Potentials and limitations of using large-scale forest inventory data for evaluating forest succession models

Forest gap models have been applied widely to examine forest development under natural conditions and to investigate the effect of climate change on forest succession. Due to the complexity and parameter requirements of such models a rigorous evaluation is required to build confidence in the simulation results. However, appropriate data for model assessment are scarce at the large spatial and temporal scales of successional dynamics. In this study, we explore a data source for the evaluation of forest gap models that has been used only little in the past, i.e., large-scale National Forest Inventory data. The key objectives of this study were (a) to examine the potentials and limitations of using large-scale forest inventory data for evaluating the performance of forest gap models and (b) to test two particular models as case studies to derive recommendations for their future improvement.     

An overview of systems analysis methods in delineating environmental quality indices

Environmental quality indices (EQIs) have been developed for a variety of purposes ranging from enforcement of environmental standards, to analysis of trends of environmental degradation or improvement, to scientific research. EQIs currently in use are not organized within an integrated framework and thus it has been difficult to analyze adequately complex, multidisciplinary, large-scale, global phenomena. In this paper we compare four different approaches to developing EQIs within a systems perspective. Our analysis suggests that: (1) non-linear regression models that represent an ecosystem's response to different impacts within a stress-response framework (method of response functions) are useful tools for analysis of environmental data; (2) non-equilibrium thermodynamics models based on the concept of exergy, which represents the free energy a system possesses in relation to its environment, provide a common basis for representing many aspects of ecosystem development and response to environmental impacts as a single measure; (3) diagram models based on the concept of emergy, which represents both environmental values and economic values with a single measure, provide a common basis for integrating economic development and environmental protection values into one index; and (4) complex systems simulation models based on general systems theory, which use the methodologies of systems analysis and simulation to identify, quantify, and interrelate EQIs within a dynamic systems context, provide explicit linkages between causes and effects (vertical integration) and identify cross-linkages among different environmental issues (horizontal integration).     

东北过伐林区不同林分类型土壤肥力质量评价研究

保持和提高森林土壤肥力质量是实现森林健康的基础。研究不同林型下土壤肥力质量对森林可持续经营具有重要意义。以东北过伐林区金仓林场中的落叶松Lartx gmelinii人工纯林、云杉Picea asperatax紫椴Tilia amurensis天然混交林、紫椴×白桦Betula platyphylla天然混交林、五角槭Acer monox白桦×落叶松天然混交林、五角槭×白桦×紫椴天然混交林、白桦×落叶松天然混交林和五角械×紫椴×青杨Populus pseudo-simonii天然混交林为研究对象,分析和比较了不同林分下的土壤物理和化学性质,并采用主成分分析与聚类分析相结合的方法评价了其土壤肥力质量。结果表明：①林分类型对土壤理化性质影响显著;随土壤深度增加,土壤密度和土壤pH值增大,而土壤含水量、物理性粘粒含量和养分质量分数减少,但其在不同林分下的变化程度不同;②土壤因子之间关系密切,物理性粘粒含量与含水量、全氮、速效钾质量分数呈极显著正相关,而与土壤密度和pH值呈显著负相关;土壤养分质量分数之间具有不同程度的显著正相关关系;③采用主成分分析法对不同林分下0～60cm的土壤肥力质量进行了评价,土壤肥力质量表现为天然混交林高于落叶松人工纯林;采伐降低了土壤的肥力质量;在落叶松人工纯林中,随着林龄的增加,土壤的肥力质量下降。通过对土壤肥力质量综合指标值的聚类分析,将研究区土壤肥力质量分为优、良、中、差4个等级,肥力质量属于中等以上（优、良、中等）的林地所占研究样地的比例为66．7％,研究区森林土壤肥力质量属于中等水平。建议在经营过伐林时,注意调整林分结构和树种组成,控制采伐强度,同时进行长期定位观测和比较,以改善林分整体的肥力状况。本研究结果为该地区林业可持续经营提供直接依据,也为东北地区森林土壤肥力质量评价提供参考。     

A proposed standard method for composite sampling of water chemistry and plankton in small lakes

In this paper a method for collection of vertically and horizontally integrated volume-weighted composite samples for analysis of water chemistry and plankton is presented. The method, which requires a proper knowledge of lake morphometry parameters, includes proposed standard procedures for determination of sampling interval thickness, maximum depth of sampling, selection of sampling stations, and distribution of discrete samples. An example of the outcome of the method in a lake with uncomplicated basin morphometry is given and the results are discussed against background of general lake basin morphometry data. The aim of the paper is to start a debate about optimization (statistical as well as ecological) of volume weighted composite sampling.     

