Efficient and sustainable management of complex forest ecosystems

A large range of models has been developed for the analysis of optimal forest management strategies, with the well-known Faustmann models dating back to the mid-19th century. To date, however, there has been relatively little attention for the implications of complex ecosystem dynamics for optimal forest management. This paper examines the implications of irreversible ecosystem responses for efficient and sustainable forest management. The paper is built around two forest models that comprise two ecosystem components, forest cover and topsoil, the interactions between these components, and the supply of the ecosystem services ‘wood’ and ‘erosion control’. The first model represents a forest that responds in a reversible way to overharvesting. In the second model, an additional ecological process has been included and the ecosystem irreversibly collapses below certain thresholds in forest cover and topsoil depth. The paper presents a general model, and demonstrates the implications of pursuing efficient as well as sustainable forest management for the two forest ecosystems. Both fixed and variable harvesting cycles are examined. Efficient and sustainable harvesting cycles are compared, and it is shown that irreversible ecosystem behaviour reduces the possibilities to reconcile efficient and sustainable forest management through a variable harvesting cycle.     

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.     

Model-based analysis of the influence of ecological processes on forest point pattern formation—A case study

Many different spatio-temporal individual-based models (IBM) for forests have been developed for studying the development of trees in space and time. Such models typically depend on various numerical parameters that represent the ecological processes of growth (G), inter-plant competition (C) and birth-and-death (B&D; also called regeneration and mortality). Until now little work has been done to systematically trace the influence of these processes and their model parameters on the spatial structure of forest ecosystems.This paper attempts to fill this gap by addressing an important aspect of forest structure, spatial variability, characterised by the mark variogram as a summary characteristic. The model used was inspired by components of various well-established IBMs including a shot-noise competition field. Time series data from monospecies forests in three different countries of the northern hemisphere provided ecological reference scenarios. Though a case study, the paper's methodology is rather general and can be applied to any model and forest ecosystem.Methods of sensitivity analysis revealed that only a small number of model parameters is crucial for forming spatial variability. Particularly important is the range of competition between trees; with increasing range the variability increases. Growth processes have considerable importance particularly with short observation periods and in young forests, whereas mortality processes become more influential in the long-term. Naturally, these statements depend upon the initial structure and on the length of the observation period.     

Postfire Management on Forested Public Lands of the Western United States

Abstract:  Forest ecosystems in the western United States evolved over many millennia in response to disturbances such as wildfires. Land use and management practices have altered these ecosystems, however, including fire regimes in some areas. Forest ecosystems are especially vulnerable to postfire management practices because such practices may influence forest dynamics and aquatic systems for decades to centuries. Thus, there is an increasing need to evaluate the effect of postfire treatments from the perspective of ecosystem recovery. We examined, via the published literature and our collective experience, the ecological effects of some common postfire treatments. Based on this examination, promising postfire restoration measures include retention of large trees, rehabilitation of firelines and roads, and, in some cases, planting of native species. The following practices are generally inconsistent with efforts to restore ecosystem functions after fire: seeding exotic species, livestock grazing, placement of physical structures in and near stream channels, ground-based postfire logging, removal of large trees, and road construction. Practices that adversely affect soil integrity, persistence or recovery of native species, riparian functions, or water quality generally impede ecological recovery after fire. Although research provides a basis for evaluating the efficacy of postfire treatments, there is a continuing need to increase our understanding of the effects of such treatments within the context of societal and ecological goals for forested public lands of the western United States.     

Modelling the forest carbon budget of a Mediterranean region through the integration of ground and satellite data

This paper introduces an innovative modelling strategy aimed at simulating the main terms of net forest carbon budget (net primary production, NPP and net ecosystem exchange, NEE) in Tuscany (Central Italy). The strategy is based on the preliminary calibration and application of parametric and bio-geochemical models (C-Fix and BIOME-BGC, respectively), which simulate the behaviour of forest ecosystems close to equilibrium condition (climax). Next, the ratio of actual over-potential tree volume is computed as an indicator of ecosystem distance from climax and is combined with the model outputs to estimate the NPP and NEE of real forests. The per-pixel application of the new modelling strategy was made possible by the collection of several data layers (maps of forest type and volume, daily meteorological data and monthly normalized difference vegetation index (NDVI) images for the years 1999–2003) which served to characterize the eco-climatic and forest features of the region. The obtained estimates of forest NPP and NEE were evaluated against ground measurements of accumulated woody biomass and net carbon exchange. The results of these experiments testify the good potential of the proposed strategy and indicate some problem areas which should be the subject of future research.     

