Optimization models for environmental pollution control: A synthesis

The optimization models presented here represent a synthesis between input-output analysis and mathematical programming models for environmental pollution control. The pivotal construct is a social cost for each unit of consumption; it is derived from the input-output analysis and is used in the objective function of the mathematical programming models which seek to optimize the final value of bill of goods and bads. The theory of optimization with relative bounded variables in nonlinear programming is developed and utilized.     

Soil C and N models that integrate microbial diversity

Industrial agriculture is yearly responsible for the loss of 55–100 Pg of historical soil carbon and 9.9 Tg of reactive nitrogen worldwide. Therefore, management practices should be adapted to preserve ecological processes and reduce inputs and environmental impacts. In particular, the management of soil organic matter (SOM) is a key factor influencing C and N cycles. Soil microorganisms play a central role in SOM dynamics. For instance, microbial diversity may explain up to 77 % of carbon mineralisation activities. However, soil microbial diversity is actually rarely taken into account in models of C and N dynamics. Here, we review the influence of microbial diversity on C and N dynamics, and the integration of microbial diversity in soil C and N models. We found that a gain of microbial richness and evenness enhances soil C and N dynamics on the average, though the improvement of C and N dynamics depends on the composition of microbial community. We reviewed 50 models integrating soil microbial diversity. More than 90 % of models integrate microbial diversity with discrete compartments representing conceptual functional groups (64 %) or identified taxonomic groups interacting in a food web (28 %). Half of the models have not been tested against an empirical dataset while the other half mainly consider fixed parameters. This is due to the difficulty to link taxonomic and functional diversity.     

Integrated models to support multiobjective ecological restoration decisions

Many objectives motivate ecological restoration, including improving vegetation condition, increasing the range and abundance of threatened species, and improving species richness and diversity. Although models have been used to examine the outcomes of ecological restoration, few researchers have attempted to develop models to account for multiple, potentially competing objectives. We developed a combined state‐and‐transition, species‐distribution model to predict the effects of restoration actions on vegetation condition and extent, bird diversity, and the distribution of several bird species in southeastern Australian woodlands. The actions reflected several management objectives. We then validated the models against an independent data set and investigated how the best management decision might change when objectives were valued differently. We also used model results to identify effective restoration options for vegetation and bird species under a constrained budget. In the examples we evaluated, no one action (improving vegetation condition and extent, increasing bird diversity, or increasing the probability of occurrence for threatened species) provided the best outcome across all objectives. In agricultural lands, the optimal management actions for promoting the occurrence of the Brown Treecreeper (Climacteris picumnus), an iconic threatened species, resulted in little improvement in the extent of the vegetation and a high probability of decreased vegetation condition. This result highlights that the best management action in any situation depends on how much the different objectives are valued. In our example scenario, no management or weed control were most likely to be the best management options to satisfy multiple restoration objectives. Our approach to exploring trade‐offs in management outcomes through integrated modeling and structured decision‐support approaches has wide application for situations in which trade‐offs exist between competing conservation objectives.     

Modeling Prescribed Surface-Fire Regimes for Pinus strobus Conservation

Abstract:  We developed a simple model of   Pinus strobus L. stand dynamics to compare the impacts of different temporal arrangements of surface fires designed to reflect the application of fire as both an essential ecosystem process (natural fire) and as an efficient means of producing specific habitat features or other values (optimal fire). We used a stochastic simulation model of fire processes to estimate the mean fire-return interval that would maximize stand structural diversity. We investigated trade-offs between structural diversity and temporal population stability associated with changes in the fire interval and used a deterministic version of the model to explore the effects of scheduling fires at fixed intervals. In stochastic simulations, maximum structural diversity occurred at intermediate levels of disturbance (40-year mean fire interval). When fires were scheduled at fixed intervals, a longer, 100-year return interval maximized diversity. Mean fire-return interval was a mitigating factor in the diversity-stability relationship, which changed from positive to negative as the fire interval was reduced progressively from 250 to 5 years. As an alternative to scheduling fires at specified mean intervals, we developed a goal-programming model (a form of linear programming model) and used it to identify an optimal fire schedule for achieving habitat and visual-quality objectives. In comparison with the 40-year stochastic mean fire interval, which maximized structural diversity, the optimal schedule produced comparable levels of both diversity and fire frequency. Our results show how simulation and goal-programming models can be used to evaluate prescribed fire-scheduling alternatives and to explore the comparative advantages of natural and optimal fire-management approaches.     

