Evaluation of a Reproductive Index for Estimating Productivity of Grassland Breeding Birds

Declining populations of grassland breeding birds have led to increased efforts to assess habitat quality, typically by estimating density or relative abundance. Because some grassland habitats may function as ecological traps, a more appropriate metric for determining quality is breeding success, which is challenging to determine for many cryptic-nesting grassland birds. This difficulty led Vickery et al. (1992) to propose a reproductive index based on behavioral observations rather than nest fate. We rigorously evaluated the index for 2 years using a Savannah Sparrow (Passerculus sandwichensis) population in western New York and found a weak correlation in classification of the breeding stages of monitored territories among multiple observers (r = 0.398). We also discovered a large difference between overall territory and nest success rates independently estimated with the index (9.8% over the entire breeding cycle) and with nest searching and monitoring (41.7% of nests successfully fledged young). Most importantly, we made territory-level comparisons of index estimates with actual nest fate and found that the index correctly predicted fates for only 43% of the monitored nests. A Mayfield logistic regression analysis demonstrated that only index rank 4 (eggs hatched, but young failed to fledge) showed a strong positive correlation with nest success. Although the reproductive index may function as a coarse indicator of habitat suitability (e.g., documenting production in potential ecological traps), in our study the index exhibited neither internal consistency nor the ability to predict nest fate at the plot or territory level and functioned poorly as a substitute for nest searching and monitoring

Structured decision making as a conceptual framework to identify thresholds for conservation and management

Thresholds and their relevance to conservation have become a major topic of discussion in the ecological literature. Unfortunately, in many cases the lack of a clear conceptual framework for thinking about thresholds may have led to confusion in attempts to apply the concept of thresholds to conservation decisions. Here, we advocate a framework for thinking about thresholds in terms of a structured decision making process. The purpose of this framework is to promote a logical and transparent process for making informed decisions for conservation. Specification of such a framework leads naturally to consideration of definitions and roles of different kinds of thresholds in the process. We distinguish among three categories of thresholds. Ecological thresholds are values of system state variables at which small changes bring about substantial changes in system dynamics. Utility thresholds are components of management objectives (determined by human values) and are values of state or performance variables at which small changes yield substantial changes in the value of the management outcome. Decision thresholds are values of system state variables at which small changes prompt changing in management actions in order to reach specified management objectives. The approach that we present focuses directly on the objectives of management, with an aim to providing decisions that are optimal with respect to those objectives. This approach clearly distinguishes the components of he decision process that are inherently subjective (management objectives, potential management actions) from those that are more objective (systems models, estimates of system state). Optimization based on these components then leads to decision matrices specifying optimal actions to be taken at various values of system state variables. Values of state variables separating different actions in such matrices are viewed as decision thresholds. Utility thresholds are included in the objectives component, and ecological thresholds may be embedded in models projecting consequences of management actions. Decision thresholds are determined by the above-listed components of a structured decision process. These components may themselves vary over time, inducing variation in the decision threshold inherited from them. These dynamic decision thresholds can then be determined using adaptive management. We provide numerical examples (that are based on patch occupancy models) of structures decision process that include all three kinds of thresholds

Structured decision making as a conceptual framework to identify thresholds for conservation and management

Threshold and their relevance to conservation have become a major topic of discussion in the ecological literature. Unfortunately, in many cases the lack of a clear conceptual framework for thinking about thresholds in terms of a structured decision making process. The purpose of this framework is to promote a logical and transparent process for making informed decisions for conservation. Specification of such a framework leads naturally to consideration of definitions and roles of different kinds of thresholds in the process. We distinguish among three categories of thresholds. Ecological thresholds are values of system state variables at which small changes bring about substantial changes in system dynamics. Utility thresholds are components of management objectives (determined by human values) and are values of state or performance variables at which small changes yield substantial changes in the value of the management outcome. Decision thresholds are values of system state variables at which small changes prompt changes in management actions in order to reach specified management objectives. The approach that we present focuses directly on the objectives of management, with an aim to providing decisions that are optimal with respect to those objectives. This approach clearly distinguishes the components of the decision process that are inherently subjective (management objectives, potential management actions) from those that are more objectives (system models, estimates of system state). Optimization based on these components then leads to decision matrices specifying optimal actions to be taken at various values of system state variables. Values of state variables separating different actions in such matrices are viewed as decision thresholds. Utility thresholds are included i the objectives component, and ecological thresholds may be embedded in models projecting consequences of management actions. Decision threshold are determined by the above-listed components of a structured decision thresholds inherited from them. These dynamic decision thresholds can then be determined using adaptive management. We provide numerical examples (that are based on patch occupancy models) of structured decision processes that include all three kinds of thresholds

