Adaptive resource management and the value of information

The value of information is a general and broadly applicable concept that has been used for several decades to aid in making decisions in the face of uncertainty. Yet there are relatively few examples of its use in ecology and natural resources management, and almost none that are framed in terms of the future impacts of management decisions. In this paper we discuss the value of information in a context of adaptive management, in which actions are taken sequentially over a timeframe and both future resource conditions and residual uncertainties about resource responses are taken into account. Our objective is to derive the value of reducing or eliminating uncertainty in adaptive decision making. We describe several measures of the value of information, with each based on management objectives that are appropriate for adaptive management. We highlight some mathematical properties of these measures, discuss their geometries, and illustrate them with an example in natural resources management. Accounting for the value of information can help to inform decisions about whether and how much to monitor resource conditions through time.     

Theoretical perspectives on resource pulses

Over the last several decades, there has been a growing appreciation of the importance of nonequilibrial phenomena and transient dynamics in explaining the structure of ecological communities. This paper provides an overview of theoretical themes related to resource pulses. Theoretical models suggest short-term responses to a single pulse can qualitatively differ from longer-term responses. Recurrent resource pulses can alter community structure, permitting coexistence that otherwise would not occur, or hamper coexistence mechanisms effective in stable environments. For a given resource input, system responses can be more dramatic with short pulses. Resource pulses can cause transitions between alternative states. Dispersal permits species to exploit locally sporadic resource pulses and persist in environments that on average are unsuitable. All these issues are ripe for further theoretical explorations.     

The Scotia Sea krill fishery and its possible impacts on dependent predators: modeling localized depletion of prey

The nature and impact of fishing on predators that share a fished resource is an important consideration in ecosystem-based fisheries management. Krill (Euphausia superba) is a keystone species in the Antarctic, serving as a fundamental forage source for predators and simultaneously being subject to fishing. We developed a spatial multispecies operating model (SMOM) of krill-predator fishery dynamics to help advise on allocation of the total krill catch among 15 small-scale management units (SSMUs) in the Scotia Sea, with a goal to reduce the potential impact of fishing on krill predators. The operating model describes the underlying population dynamics and is used in simulations to compare different management options for adjusting fishing activities (e.g., a different spatial distribution of catches). The numerous uncertainties regarding the choice of parameter values pose a major impediment to constructing reliable ecosystem models. The pragmatic solution proposed here involves the use of operating models that are composed of alternative combinations of parameters that essentially try to bound the uncertainty in, for example, the choice of survival rate estimates as well as the functional relationships between predators and prey. Despite the large uncertainties, it is possible to discriminate the ecosystem impacts of different spatial fishing allocations. The spatial structure of the model is fundamental to addressing concerns of localized depletion of prey in the vicinity of land-based predator breeding colonies. Results of the model have been considered in recent management deliberations for spatial allocations of krill catches in the Scotia Sea and their associated impacts on dependent predator species.     

Assessment of uncertainties in expert knowledge, illustrated in fuzzy rule-based models

The coherence between different aspects in the environmental system leads to a demand for comprehensive models of this system to explore the effects of different management alternatives. Fuzzy logic has been suggested as a means to extend the application domain of environmental modelling from physical relations to expert knowledge. In such applications the expert describes the system in terms of fuzzy variables and inference rules. The result of the fuzzy reasoning process is a numerical output value. In such a model, as in any other, the model context, structure, technical aspects, parameters and inputs may contribute uncertainties to the model output. Analysis of these contributions in a simplified model for agriculture suitability shows how important information about the accuracy of the expert knowledge in relation to the other uncertainties can be provided. A method for the extensive assessment of uncertainties in compositional fuzzy rule-based models is proposed, combining the evaluation of model structure, input and parameter uncertainties. In an example model, each of these three appear to have the potential to dominate aggregated uncertainty, supporting the relevance of an ample uncertainty approach.     