Book Reviews

The study focused on the so-called dark coniferous forest belt on the northern slope of Changbai Mountain, at an altitude of 1100 to 1700 m. Forty tree species, 50 shrub species and 165 herb species were recorded in a series of transects. The main impact factors on forest diversity and proposals for sustainable management of this diversity were studied using an altitude and area gradient pattern method. The results showed that the diversity of dark coniferous forest gradually decreased from lower to upper altitude; while the importance value of key species increased. The methodology used to assess attributes for conservation of dark coniferous forest diversity involved measurement of individual trees, number of species, age structure, stand structure, diameter at breast height (DBH), and cumulative wood storage. Different conservation strategies have been developed and are discussed for different parts of the forest.     

A multidimensional decision-support approach to sustainable development planning

SUMMARY

The concept of sustainable development has become widely accepted as an instrumental objective of resource planning and environmental policy analysis. Nevertheless, applied planning approaches appropriate to this task have been slow in forthcoming. This paper suggests that one avenue for the application of sustainable development principles to resource management problems may be through multidimensional decision-support models. This approach recognizes that contemporary decision problems in the field of environmental planning are characterized by a diversity of structures and processes, incommensurable variables, and conflicting development objectives and constraints. On the basis of the articulated approach to sustainable development, a case study centred on Clayoquot Sound, British Columbia, Canada is presented. The case study serves to illustrate the efficacy of a multidimensional decision-support approach to sustainable development.     

Malthusian overfishing and efforts to overcome it on Kenyan coral reefs

This study examined trends along a gradient of fishing intensity in an artisanal coral reef fishery over a 10-year period along 75 km of Kenya's most populated coastline. As predicted by Malthusian scenarios, catch per unit effort (CPUE), mean trophic level, the functional diversity of fished taxa, and the diversity of gear declined, while total annual catch and catch variability increased along the fishing pressure gradient. The fishery was able to sustain high (approximately 16 Mg x km(-2) x yr(-1)) but variable yields at high fishing pressure due to the dominance of a few productive herbivorous fish species in the catch. The effect of two separate management strategies to overcome this Malthusian pattern was investigated: fisheries area closure and elimination of the dominant and most "competitive" gear. We found that sites within 5 km of the enforced closure showed significantly lower total catch and CPUE, but increased yield stability and trophic level of catch than predicted by regression models normalized for fishing effort. Sites that had excluded illegal beach seine use through active gear management exhibited increased total catch and CPUE. There was a strong interaction between closure and gear management, which indicates that, for closures to be effective at increasing catch, there must be simultaneous efforts at gear management around the periphery of the closures. We propose that Malthusian effects are responsible for the variation in gear and catch and that active management through reduced effort and reductions in the most competitive gear have the greatest potential to increase the functional and trophic diversity and per-person productivity.     

A spatial-temporal optimization approach to watershed management: Acid mine drainage treatment in the Cheat River watershed, WV, USA

Most water management studies concentrate on the inter-temporal allocation problem or, more recently, spatial dynamics - but not both. While early spatial-temporal studies focused on the allocation of water quantity, this paper presents an approach to water quality analysis that incorporates both spatial and temporal dynamics in a watershed framework. The acid mine drainage (AMD) problem in the Cheat River watershed of West Virginia, USA, serves as a case study and provides an opportunity to test the modeling approach developed. The empirical models are written in General Algebraic Modeling System (GAMS) and solved using the CPLEX mixed integer programming package. The results suggest that available investments should be concentrated in heavily impaired stream segments. The model can be used to assess the economic implications of alternative watershed Total Maximum Daily Load (TMDL) implementation or other management strategies.     

Tree species diversity and its relationship to stand parameters and geomorphology features in the eastern Black Sea region forests of Turkey

We studied the effects of stand parameters (crown closure, basal area, stand volume, age, mean stand diameter number of trees, and heterogeneity index) and geomorphology features (elevation, aspect and slope) on tree species diversity in an example of untreated natural mixed forest stands in the eastern Black Sea region of Turkey. Tree species diversity and basal area heterogeneity in forest ecosystems are quantified using the Shannon-Weaver and Simpson indices. The relationship between tree species diversity basal area heterogeneity stand parameters and geomorphology features are examined using regression analysis. Our work revealed that the relationship between tree species diversity and stand parameters is loose with a correlation coefficient between 0.02 and 0.70. The correlation of basal area heterogeneity with stand parameters fluctuated between 0.004 and 0.77 (R2). According to our results, stands with higher tree species diversity are characterised by higher mean stand diameter number of diameter classes, basal area and lower homogeneity index value. Considering the effect of geomorphology features on tree species or basal area heterogeneity we found that all investigated relationships are loose with R < or = 0.24. A significant correlation was detected only between tree species diversity and aspect. Future work is required to verify the detected trends in behaviour of tree species diversity if it is to estimate from the usual forest stand parameters and topography characteristics.     

