Search

Drought-induced tree mortality has increased in many parts of the world because of climate change, and in some regions, has altered forest structure, species composition and ecosystem functions. These developments have the potential to reduce forest resilience and push forests over a tipping point to an alternate state (i.e. a different forest type or a non-forest ecosystem). Texas experienced an exceptional drought in 2011, which killed an estimated 65.5 million trees in the heavily forested areas of the East Texas region. The objective of this study was to understand the effects of the 2011 drought on mortality, biomass and growth in this region and explore forest stability at species, forest and ecoregion levels. We categorized 19 years’ time-series data of 1455 Forest Inventory and Analysis plots into four periods, base (2001–2003), pre-drought (2004–2010), drought (2011–2016) and post-drought (2017–2019), and used repeated-measures analysis of variance to analyse annual mortality, biomass loss, growth rates and the Forest Stability Index to understand forest stability. Our results show that tree mortality and biomass loss increased significantly during the drought period and annual growth rates declined. During the post-drought period, mortality and biomass loss rates returned to the pre-drought level and growth partially recovered. During the drought period, FSI dropped at species, forest type and ecoregion levels but recovered during the post-drought period, except for the Oak Woods and Prairies ecoregion and for forests dominated by southern red oak. Our results indicate that East Texas forests are undergoing a reorganization and recovery stage (in terms of species composition and stand structure) but have yet to reach a tipping point. Given the increased frequency and severity of climate change-induced weather events, East Texas forests could approach a tipping point in the future if there is insufficient time between events for reorganization and recovery. Further analyses are needed to understand the fate of tree species and forests in East Texas under global climate change.

Changes in tree mortality due to severe drought can alter forest structure, composition, dynamics, ecosystem services, carbon fluxes, and energy interactions between the atmosphere and land surfaces. We utilized long-term (2000‒2017, 3 full inventory cycles) Forest Inventory and Analysis (FIA) data to examine tree mortality and biomass loss in drought-affected forests for East Texas, USA. Plots that experienced six or more years of droughts during those censuses were selected based on 12-month moderate drought severity [Standardized Precipitation Evaporation Index (SPEI) -1.0]. Plots that experienced other disturbances and inconsistent records were excluded from the analysis. In total, 222 plots were retained from nearly 4000 plots. Generalized nonlinear mixed models (GNMMs) were used to examine the changes in tree mortality and recruitment rates for selected plots. The results showed that tree mortality rates and biomass loss to mortality increased overall, and across tree sizes, dominant genera, height classes, and ecoregions. An average mortality rate of 5.89% year−1 during the study period could be incited by water stress created by the regional prolonged and episodic drought events. The overall plot and species-group level recruitment rates decreased during the study period. Forest mortality showed mixed results regarding basal area and forest density using all plots together and when analyzed the plots by stand origin and ecoregion. Higher mortality rates of smaller trees were detected and were likely compounded by density-dependent factors. Comparative analysis of drought-induced tree mortality using hydro-meteorological data along with drought severity and length gradient is suggested to better understand the effects of drought on tree mortality and biomass loss around and beyond East Texas in the southeastern United States.

The interdependence of different energy forms in multiple energy systems (MESs) could leverage their synergies to reduce carbon emissions. However, such synergies cannot be exploited without the right incentives. This paper studies the low-carbon operation of MESs by coordinating the transmission-level and distribution-level via the energy-carbon integrated prices. Energy prices are decided by locational marginal pricing principles in the transmission-level MES. At the same time, the carbon emissions of different energy systems are uniformly priced using a carbon emission flow (CEF) model based on the consumers’ actual emission contributions by tracing the embedded flow of CO2. Various distribution-level MESs modeled by energy hubs (EHs) are independently operated in response to the variation in the integrated prices. The whole bi-level model formulates an equilibrium problem and is solved iteratively. Case studies based on two MESs at different scales illustrate the effectiveness and benefit of the proposed carbon pricing method in reducing carbon emissions more efficiently than current methods.

