Impact of the quality of climate models for modelling species occurrences in countries with poor climatic documentation: a case study from Bolivia

The quality of climate models has largely been overlooked as a possible source of uncertainty that may affect the outcomes of species distribution models, especially in the tropics, where comparatively few climatic stations are available. We compared the geographical discrepancies and potential conservation implications of using two different climate models (Saga and Worldclim) in combination with the species modelling approach Maxent in Bolivia. We estimated ranges of selected bird and fern species biogeographically restricted to either humid montane forest of the northern Bolivian Andes or seasonal dry tropical forests (in the Andes and southern lowlands). Saga and Worldclim predicted roughly similar climate patterns of temperature that were significantly correlated. Precipitation layers of both climate models were also roughly similar, but showed important differences. Species ranges estimated with Worldclim and Saga likewise produced different results. Ranges of species endemic to humid montane forests estimated with Saga had higher AUC (Area under the curve) values than those estimated with Worldclim, which for example predicted the occurrence of humid montane forest bird species near Lake Titicaca, an area that is clearly unsuitable for these species. Likewise, Worldclim overpredicted the occurrence of fern and bird species in the lowlands of the Chapare region and well south of the Andean Elbow, where more seasonal biomes occur. By contrast, Saga predictions were coherent with the known distribution of humid montane forests in the northern Bolivian Andes. Estimated ranges of species endemic to seasonal dry tropical forests predicted with Saga and Worldclim were not statistically different in most cases. However, detailed comparisons revealed that Saga was able to distinguish fragments of seasonal dry tropical forests in rain-shadow valleys of the northern Bolivian Andes, whereas Worldclim was not. These differences highlight the neglected influence of climate layers on modelling results and the importance of using the most accurate climate data available when modelling species distributions.     

Misspecification of within-area exposure distribution in ecological Poisson models

Ecological studies enable investigation of geographic variations in exposure to environmental variables, across groups, in relation to health outcomes measured on a geographic scale. Such studies are subject to ecological biases, including pure specification bias which arises when a nonlinear individual exposure-risk model is assumed to apply at the area level. Introduction of the within-area variance of exposure should induce a marked reduction in this source of ecological bias. Assuming several measurements per area of exposure and no confounding risk factors, we study the model including the within-area exposure variability when Gaussian within-area exposure distribution is assumed. The robustness is assessed when the within-area exposure distribution is misspecified. Two underlying exposure distributions are studied: the Gamma distribution and an unimodal mixture of two Gaussian distributions. In case of strong ecological association, this model can reduce the bias and improve the precision of the individual parameter estimates when the within-area exposure means and variances are correlated. These different models are applied to analyze the ecological association between radon concentration and childhood acute leukemia in France.

A review of recent developments in lake modelling

This paper reviews the lake models published the last five years, mainly in Ecological Modelling. The review shows that structurally dynamic modelling and coupling between hydrodynamic and ecological models are applied increasingly. A number of processes that have not been included in lake models before have been proposed. It has been shown that these additional processes in specific case studies are significant, for instance the competition between phytoplankton and macrophytes or cyanobacteria growth and growth of mussels. It is recommended to study these models for the development of models for case studies where these processes are relevant.     

Integrating selected ecological effects of mixed European beech–Norway spruce stands in bioeconomic modelling