人为干扰对江油地区马尾松人工林群落结构和物种多样性的影响

物种多样性是群落功能复杂性和稳定性的重要量度指标,人为干扰对森林群落的影响可以通过群落结构和物种多样性的变化而直接显现,不同干扰强度下的森林群落结构和物种多样性特征不同。采用典型样地法,对比研究两种人为干扰强度（干扰强和弱）对江油地区的马尾松（Pinus massoniana）人工林群落的物种组成、群落结构和物种多样性的影响,采用物种丰富度指数D值、Shannon-wienner指数H值、Simpson优势度指数H′值和均匀度指数Jsw值来综合衡量群落的物种多样性水平。结果表明,（1）在总面积3200 m2的8个样地中记录到124个物种,隶属于105属56科,干扰强的群落各层次物种数均低于干扰弱的群落。（2）不同强度人为干扰下马尾松人工林的群落结构不同,干扰弱的群落径级结构呈近正态分布,在径级Ⅵ（7 cm≤d〈9 cm）处出现数量的峰值26株,群落结构较稳定;干扰强的群落径级结构不呈正态分布,在径级Ⅶ（13 cm≤d〈15 cm）处出现峰值43株。干扰弱和干扰强的群落高度级结构与其径级结构具有相似性,干扰弱的群落的个体主要集中在低中高度级（3≤H〈17）;干扰强的群落的个体数在各高度级分布不均匀,主要分布在中高高度级（H≥13）;干扰强的群落的个体数在各径级和高度级分布相对不均匀,群落结构趋于不稳定。（3）人为干扰对马尾松人工林群落造成负面影响,随着人为干扰强度的增加,物种丰富度指数D值、Shannon-wiener多样性指数H值、均匀度多样性指数Jsw值降低,Simpson优势度指数H′值增大,物种多样性呈下降趋势。     

Expanding Kenya's protected areas under the Convention on Biological Diversity to maximize coverage of plant diversity

Biodiversity is highly valuable and critically threatened by anthropogenic degradation of the natural environment. In response, governments have pledged enhanced protected‐area coverage, which requires scarce biological data to identify conservation priorities. To assist this effort, we mapped conservation priorities in Kenya based on maximizing alpha (species richness) and beta diversity (species turnover) of plant communities while minimizing economic costs. We used plant‐cover percentages from vegetation surveys of over 2000 plots to build separate models for each type of diversity. Opportunity and management costs were based on literature data and interviews with conservation organizations. Species richness was predicted to be highest in a belt from Lake Turkana through Mount Kenya and in a belt parallel to the coast, and species turnover was predicted to be highest in western Kenya and along the coast. Our results suggest the expanding reserve network should focus on the coast and northeastern provinces of Kenya, where new biological surveys would also fill biological data gaps. Meeting the Convention on Biological Diversity target of 17% terrestrial coverage by 2020 would increase representation of Kenya's plant communities by 75%. However, this would require about 50 times more funds than Kenya has received thus far from the Global Environment Facility.     

Quadratic diversity: Its maximization can reduce the richness of species

In recent decades numerous diversity indices have been introduced. Among them the quadratic entropy index Q expresses the mean difference between two individuals chosen from the community at random. Differing from diversity indices habitually employed, Q does not satisfy a property postulated earlier for those measures. Namely, the uniform distribution of species does not necessarily yield the maximal index value. Q is based on the difference matrix of species. For a given matrix one can seek for the vector yielding the maximum quadratic entropy. This task leads to a quadratic programming problem. Using the appropriate program of a program package, we determined the maximum vector for a genetic difference matrix of crane species, as published in the literature. We discovered that some components (frequencies) in the maximum vector are equal to zero. That is, by maximizing the quadratic diversity some species can be eliminated. We discuss briefly the possible implications of this observation. Moreover, even if all elements in the maximum vector are positive, the elements can differ.     