With the expansion of plantations all over the world, there are increasingly more concerns about their ability to support multiple ecosystem services. We hypothesized that mixed plantations with a high number of tree species could provide a higher level of ecosystem services than monocultures. To test this hypothesis, we selected the experimental forest of the Huitong National Research Station of Forest Ecosystem as our study area and applied the Integrated Valuation of Ecosystem Services and Tradeoffs Model (InVEST) and the Integrated Water Storage Capacity Model to evaluate five types of ecosystem services (timber production, water provision, carbon storage, soil conservation, and water retention) provided by plantations and natural forests. None of the plantations or natural forests were found to have a constantly high level of multiple ecosystem services. The results showed that the overall benefits of the ecosystem services were highest in mixed plantations, followed by coniferous plantations and broadleaf plantations. Natural forests in our study had relatively high values of regulating services. These findings suggest that plantation management should increase the number of mixed plantations rather than monocultures. In addition, the future protection of natural forests requires urgent consideration.

Drought is one of the most complex and least understood climate-related natural hazards. Active drought mitigation and contingency plan formulation often require a reliable drought distribution map. This study analyzed different spatial interpolation techniques to produce drought distribution map in East Texas, USA. Deterministic [inverse distance weighting (IDW) and spline], and geostatistical [ordinary kriging (Gaussian (KG) and spherical (KS))] interpolation techniques were employed as candidate methods for evaluation. Thirty-four years (1980–2013) of weather station data (N = 47) were used to calculate a 12-month Standardized Precipitation Evaporation Index (SPEI). The dataset was randomly divided into test data (70%, N = 33) and validation data (30%, N = 14). The resulting SPEI maps were cross-checked and validated through a validation dataset by calculating error matrices. The results indicate that KG tends to perform well in relatively drier conditions while IDW shows mixed results, performing well both in dry and wet conditions. The overall power of the four techniques to map 12-month drought conditions resulted in the order of IDW > KG > KS > spline.

Windthrow plays a critical role in maintaining species diversity in temperate forests. Do large-scale strong wind events (i.e., tropical cyclones, including hurricanes, typhoons and severe cyclonic storms) increase tree diversity in severely damaged forest areas? Do hurricanes (tropical cyclones that occurs in the Atlantic Ocean and northeastern Pacific Ocean) lead to altered relative abundance of shade-tolerant and shade-intolerant species? Did historic hurricanes alter the succession trajectory of the damaged forests? We used nearly 70-year tree demographic data to assess the effects of two major hurricanes on woody species diversity in Piedmont forests, North Carolina, USA. Species richness (S) and Shannon–Wiener’s diversity index (H′) were used to evaluate the changes in tree diversity. The changes in composition were assessed with Nonmetric Multidimensional Scaling. The pre-hurricane successional phase can strongly influence both the damage severity and subsequent responses. Although there is often an immediate drop in diversity following a hurricane, understory tree diversity quickly increases to levels that exceed those prior to the disturbance. This leads to an increase in diversity in stands that were substantially damaged. Hurricanes significantly decrease the dominance of shade-intolerant canopy species while increasing pre-established, more shade-tolerant species. We conclude that large, and infrequent hurricanes help to maintain local tree diversity, but also accelerate the increase in dominance of understory species such as red maple and beech.