Investigations into a plankton population model: Mortality and its importance in climate change scenarios

The potential for marine plankton ecosystems to influence climate by the production of dimethylsulphide (DMS) has been an important topic of recent research into climate change. Several General Circulation Models, used to predict climate change, have or are being modified to include interactions of ecosystems with climate. Climate change necessitates that parameters within ecosystem models must change during long-term simulations, especially mortality parameters that increase as organisms are pushed toward the boundaries of their thermal tolerance. Changing mortality parameters can have profound influences on ecosystem model dynamics. There is therefore a pressing need to understand the influence of varying mortality parameters on the long-term behaviour of ecosystem models. This work examines the sensitivity of a model of DMS production by marine ecosystems to variations in three linear mortality coefficients. Significant differences in behaviour are observed, and we note the importance of these results in formulating ecosystem models for application in simulations of climate change.     

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.     

Modelling the impact of flooding stress on the growth performance of woody species using fuzzy logic

Among the driving processes responsible for riparian forest dynamics the species-specific impact of flooding on the development of woody plants plays a key role—particularly for lowland rivers. Only a few of the forest succession models currently in use incorporate the flooding stress response of trees. This situation is mainly due to the incomplete investigation of the flooding tolerance processes and the related abiotic and biotic factors. In an attempt to use the wide-ranging but still rather vague knowledge available on flooding stress, the research presented in this paper proposes an approach to model tree response to flooding using the fuzzy set theory. The model is illustrated for the case of central European species. Flooding stress response to the abiotic factors of duration, depth and frequency of flooding differs according to five flooding tolerance classes and is expressed by means of a growth factor that limits optimal tree growth. We show that existing fuzzy set theory is able to generate and calibrate a flood stress response model which in turn can be incorporated into more complex forest succession models adapted to riparian areas.     

Regression analysis of forest damage by marginal models for correlated ordinal responses

Studies on forest damage generally cannot be carried out by common regression models, for two main reasons: Firstly, the response variable, damage state of trees, is usually observed in ordered categories. Secondly, responses are often correlated, either serially, as in a longitudinal study, or spatially, as in the application of this paper, where neighbourhood interactions exist between damage states of spruces determined from aerial pictures. Thus so-called marginal regression models for ordinal responses, taking into account dependence among observations, are appropriate for correct inference. To this end we extend the binary models of Liang and Zeger (1986) and develop an ordinal GEEI model, based on parametrizing association by global cross-ratios. The methods are applied to data from a survey conducted in Southern Germany. Due to the survey design, responses must be assumed to be spatially correlated. The results show that the proposed ordinal marginal regression models provide appropriate tools for analysing the influence of covariates, that characterize the stand, on the damage state of spruce.     

A model for wildfire prevention planning in game resources

The high incidence of hunting activity and forest fires in different ecosystems (particularly in Mediterranean ecosystems) requires a model, which allows for the comprehensive management of hunting resources and estimating the potential damage caused by this type of disturbance. This paper proposes a model for evaluating the socio-economic effects of forest fires on hunting. Its cornerstone lies in evaluating hunting resource availability for each ecosystem within its territorial mosaic. Each game management unit (GMU) is identified by vegetation structure and habitat type. It presents a novel approach in which the economic value of each game management unit is linked to potential forest fire damages. The effect a forest fire has on an entire ecosystem depends on the intensity of its flames. A sample study was undertaken in the province of Huelva in Andalusia (southern Spain). The socio-economic hunting vulnerability of the province of Huelva was 45,188,000€. The results obtained confirmed the need for an economic appraisal of non-forest products in the forest and other woodland areas. Geographic Information System increases the flexibility and simplicity of our methodology which permits immediate extrapolation to other agroforestry territories.     

