Helen M. Regan

A TAXONOMY AND TREATMENT OF UNCERTAINTY FOR ECOLOGY AND CONSERVATION BIOLOGY

Uncertainty is pervasive in ecology where the difficulties of dealing with sources of uncertainty are exacerbated by variation in the system itself. Attempts at classifying uncertainty in ecology have, for the most part, focused exclusively on epistemic uncertainty. In this paper we classify uncertainty into two main categories: epistemic uncertainty (uncertainty in determinate facts) and linguistic uncertainty (uncertainty in language). We provide a classification of sources of uncertainty under the two main categories and demonstrate how each impacts on applications in ecology and conservation biology. In particular, we demonstrate the importance of recognizing the effect of linguistic uncertainty, in addition to epistemic uncertainty, in ecological applications. The significance to ecology and conservation biology of developing a clear understanding of the various types of uncertainty, how they arise and how they might best be dealt with is highlighted. Finally, we discuss the various general strategies for dealing with each type of uncertainty and offer suggestions for treating compounding uncertainty from a range of sources.

Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models

Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.

ROBUST DECISION-MAKING UNDER SEVERE UNCERTAINTY FOR CONSERVATION MANAGEMENT

In conservation biology it is necessary to make management decisions for endangered and threatened species under severe uncertainty. Failure to acknowledge and treat uncertainty can lead to poor decisions. To illustrate the importance of considering uncertainty, we reanalyze a decision problem for the Sumatran rhino, Dicerorhinus sumatrensis, using information-gap theory to propagate uncertainties and to rank management options. Rather than requiring information about the extent of parameter uncertainty at the outset, information-gap theory addresses the question of how much uncertainty can be tolerated before our decision would change. It assesses the robustness of decisions in the face of severe uncertainty. We show that different management decisions may result when uncertainty in utilities and probabilities are considered in decision-making problems. We highlight the importance of a full assessment of uncertainty in conservation management decisions to avoid, as much as possible, undesirable outcomes.

Guiding ecological principles for marine spatial planning

The declining health of marine ecosystems around the world is evidence that current piecemeal governance is inadequate to successfully support healthy coastal and ocean ecosystems and sustain human uses of the ocean. One proposed solution to this problem is ecosystem-based marine spatial planning (MSP), which is a process that informs the spatial distribution of activities in the ocean so that existing and emerging uses can be maintained, use conflicts reduced, and ecosystem health and services protected and sustained for future generations. Because a key goal of ecosystem-based MSP is to maintain the delivery of ecosystem services that humans want and need, it must be based on ecological principles that articulate the scientifically recognized attributes of healthy, functioning ecosystems. These principles should be incorporated into a decision-making framework with clearly defined targets for these ecological attributes. This paper identifies ecological principles for MSP based on a synthesis of previously suggested and/or operationalized principles, along with recommendations generated by a group of twenty ecologists and marine scientists with diverse backgrounds and perspectives on MSP. The proposed four main ecological principles to guide MSP--maintaining or restoring: native species diversity, habitat diversity and heterogeneity, key species, and connectivity--and two additional guidelines, the need to account for context and uncertainty, must be explicitly taken into account in the planning process. When applied in concert with social, economic, and governance principles, these ecological principles can inform the designation and siting of ocean uses and the management of activities in the ocean to maintain or restore healthy ecosystems, allow delivery of marine ecosystem services, and ensure sustainable economic and social benefits.

Mapping epistemic uncertainties and vague concepts in predictions of species distribution

Most habitat maps are presented as if they were a certain fact, with no indication of uncertainties. In many cases, researchers faced with the task of constructing such maps are aware of problems with the modelling data and of decisions that they make within the modelling process that are likely to affect the output, but they find it difficult to quantify this information. In some cases they attempt to evaluate the modelled predictions against independent data, but the summary statistics have no spatial component and do not address errors in the predictions. It is proposed that maps of uncertainty would help in the interpretation of these summaries, and to emphasize patterns in uncertainty such as spatial clustering or links with particular covariates. This paper reviews the aspects of uncertainty that are relevant to habitat maps developed with logistic regression, and suggests methods for investigating and communicating these uncertainties. It addresses the problems of subjective judgement, model uncertainty and vague concepts along with the more commonly considered uncertainties of random and systematic error. Methods for developing realistic confidence intervals are presented along with suggestions on how to visualize the information for use by decision-makers.

