Modeling net primary production of a fast-growing forest using a light use efficiency model

As interest grows in the quantification of global carbon cycles, Light Use Efficiency (LUE) model predictions of the forest net primary production (NPP) are being developed at an accelerating rate. Such models can provide useful predictions at large scales, but evaluating their performance has been difficult. In this study, a remote sensing-based LUE model was established to estimate forest NPP. Using the forest inventory data (FID) from the regional forest inventory survey in China and established allometric biomass equations, we calculated the biomass, the biomass increment, and the NPP of Eucalyptus urophylla (E. urophylla) plantation plots in the forestry jurisdiction of the Leizhou Forestry Bureau, Southern China. The FID-based NPP and the NPP from LUE model predictions were then compared to each other. Results show that the NPP from model predictions at a spatial resolution of 30 m × 30 m varied from 0 to 265 gC/(m² month) and showed regional differences. In addition, the stand age had variable effects on the average individual biomass of the E. urophylla plantation plots. The average individual biomass of the young and mid-age forests increased exponentially and logarithmically with the stand age (R² = 0.9178 and R² = 0.8683), respectively. For young and mid-age E. urophylla plantation plots, the LUE model-predicted NPP was fairly consistent with the FID-based NPP, but the model predictions of the NPP were higher than the estimates from FID. Through the analysis of the causes of uncertainty and the possible reasons for the discrepancy between the model-based NPP and FID-based NPP, the FID-derived estimates provided a foundation for model evaluation.     

Comparison and ranking of different modelling techniques for prediction of site index in Mediterranean mountain forests

Forestry science has a long tradition of studying the relationship between stand productivity and abiotic and biotic site characteristics, such as climate, topography, soil and vegetation. Many of the early site quality modelling studies related site index to environmental variables using basic statistical methods such as linear regression. Because most ecological variables show a typical non-linear course and a non-constant variance distribution, a large fraction of the variation remained unexplained by these linear models. More recently, the development of more advanced non-parametric and machine learning methods provided opportunities to overcome these limitations. Nevertheless, these methods also have drawbacks. Due to their increasing complexity they are not only more difficult to implement and interpret, but also more vulnerable to overfitting. Especially in a context of regionalisation, this may prove to be problematic. Although many non-parametric and machine learning methods are increasingly used in applications related to forest site quality assessment, their predictive performance has only been assessed for a limited number of methods and ecosystems.In this study, five different modelling techniques are compared and evaluated, i.e. multiple linear regression (MLR), classification and regression trees (CART), boosted regression trees (BRT), generalized additive models (GAM), and artificial neural networks (ANN). Each method is used to model site index of homogeneous stands of three important tree species of the Taurus Mountains (Turkey): Pinus brutia, Pinus nigra and Cedrus libani. Site index is related to soil, vegetation and topographical variables, which are available for 167 sample plots covering all important environmental gradients in the research area. The five techniques are compared in a multi-criteria decision analysis in which different model performance measures, ecological interpretability and user-friendliness are considered as criteria.When combining these criteria, in most cases GAM is found to outperform all other techniques for modelling site index for the three species. BRT is a good alternative in case the ecological interpretability of the technique is of higher importance. When user-friendliness is more important MLR and CART are the preferred alternatives. Despite its good predictive performance, ANN is penalized for its complex, non-transparent models and big training effort.     

Hierarchical Bayesian Spatial Models for Multispecies Conservation Planning and Monitoring

Abstract: Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence–absence data derived from regional monitoring programs to develop models with both landscape and site‐level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence–absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad‐scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km² hexagons), can increase the relevance of habitat models to multispecies conservation planning.     

多色强光手电筒在森林防火中的应用研究

本文介绍了一种用于实现林区夜晚信息互通的应急通信工具—多色强光手电筒,并对其构成、使用方法、适用范围及应用前景进行了详尽的分析研究。     

Effects of precipitation and temperature on rain-use efficiency of China's forests北大核心CSCD

Water plays an important role in the growth of plants. It is important to investigate the responses of different ecosystems to precipitation patterns, especially in terms of global changes involving extreme precipitation or drought. However, little is known about the rain-use efficiency (RUE) in China's forests and the correlation of the RUE with the precipitation and other environmental factors. Furthermore, it is unclear whether differences in the forest types or functional groups result in divergent RUE patterns. To investigate the RUE in China's forests, we analyzed the data from 1 266 sampling plots from 17 forest types. The results indicated that: (1) the mean RUE of China's forests is 1.21 g m-2 mm-1. The RUE and precipitation are negatively correlated in all the 17 forest types; (2) the average RUE of broadleaved forests (mainly angiosperms) is higher than that of coniferous forests (mainly gymnosperms), and the angiosperms are more adaptable to changes in the precipitation than gymnosperms; (3) the average RUE of deciduous forests is higher than that of the evergreen forests. The RUE of deciduous forests declines with increasing precipitation to a threshold value. However, the RUE of evergreen forests are unaffected by changes in the precipitation; and (4) the latitude and mean annual temperature are the major factors constraining the RUE under comprehensive environmental factors. We conclude that the mean RUE declines with increasing precipitation to a threshold value, and that the temperature is a crucial factor for RUE. © 2018 Science Press. All rights reserved.     

