Ecological-economic modeling for biodiversity management: Potential, pitfalls, and prospects

Ecologists and economists both use models to help develop strategies for biodiversity management. The practical use of disciplinary models, however, can be limited because ecological models tend not to address the socioeconomic dimension of biodiversity management, whereas economic models tend to neglect the ecological dimension. Given these shortcomings of disciplinary models, there is a necessity to combine ecological and economic knowledge into ecological-economic models. It is insufficient if scientists work separately in their own disciplines and combine their knowledge only when it comes to formulating management recommendations. Such an approach does not capture feedback loops between the ecological and the socioeconomic systems. Furthermore, each discipline poses the management problem in its own way and comes up with its own most appropriate solution. These disciplinary solutions, however are likely to be so different that a combined solution considering aspects of both disciplines cannot be found. Preconditions for a successful model-based integration of ecology and economics include (1) an in-depth knowledge of the two disciplines, (2) the adequate identification and framing of the problem to be investigated, and (3) a common understanding between economists and ecologists of modeling and scale. To further advance ecological-economic modeling the development of common benchmarks, quality controls, and refereeing standards for ecological-economic models is desirable.

Precautionary principles: a jurisdiction-free framework for decision-making under risk

Fundamental principles of precaution are legal maxims that ask for preventive actions, perhaps as contingent interim measures while relevant information about causality and harm remains unavailable, to minimize the societal impact of potentially severe or irreversible outcomes. Such principles do not explain how to make choices or how to identify what is protective when incomplete and inconsistent scientific evidence of causation characterizes the potential hazards. Rather, they entrust lower jurisdictions, such as agencies or authorities, to make current decisions while recognizing that future information can contradict the scientific basis that supported the initial decision. After reviewing and synthesizing national and international legal aspects of precautionary principles, this paper addresses the key question: How can society manage potentially severe, irreversible or serious environmental outcomes when variability, uncertainty, and limited causal knowledge characterize their decision-making? A decision-analytic solution is outlined that focuses on risky decisions and accounts for prior states of information and scientific beliefs that can be updated as subsequent information becomes available. As a practical and established approach to causal reasoning and decision-making under risk, inherent to precautionary decision-making, these (Bayesian) methods help decision-makers and stakeholders because they formally account for probabilistic outcomes, new information, and are consistent and replicable. Rational choice of an action from among various alternatives-defined as a choice that makes preferred consequences more likely-requires accounting for costs, benefits and the change in risks associated with each candidate action. Decisions under any form of the precautionary principle reviewed must account for the contingent nature of scientific information, creating a link to the decision-analytic principle of expected value of information (VOI), to show the relevance of new information, relative to the initial ( and smaller) set of data on which the decision was based. We exemplify this seemingly simple situation using risk management of BSE. As an integral aspect of causal analysis under risk, the methods developed in this paper permit the addition of non-linear, hormetic dose-response models to the current set of regulatory defaults such as the linear, non-threshold models. This increase in the number of defaults is an important improvement because most of the variants of the precautionary principle require cost-benefit balancing. Specifically, increasing the set of causal defaults accounts for beneficial effects at very low doses. We also show and conclude that quantitative risk assessment dominates qualitative risk assessment, supporting the extension of the set of default causal models.

Advantage of single-trial models for response to selection in wheat breeding multi-environment trials

An investigation was conducted to evaluate the impact of experimental designs and spatial analyses (single-trial models) of the response to selection for grain yield in the northern grains region of Australia (Queensland and northern New South Wales). Two sets of multi-environment experiments were considered. One set, based on 33 trials conducted from 1994 to 1996, was used to represent the testing system of the wheat breeding program and is referred to as the multi-environment trial (MET). The second set, based on 47 trials conducted from 1986 to 1993, sampled a more diverse set of years and management regimes and was used to represent the target population of environments (TPE). There were 18 genotypes in common between the MET and TPE sets of trials. From indirect selection theory, the phenotypic correlation coefficient between the MET and TPE single-trial adjusted genotype means [r(p(MT))] was used to determine the effect of the single-trial model on the expected indirect response to selection for grain yield in the TPE based on selection in the MET. Five single-trial models were considered: randomised complete block (RCB), incomplete block (IB), spatial analysis (SS), spatial analysis with a measurement error (SSM) and a combination of spatial analysis and experimental design information to identify the preferred (PF) model. Bootstrap-resampling methodology was used to construct multiple MET data sets, ranging in size from 2 to 20 environments per MET sample. The size and environmental composition of the MET and the single-trial model influenced the r(p(MT)). On average, the PF model resulted in a higher r(p(MT)) than the IB, SS and SSM models, which were in turn superior to the RCB model for MET sizes based on fewer than ten environments. For METs based on ten or more environments, the r(p(MT)) was similar for all single-trial models.

