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.     

Biogeochemical model (BGC-ES) and its basin-level application for evaluating ecosystem services under forest management practices

It is important for humans to live in harmony with ecosystems. Evaluation of ecosystem services (ES) may be helpful in achieving this objective. In Japan, forest ecosystems need to be re-evaluated to prevent their degradation due to lack of forest management.In order to evaluate the effects of forest management on forest ES, we developed a process-based biogeochemical model to estimate water, carbon, and nitrogen cycles in forest ecosystems (BGC-ES). This model consists of four submodels: biomass, water cycle, carbon-nitrogen (CN) cycles, and forest management. The biomass submodel can calculate growth of forest biomass under forest managements.Several parameters of the model were calibrated using data from observations of evapotranspiration flux and quality of stream flow in forests. The model results were compared with observations of runoff water from a dam catchment site and with carbon flux observations.Our model was coupled with a basin-level GIS database of forests. Evaluations under various forest management scenarios were carried out for forests in a basin contained in the Ise Bay basin (Chubu region, Japan), where plantations (artificial forests) seemed to have degraded from poor forest management.Comparing our simulation results with those of forests without management in the basin, we found that the amounts of absorbed carbon and runoff were larger in managed forests. In addition, the volume of harvested timber was larger and its quality (diameter) was better in managed forests. Changes of ES within the various scenarios were estimated for their economic value and were compared with the cost of forest management.     

Expert views on sustainability and technology implementation

The role of non-timber forest products in sustaining rural economies of the southern African region has been underestimated because of inadequate policy recognition. As a result, factors affecting the sustainability of these important resources are being undermined. The aim of the paper is to examine trade in two selected NTFPs and implications for sustaining the resource base in Zimbabwe and South Africa. In eastern Zimbabwe, baobab (Adansonia digitata) bark is harvested for craft purposes, but in danger of destruction in the short term as a result of harvesting and trade arrangements. Unless appropriate harvesting and marketing mechanisms including harvesting cycles and adaptive management are adopted, the baobabs and livelihoods of humans will be threatened in the next decade. For wood products from communal woodlands in the South African study, uncontrolled trade poses danger to sustaining the natural woodlands. In both case studies, the role of non-resident NTFP dealers is a source of inevitable threat in promoting sustainable harvesting and trade. Market forces of demand and supply factors are identified as opportunities or threats and presented in a conceptualised framework. Additionally, the NTFP sector management will need to include opportunistic improvement of small-scale agropastoralism.     

Modelling carbon and nitrogen dynamics in forest ecosystems of Central Russia under different climate change scenarios and forest management regimes

The individual-based stand-level model EFIMOD was used for large-scale simulations using standard data on forest inventories as model inputs. The model was verified for the case-study of field observations, and possible sources of uncertainties were analysed. The approach developed kept the ability for fine-tuning to account for spatial discontinuity in the simulated area. Several forest management regimes were simulated as well as forest wildfires and climate changes. The greatest carbon and nitrogen accumulations were observed for the regime without cuttings. It was shown that cuttings and wildfires strongly influence the processes of carbon and nitrogen accumulations in both soil and forest vegetation. Modelling also showed that the increase in annual average temperatures resulted in the partial relocation of carbon and nitrogen stocks from soil to plant biomass. However, forest management, particularly harvesting, has a greater effect on the dynamics of forest ecosystems than the prescribed climate change.     

Using land as a control variable in density-dependent bioeconomic models

The bioeconomic analysis of endangered species without consumptive values can be problematic when analysed with density-dependent models that assume a fixed environment size. Most bioeconomic models use harvest as a control variable, yet when modelling non-harvestable species, frequently the only variable under control of conservationists is the quantity of habitat to be made available. The authors explore the implications of this in a model developed to analyse the potential population recovery of New Zealand’s yellow-eyed penguin. The penguin faces severe competition with man for the terrestrial resources required for breeding and has declined in population to perilously low levels. The model was developed to estimate the land use required for recovery and preservation of the species and to compare the results to current tourism-driven conservation efforts. It is demonstrated that land may serve as a useful control variable in bioeconomic models and that such a model may be useful for determining whether sufficient incentives exist to preserve a species. However, the model may generate less useful results for providing a specific estimate of the optimal allocation of land to such a species.     