Buying into conservation: intrinsic versus instrumental value.

Many conservation biologists believe the best ethical basis for conserving natural entities is their claimed intrinsic value, not their instrumental value for humans. But there is significant confusion about what intrinsic value is and how it could govern conservation decision making. After examining what intrinsic value is supposed to be, we argue that it cannot guide the decision making conservation requires. An adequate ethical basis for conservation must do this, and instrumental value does it best.

Relationships between human disturbance and wildlife land use in urban habitat fragments

Habitat remnants in urbanized areas typically conserve biodiversity and serve the recreation and urban open-space needs of human populations. Nevertheless, these goals can be in conflict if human activity negatively affects wildlife. Hence, when considering habitat remnants as conservation refuges it is crucial to understand how human activities and land uses affect wildlife use of those and adjacent areas. We used tracking data (animal tracks and den or bed sites) on 10 animal species and information on human activity and environmental factors associated with anthropogenic disturbance in 12 habitat fragments across San Diego County, California, to examine the relationships among habitat fragment characteristics, human activity, and wildlife presence. There were no significant correlations of species presence and abundance with percent plant cover for all species or with different land-use intensities for all species, except the opossum (Didelphis virginiana), which preferred areas with intensive development. Woodrats (Neotoma spp.) and cougars (Puma concolor) were associated significantly and positively and significantly and negatively, respectively, with the presence and prominence of utilities. Woodrats were also negatively associated with the presence of horses. Raccoons (Procyon lotor) and coyotes (Canis latrans) were associated significantly and negatively and significantly and positively, respectively, with plant bulk and permanence. Cougars and gray foxes (Urocyon cinereoargenteus) were negatively associated with the presence of roads. Roadrunners (Geococcyx californianus) were positively associated with litter. The only species that had no significant correlations with any of the environmental variables were black-tailed jackrabbits (Lepus californicus) and mule deer (Odocoileus hemionus). Bobcat tracks were observed more often than gray foxes in the study area and bobcats correlated significantly only with water availability, contrasting with results from other studies. Our results appear to indicate that maintenance of habitat fragments in urban areas is of conservation benefit to some animal species, despite human activity and disturbance, as long as the fragments are large.

The Currency and Tempo of Extinction

This study examines estimates of extinction rates for the current purported biotic crisis and from the fossil record. Studies that compare current and geological extinctions sometimes use metrics that confound different sources of error and reflect different features of extinction processes. The per taxon extinction rate is a standard measure in paleontology that avoids some of the pitfalls of alternative approaches. Extinction rates reported in the conservation literature are rarely accompanied by measures of uncertainty, despite many elements of the calculations being subject to considerable error. We quantify some of the most important sources of uncertainty and carry them through the arithmetic of extinction rate calculations using fuzzy numbers. The results emphasize that estimates of current and future rates rely heavily on assumptions about the tempo of extinction and on extrapolations among taxa. Available data are unlikely to be useful in measuring magnitudes or trends in current extinction rates.

Equivalence of methods for uncertainty propagation of real-valued random variables

Abstract In this paper we compare four methods for the reliable propagation of uncertainty through calculations involving the binary operations of addition, multiplication, subtraction and division. The methods we investigate are: (i) dependency bounds convolution; (ii) Distribution Envelope Determination; (iii) interval probabilities; and (iv) Dempster–Shafer belief functions. We show that although each of these methods were constructed for different types of applications, they converge to equivalent methods when they are restricted to cumulative distribution functions on the positive reals. We also show that while some of the methods have been formally constructed to deal only with operations on random variables under an assumption of independence, all of the methods can be extended to deal with unknown dependencies and perfect positive and negative dependence among variables.

A proposal for fuzzy International Union for the Conservation of Nature (IUCN) categories and criteria

Abstract The classification of endangered species uses categories “extinct in the wild”, “endangered” and so on that are intrinsically vague. This vagueness presents various problems for those trying to classify species. The usual way of dealing with this vagueness is to eliminate it by providing precise definitions of the categories in question. In this paper we propose a fuzzy set-theoretic alternative that respects the inherent vagueness of the crucial categories without compromising the utility of the classification scheme. Moreover, we argue that it leads to intuitively more appropriate classifications in many cases.