Pastiches sovversivi. Strategie della parodia e della satira in Luciano di Samosata

Parody and pastiche are among the main literary and satirical strategies used by Lucian of Samosata. The aim of this article is to explore the relationship between the reuse of the tradition of Greek paideia and the new perspectives of literature through the analysis of a serie of examples (cat., hist. conscr., VH, Peregr., Alex.). On the one hand, there is the recognition of the greatness of the ancient authors and certainly there is also the literary pleasure of pepaideumenos. At the same time, in contrast to what happens for mimesis in the Second Sophistic, Lucian’s parody and satirical pastiches look in other directions, because parody, by its nature and through the 'necessary gap', always implies a principle of subversion of the tradition: in Lucian's Works the satiric rule of «believing in nothing» produces its effects in the development of Literature

An Adaptive Decision Framework for the Conservation of a Threatened Plant

This is the publisher's version, also available electronically from http://www.fwspubs.org/.Mead's milkweed Asclepias meadii, a long-lived perennial herb of tallgrass prairie and glade communities of the central United States, is a species designated as threatened under the U.S. Endangered Species Act. Challenges to its successful management include the facts that much about its life history is unknown, its age at reproductive maturity is very advanced, certain life stages are practically unobservable, its productivity is responsive to unpredictable environmental events, and most of the known populations occur on private lands unprotected by any legal conservation instrument. One critical source of biological uncertainty is the degree to which fire promotes growth and reproductive response in the plant. To aid in its management, we developed a prototype population-level state-dependent decision-making framework that explicitly accounts for this uncertainty and for uncertainties related to stochastic environmental effects and vital rates. To parameterize the decision model, we used estimates found in the literature, and we analyzed data from a long-term monitoring program where fates of individual plants were observed through time. We demonstrate that different optimal courses of action are followed according to how one believes that fire influences reproductive response, and we show that the action taken for certain population states is informative for resolving uncertainty about competing beliefs regarding the effect of fire. We advocate the use of a model-predictive approach for the management of rare populations, particularly when management uncertainty is profound. Over time, an adaptive management approach should reduce uncertainty and improve management performance as predictions of management outcome generated under competing models are continually informed and updated by monitoring data

Two-step adaptive management for choosing between two management actions

Adaptive management is widely advocated to improve environmental management. Derivations of optimal strategies for adaptive management, however, tend to be case specific and time consuming. In contrast, managers might seek relatively simple guidance, such as insight into when a new potential management action should be considered, and how much effort should be expended on trialing such an action. We constructed a two-time-step scenario where a manager is choosing between two possible management actions. The manager has a total budget that can be split between a learning phase and an implementation phase. We use this scenario to investigate when and how much a manager should invest in learning about the management actions available. The optimal investment in learning can be understood intuitively by accounting for the expected value of sample information, the benefits that accrue during learning, the direct costs of learning, and the opportunity costs of learning. We find that the optimal proportion of the budget to spend on learning is characterized by several critical thresholds that mark a jump from spending a large proportion of the budget on learning to spending nothing. For example, as sampling variance increases, it is optimal to spend a larger proportion of the budget on learning, up to a point: if the sampling variance passes a critical threshold, it is no longer beneficial to invest in learning. Similar thresholds are observed as a function of the total budget and the difference in the expected performance of the two actions. We illustrate how this model can be applied using a case study of choosing between alternative rearing diets for hihi, an endangered New Zealand passerine. Although the model presented is a simplified scenario, we believe it is relevant to many management situations. Managers often have relatively short time horizons for management, and might be reluctant to consider further investment in learning and monitoring beyond collecting data from a single time period