Modelling pre-clearing vegetation distribution using GIS-integrated statistical, ecological and data models: A case study from the wet tropics of Northeastern Australia

Traditional vegetation mapping methods use high cost, labour-intensive aerial photography interpretation. This approach can be subjective and is limited by factors such as the extent of remnant vegetation, and the differing scale and quality of aerial photography over time. An alternative approach is proposed which integrates a data model, a statistical model and an ecological model using sophisticated Geographic Information Systems (GIS) techniques and rule-based systems to support fine-scale vegetation community modelling. This approach is based on a more realistic representation of vegetation patterns with transitional gradients from one vegetation community to another. Arbitrary, though often unrealistic, sharp boundaries can be imposed on the model by the application of statistical methods. This GIS-integrated multivariate approach is applied to the problem of vegetation mapping in the complex vegetation communities of the Innisfail Lowlands in the Wet Tropics bioregion of Northeastern Australia. The paper presents the full cycle of this vegetation modelling approach including sampling sites, variable selection, model selection, model implementation, internal model assessment, model prediction assessments, models integration of discrete vegetation community models to generate a composite pre-clearing vegetation map, independent data set model validation and model prediction's scale assessments. An accurate pre-clearing vegetation map of the Innisfail Lowlands was generated (0.83r(2)) through GIS integration of 28 separate statistical models. This modelling approach has good potential for wider application, including provision of. vital information for conservation planning and management; a scientific basis for rehabilitation of disturbed and cleared areas; a viable method for the production of adequate vegetation maps for conservation and forestry planning of poorly-studied areas. (c) 2006 Elsevier B.V. All rights reserved.

An analysis of changing management roles in small Australian services exporters in response to the stages in industry development

Life cycle models have become important in explaining the changing size structure of firms based on the carrying capacity of regions or industries. In particular, the population ecology model predicts stages of growth, maturity and eventually decline in the number of firms in an industry. There has been criticism of such models because of their focus on external variables as pre-determinants of the potential for enterprise development. This paper attempts to reconcile the external focus of the population ecology model with relevant internal management factors in enterprise development. A survey was conducted of Australian services exporters, and the results not only confirm the existence of four separate life cycle stages in the population ecology model, but also identify the external and internal variables that are strategically relevant at each of the stages. The findings provide potentially useful information in a range of contexts including the design of small business assistance as well a providing “guide posts” to entrepreneurs engaged in enterprise development.

Analysis of Melanoma Onset: Assessing Familial Aggregation by Using Estimating Equations and Fitting Variance Components via Bayesian Random Effects Models

We investigate whether relative contributions of genetic and shared environmental factors are associated with an increased risk in melanoma. Data from the Queensland Familial Melanoma Project comprising 15,907 subjects arising from 1912 families were analyzed to estimate the additive genetic, common and unique environmental contributions to variation in the age at onset of melanoma. Two complementary approaches for analyzing correlated time-to-onset family data were considered: the generalized estimating equations (GEE) method in which one can estimate relationship-specific dependence simultaneously with regression coefficients that describe the average population response to changing covariates; and a subject-specific Bayesian mixed model in which heterogeneity in regression parameters is explicitly modeled and the different components of variation may be estimated directly. The proportional hazards and Weibull models were utilized, as both produce natural frameworks for estimating relative risks while adjusting for simultaneous effects of other covariates. A simple Markov Chain Monte Carlo method for covariate imputation of missing data was used and the actual implementation of the Bayesian model was based on Gibbs sampling using the free ware package BUGS. In addition, we also used a Bayesian model to investigate the relative contribution of genetic and environmental effects on the expression of naevi and freckles, which are known risk factors for melanoma.