Understanding physiological responses and drought adaptation strategies of woody plant leaf traits in sub-humid to semi-arid regions is of vital importance to understand the interplay between ecological processes and plant resource-allocation strategies of different tree species. Seasonal variations of leaf morphological traits, stoichiometric traits and their relationships of two drought tolerant woody species, live oak (Quercus virginiana) and honey mesquite (Prosopis glandulosa) and two less drought tolerant species, sugarberry (Celtis laevigata) and white ash (Fraxinus americana) were analyzed in a sub-humid to semi-arid area of south Texas, USA. Our findings demonstrate that for the two drought tolerant species, the leguminous P. glandulosa had the highest specific leaf area, leaf N, P, and lowest leaf area and dry mass, indicating that P. glandulosa adapts to an arid habitat by decreasing leaf area, thus reducing water loss, reflecting a resource acquisition strategy. While the evergreen species Q. virginiana exhibited higher leaf dry mass, leaf dry matter content, C content, C:N, C:P and N:P ratios, adapts to an arid habitat through increased leaf thickness and thus reduced water loss, reflecting a resource conservation strategy in south Texas. For the two less drought tolerant deciduous species, the variations of leaf traits in C. laevigata and F. americana varied between Q. virginiana and P. glandulosa, reflecting a trade-off between rapid plant growth and nutrient maintenance in a semi-arid environment.

As a type of the elastic load, the demand-side controllable air-conditioning load can respond to electricity demand based on incentives or electricity prices. By adopting a reasonable control strategy for the optimal combination of controllable air-conditioning load groups, the air-conditioning loads of large-scale buildings can be guided to execute various dispatch commands of the power grid in the best response to electricity consumption. This paper constructs an air-conditioning load model. On this basis, a day-ahead dispatch model of the power grid with the extensive participation of central air-conditioning loads is established. The case shows that the participation of large-scale air-conditioning load in demand response can effectively reduce the peak load and realize the economic operation of the system.

Elastic load can be regarded as a demand response resource, such as the temperature-controlled loads, the energy storage and the electric vehicles. It participates in the operation and dispatch of the power grid, and its position is becoming more and more important in the future power system. Due to the complex economic environment of the power market, all users involved in demand response are required to interact with each other to obtain an efficient control and dispatch method. From the perspective of user economy, this article takes the minimum total cost of user electricity as the objective function to optimize the load demand response. Two different algorithms, the particle swarm algorithm and the nonlinear algorithm, are used to solve the problem. The results show that the application of particle swarm optimization in the elastic load demand response has obvious characteristics and advantages.

There is increasing interest worldwide regarding managing plantation forests in a manner that maintains or improves timber production, enhances ecosystem services, and promotes long‐term sustainability of forest resources. We selected the Gan River Basin, the largest catchment of Poyang Lake and a region with a typical plantation distribution in South China, as the study region. We evaluated and mapped four important forest ecosystem services, including wood volume, carbon storage, water yield, and soil retention at a 30 × 30 m resolution, then quantified their trade‐offs and synergies at the county and subwatershed scales. We found that the wood volume and carbon storage services, as well as the soil retention and water yield, exhibited synergistic relationships. However, the carbon storage displayed a trade‐off relationship with the water yield. Additionally, we compared the beneficial spatial characteristics among dominant species in the study region. The results showed that the Chinese fir forest and the pine forest exhibited lower overall benefits than natural forests including the broad‐leaved forest and the bamboo forest. To propose a suitable management strategy for the study region, method of spatial cluster analysis was used based on the four eco‐services at the subwatershed scale. The basin was divided into four management groups instead of treating the region as a homogenous management region. Finally, we proposed more specific and diverse management strategies to optimize forest benefits throughout the entire region.

Slender rush-pea (Hoffmannseggia tenella) is an endangered herbaceous legume endemic to southern Texas. Agricultural expansion and invasive nonnative grasses have caused reductions in its range, threatening existing populations. We compared three management techniques that control competition to no management (control) to determine effects on slender rush-pea survival and morphology. We treated some slender rush-pea plants with summer prescribed burning. In the mechanical treatment we controlled above-ground competition surrounding target slender rush-pea plants with a string trimmer and we removed both above- and below-ground competition with herbicide in the chemical treatment. No slender rush-pea plants died during our two-year study. Plants in each competition removal treatment produced more main stems than control plants at various times throughout the study. Summer prescribed burning produced longer stems, while both summer burning and chemical treatment resulted in more leaves on the long...