The simplicity of many bioeconomic models has been criticised several times, due to their lack of realism resulting from a deterministic nature and a single-species focus. In this context it was interesting to test the financial sensitivity of bioeconomic modelling against fairly well documented ecological effects in mixed forests. For this purpose our study linked existing results of ecological research with bioeconomic modelling. The presented methodological approach could not only show the importance of considering ecological effects in bioeconomic models; it in fact enabled prioritising ecological research from a financial point of view.In a first step, the possible influence of the tree species mixture on forest stand resistance, productivity and timber quality was derived from existing studies. In a second step, the available Monte Carlo simulations for Norway spruce (Picea abies [L.] Karst.) and European beech (Fagus sylvatica L.), simulated under site conditions and risks typical of southern Germany, were extended by the mentioned ecological effects and then evaluated from a financial perspective.The results showed a clear influence of all tested ecological effects on the financial indicators, financial risk and return. While testing each ecological effect separately, an increased resistance against wind, snow and insect attacks had the greatest influence on financial risk and return. It over-proportionally enhanced the financial return while simultaneously the financial risk was reduced. In contrast, a degraded timber quality could eliminate the positive effect of risk compensation in mixed forests almost completely. The least influence on the financial indicators finally showed a changed volume growth in mixed forests.A combination of the separately tested ecological effects (increased resistance, changed volume growth and decreased timber quality), between both tree species, underlined the dominating importance of the stand resistance. The integration of ecological effects, induced by interdependent tree species, in our bioeconomic model resulted in significantly lower financial risk than ignoring these effects. Moreover, the financial return of mixed stand variants with a proportion of Norway spruce greater than 60% even exceeded that of the most profitable pure stand.In conclusion this paper clearly confirmed that ignoring ecological effects in bioeconomic models could lead to seriously biased financial results. While a changed volume growth proved rather to be of minor importance for European beech/Norway spruce stands, tree resistance and timber quality may change the financial results significantly.     

Representing general theoretical concepts in structural equation models: the role of composite variables

Structural equation modeling (SEM) holds the promise of providing natural scientists the capacity to evaluate complex multivariate hypotheses about ecological systems. Building on its predecessors, path analysis and factor analysis, SEM allows for the incorporation of both observed and unobserved (latent) variables into theoretically-based probabilistic models. In this paper we discuss the interface between theory and data in SEM and the use of an additional variable type, the composite. In simple terms, composite variables specify the influences of collections of other variables and can be helpful in modeling heterogeneous concepts of the sort commonly of interest to ecologists. While long recognized as a potentially important element of SEM, composite variables have received very limited use, in part because of a lack of theoretical consideration, but also because of difficulties that arise in parameter estimation when using conventional solution procedures. In this paper we present a framework for discussing composites and demonstrate how the use of partially-reduced-form models can help to overcome some of the parameter estimation and evaluation problems associated with models containing composites. Diagnostic procedures for evaluating the most appropriate and effective use of composites are illustrated with an example from the ecological literature. It is argued that an ability to incorporate composite variables into structural equation models may be particularly valuable in the study of natural systems, where concepts are frequently multifaceted and the influence of suites of variables are often of interest.     

Using data augmentation via the Gibbs Sampler to incorporate missing covariate structure in linear models for ecological assessments

Missing covariate values in linear regression models can be an important problem facing environmental researchers. Existing missing value treatment methods such as Multiple Imputation (MI), the EM algorithm and Data Augmentation (DA) have the assumption that both observed and unobserved data come from the same distribution, most commonly a multivariate normal or a conditionally multivariate normal family. These methods do try to incorporate the missing data mechanism and rely on the assumption of Missing At Random (MAR). We present a DA method which does not rely on the MAR assumption and can model missing data mechanisms and covariate structure. This method utilizes the Gibbs Sampler as a tool for incorporating these structures and mechanisms. We apply this method to an ecological data set that relates fish condition to environmental variables. Notice that the presented DA method detects relationships that are not detected when other missing data methods are employed.

Combining state and transition models with dynamic Bayesian networks

Bashari et al. (2009) propose combining state and transition models (STMs) with Bayesian networks for decision support tools where the focus is on modelling the system dynamics. There is already an extension of Bayesian networks - so-called dynamic Bayesian networks (DBNs) - for explicitly modelling systems that change over time, that has also been applied in ecological modelling. In this paper we propose a combination of STMs and DBNs that overcome some of the limitations of Bashari et al.’s approach including providing an explicit representation of the next state, while retaining its advantages, such an the explicit representation of transitions. We then show that the new model can be applied iteratively to predict into the future consistently with different time frames. We use Bashari et al.’s rangeland management problem as an illustrative case study. We present a comparative complexity analysis of the different approaches, based on the structure inherent in the problem being modelled. This analysis showed that any models that explicitly represent all the transitions only remain tractable when there are natural constraints in the domain. Thus we recommend modellers should analyse these aspects of their problem before deciding whether to use the framework.     