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.     

Variance estimation in the EMAP strategy for sampling discrete ecological resources

The United States Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP) is designed to describe status, trends and spatial pattern of indicators of condition of the nation's ecological resources. The proposed sampling design for EMAP is based on a triangular systematic grid and employs both variable probability and double sampling. The Horvitz-Thompson estimator provides the foundation of the design-based estimation strategy used in EMAP. However, special features of EMAP designed to accommodate the complexity of sampling environmental resources on a national scale require modifications of standard variance estimation procedures as well as development of new techniques. An overview of variance estimation methods proposed for application to EMAP's sampling strategy for discrete resources is presented.     

几种不同更新的森林群落碳储量结构特征分析

森林更新是维持和扩大森林资源的主要途径,也是森林结构调整、森林可持续经营和构建多功能高效的森林生态系统的过程。在安徽南部的岭南林场,选择了马尾松（Pinus massoniana Lamb）人工林（MP）、杉木（Cunninghamia lanceolata）人工林（CF）、阔叶混交天然次生林（MB）和针阔混交人工次生林（MN）等4种具有典型代表性的森林群落类型,研究了不同更新方式形成的森林群落的碳储量结构特征。结果表明：（1）针阔混交次生林树干生物量密度最大,为（67.32±56.57）mg.hm-2,杉木人工林生物量密度最小,为（43.79±9.13）mg.hm-2,而马尾松树干生物量所占比例最大,为（64.04±1.49）%。阔叶混交次生林碳储量最高,为（126.47±90.75）mg.hm-2;（2）4种群落类型中,阔叶混交林与马尾松群落碳密度最大,分别为95.67和98.21mg.hm-2,杉木群落碳密度最小,为55.41 mg.hm-2。阔叶混交林中的灌木层生物量碳密度最大,为（17.438±24.627）mg hm-2,马尾松林的草本层和枯落层生物量碳密度最高,分别为（1.326±0.431）、（5.517±2.846）mg.hm-2;（3）阔叶混交林群落的地下碳储量最高,为（10.5±9.8）mg.hm-2,群落地下碳储量从大到小的顺序是阔叶混交林〉针阔混交林〉杉木林〉马尾松林。相应的群落地上碳储量从大到小的顺序是阔叶混交林〉针阔混交林〉马尾松林〉杉木林。杉木林根茎比（R/S）最大,为0.21±0.01,杉木林群落中的灌木层根茎比（R/S）最大,为1.61±0.11;（4）在阔叶混交林中,株数密度与乔木层、草本层的碳比例正相关。在杉木林群落中,平均胸径、株数密度与乔木层碳所占比例成负相关。除杉木林群落外,灌木层碳含量之比与胸径及密度等调查因子都呈负相关。     

The impact of fragmentation and density regulation on forest succession in the Atlantic rain forest

The Atlantic Rain Forest, an important biodiversity hot spot, has faced severe habitat loss since the last century which has resulted in a highly fragmented landscape with a large number of small forest patches (<100 ha). For conservation planning it is essential to understand how current and future forest regeneration depends on ecological processes, fragment size and the connection to the regional seed pool. We have investigated the following questions by applying the forest growth simulation model FORMIND to the situation of the Atlantic Forest in the state of São Paulo, SE Brazil: (1) which set of parameters describing the local regeneration and level of density regulation can reproduce the biomass distribution and stem density of an old growth forest in a reserve? (2) Which additional processes apart from those describing the dynamics of an old growth forest, drive forest succession of small isolated fragments? (3) Which role does external seed input play during succession? Therefore, more than 300 tree species have been classified into nine plant functional types (PFTs), which are characterized by maximum potential height and shade tolerance. We differentiate between two seed dispersal modes: (i) local dispersal, i.e. all seedlings originated from fertile trees within the simulated area and (ii) external seed rain. Local seed dispersal has been parameterized following the pattern oriented approach, using biomass estimates of old growth forest. We have found that moderate density regulation is essential to achieve coexistence for a broad range of regeneration parameters. Considering the expected uncertainty and variability in the regeneration processes it is important that the forest dynamics are robust to variations in the regeneration parameters. Furthermore, edge effects such as increased mortality at the border and external seed rain have been necessary to reproduce the patterns for small isolated fragments. Overall, simulated biomass is much lower in the fragments compared to the continuous forest, whereas shade tolerant species are affected most strongly by fragmentation. Our simulations can supplement empirical studies by extrapolating local knowledge on edge effects of fragments to larger temporal and spatial scales. In particular our results show the importance of external seed rain and therefore highlight the importance of structural connectivity between regenerating fragments and mature forest stands.     