Forestry administration and policies in the Philippines

This article begins by summarizing the importance of the forestry sector in the Philippine economy It provides an overview of the multiplicity of Philippine governmental institutions involved in forestry in 1982 Then it discusses forestry laws in the country and concludes by examining fifteen critical forest policy issues: sustained yield management; area-specific logging bans; increased use of wood wastes; revision of forest charges; unprocessed log export ban; rationalization of the forest industry, acceleration of reforestation; protection of watersheds; recognition of the social dimensions of slash- and-burn agriculture; fuelwood supply; public land classification for forestry and agriculture, development of plantations for dendrothermal electricity; multiple-use management; preservation of mangrove areas, and improvements in administration and implementation.Research for this paper was supported by the East-West Center Environment and Policy Institute. The author would like to acknowledge the assistance of the Natural Resources Management Center of the Philippine Ministry of Natural Resources.     

Carbon Stocks and Projections on Public Forestlands in the United States, 1952–2040

Approximately 37% of forestlands in the conterminous United States are publicly owned; they represent a substantial area of potential carbon sequestration in US forests and in forest products. However, large areas of public forestlands traditionally have been less intensively inventoried than privately owned forests. Thus, less information is available about their role as carbon sinks. We present estimates of carbon budgets on public forestlands of the 48 conterminous states, along with a discussion of the assumptions necessary to make such estimates. The forest carbon budget simulation model, FORCARB2, makes estimates for US forests primarily based on inventory data. We discuss methods to develop consistent carbon budget estimates from inventory data at varying levels of detail. Total carbon stored on public forestlands in the conterminous US increased from 16.3 Gt in 1953 to the present total of 19.5 Gt, while area increased from 87.1 million hactares to 92.1 million hactares. At the same time the proportion of carbon on public forestlands relative to all forests increased from 35% to 37%. Projections for the next 40 years depend on scenarios of management influences on growth and harvest.This article was written and prepared by US Government employees on official time, and it is therefore in the public domain and not subject to copyright.     

Forest Health,Collective Behaviors,and Management

This study compares community-based managed forests under different purposes of management, namely, state-driven conservation or community-designed utilization in two villages located in the Sopsai watershed, Nan Province, northern Thailand. The forest health under different intensity of uses is assessed in association with the collective behaviors and long-term purposes embedded in village social–cultural context. The study found no significant differences in forest succession and proportion in diameter at 1.3 m (dbh) class and height-class distribution of the forest under different use intensity. The forest for utilization also showed higher density and basal area of the local preferred species than the conservation forest. In the utilization forest, we also found a higher number of multipurpose and preferred species than in the conservation forest, which actually responded to the needs of the community in the long term to have more wood products (both firewood and timbers). The community-based forest management (CBFM) for utilization can also lead to natural regeneration and biodiversity similar to conservation forests. Through CBFM, forest resources can be managed to maintain the healthy condition under different intensities and respond to both community needs and external expectation. The findings also emphasize the importance of recognizing community needs and management objectives in watershed restoration and improving the productivity of forests under collective management.     

A Brief Overview of Carbon Sequestration Economics and Policy

This article provides an overview of the issues and challenges involved in analyzing the costs and program design for carbon sequestration. The first section examines some of the pitfalls of comparing the results of carbon sequestration cost studies and suggests some simple ways in which analysts could make their results more useful. The pitfalls in comparing studies include different definitions for the summary statistic dollars per ton, differences in the type of costs that are estimated, and differences in underlying assumptions regarding program design and implementation. Future cost studies will benefit from improved treatment of leakage, general equilibrium interactions, and public finance interactions. The second section reviews issues related to the implementation of a carbon sequestration program, including which policy tools are available and which have received the most attention, some of the challenges for using those policy tools, and one alternative that has received little attention, but may become necessary. The discussion also provides an overview and analysis of the bills introduced in the last two congresses and considers the general policy implications of those proposals.