Examining the relationship between ecosystem structure and function using structural equation modelling: A case study examining denitrification potential in restored wetland soils

An ongoing debate in ecology is the relationship between community or ecosystem structure and function. This relationship is particularly important in restored ecosystems because it is often assumed that restoring ecosystem structure will restore ecosystem functioning, but this assumption is frequently not tested. In this study, we used a novel application of structural equation modelling (SEM) to examine the relationship between ecosystem structure and function. To exemplify how to apply SEM to explore this relationship, we used a case study examining soil controls on denitrification potential (DNP) in two restored wetlands. Our objectives were to examine (1) whether both restored wetland soil ecosystems had similar relationships among soils variables (i.e. similar soil ecosystem structure) and (2) whether the soil variables driving denitrification potential (DNP) were similar at both sites (i.e. the soil ecosystems were functioning in a similar manner). Using the unique ability of SEM to test model structure, we proposed a SEM to represent the soil ecosystem and tested this structure with field data. We determined that the same model structure was supported by data from both systems suggesting that the two restored wetland systems had similar soil ecosystem structure. To test whether both ecosystems were functioning in a similar way, we examined the parameters of each model. We determined that the drivers of DNP function were not the same at both sites. Higher soil organic matter was the most important predictor of higher DNP at both sites. However, the other significant relationships among soils variables were different at each system indicating that the soils were not functioning in exactly the same way at each site. Overall, these results suggest that the restoration of ecosystem structure may not necessarily ensure the restoration of ecosystem functioning. In this study we capitalize on an inherent feature of SEM, the ability to test model structure, to test a fundamental ecological question. This novel approach is widely applicable to other systems and improves our understanding of the general relationship between ecosystem structure and function.     

Common challenges for ecological modelling: Synthesis of facilitated discussions held at the symposia organized for the 2009 conference of the International Society for Ecological Modelling in Quebec City, Canada, (October 6-9, 2009)

The eleven symposia organized for the 2009 conference of the International Society for Ecological Modelling (ISEM 2009) held in Quebec City, Canada, October 6-9, 2009, included facilitated discussion sessions following formal presentations. Each symposium focused on a specific subject, and all the subjects could be classified into three broad categories: theoretical development, population dynamics and ecosystem processes. Following discussions with the symposia organizers, which indicated that they all shared similar issues and concerns, the facilitated discussions were task-oriented around four basic questions: (1) key challenges in the research area, (2) generating and sharing new ideas, (3) improving collaboration and networking, and (4) increasing visibility to decision-makers, partners and clients. Common challenges that emerged from the symposia included the need for improved communication and collaboration among different academic disciplines, further progress in both theoretical and practical modelling approaches, and accentuation of technology transfer. Regarding the generation and sharing of new ideas, the main issue that emerged was the type of positive interactions that should be encouraged among potential collaborators. The usefulness of the Internet, particularly for the sharing of open-source software and conducting discussion forums, was highlighted for improving collaboration and networking. Several communication tools are available today, and it is important for modellers to use them more intensively. Visibility can be increased by publishing professional newsletters, maintaining informal contacts with the public, organizing educational sessions in primary and secondary schools, and developing simplified analytical frameworks and pilot studies. Specific issues raised in each symposium are also discussed.     

Application of eco-exergy for assessment of ecosystem health and development of structurally dynamic models

Eco-exergy has been widely used in the assessment of ecosystem health, parameter estimations, calibrations, validations and prognoses. It offers insights into the understanding of ecosystem dynamics and disturbance-driven changes. Particularly, structurally dynamic models (SDMs), which are developed using eco-exergy as the goal function, have been applied in explaining and exploring ecosystem properties and changes in community structure driven by biotic and abiotic factors. In this paper, we review the application of eco-exergy for the assessment of ecosystem health and development of structurally dynamic models (SDMs). The limitations and possible future applications of the approach are also addressed.     