A Strategy for Monitoring and Managing Declines in an Amphibian Community

Although many taxa have declined globally, conservation actions are inherently local. Ecosystems degrade even in protected areas, and maintaining natural systems in a desired condition may require active management. Implementing management decisions under uncertainty requires a logical and transparent process to identify objectives, develop management actions, formulate system models to link actions with objectives, monitor to reduce uncertainty and identify system state (i.e., resource condition), and determine an optimal management strategy. We applied one such structured decision‐making approach that incorporates these critical elements to inform management of amphibian populations in a protected area managed by the U.S. National Park Service. Climate change is expected to affect amphibian occupancy of wetlands and to increase uncertainty in management decision making. We used the tools of structured decision making to identify short‐term management solutions that incorporate our current understanding of the effect of climate change on amphibians, emphasizing how management can be undertaken even with incomplete information. Estrategia para Monitorear y Manejar Disminuciones en una Comunidad de Anfibios     

Implementing a new model to measure and assess eco-effectiveness as an indicator of sustainability

A model able to measure eco-effectiveness, which was theoretically proposed and illustrated in a previous article, is here developed and implemented for three case studies (USA, EU-15 and Japan) in order to verify its potential usefulness in the natural resources field. The results obtained by the application of the 'loss function' – ability to measure the distance between a real and an ideal situation – show that the model can be seen as a fundamental basis to assess the exploitation intensity of resources among different countries/areas and/or over time, especially if new measures and best environmental practices are adopted to increase resource productivity and to reduce environmental burdens. Since a main issue in the model implementation is related to the subjective choice of weights to be given to the various resources in the loss function (materials, fossil fuels and biomass), a graphical approach based on a 'weighting triangle' is also proposed to overcome the problem of previous weight selection. This tool permits us to make a distinction between a 'non-sustainability' area and a 'sustainability' area, based on whether an increase or a decrease of the loss function is more plausible.     

Modeling resource selection using polytomous logistic regression and kernel density estimates

Wildlife resource selection studies typically compare used to available resources; selection or avoidance occurs when use is disproportionately greater or less than availability. Comparing used to available resources is problematic because results are often greatly influenced by what is considered available to the animal. Moreover, placing relocation points within resource units is often difficult due to radiotelemetry and mapping errors. Given these problems, we suggest that an animal’s resource use be summarized at the scale of the home range (i.e., the spatial distribution of all point locations of an animal) rather than by individual points that are considered used or available. To account for differences in use-intensity throughout an animal’s home range, we model resource selection using kernel density estimates and polytomous logistic regression. We present a case study of elk (Cervus elaphus) resource selection in South Dakota to illustrate the procedure. There are several advantages of our proposed approach. First, resource availability goes undefined by the investigator, which is a difficult and often arbitrary decision. Instead, the technique compares the intensity of animal use throughout the home range. This technique also avoids problems with classifying locations rigidly as used or unused. Second, location coordinates do not need to be placed within mapped resource units, which is problematic given mapping and telemetry error. Finally, resource use is considered at an appropriate scale for management because most wildlife resource decisions are made at the level of the patch. Despite the advantages of this use-intensity procedure, future research should address spatial autocorrelation and develop spatial models for ordered categorical variables.     

Interdisciplinary models of water systems

To evaluate the complex interactions of various types of water systems, a water resource management agency is invariably involved in the preliminary step of reviewing the available quantitative methods for formulating interdisciplinary aspects of the water systems. With a view to supplement their efforts, an attempt is made in this paper to review briefly the major useful concepts and models which are intended to broaden the technical horizon of the professionals associated with the regional water resource management programs. Initially, various pathways of model building procedure are outlined. Then associated ecological, economic, social, political, technological and environmental models are discussed in light of some reported quantitative examples. With the understanding of the basic mechanics of these interdisciplinary models, the adequacy of these models and their applications can be examined by the concerned professionals to aid the decision making process for the specific water system in question.     