Multi-energy systems (MES) make it possible to supply one load by several energy infrastructures, thus increasing the reliability of energy supply compared to separate energy systems (SES). To accurately and efficiently evaluate the reliability of MES, this paper proposes a fast MES reliability evaluation method using multi-parametric linear programming (MPLP). The energy conversion, transmission and storage in MES are compactly and linearly descried by energy hub model, making the load curtailment optimization problem of MES a linear programming (LP) problem. MPLP is introduced to avoid computational burdens caused by iteratively solving LP problems for a large number of samples during the evaluation process. Case studies are conducted on both imaginary MES and SES. The results show that the proposed method improves the evaluation efficiency by an order of magnitude compared to the traditional LP method and the reliability of energy supply is distinctly improved due to energy integration.

Global and regional environmental changes such as land use and climate change have significantly integrated and interactive effects on forest. These integrated effects will undoubtedly alter the distribution, function and succession processes of forest ecosystems. In order to adapt to these changes, it is necessary to understand their individual and integrated effects. In this study, we proposed a framework by using coupling models to gain a better understanding of the complex ecological processes. We combined an agent-based model for land use and land cover change (ABM/LUCC), an ecosystem process model (PnET-II), and a forest dynamic landscape model (LANDIS-II) to simulate the change of forest aboveground biomass (AGB) which was driven by land use and climate change factors for the period of 2010–2050 in Taihe County of southern China, where subtropical coniferous plantations dominate. We conducted a series of land use and climate change scenarios to compare the differences in forest AGB. The results show that: (1) land use, including town expansion, deforestation and forest conversion and climate change are likely to influence forest AGB in the near future in Taihe County. (2) Though climate change will make a good contribution to an increase in forest AGB, land use change can result in a rapid decrease in the forest AGB and play a vital role in the integrated simulation. The forest AGB under the integrated scenario decreased by 53.7% (RCP2.6 + land use), 57.2% (RCP4.5 + land use), and 56.9% (RCP8.5 + land use) by 2050, which is in comparison to the results under separate RCPs without land use disturbance. (3) The framework can offer a coupled method to better understand the complex and interactive ecological processes, which may provide some supports for adapting to land use and climate change, improving and optimizing plantation structure and function, and developing measures for sustainable forest management.

Understanding the physiological response mechanisms of plant leaf traits to forest plantation types in semi-arid regions is of vital importance to better understanding the interplay between ecological process and plant resource-allocation strategies of different tree species. Experimental forest plantations were constructed on the Loess Plateau of China in order to study leaf morphological, physiological and stoichiometric traits among four forest plantation types of Ulmus pumila and Robinia pseudoacacia : a single-species Ulmus pumila plantation (SP-U), a single-species Robinia pseudoacacia plantation (SP-R) and three mixed plantation ratios of U. pumila-R. pseudoacacia (UR) [2:1 (2U1R), 1:1 (1U1R) and 1:2 (1U2R)]. Leaf morphological traits examined include: specific leaf area (SLA), leaf dry mass (LM), leaf area (LA) and leaf dry matter content (LDMC); physiological traits: net photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (Gs) and instantaneous water use efficiency (WUE); and stoichiometric traits: leaf nitrogen content (LNC), leaf phosphorus content (LPC), leaf carbon content (LCC), N:P, C:N and C:P were examined for the four plantation types on the Loess Plateau of China. The results indicate SLA, Pn, Tr, Gs, LPC, LCC, C:N and C:P of R. pseudoacacia and U. pumila varied significantly among the four plantation types (SP, 2U1R, 1U1R and 1U2R). However, LA, LM, LDMC, WUE, LNC and LPC differed little among forest plantation types. The relationships between leaf morphological and physiological traits, in particular SLA revealed a significantly negative correlation with LDMC, but a positive correlation with Pn, Tr and Gs. With regard to the leaf morphological and stoichiometric traits in the study area, SLA was positively correlated with LNC and LPC, but negatively correlated with LCC. As a nitrogen fixation species, R. pseudoacacia always showed higher SLA, Pn, Tr, Gs, LNC and LPC while U. pumila showed higher LDMC, WUE, LCC, C:N, C:P and N:P. This may reflect different environmental adaption strategies between the two tree species. Compared with R. pseudoacacia , U. pumila responded to the arid habitats by increasing leaf thickness and thus reducing water loss, showing potential physiological plasticity in adapting to dry environments. Regarding the four forest plantation types, the mixed plantation displayed increased plant leaf nutrient content and photosynthetic rate when compared to the SP treatment, especially the mixed 1U2R treatment. Based on the results herein, the mixed plantation of R. pseudoacacia and U. pumila could effectively improve leaf nutrient contents and photosynthetic capacity of both tree species, with the optimal planting ratio studied here being the 1U2R treatment of R. pseudoacacia and U. pumila among the four forest plantation types on the Loess Plateau of China.