Oxygen sensors and energy sensors act synergistically to achieve a graded alteration in gene expression: Consequences for assessing the level of neuroprotection in response to stressors

Changes in gene expression are associated with switching to an autoprotected phenotype in response to environmental and physiological stress. Ubiquitous molecular chaperones from the heat shock protein (HSP) superfamily confer neuronal protection that can be blocked by antibodies. Recent research has focused on the interactions between the molecular sensors that affect the increased expression of neuroprotective HSPs above constitutive levels. An examination of the conditions under which the expression of heat shock protein 70 (Hsp70) was up regulated in a hypoxia and anoxia tolerant tropical species, the epaulette shark (Hemiscyllium ocellatum), revealed that up-regulation was dependent on exceeding a stimulus threshold for an oxidative stressor. While hypoxic-preconditioning confers neuroprotective changes, there was no increase in the level of Hsp70 indicating that its increased expression was not associated with achieving a neuroprotected state in response to hypoxia in the epaulette shark. Conversely, there was a significant increase in Hsp70 in response to anoxic-preconditioning, highlighting the presence of a stimulus threshold barrier and raising the possibility that, in this species, Hsp70 contributes to the neuroprotective response to extreme crises, such as oxidative stress. Interestingly, there was a synergistic effect of coincident stressors on Hsp70 expression, which was revealed when metabolic stress was superimposed upon oxidative stress. Brain energy charge was significantly lower when adenosine receptor blockade, provided by treatment with aminophylline, was present prior to the final anoxic episode, under these circumstances, the level of Hsp70 induced was significantly higher than in the pair-matched saline treated controls. An understanding of the molecular and metabolic basis for neuroprotective switches, which result in an up-regulation of neuroprotective Hsp70 expression in the brain, is needed so that intervention strategies can be devised to manage CNS pathologies and minimise damage caused by ischemia and trauma. In addition, the current findings indicate that measurements of HSP expression per se may provide a useful correlate of the level of neuroprotection achieved in the switch to an autoprotected phenotype.

Expanding the scope of the social response context model

Descriptive models of social response are concerned with identifying and discriminating between different types of response to social influence. In a previous article (Nail, MacDonald, & Levy, 2000), the authors demonstrated that 4 conceptual dimensions are necessary to adequately distinguish between such phenomena as conformity, compliance, contagion, independence, and anticonformity in a single model. This article expands the scope of the authors' 4-dimensional approach by reviewing selected experimental and cultural evidence, further demonstrating the integrative power of the model. This review incorporates political psychology, culture and aggression, self-persuasion, group norms, prejudice, impression management, psychotherapy, pluralistic ignorance, bystander intervention/nonintervention, public policy, close relationships, and implicit attitudes.

Using the canonical modelling approach to simplify the simulation of function in functional-structural plant models

Functional-structural plant models that include detailed mechanistic representation of underlying physiological processes can be expensive to construct and the resulting models can also be extremely complicated. On the other hand, purely empirical models are not able to simulate plant adaptability and response to different conditions. In this paper, we present an intermediate approach to modelling plant function that can simulate plant response without requiring detailed knowledge of underlying physiology. Plant function is modelled using a 'canonical' modelling approach, which uses compartment models with flux functions of a standard mathematical form, while plant structure is modelled using L-systems. Two modelling examples are used to demonstrate that canonical modelling can be used in conjunction with L-systems to create functional-structural plant models where function is represented either in an accurate and descriptive way, or in a more mechanistic and explanatory way. We conclude that canonical modelling provides a useful, flexible and relatively simple approach to modelling plant function at an intermediate level of abstraction.

Do open-cycle hatcheries relying on tourism conserve sea turtles? Sri Lankan developments and economic-ecological considerations

By combining economic analysis of markets with ecological parameters, this article considers the role that tourism-based sea turtle hatcheries (of an open-cycle type) can play in conserving populations of sea turtles. Background is provided on the nature and development of such hatcheries in Sri Lanka. The modeling facilitates the assessment of the impacts of turtle hatcheries on the conservation of sea turtles and enables the economic and ecological consequences of tourism, based on such hatcheries, to be better appreciated. The results demonstrate that sea turtle hatcheries serving tourists can make a positive contribution to sea turtle conservation, but that their conservation effectiveness depends on the way they are managed. Possible negative effects are also identified. Economic market models are combined with turtle population survival relationships to predict the conservation impact of turtle hatcheries and their consequence for the total economic value obtained from sea turtle populations.