Redesigning harvest strategies for sustainable fishery management in the face of extreme environmental variability

Short-lived, fast-growing species that contribute greatly to global capture fisheries are sensitive to fluctuations in the environment. Uncertainties in exact stock–environment relationships have meant that environmental variability and extremes have been difficult to integrate directly into fisheries management. We applied a management strategy evaluation approach for one of Australia's large prawn stocks to test the robustness of harvest control rules to environmental variability. The model ensemble included coupled environmental-population models and an alternative catchability scenario fitted to historical catch per unit effort data. We compared the efficacy of alternative management actions to conserve marine resources under a variable environment while accounting for fisher livelihoods. Model fits to catch per unit effort were reasonably good and similar across operating models (OMs). For models that were coupled to the environment, environmental parameters for El Niño years were estimated with good associated precision, and OM3 had a lower AIC score (77.61)  than the base model (OM1, 80.39), whereas OM2 (AIC 82.41) had a similar AIC score, suggesting the OMs were all plausible model alternatives. Our model testing resulted in a plausible subset of management options, and stakeholders selected a permanent closure of the first fishing season based on overall performance of this option; ability to reduce the risk of fishery closure and stock collapse; robustness to uncertainties; and ease of implementation. Our simulation approach enabled the selection of an optimal yet pragmatic solution for addressing economic and conservation objectives under a variable environment with extreme events.     

Habitat and population modelling of roe deer using an interactive geographic information system

Management of German roe deer (Capreolus capreolus) populations is a challenge for wildlife managers and foresters because population densities are difficult to estimate in forests and forest regeneration can be negatively affected when roe deer density is high. We describe a model to determine deer population densities compatible with forest management goals, and to assess harvest rates necessary to maintain desired deer densities. A geographic information system (GIS) was used to model wildlife habitat and population dynamics over time. Our model interactively incorporates knowledge of field biologists and foresters via a graphical user interface (GUI). Calibration of the model with deer damage maps allowed us to evaluate density dependence of a roe deer population. Incorporation of local knowledge into temporally dynamic and spatial models increases understanding of population dynamics and improves wildlife management.     

Resolving structural uncertainty in natural resources management using POMDP approaches

In recent years there has been a growing focus on the uncertainties of natural resources management, and the importance of accounting for uncertainty in assessing management effectiveness. This paper focuses on uncertainty in resource management in terms of discrete-state Markov decision processes (MDP) under structural uncertainty and partial observability. It describes the treatment of structural uncertainty with approaches developed for partially observable resource systems. In particular, I show how value iteration for partially observable MDPs (POMDP) can be extended to structurally uncertain MDPs. A key difference between these process classes is that structurally uncertain MDPs require the tracking of system state as well as a probability structure for the structure uncertainty, whereas with POMDPs require only a probability structure for the observation uncertainty. The added complexity of the optimization problem under structural uncertainty is compensated by reduced dimensionality in the search for optimal strategy. A solution algorithm for structurally uncertain processes is outlined for a simple example in conservation biology. By building on the conceptual framework developed for POMDPs, natural resource analysts and decision makers who confront structural uncertainties in natural resources can take advantage of the rapid growth in POMDP methods and approaches, and thereby produce better conservation strategies over a larger class of resource problems.     

Simple Spatial Modeling Tool for Prioritizing Prescribed Burning Activities at the Landscape Scale

Abstract:   Resources for prescribed fire are frequently insufficient to manage public lands for all conservation and resource management objectives, necessitating prioritization of the application of fire across the landscape within any given year. Defining tradeoffs when applying prescribed fire to large landscapes is problematic not only because of the complexity of weighing competing management objectives at the landscape scale, but also because of the difficult nature of independently applying need-to-burn criteria to large areas. We present a case study of a simple modeling process implemented at Eglin Air Force Base in the Florida Panhandle (U.S.A.) to prioritize the application of prescribed fire. In a workshop setting, managers and biologists identified key conservation criteria and landscape management objectives that drive the application of prescribed fire. Remote sensing and other spatial data were developed to directly or indirectly represent all these criteria. Using geographic information system software, managers and biologists weighted each criterion according to its relative contribution to overall burn prioritization, and individual values for the criterion were scored according to how they influence the need to burn. Subsequently, this process has been validated and modified through ecological monitoring. This modeling process has also been applied to the 77,400-ha Blackwater River State Forest, public land adjacent to Eglin Air Force Base, demonstrating its applicability to lands with varying management priorities. The advantages of this model-based approach for prioritizing prescribed fire include the reliance on accessible, inexpensive software, the development of spatially explicit management objectives, the ease of transferability, and clearly stated assumptions about management that may be tested and reviewed through monitoring and public comment.     