Mid-subtropical forests are the main vegetation type of global terrestrial biomes, and are critical for maintaining the global carbon balance. However, estimates of forest biomass increment in mid-subtropical forests remain highly uncertain. It is critically important to determine the relative importance of different biotic and abiotic factors between plants and soil, particularly with respect to their influence on plant regrowth. Consequently, it is necessary to quantitatively characterize the dynamic spatiotemporal distribution of forest carbon sinks at a regional scale. This study used a large, long-term dataset in a boosted regression tree (BRT) model to determine the major components that quantitatively control forest biomass increments in a mid-subtropical forested region (Wuyishan National Nature Reserve, China). Long-term, stand-level data were used to derive the forest biomass increment, with the BRT model being applied to quantify the relative contributions of various biotic and abiotic variables to forest biomass increment. Our data show that total biomass (t) increased from 4.62 × 106 to 5.30 × 106 t between 1988 and 2010, and that the mean biomass increased from 80.19 ± 0.39 t ha−1 (mean ± standard error) to 94.33 ± 0.41 t ha−1 in the study region. The major factors that controlled biomass (in decreasing order of importance) were the stand, topography, and soil. Stand density was initially the most important stand factor, while elevation was the most important topographic factor. Soil factors were important for forest biomass increment but have a much weaker influence compared to the other two controlling factors. These results provide baseline information about the practical utility of spatial interpolation methods for mapping forest biomass increments at regional scales.

With the increasing penetration of variable renewable generation in power systems., planning for the effects of variability will become more important. This paper analyzed the flexibility metric that reflects the flexibility variability in its time series and the flexibility of a system to manage periods of variability. The time series of system flexibility demand and supply scenarios are established based on the proposed flexibility metric. The timing characteristics of flexibility requirements and flexibility resources are integrated into the traditional coordinated DG and network planning through a bi-level planning model. The upper-level model is a multi-objective model aimed at maximizing the balance between the system flexibility demand and supply., and the social and economic benefits. The optimal scheduling strategies for various flexibility resources can be achieved by the multiobjective particle swarm optimization algorithm based on meshing. The lower model optimizes the location of DG and demand side loads., and the line expansion decision according to previously constructed flexibility requirement scenarios and flexibility resource deployment strategies. Through this new bilevel planning method., available flexibility providers from the resources., network., loads and storage are considering into the planning of distribution system.