Revisiting the evolution of ecological specialization, with emphasis on insect-plant interactions

Ecological specialization is a fundamental and well-studied concept, yet its great reach and complexity limit current understanding in important ways. More than 20 years after the publication of D. J. Futuyma and G. Moreno's oft-cited, major review of the topic, we synthesize new developments in the evolution of ecological specialization. Using insect-plant interactions as a model, we focus on important developments in four critical areas: genetic architecture, behavior, interaction complexity, and macroevolution. We find that theory based on simple genetic trade-offs in host use is being replaced by more subtle and complex pictures of genetic architecture, and multitrophic interactions have risen as a necessary framework for understanding specialization. A wealth of phylogenetic data has made possible a more detailed consideration of the macroevolutionary dimension of specialization, revealing (among other things) bidirectionality in transitions between generalist and specialist lineages. Technological advances, including genomic sequencing and analytical techniques at the community level, raise the possibility that the next decade will see research on specialization spanning multiple levels of biological organization in non-model organisms, from genes to populations to networks of interactions in natural communities. Finally, we offer a set of research questions that we find to be particularly pressing and fruitful for future research on ecological specialization.     

Spatio-temporal modelling of ground vegetation development in mountain spruce forests

More complex models of forest ecosystems are required to understand how land-cover changes can impact vegetation dynamics and spatial pattern. In order to document spatio-temporal modelling abilities, the observations conducted in the declined climax mountain Norway spruce forest during the recovery period (1995-2006) are used for simulation and spatial analysis in the GIS environment. The developed spatio-temporal model is used for simulation of forest vegetation dynamics in a mountain spruce forest in the framework of regeneration processes after stress from air pollution. In order to explore the spatial and temporal phenomena of regeneration processes, the spatio-temporal model is based on a large set of ordinary differential equations that solve dynamic processes in sets of microsites arranged in grids for each ground vegetation species and each age group of Norway spruce seedlings. The spatial extent of the explored site is composed of a set of 50 × 50 microsites. Each microsite is represented by a square with dimensions of 1 m × 1 m. The presented simulation studies are mainly focused on seedlings from the seed year 1992, in order to explore the longest monitored time series of survival. It is based on exponential growth models that are related to the environmental conditions for each microsite. The canopy gaps based on estimates of the local crown projected area, the soil type layer, and the dominant grass density are used to provide case simulation studies. The first case study simulates the influence of microsite positions in relation to the local tree crown projections on the survival of spruce seedlings. It is assumed that the density of the trees is the main factor that determines the light and heat supply to the ground level of the Norway spruce seedlings. The second case study extends the previous study to include terms that determine the growth ratio in dependence on the crown projection area. The third case study provides further extensions in order to simulate growth ratio relations to the local soil type. The fourth case study demonstrates the local influence of the dominant grasses, such as Avenella flexuosa and Calamagrostis villosa, on the natural regeneration of Norway spruce. Starting from the conditions at the sites before the recovery period, the case simulation studies are able to project the short-term succession for a regeneration decade and the approximate long-term development. In addition to the standard simulation procedures based on solution of ordinary differential equations, spatio-temporal modelling in the GIS environment is able to provide spatial data management, analysis and visualization of the data.     

Model-based analysis of the influence of ecological processes on forest point pattern formation—A case study

Many different spatio-temporal individual-based models (IBM) for forests have been developed for studying the development of trees in space and time. Such models typically depend on various numerical parameters that represent the ecological processes of growth (G), inter-plant competition (C) and birth-and-death (B&D; also called regeneration and mortality). Until now little work has been done to systematically trace the influence of these processes and their model parameters on the spatial structure of forest ecosystems.This paper attempts to fill this gap by addressing an important aspect of forest structure, spatial variability, characterised by the mark variogram as a summary characteristic. The model used was inspired by components of various well-established IBMs including a shot-noise competition field. Time series data from monospecies forests in three different countries of the northern hemisphere provided ecological reference scenarios. Though a case study, the paper's methodology is rather general and can be applied to any model and forest ecosystem.Methods of sensitivity analysis revealed that only a small number of model parameters is crucial for forming spatial variability. Particularly important is the range of competition between trees; with increasing range the variability increases. Growth processes have considerable importance particularly with short observation periods and in young forests, whereas mortality processes become more influential in the long-term. Naturally, these statements depend upon the initial structure and on the length of the observation period.     