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.     

Review and comparison of methods to study the contribution of variables in artificial neural network models

Convinced by the predictive quality of artificial neural network (ANN) models in ecology, we have turned our interests to their explanatory capacities. Seven methods which can give the relative contribution and/or the contribution profile of the input factors were compared: (i) the ‘PaD’ (for Partial Derivatives) method consists in a calculation of the partial derivatives of the output according to the input variables; (ii) the ‘Weights’ method is a computation using the connection weights; (iii) the ‘Perturb’ method corresponds to a perturbation of the input variables; (iv) the ‘Profile’ method is a successive variation of one input variable while the others are kept constant at a fixed value; (v) the ‘classical stepwise’ method is an observation of the change in the error value when an adding (forward) or an elimination (backward) step of the input variables is operated; (vi) ‘Improved stepwise a’ uses the same principle as the classical stepwise, but the elimination of the input occurs when the network is trained, the connection weights corresponding to the input variable studied is also eliminated; (vii) ‘Improved stepwise b’ involves the network being trained and fixed step by step, one input variable at its mean value to note the consequences on the error. The data tested in this study concerns the prediction of the density of brown trout spawning redds using habitat characteristics. The PaD method was found to be the most useful as it gave the most complete results, followed by the Profile method that gave the contribution profile of the input variables. The Perturb method allowed a good classification of the input parameters as well as the Weights method that has been simplified but these two methods lack stability. Next came the two improved stepwise methods (a and b) that both gave exactly the same result but the contributions were not sufficiently expressed. Finally, the classical stepwise methods gave the poorest results.     

Solving multidimensional bioeconomic problems with singular-perturbation reduction methods: Application to managing pest resistance to pesticidal crops

We investigate the application of ‘singular-perturbation’ reduction methods from the dynamical-systems literature to solve continuous-time multidimensional bioeconomic models resulting from integrating economics with increasingly complex biological structures. These methods reduce multidimensional solution space to the lower-dimensional subspace confining long-term dynamics. They arise naturally in problems with state variables evolving on widely disparate time scales. In particular, we demonstrate how the methods reduce the solution space of a linear-control specification—characterized by two state variables adjusting at widely disparate rates—to a single differential equation in the slow variable. All other system variables are determined by algebraic equations. We apply singular-perturbation methods to investigate the optimal management of pest resistance to pesticidal crops. The pest population evolves on a fast-time scale, while the population's genetic composition evolves on a slow-time scale. In comparison with past work, we can more fully characterize the continuous-time dynamics associated with a complex genetic specification.     

Integrated ecological models: simulation of socio-cultural constraints on ecological dynamics

We suggest that general systems theory provides a common philosophical basis for dialog between ecological and social scientists interested in studying the reciprocal interactions of humans and their environment. We (1) provide a synopsis of the ‘systems approach' as viewed from the biological and social sciences, respectively; (2) develop a conceptual framework for the explicit linking of ecological and social variables, and (3) draw upon game theoretic results of the Prisoner's Dilemma to represent human decision-making quantitatively in a model that simulates the tragedy of the commons. The model consists of 5 submodels that represent the ‘observers world' and each of 4 ‘participant's worlds.' The observer's-world represents the decision processes, either Optimize or Tit-for-Tat, by which each of 2 users decides to add or remove animals. The 4 perceived worlds represent hypothetical situations in which (1) persons A and B both add an animal; (2) A adds and B does not; (3) B adds and A does not, and (4) neither A nor B add an animal. Simulation results indicate that net worth of the community and of each person individually under Tit-for-Tat is more than double the net worth attained under Optimize. Replacement of the static payoff matrix assumed in game theory with a dynamic quantitative model illustrates how ‘norm-based' approaches to ecosystem management can outperform optimizing approaches based on predicted outcomes. Although ‘soft systems' techniques may better help decision-makers reach norm-based agreements on ecosystem management, quantitative models have more explanatory value, and if developed sufficiently such models could incorporate complex social dimensions that would enhance further their explanatory value.     