Tropical cyclones are large-scale strong wind disturbance events that occur frequently in tropical and subtropical coastal regions and often bring catastrophic physical destruction to ecosystems and economic disruption to societies along their paths. Major tropical cyclones can infrequently move into the midaltitudes and inland areas. Ecologically, tropical cyclones have profound impacts on diversity, structure, succession and function of forest ecosystems. The ecological effects are both dramatic and subtle. The dramatic effects can be visible, noticeable and to some extent predictable over the short-term and relatively well documented in the literature. However, the subtle effects are often invisible, complex and at smaller scale relatively unpredictable in the long-term. Many factors, meteorologic, topographic and biologic, simultaneously interact to influence the complexity of patterns of damage and dynamics of recovery. I present a global synthesis on the effects of tropical cyclones on forest ecosystems and the complexity of forest responses, with particular attention on the response to large hurricanes in the neotropics and the temperate North America, and strong typhoons on the subtropical and temperate forests in the East and Southeast Asia. Four major aspects provide on organizational framework for this synthesis: (1) consistent damage patterns, (2) factors that influence response patterns and predict damage risks, (3) complexity of forest responses and recovery, and (4) the long-term effects. This review reveals highly variable and complex effects of tropical cyclones on forest ecosystems. A deep understanding of the synergistic effects of tropical cyclones is essential for effective forest management and biodiversity conservation.

The Forest Landscape Model (FLM) is an efficiency tool of quantified expression of forest ecosystem's structure and function. This paper, on the basis of identifying FLM, ac- cording to the stage of development, summarizes the development characteristics of the model, which includes the theoretical foundation of mathematical model, FLM of stand-scale, primary development of spatial landscape model, rapid development of ecosystem process model as the priority, and developing period of structure and process driven by multi-factor. According to the characteristics of different FLMs, this paper classifies the existing FLM in terms of mechanism, property and application, and elaborates the identifications, advantages and disadvantages of different types of models. It summarizes and evaluates the main ap- plication fields of existing models from two aspects which are the changes of spatial pattern and ecological process. Eventually, this paper presents FLM's challenges and directions of development in the future, including: (1) more prominent service on the practical strategy of forest management's objectives; (2) construction of multi-modules and multi-plugin to satisfy landscape research demand in various conditions; (3) adoption of high resolution's spa- tial-temporal data; (4) structural construction of multi-version module; (5) improving the spatial suitability of model application.

Six national programs—including the Natural Forest Protection Program (NFPP), Sloping Land Conversion Program (SLCP), Desertification Combating Program around Beijing and Tianjin (DCBT), Shelterbelt Network Development Program (SNDP), Wildlife Conservation and Nature Reserve Protection Program (WCNR), and Industrial Timberland Plantation Program (ITPP)—were adopted as means to achieve the Chinese Government sustainable development national policy. While the programs have made promising progress circa 10 yr at the national level, problems exist at the regional and locals levels. This article, therefore, reviews the achievements and problems associated with the programs and their implementations, and provides recommendations for the full realization of the goals of the programs. We recommend a comprehensive strategy for future activities—including promotion of sustainability science, reformation of rigid policies and regulations, adoption of sustainable forestry practices, integrated ecosystem management ap...

Eastern hemlock (Tsuga canadensis Carriere) and the Carolina hemlock (Tsuga caroliniana Engelmann) are ecologically important tree species in eastern North America forests that are currently threatened by the hemlock woolly adelgid (HWA, Adelges tsugae Annand, Hemiptera: Adelgidae). HWA has spread rapidly from its original introduction site into new areas. Once present, HWA kills its hosts over a period of 4 to 10 years leading to a phenomenon that is known scientifically and colloquially as hemlock decline. To date, quarantine, chemical management, and biocontrol efforts have failed to curb the spread of the HWA. As such, forest management efforts are now being redirected towards developing an understanding of the effects of hemlock removal on vegetation dynamics, changes in forest composition, and changes in ecosystem function. In this study, we parameterize a spatially explicit landscape simulation model LANDIS II for a specific forested region of the southern Appalachians. Parameterization involves defining the life-history attributes of 37 tree species occupying 11 ecological zones and is based on knowledge of: current vegetation composition data, recent historic management and fire regimes, and life-history traits of each species. The parameterized model is used to explore a simple scenario of catastrophic hemlock mortality likely to occur as a result of HWA herbivory. Our results emphasize that hemlock is an important foundation species. When hemlock is removed from the system, forest composition changes considerably with a greater presence of shade intolerant pine and oak species. Additionally, hemlock removal leads to a period of transient, relatively unstable vegetation dynamics as the forest communities restructure.