Conservation practitioners’ understanding of how to manage evolutionary processes

Both academics and practitioners consider a lack of knowledge about evolutionary theory to be a general barrier to effectively managing genetic diversity. However, it is challenging to judge practitioners’ level of understanding and how this influences their management decisions. Knowledge built through experience may be difficult for practitioners to articulate, but could nonetheless result in appropriate management strategies. To date, researchers have assessed only the explicit (formal) knowledge practitioners have of evolutionary concepts. To explore practitioners’ understanding of evolutionary concepts, it is necessary to consider how they might apply explicit and implicit knowledge to their management decisions. Using an online survey, we asked Australian practitioners to respond to 2 common management scenarios in which there is strong evidence that managing genetic diversity can improve outcomes: managing small, isolated populations and sourcing seeds for restoration projects. In describing their approach to these scenarios, practitioners demonstrated a stronger understanding of the effective management of genetic diversity than the definitions of the relevant concepts. However, their management of genetic diversity within small populations was closer to best practice than for restoration projects. Moreover, the risks practitioners described in implementing best practice management were more likely to affect their approach to restoration than translocation projects. These findings provide evidence that strategies to build the capacity of practitioners to manage genetic diversity should focus on realistic management scenarios. Given that practitioners recognize the importance of adapting their practices and the strong evidence for the benefits of actively managing genetic diversity, there is hope that better engagement by evolutionary biologists with practitioners could facilitate significant shifts toward evolutionarily enlightened management.     

东北过伐林灌木层物种多样性与林分因子的典型相关分析

研究林分特征尤其是经营上可以控制的因子对生物多样性的影响，将有助于制定合理的经营措施来维持和保护生物多样性，本文作者以我国东北过伐林区3种典型天然林类型为对象，采用典型相关分析方法，研究影响灌木层物种多样性的主要因子。结果表明：影响灌木层物种多样性的主要因子包括土壤含水率，树种多样性和林分密度；灌木层多样性组的变异被林分组第一典型变量解释的比例为68.32%,仍有31.68%的变异不能得到解释。     

An interval joint-probabilistic programming method for solid waste management: a case study for the city of Tianjin, China

Currently, environmental protection and resources conservation continue to be challenges faced by solid-waste managers in China. These challenges are being further compounded by rapid socioeconomic devel- opment and population growth associated with increased waste generation rates and decreased waste disposal capacities. In response to these challenges, an interval joint-probabilistic mixed-integer programming （IJMP） method is developed for supporting long-term planning of waste management activities in the city of Tianjin, which is one of the largest municipalities in the northern part of China. In the IJMP, joint probabilistic constraints are introduced into an interval-parameter mixed-integer programming framework, such that uncertainties presented in terms of interval values and random variables can be reflected. Moreover, a number of violation levels for the waste-management-capacity constraints are examined, which can facilitate in-depth analyses of tradeoffs among economic objective and system-failure risk. The results indicate that reasonable solutions have been generated. They are valuable for supporting the adjustment of the city＇s existing waste-management practices and the long- term planning of the city＇s waste-management facilities.     

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.     

Leaf-area index and light attenuation in rapidly expanding shrub thickets

There is increasing interest in the changes in ecosystem services that accompany the conversion of grasslands to shrub-dominated communities. Shrub structure and associated effects on the light environment may be especially important in affecting productivity and diversity. Leaf-area index (LAI) and understory light levels of Morella cerifera shrub thickets were assessed on Hog Island, Virginia, USA, at four sites along a soil chronosequence. LAI was estimated from annual leaf litter, with allometric models relating stem diameter to leaf area, with a portable integrating radiometer (LI-COR LAI-2000), and from photosynthetically active radiation (PAR) using the Beer-Lambert law. For the two youngest thickets, LAI estimates from leaf litter (approximately 10.0) approached levels often associated with tropical rain forest. Allometric models estimated LAI values at 9.8 and 12.5 for the same thickets. High LAI in thickets also results in high light attenuation. Light levels within thickets were as low as 0.7% of above-canopy PAR in the youngest thicket. These data suggest that M. cerifera shrub thickets have a very high potential for annual net primary production. Furthermore, extreme modification of the light environment, coupled with heavy shrub litter fall, may exclude potential competitors during thicket establishment and rapidly alter community structure and ecosystem function.     