Ecological network determination of sectoral linkages, utility relations and structural characteristics on urban ecological economic system

Analyzing the structure and functioning of the urban system revealed ways to optimize its structure by adjusting the relationships among compartments, thereby demonstrating how ecological network analysis can be used in urban system research. Based on the account of the extended exergy utilization in the sector of urban socio-economic system, which is considered as the composition of extraction (Ex), conversion (Co), agriculture (Ag), industry (In), transportation (Tr), tertiary (Te) and households (Do) sectors, an urban ecological network model is constructed to gain insights into the economic processes oriented to sustainable urban development. Taking Beijing city as the case, the network accounting and related ecological evaluation of a practical urban economy are carried out in this study in the light of flux, efficiency, utility and structure analysis. The results showed that a large quantity of energy and resources have to be consumed to maintain the structure and function of a city. The thermodynamic efficiencies of individual sector in Beijing remain at a low level. The social system in Beijing is a highly competitive network, and there are 8 competitive relations and only two mutualistic ones. The Domestic and Agricultural sector are the major controlling factors of the system. Moreover, the assessment results of Beijing are compared with the other three socio-economic systems, Norway, UK and Italy, and the ecological network function and structure comparisons are correspondingly illuminated and discussed. The conclusions indicate that the exergy-based network analysis can be refined to become an integrative tool for evaluation, policy-making and regulation for urban socio-economic system management concerning structure and efficiency at urban levels.     

Implications of ecological data constraints for integrated policy and livelihoods modelling: An example from East Kalimantan, Indonesia

Policy and human livelihoods modelling increasingly demands integrated research which requires ecological expertise. However, contributions from ecologists are often based on sparse data. Rather than discounting such data, in this paper we demonstrate how ecological modelling can effectively contribute to the development of policy recommendations in spite of data constraints. In a petrol subsidy analysis in East Kalimantan, Indonesia, we accounted for ecological data uncertainty by (a) assuming large parameter value ranges and (b) conducting a robustness test for policy recommendations. In addition to data scarcity, counter-intuitive results emerged emphasising the need for model validation. These counter-intuitive results indicated that decreasing petrol prices led to increased poverty. This informed a policy recommendation to prevent the reduction of petrol prices below IDR 5500 per litre. Using two key livelihood resources (fish and honey), we found that while a traditional sensitivity analysis suggested highly robust results, a robustness test indicated that policy recommendations would change if the incorrectness of parameter values approached 50%. The results show that ecological modelling can contribute effectively in spite of sparse data to guide policy, as well as identifying future research priorities.     

华南退化生态系统三种典型生态恢复模式的小气候效应研究

为了评价南亚热带典型退化生态系统典型生态恢复模式的小气候调节效应,从而为退化生态系统生态恢复方式和造林树种的选择提供参照,作者在广东鹤山森林生态系统国家野外科学观测研究站的3种典型生态恢复模式样地,自然恢复草坡、马尾松林（Pinus massoniana）、马占相思林（Acacia mangium）中安装了HOBO小气候仪,对光辐射、风速风向、降水、土壤含水量、地温、气温等小气候指标进行为期1年的自动观测,并进行了对比分析,结果表明,（1）华南退化生态系统3种典型生态恢复模式具有不同的小气候效应,在林间温度调节方面,人工林和草坡的平均林间温度相差不大,但草坡的最低、最高温度均比人工林低和高。人工林的林间温度变化较草坡小,具有更好的保温调节作用。对比2种人工林,不管是平均温度还是最高温度马占相思林都略大于针叶林,而二者最低温度相差不明显。针叶林的保温调节作用略优于阔叶的马占相思林;（2）在土壤温度方面,地表温度全年基本都表现为草坡〉马占相思林〉针叶林,草坡的地表温度的波动远大于2种人工林;全年20 cm土壤温度3─12月都表现为草坡〉马占相思林〉针叶林,1─2月相反,草坡20 cm土层的土壤温度波动相对较大,人工林的波动很小。（3）3种恢复模式中,自然恢复草坡的辐射强度明显高于2种人工林,年辐射总量分别马占相思林和针叶林的1.9和5.8倍,马占相思林的年辐射量为针叶林的3倍。人工林,特别是乡土的针叶林能给林下生物构建更为稳定、适中的辐射环境。（4）人工林的平均林间风速、最大阵风风速均少于草坡,针叶林的风速小于阔叶林,针叶林降低风速的效果好于相思林和草坡。（5）人工林的林间相对湿度均高于草坡,针叶林的林间空气湿度略大于相思林,针叶林的保湿效果更好。在退化生态系统恢复过程中?     