A Bayesian strategy for combining predictions from empirical and process-based models

We present a strategy for using an empirical forest growth model to reduce uncertainty in predictions made with a physiological process-based forest ecosystem model. The uncertainty reduction is carried out via Bayesian melding, in which information from prior knowledge and a deterministic computer model is conditioned on a likelihood function. We used predictions from an empirical forest growth model G-HAT in place of field observations of aboveground net primary productivity (ANPP) in a deciduous temperate forest ecosystem. Using Bayesian melding, priors for the inputs of the process-based forest ecosystem PnET-II were propagated through the model, and likelihoods for the PnET-II output ANPP were calculated using the G-HAT predictions. Posterior distributions for ANPP and many PnET-II inputs obtained using the G-HAT predictions largely matched posteriors obtained using field data. Since empirical growth models are often more readily available than extensive field data sets, the method represents a potential gain in efficiency for reducing the uncertainty of process-based model predictions when reliable empirical models are available but high-quality data are not.     

Threshold management in a coupled economic–ecological system

Economic analysis of optimal ecosystem management in the presence of a threshold has typically ignored the potential for induced behavioral responses. This paper contributes to the literature on non-convex ecosystem management by considering the implications of a particular behavioral response in a regional economy – that of amenity-led growth – to changes in ecosystem services generated by a lake ecosystem subject to a eutrophication threshold. The essential policy challenge is to achieve optimal levels of lake nutrients and urbanization given that improvements to water quality will induce additional migration and urbanization in the region with attendant ecological impacts. We show that policies that ignore the recursive relationship between urbanization and water quality unintentionally exacerbate boom-bust cycles of regional growth and decline and risk pushing the system towards long-run economic decline. In contrast, the optimal policy accounts for the behavioral feedbacks to improved ecosystem services, and balances regional growth and ecological degradation.     

Modeling the forest transition: forest scarcity and ecosystem service hypotheses.

An historical generalization about forest cover change in which rapid deforestation gives way over time to forest restoration is called "the forest transition." Prior research on the forest transition leaves three important questions unanswered: (1) How does forest loss influence an individual landowner's incentives to reforest? (2) How does the forest recovery rate affect the likelihood of forest transition? (3) What happens after the forest transition occurs? The purpose of this paper is to develop a minimum model of the forest transition to answer these questions. We assume that deforestation caused by landowners' decisions and forest regeneration initiated by agricultural abandonment have aggregated effects that characterize entire landscapes. These effects include feedback mechanisms called the "forest scarcity" and "ecosystem service" hypotheses. In the forest scarcity hypothesis, forest losses make forest products scarcer, which increases the economic value of forests. In the ecosystem service hypothesis, the environmental degradation that accompanies the loss of forests causes the value of ecosystem services provided by forests to decline. We examined the impact of each mechanism on the likelihood of forest transition through an investigation of the equilibrium and stability of landscape dynamics. We found that the forest transition occurs only when landowners employ a low rate of future discounting. After the forest transition, regenerated forests are protected in a sustainable way if forests regenerate slowly. When forests regenerate rapidly, the forest scarcity hypothesis expects instability in which cycles of large-scale deforestation followed by forest regeneration repeatedly characterize the landscape. In contrast, the ecosystem service hypothesis predicts a catastrophic shift from a forested to an abandoned landscape when the amount of deforestation exceeds the critical level, which can lead to a resource degrading poverty trap. These findings imply that incentives for forest conservation seem stronger in settings where forests regenerate slowly as well as when decision makers value the future.     