Modeling seasonal course of carbon fluxes and evapotranspiration in response to low temperature and moisture in a boreal Scots pine ecosystem

Environmental conditions act above and below ground, and regulate carbon fluxes and evapotranspiration. The productivity of boreal forest ecosystems is strongly governed by low temperature and moisture conditions, but the understanding of various feedbacks between vegetation and environmental conditions is still unclear. In order to quantify the seasonal responses of vegetation to environmental factors, the seasonality of carbon and heat fluxes and the corresponding responses for temperature and moisture in air and soil were simulated by merging a process-based model (CoupModel) with detailed measurements representing various components of a forest ecosystem in Hyytiälä, southern Finland. The uncertainties in parameters, model assumptions, and measurements were identified by generalized likelihood uncertainty estimation (GLUE). Seasonal and diurnal courses of sensible and latent heat fluxes and net ecosystem exchange (NEE) of CO₂ were successfully simulated for two contrasting years. Moreover, systematic increases in efficiency of photosynthesis, water uptake, and decomposition occurred from spring to summer, demonstrating the strong coupling between processes. Evapotranspiration and NEE flux both showed a strong response to soil temperature conditions via different direct and indirect ecosystem mechanisms. The rate of photosynthesis was strongly correlated with the corresponding water uptake response and the light use efficiency. With the present data and model assumptions, it was not possible to precisely distinguish the various regulating ecosystem mechanisms. Our approach proved robust for modeling the seasonal course of carbon fluxes and evapotranspiration by combining different independent measurements. It will be highly interesting to continue using long-term series data and to make additional tests of optional stomatal conductance models in order to improve our understanding of the boreal forest ecosystem in response to climate variability and environmental conditions.     

生物环境因子对树干呼吸时空变异的影响

树干呼吸是解释森林生态系统生产力变化的关键过程之一.测定树干呼吸速率,理解其生物环境调控机制,有助于构建森林碳循环模型,提供森林碳收支的估测精度.本文比较分析了树干呼吸3种测定方法,指出活体测定法与质量平衡方法的结合使用,可以更深入地进行树十呼吸机理研究.针对树十呼吸速率时空变异,着重探讨温度、树干液流的重要影响机制,并比较分析了不同森林生态系统的维持呼吸年通量,维持呼吸年通量与林龄、维度、年均温和降水量呈显著线性相关.表4参84     

Carbon sequestration of black locust forests in the Yellow River Delta region,China

The Yellow River Delta region in China is a land area of 1,200,000 ha with rich natural resources. Adverse environmental conditions, such as low rainfall and high salinity, promote the dominance of black locust trees for afforestation. With the increase of CO₂ in the atmosphere, this forest and others throughout the world have become valued for their ability to sequester and store carbon. Forests store carbon in aboveground biomass (i.e. trees), belowground biomass (i.e. roots), soils and standing litter crop (i.e. forest floor and coarse woody debris). There are well-developed methods to sample forest ecosystems, including tree inventories that are used to quantify carbon in aboveground tree biomass. Such inventories are used to estimate the types of roundwood products removed from the forest during harvesting. Based on standard plot inventories and stem analyses, carbon sequestration estimates of trees were 222.41 t ha^?1 for the Yellow River Delta region accounted for 67.12% of the whole forest. Similarly, carbon storage by herbaceous matter and soil was 0.50 and 50.34 t ha^?1, respectively. The results suggest that carbon sequestration in the forest ecosystem was performed by most of the forest, which plays an increasingly important role in sequestering carbon as the stand grows.     

A new scheme for initializing process-based ecosystem models by scaling soil carbon pools

Process-based ecosystem models are useful tools, not only for understanding the forest carbon cycle, but also for predicting future change. In order to apply a model to simulate a specific time period, model initialization is required. In this study, we propose a new scheme of initialization for forest ecosystem models, which we term a “slow-relaxation scheme”, that entails scaling of the soil carbon and nitrogen pools slowly during the spin-up period. The proposed slow-relation scheme was tested with the CENTURY version 4 ecosystem model. Three different combinations of scaled soil pools were also tested, and compared to the results from a fast-relaxation regime. The fast-relaxation of soil pools produced unstable, transient model behaviour whereas slow-relaxation overcame this instability. This approach holds promise for initializing ecosystem models, and for starting simulations with more realistic initial conditions.     