Conservation decision-making in large state spaces

When looking for the best course of management decisions to efficiently conserve metapopulation systems, a classic approach in the ecology literature is to model the optimisation problem as a Markov decision process and find an optimal control policy using exact stochastic dynamic programming techniques. Stochastic dynamic programming is an iterative procedure that seeks to optimise a value function at each timestep by evaluating the benefits of each of the actions in each state of the system defined in the Markov decision process.Although stochastic dynamic programming methods provide an optimal solution to conservation management questions in a stochastic world, their applicability in metapopulation problems has always been limited by the so-called curse of dimensionality. The curse of dimensionality is the problem that adding new state variables inevitably results in much larger (often exponential) increases in the size of the state space, which can make solving superficially small problems impossible. The high computational requirements of stochastic dynamic programming methods mean that only simple metapopulation management problems can be analysed. In this paper we overcome the complexity burden of exact stochastic dynamic programming methods and present the benefits of an on-line sparse sampling algorithm proposed by Kearns, Mansour and Ng (2002). The algorithm is particularly attractive for problems with large state spaces as the running time is independent of the size of the state space of the problem. This appealing improvement is achieved at a cost: the solutions found are no longer guaranteed to be optimal.We apply the algorithm of Kearns et al. (2002) to a hypothetical fish metapopulation problem where the management objective is to maximise the number of occupied patches over the management time horizon. Our model has multiple management options to combat the threats of water abstraction and waterhole sedimentation. We compare the performance of the optimal solution to the results of the on-line sparse sampling algorithm for a simple 3-waterhole case. We find that three look-ahead steps minimises the error between the optimal solution and the approximation algorithm. This paper introduces a new algorithm to conservation management that provides a way to avoid the effects of the curse of dimensionality. The work has the potential to allow us to approximate solutions to much more complex metapopulation management problems in the future.     

Current Near‐to‐Nature Forest Management Effects on Functional Trait Composition of Saproxylic Beetles in Beech Forests

With the aim of wood production with negligible negative effects on biodiversity and ecosystem processes, a silvicultural practice of selective logging with natural regeneration has been implemented in European beech forests (Fagus sylvatica) during the last decades. Despite this near‐to‐nature strategy, species richness of various taxa is lower in these forests than in unmanaged forests. To develop guidelines to minimize the fundamental weaknesses in the current practice, we linked functional traits of saproxylic beetle species to ecosystem characteristics. We used continental‐scale data from 8 European countries and regional‐scale data from a large forest in southern Germany and forest‐stand variables that represented a gradient of intensity of forest use to evaluate the effect of current near‐to‐nature management strategies on the functional diversity of saproxylic beetles. Forest‐stand variables did not have a statistically significant effect on overall functional diversity, but they did significantly affect community mean and diversity of single functional traits. As the amount of dead wood increased the composition of assemblages shifted toward dominance of larger species and species preferring dead wood of large diameter and in advanced stages of decay. The mean amount of dead wood across plots in which most species occurred was from 20 to 60 m³/ha. Species occurring in plots with mean dead wood >60 m³/ha were consistently those inhabiting dead wood of large diameter and in advanced stages of decay. On the basis of our results, to make current wood‐production practices in beech forests throughout Europe more conservation oriented (i.e., promoting biodiversity and ecosystem functioning), we recommend increasing the amount of dead wood to >20 m³/ha; not removing dead wood of large diameter (50 cm) and allowing more dead wood in advanced stages of decomposition to develop; and designating strict forest reserves, with their exceptionally high amounts of dead wood, that would serve as refuges for and sources of saproxylic habitat specialists. Efectos Actuales del Manejo Casi Natural de Bosques sobre la Composición de Atributos Funcionales de Escarabajos Saproxílicos en Bosques de Haya     

Applying the dark diversity concept to nature conservation

Linking diversity to biological processes is central for developing informed and effective conservation decisions. Unfortunately, observable patterns provide only a proportion of the information necessary for fully understanding the mechanisms and processes acting on a particular population or community. We suggest conservation managers use the often overlooked information relative to species absences and pay particular attention to dark diversity (i.e., a set of species that are absent from a site but that could disperse to and establish there, in other words, the absent portion of a habitat‐specific species pool). Together with existing ecological metrics, concepts, and conservation tools, dark diversity can be used to complement and further develop conservation prioritization and management decisions through an understanding of biodiversity relativized by its potential (i.e., its species pool). Furthermore, through a detailed understanding of the population, community, and functional dark diversity, the restoration potential of degraded habitats can be more rigorously assessed and so to the likelihood of successful species invasions. We suggest the application of the dark diversity concept is currently an underappreciated source of information that is valuable for conservation applications ranging from macroscale conservation prioritization to more locally scaled restoration ecology and the management of invasive species.