An assessment of sampling,preservation, and analytical procedures for arsenic speciation in potentially contaminated waters

This study was undertaken to ascertain optimal methods of sampling, preserving, separating, and analyzing arsenic species in potentially contaminated waters. Arsenic species are readily transformed in nature by slight changes in conditions. Each species has a different toxicity and mobility. The conventional field sampling method using filters of 0.45 μm in size could overestimate the dissolved arsenic concentrations, as passing suspended particles that can act as a sink or source of arsenic depending on the site condition. For arsenic species in neutral pH and iron-poor waters, the precipitation can be stable for up to 3 days without any treatment, but for longer periods, a preservative, such as phosphoric acid, is required. Also, the analytical procedure must be selected carefully because the levels and hydride generation efficiencies of arsenic in different species can vary, even for the same amount of arsenic. For arsenic speciation in samples that also include organic species, a hybrid high-performance liquid chromatography (HPLC) column and inductively coupled plasma mass spectrometry (ICP-MS) gave the best resolution and lowest detection limits. However, the procedure using a solid phase extraction (SPE) cartridge can be used economically and conveniently for analyzing samples containing only inorganic arsenic species, such as groundwater, especially that related to mine activity.     

Impact of bias in predicted height on tree volume estimation: A case-study of intrinsic nonlinearity

Bias originating from intrinsic nonlinearity in nonlinear models is caused by excess curvature in the solution locus of parameter estimates derived from least squares procedures. Bias due to intrinsic nonlinearity varies according to sample size as well as model specification. This paper analyses consequences of fractionising data into smaller sub-samples. Based on measurements of stem diameter and total tree height from the first Danish national forest inventory, it is demonstrated how data splitting at random may cause the intrinsic nonlinear curvature to exceed the critical F-value. Application of a Taylor-series expansion shows that, for all practical purposes, the bias in predictions of individual tree volume (based on stem diameter and tree height) is negligible. To minimize residual variance, intrinsic curvature and, in turn, prediction bias, it is recommended that data be stratified according to site conditions, stand characteristics or other relevant criteria. Finally, the preferred model should exhibit close-to-linear behaviour.     

Development of TRIPLEX-Management model for simulating the response of forest growth to pre-commercial thinning

In order to simulate forest growth response to pre-commercial thinning (PCT), TRIPLEX1.0 - a process-based model designed to predict forest growth as well as carbon (C) and nitrogen (N) dynamics - was modified and improved to also simulate managed forest ecosystem thinning practices. A three-parameter Weibull distribution model was integrated to simulate thinning treatments within the newly developed TRIPLEX-Management model. The thinning intensity component within the model allows users to simulate thinning treatments by applying basal area, stand density and volume to quantify thinning intensity. Natural mortality decreased following thinning due to an increase in growing space for residual stems. Predicted litterfall pools also increased after thinning events took place. The TRIPLEX-Management model was tested against published observational data for Jack Pine (Pinus banksiana Lamb.) stands subjected to PCT in Northwestern Ontario, Canada. The coefficients of determination (R²) between the predicted and observed variables including stand density, mean DBH (diameter at breast height), the quadratic mean DBH, total volume and merchantable volume as well as belowground, aboveground, and total biomass ranged from 0.50 to 0.88 (n = 20, P < 0.001) with the exception of mean tree height (R² = 0.25, n = 20, P < 0.05). Overall, the Willmott index of agreement between predicted and observed variables ranged from 0.97 to 1.00. Results show that the TRIPLEX-Management model is generally capable of simulating growth response to PCT for Jack Pine stands.     

Establishment of Markov successional model and its application for forest restoration reference in Southern China

Forest succession is the base of establishing restoration reference which plays an important role in forest restoration and restoration estimation. The study presented the establishment of a Markov successional model (MSM) and its application to restoration reference in lower subtropical forest in China. The compositions of successional system in MSM were divided into three species types: pioneering pine trees, heliophytic trees and mesophytic trees. The successional system was divided into three subsystems: early successional stage, mid-successional stage and late-successional stage. Based on the site survey on the changes in the species and their individuals in 25 years, the transition matrices in various subsystems were determined. The predicted results were used to establish the restoration reference of the vegetation restoration in lower subtropical China. According to the ecological restoration reference established in this study, it would take 150 years for the forest to change from pioneer to mature communities in the region. Successional change of tree composition was forecast by the model, and the scenario forecast by the model reflects the actual conditions observed through 52 years of long-term permanent site research. The restoration experience in the region matches the forecast results. The application of a restoration reference model indicates that forest restoration can be accelerated by taking measures which change forest structure. The above results imply that a restoration reference established on the rule of regional forest succession could be very useful not only in directing, but also in assessing and managing regional forest restoration. Previously, one “ideal reference ecosystem” was used as a restoration reference in all correlative studies. In this study, the restoration “process” was used as the restoration reference.     