Patch-Occupancy Modeling as a Method for Monitoring Changes in Forest Floristics: a Case Study in Southeastern Australia

Abstract:  The ability to monitor changes in biodiversity is fundamental to demonstrating sustainable management practices of natural resources. Disturbance studies generally focus on responses at the plot scale, whereas landscape-scale responses are directly relevant to the development of sustainable forest management. Modeling changes in occupancy is one way to monitor landscape-scale responses. We used understory vegetation data collected over 16 years from a long-term study site in southeastern Australia. The site was subject to timber harvesting and frequent prescribed burning. We used occupancy models to examine the impacts of these disturbances on the distribution of 50 species of plants during the study. Timber harvesting influenced the distribution of 9 species, but these effects of harvesting were generally lost within 14 years. Repeated prescribed fire affected 22 species, but the heterogeneity of the burns reduced the predicted negative effects. Twenty-two species decreased over time independent of treatment, and only 5 species increased over time. These changes probably represent a natural response to a wildfire that occurred in 1973, 13 years before the study began. Occupancy modeling is a useful and flexible technique for analyzing monitoring data and it may also be suitable for inclusion within an adaptive-management framework for forest management.     

Interactive Effects of Harvest and Deer Herbivory on the Population Dynamics of American Ginseng

Abstract:  Few demographic models for any species consider the role of multiple, interacting ecological threats. Many forest herbs are heavily browsed by white-tailed deer ( Odocoileus virginianus ) and a number of these are also harvested for the medicinal, floral, or horticultural trades. Previous studies of the viability of American ginseng ( Panax quinquefolius ) have separately examined the effects of harvesting and deer herbivory. We followed individually marked ginseng plants in 6 populations for 8 years and documented deer browse levels, conducted helicopter surveys to estimate the deer herd size, and documented 2 ginseng harvests. We used this long-term data set to develop a stochastic demographic model that quantified the separate and interactive role of these threats to ginseng viability. Although harvesting and deer herbivory negatively affected ginseng population growth, their effects were not additive. Deer herbivory negatively affected population growth in the absence but not in the presence of harvesting. Life table response experiments revealed that in the presence of harvesting, deer herbivory had some positive effects on vital rates because browsed plants were less apparent to harvesters. Ginseng populations that were harvested responsibly (i.e., planting seeds from harvested individuals) had higher growth rates than those that were harvested irresponsibly. We concluded that both deer populations and harvesting must be managed to ensure sustainable populations of American ginseng. Our findings underscore the importance of long-term monitoring to assess threats to viability and the need for a broad ecological understanding of the complexity of ecosystem management.     

Traditional Ecological Knowledge and Practice for Edible Wild Plants: Biodiversity Use by the Rarámuri,in the Sirerra Tarahumara,Mexico

The Rarámuri who live in the Sierra Tarahumara of Chihuahua State, Mexico have developed local knowledge and harvesting strategies for edible wild plants that have the effect of conserving the biodiversity of their forest ecosystem. This paper presents the results of ethnobotanical research undertaken in the community of Basìhuare in the Sierra Tarahumara, to provide details on some practical aspects of the Raráamuri worldview regarding interconnections between people and their environment. This traditional philosophy forms the basis for the use of edible wild plants and the harvesting strategies practiced in Basìhuare, such as selective harvesting, environmental modification and domestication. These activities provide the opportunity for harvesters to monitor the landscape and the plant resources that occur on the land, as well as present a setting for the communication and exchange of traditional ecological knowledge. However, Rarámuri harvesting practices are under stress because of increased external pressures from commercial timber extraction and other development. We discuss the state of traditional ecological knowledge and its transmission in the context of development activities in the region. The key to sustainability in the Sierra Tarahumara may be the maintenance of traditional management practices for edible wild plants, and other nontimber forest products, that lead to the conservation of biodiversity by creating patchiness and renewing the plant cover on the land.     