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.     

Interaction structures analysed from water-quality data

Fortnightly observations of water quality parameters, discharge and water temperature along the River Elbe have been subjected to a multivariate data analysis. In a previous study [Petersen, W., Bertino, L., Callies, U., Zorita, E., 2001. Process identification by principal component analysis of river-quality data. Ecol. Model. 138, 193–213] applied principal component analysis (PCA) to show that 60% of variability in the data set can be explained through just two linear combinations of eight original variables. In the present paper more advanced multivariate methods are applied to the same data set, which are supposed to suit better interpretations in terms of the underlying system dynamics.The first method, graphical modelling, represents interaction structures in terms of a set of conditional independence constraints between pairs of variables given the values of all other variables. Assuming data from a multinormal distribution conditional independence constraints are expressed by zero partial correlations. Different graphical structures with nodes for each variable and connecting edges between them can be assessed with regard to their likelihood. The second method, canonical correlation analysis (CCA), is applied for studying the correlation structures of external forcing and water quality parameters.Results of CCA turn out to be consistent with the dominant patterns of variability obtained from PCA. The percentages of variability explained by external forcing, however, are estimated to be smaller. Fitting graphical models allows a more detailed representation of interaction structures. For instance, for given discharge and temperature correlated variations of the concentrations of oxygen and nitrate, respectively, can be modelled as being mediated by variations of pH, which is a representer for algal activity. Considerably simplified graphical models do not much affect the outcomes of both PCA and CCA, and hence it is concluded that these graphical models successfully represent the main interaction structures represented by the covariance matrix of the data. The analysed conditional independence patterns provide constraints to be satisfied by directed probabilistic networks, for instance.     

Successes and Challenges from Formation to Implementation of Eleven Broad‐Extent Conservation Programs

Integration of conservation partnerships across geographic, biological, and administrative boundaries is increasingly relevant because drivers of change, such as climate shifts, transcend these boundaries. We explored successes and challenges of established conservation programs that span multiple watersheds and consider both social and ecological concerns. We asked representatives from a diverse set of 11 broad‐extent conservation partnerships in 29 countries 17 questions that pertained to launching and maintaining partnerships for broad‐extent conservation, specifying ultimate management objectives, and implementation and learning. Partnerships invested more funds in implementing conservation actions than any other aspect of conservation, and a program's context (geographic extent, United States vs. other countries, developed vs. developing nation) appeared to substantially affect program approach. Despite early successes of these organizations and benefits of broad‐extent conservation, specific challenges related to uncertainties in scaling up information and to coordination in the face of diverse partner governance structures, conflicting objectives, and vast uncertainties regarding future system dynamics hindered long‐term success, as demonstrated by the focal organizations. Engaging stakeholders, developing conservation measures, and implementing adaptive management were dominant challenges. To inform future research on broad‐extent conservation, we considered several challenges when we developed detailed questions, such as what qualities of broad‐extent partnerships ensure they complement, integrate, and strengthen, rather than replace, local conservation efforts and which adaptive management processes yield actionable conservation strategies that account explicitly for dynamics and uncertainties regarding multiscale governance, environmental conditions, and knowledge of the system? Éxitos y Retos de la Formación a la Implementación de Once Programas de Conservación de Amplio Alcance     

Assessing the risk of ignition in the Russian far east within a modeling framework of fire threat.