Mathematical analysis of change in forest carbon use efficiency with stand development: A case study on Abies veitchii Lindl.

Changes in carbon use efficiency (CUE), which is defined as the ratio of net primary production (NPP) to gross primary production (GPP), were analyzed for Abies veitchii Lindl. forests with respect to stand development by developing a simple mathematical model incorporating data on physiological variables and leaf mass ratio. A decrease in CUE with stand development was successfully expressed as a function of stand biomass (y) based on the following three assumptions: (1) a power-law relationship between mean respiration and mean individual tree mass, (2) a power-functional relationship between mean gross primary production and mean individual tree mass, and (3) self-thinning relationship between stand biomass and density. Based on this model, a parameter of CUE–y relationship was defined, and it was clarified that CUE decrease with stand development is caused not by the ratio of specific respiration rate to specific gross photosynthetic rate, but by leaf mass ratio. Since CUE is high in young forests, helpful information on selecting woody species when planting seedlings was provided from the viewpoints of reducing CO₂ in the atmosphere and global warming.     

Predicting tree species presence and basal area in Utah: A comparison of stochastic gradient boosting,generalized additive models,and tree-based methods

Many efforts are underway to produce broad-scale forest attribute maps by modelling forest class and structure variables collected in forest inventories as functions of satellite-based and biophysical information. Typically, variants of classification and regression trees implemented in Rulequest's^© See5 and Cubist (for binary and continuous responses, respectively) are the tools of choice in many of these applications. These tools are widely used in large remote sensing applications, but are not easily interpretable, do not have ties with survey estimation methods, and use proprietary unpublished algorithms. Consequently, three alternative modelling techniques were compared for mapping presence and basal area of 13 species located in the mountain ranges of Utah, USA. The modelling techniques compared included the widely used See5/Cubist, generalized additive models (GAMs), and stochastic gradient boosting (SGB). Model performance was evaluated using independent test data sets. Evaluation criteria for mapping species presence included specificity, sensitivity, Kappa, and area under the curve (AUC). Evaluation criteria for the continuous basal area variables included correlation and relative mean squared error. For predicting species presence (setting thresholds to maximize Kappa), SGB had higher values for the majority of the species for specificity and Kappa, while GAMs had higher values for the majority of the species for sensitivity. In evaluating resultant AUC values, GAM and/or SGB models had significantly better results than the See5 models where significant differences could be detected between models. For nine out of 13 species, basal area prediction results for all modelling techniques were poor (correlations less than 0.5 and relative mean squared errors greater than 0.8), but SGB provided the most stable predictions in these instances. SGB and Cubist performed equally well for modelling basal area for three species with moderate prediction success, while all three modelling tools produced comparably good predictions (correlation of 0.68 and relative mean squared error of 0.56) for one species.     

Model correlation in stochastic forest simulators—A case of multilevel multivariate model for seedling establishment

Forest development can be predicted by the use of forest simulators based on various statistical models describing the forest and its dynamics. One potential approach to study the reliability of the simulators is to utilise Monte Carlo simulation techniques to generate a predictive distribution of a forest characteristic. One problem in examining the effect of model uncertainty in forestry decision making, however, is correlation between the models. If this is not taken into account, predictions of the model systems may become biased, and the effect of errors on decision making may be underestimated. In reality, the models often are interdependent, but the correlations usually are not known because the models have been estimated in separate studies. The aim of this paper is to study the impacts of between-model dependencies on the predictive distribution of forest characteristics by Monte Carlo simulation techniques. We utilise a case of predicting seedling establishment of planted Norway spruce (Picea abies (L.) Karst.) stands as an example with multivariate multilevel model structures. Regardless of low cross-correlations between the models, ignoring them led to significant underestimation of the amount of competing broadleaves to be removed in pre-commercial thinning. Therefore, we recommend that between-model dependencies are clarified and considered in stochastic simulations. In our case, between-model interdependencies can be reliably estimated with a limited dataset. In addition, estimating the models separately and using the model residuals to estimate interdependencies between models were also sufficient to take the between-model dependencies into account when producing stochastic predictions for silvicultural decision making.     

