM) based on both goodness-of-fit and prediction statistics.

Modeling mortality of individual trees in drained peatland sites in Finland

Multilevel logistic regression models were constructed to predict the 5-year mortality of Scots pine (Pinus sylvestris L.) and pubescent birch (Betula pubescens Ehrh.) growing in drained peatland stands in northern and central Finland. Data concerning tree mortality were obtained from two successive measurements of the National Forest Inventory-based permanent sample plot data base covering pure and mixed stands of Scots pine and pubescent birch. In the modeling data, Scots pine showed an average observed mortality of 2.73% compared to 2.98% for pubescent birch. In the model construction, stepwise logistic regression and multilevel models methods were applied, the latter making it possible to address the hierarchical data, thus obtaining unbiased estimates for model parameters. For both species, mortality was explained by tree size, competitive position, stand density, species admixture, and site quality. The expected need for ditch network maintenance or re-paludification did not influence mortality. The multilevel models showed the lowest bias in the modeling data. The models were further validated against independent test data and by embedding them in a stand simulator. In 100-year simulations with different initial stand conditions, the models resulted in a 72% and 66% higher total mortality rate for the stem numbers of pine and birch, respectively, compared to previously used mortality models. The developed models are expected to improve the accuracy of stand forecasts in drained peatland sites.

Ponderosa pine mortality following fire in northern Arizona

Sampling of 1367 trees was conducted in the Side wildfire (4 May 1996), Bridger-Knoll wildfire (20 June 1996) and Dauber prescribed fire (9 September 1995) in northern Arizona ponderosa pine forests (Pinus ponderosa). Tree mortality was assessed for 3 years after each fire. Three-year post-fire mortality was 32.4% in the Side wildfire, 18.0% in the Dauber prescribed fire, and 13.9% in the Bridger-Knoll wildfire. In the Dauber and Side fires, 95% and 94% of 3-year post-fire mortality occurred by year 2, versus 76% in the Bridger-Knoll wildfire. Compared with trees that lived for 3 years after fire, dead trees in all fires had more crown scorch, crown consumption, bole scorch, ground char, and bark beetle attacks. Logistic regression models were used to provide insight on factors associated with tree mortality after fire. A model using total crown damage by fire (scorch + consumption) and bole char severity as independent variables was the best two-variable model for predicting individual tree mortality for all fires. The amount of total crown damage associated with the onset of tree mortality decreased as bole char severity increased. Models using diameter at breast height (dbh) and crown volume damage suggested that tree mortality decreased as dbh increased in the Dauber prescribed fire where trees were smallest, and tree mortality increased as dbh increased in the Side and Bridger-Knoll wildfires where trees were largest. Moreover, a U-shaped dbh–mortality distribution for all fires suggested higher mortality for the smallest and largest trees compared with intermediate-size trees. We concluded that tree mortality is strongly influenced by interaction between crown damage and bole char severity, and differences in resistance to fire among different-sized trees can vary among sites.

Corrigendum to: Ponderosa pine mortality following fire in northern Arizona

Sampling of 1367 trees was conducted in the Side wildfire (4 May 1996), Bridger-Knoll wildfire (20 June 1996) and Dauber prescribed fire (9 September 1995) in northern Arizona ponderosa pine forests (Pinus ponderosa). Tree mortality was assessed for 3 years after each fire. Three-year post-fire mortality was 32.4% in the Side wildfire, 18.0% in the Dauber prescribed fire, and 13.9% in the Bridger-Knoll wildfire. In the Dauber and Side fires, 95% and 94% of 3-year post-fire mortality occurred by year 2, versus 76% in the Bridger-Knoll wildfire. Compared with trees that lived for 3 years after fire, dead trees in all fires had more crown scorch, crown consumption, bole scorch, ground char, and bark beetle attacks. Logistic regression models were used to provide insight on factors associated with tree mortality after fire. A model using total crown damage by fire (scorch + consumption) and bole char severity as independent variables was the best two-variable model for predicting individual tree mortality for all fires. The amount of total crown damage associated with the onset of tree mortality decreased as bole char severity increased. Models using diameter at breast height (dbh) and crown volume damage suggested that tree mortality decreased as dbh increased in the Dauber prescribed fire where trees were smallest, and tree mortality increased as dbh increased in the Side and Bridger-Knoll wildfires where trees were largest. Moreover, a U-shaped dbh–mortality distribution for all fires suggested higher mortality for the smallest and largest trees compared with intermediate-size trees. We concluded that tree mortality is strongly influenced by interaction between crown damage and bole char severity, and differences in resistance to fire among different-sized trees can vary among sites.

The effects of harvest-created gaps on plant species diversity, composition, and abundance in a Maine oak–pine forest

