Estimates of species- and ecosystem-level respiration of woody stems along an elevational gradient in the Luquillo Mountains, Puerto Rico

We measured CO₂ efflux from stems of seven subtropical tree species situated along an elevational gradient in the Luquillo Mountains, Puerto Rico and scaled these measurements up to the landscape level based on modeled and empirical relations. The most important determinants of ecosystem stem respiration were species composition and stem temperature. At a species scale, measured CO₂ efflux per unit bole surface area at a given temperature was highest in the early successional species Cecropia schreberiana and lowest in species that inhabit high elevations such as Micropholis garciniifolia and Tabebuia rigida. Carbon dioxide efflux rates followed a diel pattern that lagged approximately 6 h behind changes in sapwood temperatures. At an ecosystem scale, our simulation model indicates a decreasing trend of stem respiration rates with increasing elevation due to shifts in species composition, lower temperatures and reductions in branch surface area. The highest estimated stem respiration rates were present in the lowland tabonuco forest type and the lowest rates were present in the elfin forest type (mean 7.4 and 2.1 Mg C ha⁻¹ yr⁻¹, respectively). There was slight temperature-induced seasonal variation in simulated stem respiration rates at low elevations, with a maximum difference of 19% between the months of February and July. Our results coincide well with those of Odum and Jordan [Odum, H.T., Jordan, C.F., 1970. Metabolism and evapotranspiration of the lower forest in a giant plastic cylinder. In: Odum, H.T., Pigeon, R.F. (Eds.), A Tropical Rain Forest: A Study of Irradiation and Ecology at El Verde, Puerto Rico. U.S. Atomic Energy Commission, Oak Ridge, TN, pp. I165–I189] for the tabonuco forest type and extend their work by presenting estimates and spatial patterns of woody tissue respiration for the entire mountain rather than for a single forested plot.     

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.     

How humans shape wolf behavior in Banff and Kootenay National Parks, Canada

This paper describes the conceptualization and implementation of an agent-based model to investigate how varying levels of human presence could affect elements of wolf behavior, including highway crossings; use of areas in proximity to roads and trails; size of home ranges; activities, such as hunting, patrolling, resting, and feeding pups; and survival of individuals in Banff and Kootenay National Parks, Canada. The model consists of a wolf module as the primary component with five packs represented as cognitive agents, and grizzly bear, elk, and human modules that represent dynamic components of the environment. A set of environmental data layers was used to develop a friction model that serves as a base map representing the landscape over which wolves moved. A decision model was built to simulate the sequence of wolf activities. The model was implemented in a Java Programming Language using RePast, an agent-based modeling library. Six months of wolf activities were simulated from April 16 to October 15 (i.e., a season coherent with regard to known wolf behaviors), and calibrated with GPS data from wolf radiocollars (n = 15) deployed from 2002 to 2004. Results showed that the simulated trajectories of wolf movements were correlated with the observed trajectories (Spearman's rho 0.566, P < 0.001); other critical behaviors, such as time spent at the den and not traveling were also correlated. The simulations revealed that wolf movements and behaviors were noticeably affected by the intensity of human presence. The packs’ home ranges shrank and wolves crossed highways less frequently with increased human presence. In an extreme example, a wolf pack whose home range is traversed by a high-traffic-volume highway was extirpated due to inability to hunt successfully under a scenario wherein human presence levels were increased 10-fold. The modeling prototype developed in this study may serve as a tool to test hypotheses about human effects on wolves and on other mammals, and guide decision-makers in designing management strategies that minimize impacts on wolves and on other species functionally related to wolves in the ecosystem.     

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.     

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.     

Sensitivity of stand dynamics to grazing in mixed Pinus sylvestris and Quercus pubescens forests: A modelling study

Only recently, studies of forest succession have started to include the effects of browsing by wild or domestic ungulates. We aim to contribute to this topic by analysing the influence of goat grazing on the long-term coexistence of Scots pine (Pinus sylvestris L.) and pubescent oak (Quercus pubescens Willd.) in the low-elevation forests of an inner-Alpine dry valley. The forest gap model ForClim was first adapted to these site conditions by examining the site-dependent sensitivity of the model with regard to the species-specific parameterisation of the drought tolerance as well as the light demand of establishing and adult trees. In a second step, the behaviour of the model was investigated with respect to different grazing intensities and species-specific browsing susceptibilities. The last step was the application of a grazing scenario based on forest history, with 150 years of heavy browsing (by goats) at the beginning of the simulated forest succession, followed by less intensive grazing pressure.     

A Bayesian approach to multi-source forest area estimation

In efforts such as land use change monitoring, carbon budgeting, and forecasting ecological conditions and timber supply, there is increasing demand for regional and national data layers depicting forest cover. These data layers must permit small area estimates of forest area and, most importantly, provide associated error estimates. This paper presents a model-based approach for coupling mid-resolution satellite imagery with plot-based forest inventory data to produce estimates of probability of forest and associated error at the pixel-level. The proposed Bayesian hierarchical model provides access to each pixel’s posterior predictive distribution allowing for a highly flexible analysis of pixel and multi-pixel areas of interest. The paper presents a trial using multiple dates of Landsat imagery and USDA Forest Service Forest Inventory and Analysis plot data. The results describe the spatial dependence structure within the trial site, provide pixel and multi-pixel summaries of probability of forest land use, and explore discretization schemes of the posterior predictive distributions to forest and non-forest classes. Model prediction results of a holdout set analysis suggest the proposed model provides high classification accuracy, 88%, for the trial site.

南岳森林土壤的研究-Ⅲ.土壤颗粒组成

本文介绍了南岳森林土壤颗粒组成状况及其与环境间的关系,以及土壤的颗粒组成状况对其理化性质的影响。研究表明,南岳土壤质地主要为粉壤土、面砂土和壤粘土等。土壤质地的差异主要受植被类型、植物生长状况、放牧严重与否的影响,其次是受坡度和气候条件的影响。土壤颗粒组成状况显著地影响土壤的速效磷、速效钾、浸水容重、吸湿率、烧失率、pH值等,对土壤紧实度、有机质、碱解氮也有一定的影响。     

Multi-stand Forest Management under a Climatic Risk: Do Time and Risk Preferences Matter?

We propose a stochastic dynamic programming framework to model the management of a multi-stand forest under climate risk (strong wind occurrence). The preferences of the forest-owner are specified by a non-expected utility in order to separately analyze intertemporal substitution and risk aversion effects. A numerical method is developed to characterize the optimal forest management policies and the optimal consumption-saving strategy. The stochastic dynamic programming framework is applied to a non-industrial private forest-owner located in North-East of France. We show that the optimal decisions both depend upon risk and time preferences. The authors would like to thank participants at the international conference on Economics of Sustainable Forest Management in Toronto, at the PARIS 1 seminar on Environmental and Natural Resource Economics, at the 2004 Applied Microeconomics Conference in Lille and at the 13th annual conference of the European Association of Environmental and Resource Economists at Budapest.