The forests of high biological importance in the Russian Far East (RFE) have been experiencing increasing pressure from growing demands for natural resources under the changing economy of post-Soviet Russia. This pressure is further amplified by the rising threat of large and catastrophic fire occurrence, which threatens both the resources and the economic potential of the region. In this paper we introduce a conceptual Fire Threat Model (FTM) and use it to provide quantitative assessment of the risk of ignition in the Russian Far East. The remotely sensed data driven FTM is aimed at evaluating potential wildland fire occurrence and its impact and recovery potential for a given resource. This model is intended for use by resource managers to assist in assessing current levels of fire threat to a given resource, projecting the changes in fire threat under changing climate and land use, and evaluating the efficiency of various management approaches aimed at minimizing the fire impact. Risk of ignition (one of the major uncertainties within fire threat modeling) was analyzed using the MODIS active fire product. The risk of ignition in the RFE is shown to be highly variable in spatial and temporal domains. However, the number of ignition points is not directly proportional to the amount of fire occurrence in the area. Fire ignitions in the RFE are strongly linked to anthropogenic activity (transportation routes, settlements, and land use). An increase in the number of fire ignitions during summer months could be attributed to (1) disruption of the summer monsoons and subsequent changes in fire weather and (2) an increase in natural sources of fire ignitions.     

A framework for evaluating regional-scale numerical photochemical modeling systems

This paper discusses the need for critically evaluating regional-scale (~200–2,000 km) three-dimensional numerical photochemical air quality modeling systems to establish a model’s credibility in simulating the spatio-temporal features embedded in the observations. Because of limitations of currently used approaches for evaluating regional air quality models, a framework for model evaluation is introduced here for determining the suitability of a modeling system for a given application, distinguishing the performance between different models through confidence-testing of model results, guiding model development and analyzing the impacts of regulatory policy options. The framework identifies operational, diagnostic, dynamic, and probabilistic types of model evaluation. Operational evaluation techniques include statistical and graphical analyses aimed at determining whether model estimates are in agreement with the observations in an overall sense. Diagnostic evaluation focuses on process-oriented analyses to determine whether the individual processes and components of the model system are working correctly, both independently and in combination. Dynamic evaluation assesses the ability of the air quality model to simulate changes in air quality stemming from changes in source emissions and/or meteorology, the principal forces that drive the air quality model. Probabilistic evaluation attempts to assess the confidence that can be placed in model predictions using techniques such as ensemble modeling and Bayesian model averaging. The advantages of these types of model evaluation approaches are discussed in this paper.     

Exploring alternative states in ecological systems with a qualitative analysis of community feedback

Demonstrating and predicting the existence of alternative states in natural communities remains a challenge for ecologists and is essential for resource managers. Positive feedback is often presented as central in maintaining alternative ecosystem states, but no formal approach relates this part of theory to real world applications. Through qualitative modelling of community response to long-term perturbations, we define generic mechanistic links between positive feedback and the occurrence of alternative states. Positive feedback diminishes a system's overall resistance to change, and can create and maintain correlations in the relative abundance of variables that coincide with alternative states.Through specific models of the dynamics of Tasmanian rocky-reef communities, which are affected by climate and fishing and persist within alternative states, we demonstrate the ability of our theoretical framework to predict alternative states in ecosystems and inform management intervention. A qualitative knowledge of community structure permits a thorough analysis of system feedback and an assessment of the potential for an ecosystem to exhibit alternative states. We illustrate the usefulness of the approach to inform management priorities, and to focus monitoring and field research on the key drivers of ecosystem dynamics.     

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.     

Simulation modeling of material and energy flow through an ecosystem: Methods and documentation

This paper discusses the process of development of large-scale ecological simulation models as it proceeds through steps divided between two major phases — conceptualization and implementation. The activities in these phases are strongly influenced by model objectives. Activities transpiring in each step are discussed and documentation methods both for the modelling process and its product are introduced for each of the steps. Examples are given from CONIFER, a large-scale coniferous forest model developed by the author in cooperation with another investigator. The role of the model documentation, both in aiding model development and in clearly communicating and allowing criticism of the model, is emphasized. Model evaluation, checking that the model satisfies its objectives, is seen as an area of model development which indicates which parts of the model need reworking.