Roles of social pain and defense mechanisms in response to social exclusion: Reply to Panksepp (2005) and Coff (2005)

In comments on G. MacDonald and M. R. Leary (2005), J. Panksepp (2005) argued for more emphasis on social pain mechanisms, whereas P. J. Corr (2005) argued for more emphasis on physical defense mechanisms. In response to the former, the authors clarify their positions on the topics of anger, the usefulness of rat models, the role of analgesic mechanisms, and basic motivational processes. In response to the latter, the authors clarify their positions on the topics of the relation of social exclusion to fear, the value of the pain affect construct, and the nature of the social pain experience. The authors conclude that consideration of the roles of both social pain and defense mechanisms is essential to best understand human response to social exclusion.

Designs for generalized linear models with several variables and model uncertainty

Standard factorial designs sometimes may be inadequate for experiments that aim to estimate a generalized linear model, for example, for describing a binary response in terms of several variables. A method is proposed for finding exact designs for such experiments that uses a criterion allowing for uncertainty in the link function, the linear predictor, or the model parameters, together with a design search. Designs are assessed and compared by simulation of the distribution of efficiencies relative to locally optimal designs over a space of possible models. Exact designs are investigated for two applications, and their advantages over factorial and central composite designs are demonstrated.

Effect of rainfall as a component of climate change on estuarine fish production in Queensland, Australia

The speculation that climate change may impact on sustainable fish production suggests a need to understand how these effects influence fish catch on a broad scale. With a gross annual value of A$ 2.2 billion, the fishing industry is a significant primary industry in Australia. Many commercially important fish species use estuarine habitats such as mangroves, tidal flats and seagrass beds as nurseries or breeding grounds and have lifecycles correlated to rainfall and temperature patterns. Correlation of catches of mullet (e.g. Mugil cephalus) and barramundi (Lates calcarifer) with rainfall suggests that fisheries may be sensitive to effects of climate change. This work reviews key commercial fish and crustacean species and their link to estuaries and climate parameters. A conceptual model demonstrates ecological and biophysical links of estuarine habitats that influences capture fisheries production. The difficulty involved in explaining the effect of climate change on fisheries arising from the lack of ecological knowledge may be overcome by relating climate parameters with long-term fish catch data. Catch per unit effort (CPUE), rainfall, the Southern Oscillation Index (SOI) and catch time series for specific combinations of climate seasons and regions have been explored and surplus production models applied to Queensland's commercial fish catch data with the program CLIMPROD. Results indicate that up to 30% of Queensland's total fish catch and up to 80% of the barramundi catch variation for specific regions can be explained by rainfall often with a lagged response to rainfall events. Our approach allows an evaluation of the economic consequences of climate parameters on estuarine fisheries. thus highlighting the need to develop forecast models and manage estuaries for future climate chan e impact by adjusting the quota for climate change sensitive species. Different modelling approaches are discussed with respect to their forecast ability. (c) 2006 Elsevier Ltd. All rights reserved.

Onset of sheath extension and duration of lamina extension are major determinants of the response of maize lamina length to plant density

Background and Aims Plants regulate their architecture strongly in response to density, and there is evidence that this involves changes in the duration of leaf extension. This questions the approximation, central in crop models, that development follows a fixed thermal time schedule. The aim of this research is to investigate, using maize as a model, how the kinetics of extension of grass leaves change with density, and to propose directions for inclusion of this regulation in plant models. • Methods Periodic dissection of plants allowed the establishment of the kinetics of lamina and sheath extension for two contrasting sowing densities. The temperature of the growing zone was measured with thermocouples. Two-phase (exponential plus linear) models were fitted to the data, allowing analysis of the timing of the phase changes of extension, and the extension rate of sheaths and blades during both phases. • Key Results The duration of lamina extension dictated the variation in lamina length between treatments. The lower phytomers were longer at high density, with delayed onset of sheath extension allowing more time for the lamina to extend. In the upper phytomers—which were shorter at high density—the laminae had a lower relative extension rate (RER) in the exponential phase and delayed onset of linear extension, and less time available for extension since early sheath extension was not delayed. • Conclusions The relative timing of the onset of fast extension of the lamina with that of sheath development is the main determinant of the response of lamina length to density. Evidence is presented that the contrasting behaviour of lower and upper phytomers is related to differing regulation of sheath ontogeny before and after panicle initiation. A conceptual model is proposed to explain how the observed asynchrony between lamina and sheath development is regulated.