The Future of Scattered Trees in Agricultural Landscapes

Abstract: Mature trees scattered throughout agricultural landscapes are critical habitat for some biota and provide a range of ecosystem services. These trees are declining in intensively managed agricultural landscapes globally. We developed a simulation model to predict the rates at which these trees are declining, identified the key variables that can be manipulated to mitigate this decline, and compared alternative management proposals. We used the initial numbers of trees in the stand, the predicted ages of these trees, their rate of growth, the number of recruits established, the frequency of recruitment, and the rate of tree mortality to simulate the dynamics of scattered trees in agricultural landscapes. We applied this simulation model to case studies from Spain, United States, Australia, and Costa Rica. We predicted that mature trees would be lost from these landscapes in 90–180 years under current management. Existing management recommendations for these landscapes—which focus on increasing recruitment—would not reverse this trend. The loss of scattered mature trees was most sensitive to tree mortality, stand age, number of recruits, and frequency of recruitment. We predicted that perpetuating mature trees in agricultural landscapes at or above existing densities requires a strategy that keeps mortality among established trees below around 0.5% per year, recruits new trees at a rate that is higher than the number of existing trees, and recruits new trees at a frequency in years equivalent to around 15% of the maximum life expectancy of trees. Numbers of mature trees in landscapes represented by the case studies will decline before they increase, even if strategies of this type are implemented immediately. This decline will be greater if a management response is delayed.     

An inverse ecosystem model of year-to-year variations with first order approximation to the annual mean fluxes

Ecosystems exhibit nonlinear dynamics that are often difficult to capture in models. Consequently, linearization is commonly applied to remove some of the uncertainties associated with the nonlinear terms. However, since the true model is unknown and the operating point to linearize the model about is uncertain, developing linear ecosystems models is non-trivial. To develop a linear ecosystem model, we assume that the annual mean state of an ecosystem is a minor bias from the long-term mean state. A first order approximation inverse model to govern the year-to-year dynamics of ecosystems whose characteristic time scales are less than 1 year is developed, through theoretically formulation, on the basis of steady state analysis, time scale separation and nondimensionalization. The approach is adept at predicting year-to-year variations and to tracking system response to changes in environmental drivers when compared to data generated with a standard nonlinear NPZD model.     

Evaluation of ecosystem health for regional development in the southwestern Beijing, China

Ecosystem health assessment is one of the most important issues in regional ecological quality and safety studies. It also has a great significance to ecological conservation and regional development. This study focused on assessing the health status of forest, agriculture and urban ecosystems in the southwestern Beijing, China, including the Fangshan and Fengtai Districts. Based on field surveys and data collection, an assessment index system containing the vigor, organization and resilience factors was developed to measure the ecosystem health. Each index was scored from 1 to 5, representing five levels that contribute to the whole ecosystem health. The analytic hierarchy process (AHP) method was used to measure the weights of each index and three factors, and thus an overall score for a certain ecosystem was calculated. The results show that the forest ecosystem in the Fangshan District had higher health value than the Fengtai District, while the urban ecosystem had a slightly lower value in the Fangshan District than the Fengtai District. Both districts show lower resilience values in forest and urban ecosystems. Maintaining the ecosystem health will definitely benefit the long-term development of two districts. This study suggested that an approach for assessing the regional ecosystem health could be further developed to address spatial and synergy relationships between ecosystems and the three health factors.     

A tree and climate assessment tool for modelling ecosystem response to climate change

Understanding how vulnerable forest ecosystems are to climate change is a key requirement if sustainable forest management is to be achieved. Modelling the response of species in their regeneration niche to phenological and biophysical processes that are directly influenced by climate is one method for achieving this understanding. A model was developed to investigate species resilience and vulnerability to climate change within its fundamental-regeneration niche. The utility of the developed model, tree and climate assessment (TACA), was tested within the interior Douglas-fir ecosystem in south-central British Columbia. TACA modelled the current potential tree species composition of the ecosystem with high accuracy and modelled significant responses amongst tree species to climate change. The response of individual species suggests that the studied ecosystem could transition to a new ecosystem over the next 100 years. TACA showed that it can be an effective tool for identifying species resilience and vulnerability to changes in climate within the most sensitive stage of development, the regeneration phase. The TACA model was able to identify the degree of change in phenological and biophysical variables that control tree establishment, growth and persistence. The response to changes in one or more of these variables resulted in changes in the climatic suitability of the ecosystem for species and enabled a measure of vulnerability to be quantified. TACA could be useful to forest managers as a decision support tool for adaptation actions and by researchers interested in modelling stand dynamics under climate change.