In forests where large, stand-replacing disturbances are infrequent, small-scale disturbances associated with the mortality and replacement of individual trees are a primary source of heterogeneity in forest composition and structure. The disturbances considered in this study were canopy gaps created by a partial harvest in the winter of 1987–1988 in an oak–pine ( Quercus–Pinus) forest that is part of a long-term ecosystem study at the Holt Research Forest in coastal Maine. This study examined the gap phase of the forest turnover cycle: the brief episodes of rapid change when processes determining the structure and composition of a forest community occur. The objective was to evaluate the effects of harvest-created gaps and soil moisture (as reflected by soil drainage classes) on woody and herbaceous species diversity, composition, and abundance relative to unharvested control areas. Because the vegetation was sampled in both 1993 and 1998, detection of short-term changes was possible. Harvest gaps had higher total plant species richness in the understory (vegetation <1 m tall) than controls, primarily due to more infrequently-occurring species. Average species richness varied by soil drainage class but not treatment, whereas the Shannon–Wiener diversity index was not affected by treatment, drainage class, or time. Species abundance was more evenly distributed (i.e., higher evenness) in controls than in gaps. Species unique to harvest gaps decreased in number and abundance over time. Detrended correspondence analysis (DCA) revealed that harvest gaps exhibited greater variability in species composition than controls, although many of the gaps and controls were similar in composition. Shifts in individual species abundance were evident with treatment, drainage, and time. Diversity measures calculated for sapling density showed a significant difference among drainage classes for species richness, but no significant difference between treatments for species richness, the Shannon–Wiener index, or the evenness index. Gap size was positively correlated with the total density of saplings, the density of several species, and species richness. There were significant differences between treatments for the density of all species tested in at least one of the four height classes. DCA of sapling data revealed some separation of harvest gaps and controls but there was considerable overlap. Axis 1 tended to separate early successional species in the harvest gaps from shade tolerant species in the controls. The understory plant community at the HRF appears to be resilient to the partial harvest that created a variety of gap sizes. Silvicultural objectives were met; the harvest gaps created sites for establishment of seedlings and sprouts of tree species, particularly early successional species.

Maximum size–density relationship for constraining individual tree mortality functions

A maximum size–density relationship between quadratic mean diameter and stand density was developed based on the self-thinning concept. Several functions were compared first by fitting the average size–density relationship and two equally good functions were selected based on both fitting and prediction statistics. They were then refitted with a defined loss function to derive the maximum size–density relationship. One final function was chosen for constraining existing individual tree mortality functions developed for major species in boreal mixedwood forests. It was found that site quality did not affect this maximum size–density relationship. The results also showed that separation of this relationship by species was not possible.

Biological constraints on the growth of hardwood regeneration in upland Piedmont forests

The effects of aboveground fungi, insects, browsing mammals and weeds on the growth (height, diameter and volume index) and density of hardwood stems were studied on three upland sites in the Piedmont of North Carolina, USA during the first two growing seasons following clearcutting. Competition from weeds was the most detrimental to hardwood growth. Pesticide treatments alone (broad-spectrum insecticide, fungicide and mammal repellent) did not significantly increase growth. Compared to the control (no weeding or pesticides), stems receiving the pesticide+weeded treatment increased in height 1.6–4.5 times, diameter 1.7–5.3 times and volume index 3.4–5.1 times by the end of second growing season, across all sites. Stem density did not exhibit clear treatment effects, although individual tree mortality and recruitment in the plots were not recorded. Exclosures, with weeding, to eliminate the browsing impact of white-tailed deer ( Odocoileus virginianus Zimmermann), installed only during the second year of study, yielded a 1.9, 1.6 and 3.2 times increase in mean stem height, diameter and stem volume index, respectively, as compared to weeded only plots. Results indicate that very young hardwood regeneration can respond quickly to release from biological constraints and the rate of stand establishment and development may be enhanced with stand manipulations in the first two growing seasons.

Tree mortality in a Pinus sylvestris dominated boreal forest landscape in Vienansalo wilderness, eastern Fennoscandia

Tree mortality and its causes and spatial pattern were examined along four transects (width 40 m, length 2550–3960 m), with a total length of 12 190 m and area of 48.8 ha, in a Pinus sylvestris L. dominated, boreal forest landscape. Tree mortality was determined within a time window of 3 years by identifying those trees (dbh ≥ 10 cm) along the transects that fitted into one of the three categories: 1) current mortality: trees that had died during the year of survey (1998), 2) recent mortality: trees that had died during the year (1997) before the survey year, and 3) predicted mortality: trees that were expected to die during the year (1999) following the survey year. Long-term tree mortality was studied on 10 plots (20 m x 100 m) by dating 87 dead trees using dendrochronological methods. The mean current mortality was 1.4 m3 ha–1 (3.7 trees ha–1). Both the recent and predicted mortalities were also 1.4 m3 ha–1. Mortality was, on the average, higher on peatlands than on mineral soils. The highest mortality was found within an area recently flooded by beavers. Over half of the examined trees (52%) were judged to die without any visible signs of an external abiotic cause. At the landscape scale, tree mortality was continuous although somewhat aggregated in space. Of the 66 dated standing dead Pinus trees, 23 (35%) had died during the 19th century and two during the 18th century, demonstrating that dead Pinus can remain standing for long periods of time before falling. Our results show that autogenic mortality of individual trees or small groups of trees was the predominant mode of disturbance in this Pinus dominated landscape.

Models for individual tree mortality in Norway

Logistic models predicting probability of survival for individual trees were developed, respectively, for Norway spruce ( Picea abies (L.) Karst.), Scots pine ( Pinus sylvestris L.), birch ( Betula spp.), and for other broadleaved trees. The models were based on data from one remeasurement of a nation-wide grid of permanent sample plots recorded by the Norwegian National Forest Inventory. The data comprised 4506 sample plots with 46107 individual trees. Approximately 80% of the observations were used for model development and 20% for validation. The models were designed to be used in large scale forestry scenario models for even-aged and uneven-aged forests, as well as for forests with mixed and pure species composition. The explicatory variables in the models were the inverse of diameter at breast height, a competition index for individual trees, site index, and the proportion of basal area for the respective tree species. All parameter estimates were found highly significant ( P<0.001) in predicting mortality except site index in the model for Norway spruce ( P<0.05) and the inverse of diameter in the model for birch ( P<0.01). Although the phenomenon of mortality is a stochastic, rare and irregular event, the model fit and validation tests were fairly good. Given the general uncertainty related to large scale forestry scenario analyses, and the uncertainty related to mortality as a phenomenon, the mortality models presented in this paper were considered to have an appropriate level of reliability.