Improving multi-site benefit functions via Bayesian model averaging: A new approach to benefit transfer

A benefit function transfer obtains estimates of willingness-to-pay (WTP) for the evaluation of a given policy at a site by combining existing information from different study sites. This has the advantage that more efficient estimates are obtained, but it relies on the assumption that the heterogeneity between sites is appropriately captured in the benefit transfer model. A more expensive alternative to estimate WTP is to analyze only data from the policy site in question while ignoring information from other sites. We make use of the fact that these two choices can be viewed as a model selection problem and extend the set of models to allow for the hypothesis that the benefit function is only applicable to a subset of sites. We show how Bayesian model averaging (BMA) techniques can be used to optimally combine information from all models.The Bayesian algorithm searches for the set of sites that can form the basis for estimating a benefit function and reveals whether such information can be transferred to new sites for which only a small data set is available. We illustrate the method with a sample of 42 forests from U.K. and Ireland. We find that BMA benefit function transfer produces reliable estimates and can increase about 8 times the information content of a small sample when the forest is ‘poolable’.     

Shifting cultivation, forest fallow, and externalities in ecosystem services: Evidence from the Eastern Amazon

This study examines the value of fallow ecosystem services in shifting cultivation, including hydrological externalities that may affect other farms. Using farm-level survey data from the Brazilian Amazon, I estimate a production function to assess the value of forest fallow and test whether it provides local externalities to agricultural production. Soil quality controls, instrumental variables, and spatial econometric approaches help address endogeneity issues. I use GIS data on external forest cover at the farm level and model the hydrological externality as an upstream-to-downstream process. The estimated parameters indicate that fallow contributes significantly to productivity both on farm and downstream. In addition, most farms allocate sufficient land to fallow, accounting for both the value of hydrological spillovers and the opportunity cost of land left out of cultivation. These results suggest that farming communities may have some self-interest in preserving forest cover locally—a finding that may bolster policy efforts aimed at conserving tropical forests for their global public goods.     

Modelling forest management within a global vegetation model—Part 1: Model structure and general behaviour

This article describes a new forest management module (FMM) that explicitly simulates forest stand growth and management within a process-based global vegetation model (GVM) called ORCHIDEE. The net primary productivity simulated by ORCHIDEE is used as an input to the FMM. The FMM then calculates stand and management characteristics such as stand density, tree size distribution, tree growth, the timing and intensity of thinnings and clear-cuts, wood extraction and litter generated after thinning. Some of these variables are then fed back to ORCHIDEE. These computations are made possible with a distribution-based modelling of individual tree size. The model derives natural mortality from the relative density index (rdi), a competition index based on tree size and stand density. Based on the common forestry management principle of avoiding natural mortality, a set of rules is defined to calculate the recurrent intensity and frequency of forestry operations during the stand lifetime. The new-coupled model is called ORCHIDEE-FM (forest management).The general behaviour of ORCHIDEE-FM is analysed for a broadleaf forest in north-eastern France. Flux simulation throughout a forest rotation compare well with the literature values, both in absolute values and dynamics.Results from ORCHIDEE-FM highlight the impact of forest management on ecosystem C-cycling, both in terms of carbon fluxes and stocks. In particular, the average net ecosystem productivity (NEP) of 225 gC m⁻² year⁻¹ is close to the biome average of 311 gC m⁻² year⁻¹. The NEP of the “unmanaged” case is 40% lower, leading us to conclude that management explains 40% of the cumulated carbon sink over 150 years. A sensitivity analysis reveals 4 major avenues for improvement: a better determination of initial conditions, an improved allocation scheme to explain age-related decline in productivity, and an increased specificity of both the self-thinning curve and the biomass-diameter allometry.     

Multistate models for monitoring individual trees in permanent observation plots

This interdisciplinary research on forest ecosystems begins with some characteristics of ecosystems which are the basis for the derivation of statistical models for the development and vitality of trees. Several ecological problems which could be solved by longitudinal studies are mentioned. Statistical methods for the evaluation of the crowns of spruce trees (Picea abies Karst) in three permanent observation plots in Switzerland are described. In particular, the time-dependent proportional odds model and a transitional model are used. Through application of these multistate models the data give information on the dependence of an ordered categorical response variable on covariates characterizing the ecosystem. The response variable is observed through infrared aerial photographs. This monitoring system gives insight into the dynamic behaviour of the forest ecosystem. The need for more eco-systematically motivated statistical research using longitudinal studies is identified.