Mechanisms of moisture stress in a mid-latitude temperate forest: Implications for feedforward and feedback controls from an irrigation experiment

While it is well established that stomata close during moisture stress, strong correlations among environmental (e.g., vapor pressure deficit, soil moisture, air temperature, radiation) and internal (e.g., leaf water potential, sap flow, root-shoot signaling) variables obscure the identification of causal mechanisms from field experiments. Models of stomatal control fitted to field data therefore suffer from ambiguous parameter identification, with multiple acceptable (i.e., nearly optimal) model structures emphasizing different moisture status indicators and different processes. In an effort to minimize these correlations and improve parameter and process identification, we conducted an irrigation experiment on red maples (Acer rubrum L.) at Harvard Forest (summers of 2005 and 2006). Control and irrigated trees experienced similar radiative and boundary layer forcings, but different soil moisture status, and thus presumably different diurnal cycles of internal leaf water potential. Measured soil moisture and atmospheric forcing were used to drive a transient tree hydraulic model that incorporated a Jarvis-type leaf conductance in a Penman–Monteith framework with a Cowan-type (resistance and capacitance) tree hydraulic representation. The leaf conductance model included dependence on both leaf matric potential, Ψ_L (so-called feedback control) and on vapor pressure deficit, D (so-called feedforward control). Model parameters were estimated by minimizing the error between predicted and measured sap flow. The whole-tree irrigation treatment had the effect of elevating measured transpiration during summer dry-downs, demonstrating the limiting effect that subsurface resistance may have on transpiration during these times of moisture stress. From the best fitted model, we infer that during dry downs, moisture stress manifests itself in an increase of soil resistance with a resulting decrease in Ψ_L, leading to both feedforward and feedback controls in the control trees, but only feedforward control for the irrigated set. Increases in the sum-of-squares error when individual model components were disabled allow us to reject the following three null hypotheses: (1) the f(D) stress is statistically insignificant (p = 0.01); (2) the f(Ψ_L) stress is statistically insignificant (p = 0.07); and (3) plant storage capacitance is independent of moisture status (p = 0.07).     

Simulating the potential for ecological restoration of dryland forests in Mexico under different disturbance regimes

Examining the potential for ecological restoration is important in areas where anthropogenic disturbance has degraded forest landscapes. However, the conditions under which restoration of degraded tropical dry forests (TDF) might be achieved in practice have not been determined in detail. In this study, we used LANDIS-II, a spatially explicit model of forest dynamics, to assess the potential for passive restoration of TDF through natural regeneration. The model was applied to two Mexican landscapes under six different disturbance regimes, focusing on the impact of fire and cattle grazing on forest cover, structure and composition. Model results identified two main findings. First, tropical dry forests are more resilient to anthropogenic disturbance than expected. Results suggested that under both a scenario of small, infrequent fires and a scenario of large, frequent fires, forest area can increase relatively rapidly. However, forest structure and composition differed markedly between these scenarios. After 400 years, the landscape becomes increasingly occupied by relatively shade-tolerant species under small, infrequent fires, but only species with both relatively high shade tolerance and high fire tolerance can thrive under conditions with large, frequent fires. Second, we demonstrated that different forms of disturbance can interact in unexpected ways. Our projections revealed that when grazing acts in combination with fire, forest cover, structure and composition vary dramatically depending on the frequency and extent of the fires. Results indicated that grazing and fire have a synergistic effect causing a reduction in forest cover greater than the sum of their individual effects. This suggests that passive landscape-scale restoration of TDF is achievable in both Mexican study areas only if grazing is reduced, and fires are carefully managed to reduce their frequency and intensity.     

Disentangling the effects of heterogeneity, stochastic dynamics and sampling in a community of aquatic insects

A dynamic and heterogeneous species abundance model generating the lognormal species abundance distribution is fitted to time series of species data from an assemblage of stoneflies and mayflies (Plecoptera and Ephemeroptera) of an aquatic insect community collected over a period of 15 years. In each year except one, we analyze 5 parallel samples taken at the same time of the season giving information about the over-dispersion in the sampling relative to the Poisson distribution. Results are derived from a correlation analysis, where the correlation in the bivariate normal distribution of log abundance is used as measurement of similarity between communities. The analysis enables decomposition of the variance of the lognormal species abundance distribution into three components due to heterogeneity among species, stochastic dynamics driven by environmental noise, and over-dispersion in sampling, accounting for 62.9, 30.6 and 6.5% of the total variance, respectively. Corrected for sampling the heterogeneity and stochastic components accordingly account for 67.3 and 32.7% of the among species variance in log abundance. By using this method, it is possible to disentangle the effect of heterogeneity and stochastic dynamics by quantifying these components and correctly remove sampling effects on the observed species abundance distribution.