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.

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.     

Bridging the gap between ecophysiological and genetic knowledge to assess the adaptive potential of European beech

In this study we aimed to combine knowledge of the ecophysiology and genetics of European beech to assess the potential of this species to adapt to environmental change. Therefore, we performed field and experimental studies on the genetic and ecophysiological functioning of beech. This information was integrated through a coupled genetic–ecophysiological model for individual trees that was parameterized with information derived from our own studies or from the literature. Using the model, we evaluated the adaptive response of beech stands in two ways: firstly, through sensitivity analyses (of initial genetic diversity, pollen dispersal distance, heritability of selected phenotypic traits, and forest management, representing disturbances) and secondly, through the evaluation of the responses of phenotypic traits and their genetic diversity to four management regimes applied to 10 study plots distributed over Western Europe. The model results indicate that the interval between recruitment events strongly affects the rate of adaptive response, because selection is most severe during the early stages of forest development. Forest management regimes largely determine recruitment intervals and thereby the potential for adaptive responses. Forest management regimes also determine the number of mother trees that contribute to the next generation and thereby the genetic variation that is maintained. Consequently, undisturbed forests maintain the largest amount of genetic variation, as recruitment intervals approach the longevity of trees and many mother trees contribute to the next generation. However, undisturbed forests have the slowest adaptive response, for the same reasons.Gene flow through pollen dispersal may compensate for the loss in genetic diversity brought about by selection. The sensitivity analysis showed that the total genetic diversity of a 2 ha stand is not affected by gene flow if the pollen distance distribution is varied from highly left-skewed to almost flat. However, a stand with a prevailing short-distance gene flow has a more pronounced spatial genetic structure than stands with equal short- and long-distance gene flows. The build-up of a spatial genetic structure is also strongly determined by the recruitment interval. Overall, the modelling results indicate that European beech has high adaptive potential to environmental change if recruitment intervals are short and many mother trees contribute to the next generation.The findings have two implications for modelling studies on the impacts of climate change on forests. Firstly: it cannot be taken for granted that parameter values remain constant over a time horizon of even a few generations – this is particularly important for threshold values subject to strong selection, like budburst, frost hardiness, drought tolerance, as used in species area models. Secondly: forest management should be taken into account in future assessments, as management affects the rate of adaptive response and thereby the response on trees and forests to environmental change, and because few forests are unmanaged. We conclude that a coupled ecophysiological and quantitative genetic tree model is a useful tool for such studies.     

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

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

张家界国家森林公园地表水污染综合分析

随着旅游业的快速发展,张家界国家森林公园水环境保护、水污染治理及水资源利用问题已成为张家界旅游可持续发展中突出的问题.文章利用大量监测数据,对公园地表水污染状况进行模糊数学法综合评价,进行污染特征与污染规律分析,从而提出严格控制排污,科学规划水资源、严格控制景区客流量等对策及建议,以期为张家界国家森林公园水环境保护及张家界旅游业的持续健康发展提供决策参考.     

基于机器学习分类算法解析EIS数据的有机涂层性能评价方法

目的 基于机器学习分类算法快速评估有机涂层的防腐性能。方法 通过实验室加速试验模拟涂层真实的退化过程,并根据测得的电化学数据,分析不同退化阶段的等效电路元件参数。随后,采用随机抽样方法获取大量数据,用于机器学习模型训练。通过对比支持向量机(SVM)、k最近邻(k-NN)和随机森林(RF)3种不同的机器学习算法,以及多种输入特征集训练的涂层性能分类器模型的准确率,分析最适合用于涂层性能快速评估的机器学习算法和电化学特征。结果 根据不同输入特征训练的k-NN和RF模型均表现出良好的预测效果,而SVM模型的预测效果相对较差。根据不同频率范围训练的分类器模型中,在低频区表现最佳,而在高频区表现较差。结论 基于阻抗虚部、虚部+实部和阻抗模值3种输入特征训练的RF分类器模型的预测效果最准确。不同频率区间内,低频区的阻抗特征更能准确表征涂层性能。     

Biodiversity of plants and soils in landscapes adjacent to the Buzuluk Pine Forest

The influence of the Buzuluk Pine Forest on biodiversity of plants and soil properties in adjacent territories has been studied. The results show that in the immediate vicinity of the pine forest, under the influence of the relatively mild and humid mesoclimate, natural phytocenoses are dominated by mesophytic species. Biodiversity reaches a peak at a distance of 17–18 km from the forest, which is explained by the presence of both mesophytes and xerophytes in the same phytocenosis. The same zone is also characterized by the maximum diversity of soil properties and structural complexity of the soil cover. Grass communities on ordinary chernozems with a homogeneous soil cover, typical of the steppe zone, are formed at greater distances from the forest.     

Two methods to define and compute visual buffer strips in a forested environment

Several approaches can be used to define and construct visual buffer strips around proposed new facility sites in a forested environment. A visual buffer strip of a given value, defines a region around an object within which the probability of an unblocked view of all or portions of it by an observer are less than the buffer strip probability value. Two primary approaches are used to define visual buffer strips that take into account the size of the vegetative elements and their individual effects on visibility. Several variations and combinations of the approaches are possible. One approach defines a visual buffer strip based on the average probability of a clear view of points along the object by an observer; the other approach is based on the visibility of the feature as a whole. The computation and construction of visual buffer strips based on these two concepts are presented. Comparisons of the two approaches for specific feature shapes are also described.     

Can intensive management increase carbon storage in forests?

A possible response to increasing atmospheric CO₂ concentration is to attempt to increase the amount of carbon stored in terrestrial vegetation. One approach to increasing the size of the terrestrial carbon sink is to increase the growth of forests by utilizing intensive forest management practices. This article uses data from the literature and from forest growth and yield models to analyze the impact of three management practices on carbon storage: thinning, fertilization, and control of competing vegetation. Using Douglas-fir (Pseudotsuga menziesii) and loblolly pine (Pinus taeda) as example species, results from experiments with computer simulation models suggest that, for these two species, thinning generally does not increase carbon storage and may actually cause a decrease. The exception is thinning of very dense young stands. Fertilization generally increases carbon storage, although the response can be quite variable. The largest gains in carbon storage are likely to come from fertilizing lower-quality sites and from fertilizing thinned or less dense stands. Forests usually show increased growth in response to fertilization over a wide range of ages. Simulation of the growth of loblolly pine indicates that controlling competing vegetation at an early age helps to maximize stand growth and carbon storage. The research described in this article has been funded by the US Environmental Protection Agency. This document has been prepared at the EPA Environmental Research Laboratory in Corvallis, Oregon, through contract number 68-C8-0006 to NSI Technology Inc. It has been subjected to the agency’s peer and administrative review and approved for publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.     

Multiple-resource modeling as a tool for conservation: Its applicability in Mexico

The current Mexican environmental law provides the legal basis for comprehensive land-use planning. Under the law, development of natural ecosystems must combine goals, policies, and practices towards the sustainable use of natural resources and the protection of biological diversity. Thus, ecosystem manipulation must be able to counter fragmentation of natural ecosystems and isolation of natural reserves, while providing for human needs. Assessment of the potential of natural ecosystems and management impacts are required. Multiple-resource simulation is an assessment and land-use planning tool that permits managers and decision makers to comply with the law, providing a flexible, user-oriented system that can meet the needs of managers, conservationists, and researchers. A multiple-resource model and an example of how it can be applied to meet planning needs is presented for discussion.