SUMMARYSpatial simulation may be used to model the potential effects of current biodiversity approaches on future habitat modification under differing climate change scenarios. To illustrate the approach, spatial simulation models, including landscape-level forest dynamics, were developed for a semi-natural grassland of conservation concern in a southern Italian protected area, which was exposed to woody vegetation encroachment. A forest landscape dynamics simulator (LANDIS-II) under conditions of climate change, current fire and alternative management regimes was used to develop scenario maps. Landscape pattern metrics provided data on fragmentation and habitat quality degradation, and quantified the spatial spread of different tree species within grassland habitats. The models indicated that approximately one-third of the grassland area would be impacted by loss, fragmentation and degradation in the next 150 years. Differing forest management regimes appear to influence the type of encroaching species and the density of encroaching vegetation. Habitat modifications are likely to affect species distribution and interactions, as well as local ecosystem functioning, leading to changes in estimated conservation value. A site-scale conservation strategy based on feasible integrated fire and forest management options is proposed, considering the debate on the effectiveness of protected areas for the conservation of ecosystem services in a changing climate. This needs to be tested through further modelling and scenario analysis, which would benefit from the enhancement of current modelling capabilities of LANDIS-II and from combination with remote sensing technologies, to provide early signals of environmental shifts both within and outside protected areas.

Pumped storage can provide some of the flexibility that power system operators need to balance load and generation in an uncertain environment, and thus enhance a power system's ability to incorporate wind power. Since the process of balancing wind power involves various combinations of wind generation and loads, the amount of pumped storage capacity needed should be evaluated using a substantial number of scenarios. This paper describes a chronological production simulation platform and its application in planning pumped storage capacity for the Jiangsu (China) provincial power system. The daily dispatching of various types of units is simulated using a unit commitment module. A simulation of wind farm operation is incorporated in this module to take into account the effect of its variability on daily dispatching. A detailed cost model for thermal generating units provides an accurate estimate of the benefits of pumped storage. Simulation results clearly show how much generation cost and wind power curtailment should be expected for different amounts of pumped storage capacity. A comparison between the operating and investment costs is then used to determine the optimal pumped storage capacity. Finally, various sensitivity analyses are performed to assess the effect of key parameters on this optimal capacity.

a b s t r a c t Public forest management requires consideration of numerous objectives including protecting ecosystem health, sustaining habitats for native communities, providing sustainable forest products, and provid- ing noncommodity ecosystem services. It is difficult to evaluate the long-term, cumulative effects and tradeoffs these and other associated management objectives. To demonstrate the capabilities of tech- niques suitable to support such evaluations we combined a spatially explicit landscape-scale, succession and disturbance model (LANDIS) with wildlife habitat suitability models and a multi-criteria decision- making framework to compare four management alternatives across a 700 km 2 area of the Mark Twain National Forest in Missouri, USA. We estimated the combined, cumulative effects of tree species suc- cession, fire disturbance, fuel accumulation, fire hazard, wind disturbance and timber harvest on future species composition, age class distribution, timber products, and wildlife habitat suitability for eastern wild turkey and eastern gray squirrel. We applied a structured, multi-criteria, decision-making frame- work (PROMETHEE) to analyse forest conditions and to derive weighted composite scores for seven criteria applied to each alternative management scenario. The approach provides a systematic, repeat- able, transparent, spatially explicit framework for evaluating the long-term, landscape-scale cumulative effects of management alternatives. The methodology does not encompass all the factors that influence decisions about public land management, but it captures many important ones. The underlying models provide a way to test and accumulate knowledge about forest response to succession and disturbance and to use those relationships to support decision making with the best available science.