RIVPACS models for predicting the expected macroinvertebrate fauna and assessing the ecological quality of rivers

The European Union Water Framework Directive recognises the need for and value of biological monitoring. This paper reviews the modelling approach known as River Invertebrate Prediction and Classification System (RIVPACS for assessing the ecological quality of river sites using macroinvertebrate sampling. The RIVPACS philosophy is to develop statistical relationships between the fauna and the environmental characteristics of a large set of high quality reference sites which can be used to predict the macroinvertebrate fauna to be expected at any site in the absence of pollution or other environmental stress. The observed fauna at new test sites can then be compared with their site-specific expected fauna to derive indices of ecological quality. All methodological decisions in any such model development have implications for the reliability, precision and robustness of any resulting indices for assessing the ecological quality and ecological grade (‘status’) of individual river stretches. The choice of reference sites and environmental predictor variables, the site classification and discrimination methods, the estimation of the expected fauna, and indices for comparing the agreement, or lack of it, between the observed and expected fauna, are all discussed. The indices are assessed on the reference sites and on a separate test set of 340 sites, which are subject to a wide range of types and degrees of impairment.     

Integrated ecological models: simulation of socio-cultural constraints on ecological dynamics

We suggest that general systems theory provides a common philosophical basis for dialog between ecological and social scientists interested in studying the reciprocal interactions of humans and their environment. We (1) provide a synopsis of the ‘systems approach' as viewed from the biological and social sciences, respectively; (2) develop a conceptual framework for the explicit linking of ecological and social variables, and (3) draw upon game theoretic results of the Prisoner's Dilemma to represent human decision-making quantitatively in a model that simulates the tragedy of the commons. The model consists of 5 submodels that represent the ‘observers world' and each of 4 ‘participant's worlds.' The observer's-world represents the decision processes, either Optimize or Tit-for-Tat, by which each of 2 users decides to add or remove animals. The 4 perceived worlds represent hypothetical situations in which (1) persons A and B both add an animal; (2) A adds and B does not; (3) B adds and A does not, and (4) neither A nor B add an animal. Simulation results indicate that net worth of the community and of each person individually under Tit-for-Tat is more than double the net worth attained under Optimize. Replacement of the static payoff matrix assumed in game theory with a dynamic quantitative model illustrates how ‘norm-based' approaches to ecosystem management can outperform optimizing approaches based on predicted outcomes. Although ‘soft systems' techniques may better help decision-makers reach norm-based agreements on ecosystem management, quantitative models have more explanatory value, and if developed sufficiently such models could incorporate complex social dimensions that would enhance further their explanatory value.     

The People and Landscape Model (PALM): Towards full integration of human decision-making and biophysical simulation models

A model for simulating resource flows in a rural subsistence community is described. The People and Landscape Model (PALM) consists of a number of agents representing households, the landscape, and livestock. The landscape is made up of a number of homogeneous land units, or ‘fields’, each represented by an object containing data, methods and properties relevant to the field. Each field object consists of a number of soil layer objects, each of which contains routines to calculate its water balance and carbon and nitrogen dynamics. Organic matter decomposition is simulated by a version of the CENTURY model, while water and nitrogen dynamics are simulated by versions of the routines in the DSSAT crop models. The soil processes are simulated continuously, and vegetation types (crops, weeds, trees) can come and go in a field depending on its management. Crop growth and development are simulated by a generic model based on the DSSAT crop models, and which can be parameterised for different crops. Similarly, livestock growth and resource use is simulated by a generic model which can be parameterised for buffalo, cows, goats, sheep, chickens and pigs.     

On the consequences of aggregation and balancing of networks on system properties derived from ecological network analysis

In the ecological network analysis (ENA) of complex flow food webs the assumption is often made that the models characterizing the flows and stocks of ecosystems occur in a steady state where inflows equals outflows. An assessment of the system indices derived from ENA of six balanced and unbalanced system models, respectively, indicate to differences between indices. The aggregation of highly articulated flow models into models with fewer compartments also has drastic effects on the system metrics, particularly on the information indices.