Strengthening Links Between Waterfowl Research and Management

Waterfowl monitoring, research, regulation, and adaptive planning are leading the way in supporting science-informed wildlife management. However, increasing societal demands on natural resources have created a greater need for adaptable and successful linkages between waterfowl science and management. We presented a special session at the 2016 North American Duck Symposium, Annapolis, Maryland, USA on the successes and challenges of linking research and management in waterfowl conservation, and we summarize those thoughts in this commentary. North American waterfowl management includes a diversity of actions including management of harvest and habitat. Decisions for waterfowl management are structured using decision analysis by incorporating stakeholder values into formal objectives, identifying research relevant to objectives, integrating scientific knowledge, and choosing an optimal strategy with respect to objectives. Recently, the consideration of the value of information has been proposed as a means to evaluate the utility of research designed to meet objectives. Despite these advances, the ability to conduct waterfowl research with direct management application may be increasingly difficult in research institutions for several reasons including reduced funding for applied research and the lower perceived value of applied versus theoretical research by some university academics. In addition, coordination between researchers and managers may be logistically constrained, and communication may be ineffective between the 2 groups. Strengthening these links would help develop stronger and more coordinated approaches for the conservation of waterfowl and the wetlands upon which they depend

Strengthening Links Between Waterfowl Research and Management

Waterfowl monitoring, research, regulation, and adaptive planning are leading the way in supporting science-informed wildlife management. However, increasing societal demands on natural resources have created a greater need for adaptable and successful linkages between waterfowl science and management. We presented a special session at the 2016 North American Duck Symposium, Annapolis, Maryland, USA on the successes and challenges of linking research and management in waterfowl conservation, and we summarize those thoughts in this commentary. North American waterfowl management includes a diversity of actions including management of harvest and habitat. Decisions for waterfowl management are structured using decision analysis by incorporating stakeholder values into formal objectives, identifying research relevant to objectives, integrating scientific knowledge, and choosing an optimal strategy with respect to objectives. Recently, the consideration of the value of information has been proposed as a means to evaluate the utility of research designed to meet objectives. Despite these advances, the ability to conduct waterfowl research with direct management application may be increasingly difficult in research institutions for several reasons including reduced funding for applied research and the lower perceived value of applied versus theoretical research by some university academics. In addition, coordination between researchers and managers may be logistically constrained, and communication may be ineffective between the 2 groups. Strengthening these links would help develop stronger and more coordinated approaches for the conservation of waterfowl and the wetlands upon which they depend

Causes of delayed outbreak responses and their impacts on epidemic spread

Livestock diseases have devastating consequences economically, socially and politically across the globe. In certain systems, pathogens remain viable after host death, which enables residual transmissions from infected carcasses. Rapid culling and carcass disposal are well-established strategies for stamping out an outbreak and limiting its impact; however, wait-times for these procedures, i.e. response delays, are typically farm-specific and time-varying due to logistical constraints. Failing to incorporate variable response delays in epidemiological models may understate outbreak projections and mislead management decisions. We revisited the 2001 foot-and-mouth epidemic in the United Kingdom and sought to understand how misrepresented response delays can influence model predictions. Survival analysis identified farm size and control demand as key factors that impeded timely culling and disposal activities on individual farms. Using these factors in the context of an existing policy to predict local variation in response times significantly affected predictions at the national scale. Models that assumed fixed, timely responses grossly underestimated epidemic severity and its long-term consequences. As a result, this study demonstrates how general inclusion of response dynamics and recognition of partial controllability of interventions can help inform management priorities during epidemics of livestock diseases

Adaptive Management of Bull Trout Populations in the Lemhi Basin

The bull trout Salvelinus confluentus, a stream-living salmonid distributed in drainages of the northwestern United States, is listed as threatened under the Endangered Species Act because of rangewide declines. One proposed recovery action is the reconnection of tributaries in the Lemhi Basin. Past water use policies in this core area disconnected headwater spawning sites from downstream habitat and have led to the loss of migratory life history forms. We developed an adaptive management framework to analyze which types of streams should be prioritized for reconnection under a proposed Habitat Conservation Plan. We developed a Stochastic Dynamic Program that identified optimal policies over time under four different assumptions about the nature of the migratory behavior and the effects of brook trout Salvelinus fontinalis on subpopulations of bull trout. In general, given the current state of the system and the uncertainties about the dynamics, the optimal policy would be to connect streams that are currently occupied by bull trout. We also estimated the value of information as the difference between absolute certainty about which of our four assumptions were correct, and a model averaged optimization assuming no knowledge. Overall there is little to be gained by learning about the dynamics of the system in its current state, although in other parts of the state space reducing uncertainties about the system would be very valuable. We also conducted a sensitivity analysis; the optimal decision at the current state does not change even when parameter values are changed up to 75% of the baseline values. Overall, the exercise demonstrates that it is possible to apply adaptive management principles to threatened and endangered species, but logistical and data availability constraints make detailed analyses difficult