Small Footprint LiDAR (Light Detection And Ranging) has been proposed as an effective tool for measuring detailed biophysical characteristics of forests over broad spatial scales. However, by itself LiDAR yields only a sample of the true 3D structure of a forest. In order to extract useful forestry relevant information, this data must be interpreted using mathematical models and computer algorithms that infer or estimate specific forest metrics. For these outputs to be useful, algorithms must be validated and/or calibrated using a sub-sample of `known' metrics measured using more detailed, reliable methods such as field sampling. In this paper we describe a novel method for delineating and deriving metrics of individual trees from LiDAR data based on watershed segmentation. Because of the costs involved with collecting both LiDAR data and field samples for validation, we use synthetic LiDAR data to validate and assess the accuracy of our algorithm. This synthetic LiDAR data is generated using a simple geometric model of Loblolly pine (Pinus taeda) trees and a simulation of LiDAR sampling. Our results suggest that point densities greater than 2 and preferably greater than 4 points per m2 are necessary to obtain accurate forest inventory data from Loblolly pine stands. However the results also demonstrate that the detection errors (i.e. the accuracy and biases of the algorithm) are intrinsically related to the structural characteristics of the forest being measured. We argue that experiments with synthetic data are directly useful to forest managers to guide the design of operational forest inventory studies. In addition, we argue that the development of LiDAR simulation models and experiments with the data they generate represents a fundamental and useful approach to designing, improving and exploring the accuracy and efficiency of LiDAR algorithms.

Stochastic weather generators are useful tools for exploring the relationship between organisms and their environment. This paper describes a simple weather generator that can be used in ecological modeling projects. We provide a detailed description of methodology, and links to full C++ source code (http://weathergen.sourceforge.net) required to implement or modify the generator. We argue that understanding the principles of weather generation will allow ecologists to tailor a solution for their own requirements. The detailed, repeatable methodology we present demonstrates that weather generation is relatively straightforward for ecologists to implement and modify.

Forest landscape models simulate forest change through time using spatially referenced data across a broad spatial scale (i.e. landscape scale) generally larger than a single forest stand. Spatial interactions between forest stands are a key component of such models. These models can incorporate other spatio-temporal processes such as natural disturbances (e.g. wildfires, hurricanes, outbreaks of native and exotic invasive pests and diseases) and human influences (e.g. harvesting and commercial thinning, planting, fire suppression). The models are increasingly used as tools for studying forest management, ecological assessment, restoration planning, and climate change. In this paper, we define forest landscape models and discuss development, components, and types of the models. We also review commonly used methods and approaches of modeling forest landscapes, their application, and their strengths and weaknesses. New developments in computer sciences, geographic information systems (GIS), remote sensing technologies, decision-support systems, and geo-spatial statistics have provided opportunities for developing a new generation of forest landscape models that are increasingly valuable for ecological research, restoration planning and resource management.

Matrix models have been used to model population growth of organisms for many decades. They are popular because of both their conceptual simplicity and their computational efficiency. For some types of organisms they are relatively accurate in predicting population growth; however, for others the matrix approach does not adequately model growth rate. One of the reasons for the lack of accuracy is that most matrix-based models implicitly assume a specific degree of variability in development times for the organism. Because the variability is implicit, the implied variances are often not verified with experimental data. In this paper, we shall present extensions to the stage-classified matrix models so that organisms with arbitrary means and standard deviations of development times can be modeled.

The forests of southeastern North America are influenced by a variety of disturbances including fire and insect outbreaks. In this paper, we discuss the role of disturbances in structuring forest landscapes with particular emphasis placed on the reciprocal interaction between forest structure and outbreaks of the southern pine beetle (Dendroctonus frontalis Zimmermann). We highlight work in which we are currently involved to illustrate the importance and utility of using spatially explicit forest modeling as a tool for understanding forest–insect interactions and its potential role in determining management strategies.