Forecasts of habitat loss and fragmentation due to urban growth are sensitive to source of input data

The conversion of natural habitat to urban settlements is a primary driver of biodiversity loss, and species' persistence is threatened by the extent, location, and spatial pattern of development. Urban growth models are widely used to anticipate future development and to inform conservation management, but the source of spatial input to these models may contribute to uncertainty in their predictions. We compared two sources of historic urban maps, used as input for model calibration, to determine how differences in definition and scale of urban extent affect the resulting spatial predictions from a widely used urban growth model for San Diego County, CA under three conservation scenarios. The results showed that rate, extent, and spatial pattern of predicted urban development, and associated habitat loss, may vary substantially depending on the source of input data, regardless of how much land is excluded from development. Although the datasets we compared both represented urban land, different types of land use/land cover included in the definition of urban land and different minimum mapping units contributed to the discrepancies. Varying temporal resolution of the input datasets also contributed to differences in projected rates of development. Differential predicted impacts to vegetation types illustrate how the choice of spatial input data may lead to different conclusions relative to conservation. Although the study cannot reveal whether one dataset is better than another, modelers should carefully consider that geographical reality can be represented differently, and should carefully choose the definition and scale of their data to fit their research objectives.     

Antifouling strategies for marine and riverine sensors

Traditionally, water quality has been monitored by sampling and lab based analysis. However, there are disadvantages associated with this method, for example, deterioration of samples with time, limited sampling points, limited temporal monitoring. This has provided impetus for the development of sensors which can be deployed from remote locations over extended deployment periods. However, a major limitation of these systems is their vulnerability to biofouling. This review outlines the research that has been carried out on strategies for the protection of marine and riverine sensors against fouling.     

Evolution of male mating behavior: male spadefoot toads preferentially associate with conspecific males

The evolution of male breeding aggregations is difficult to explain because males may reduce their reproductive success by associating with their closest competitors. We examined aggregative behavior by male New Mexico spadefoot toads, Spea multiplicata, which form breeding choruses in rain-filled pools. We specifically asked whether males are attracted to conspecific calls and, if so, whether they preferentially associate with those male calls that are also attractive to females. Field observations revealed that males showed significant clustering with conspecifics within breeding ponds, whereas laboratory phonotaxis experiments revealed that males preferentially associated with conspecific male calls. Moreover, when males were presented with conspecific calls that differed in call rate, smaller males associated with the stimulus preferred by females (average call rate). Thus, males appear to evaluate the attractiveness of competitors using the same trait employed by females to assess potential mates, and males adjust their positions relative to competitors depending on their size. We discuss these results in the light of several current hypotheses on the adaptive significance of male breeding aggregations. Received: 20 December 1999 / Accepted: 18 March 2000     

Minimum viable metapopulation size, extinction debt, and the conservation of a declining species.

A key question facing conservation biologists is whether declines in species' distributions are keeping pace with landscape change, or whether current distributions overestimate probabilities of future persistence. We use metapopulations of the marsh fritillary butterfly Euphydryas aurinia in the United Kingdom as a model system to test for extinction debt in a declining species. We derive parameters for a metapopulation model (incidence function model, IFM) using information from a 625-km2 landscape where habitat patch occupancy, colonization, and extinction rates for E. aurinia depend on patch connectivity, area, and quality. We then show that habitat networks in six extant metapopulations in 16-km2 squares were larger, had longer modeled persistence times (using IFM), and higher metapopulation capacity (lambdaM) than six extinct metapopulations. However, there was a > 99% chance that one or more of the six extant metapopulations would go extinct in 100 years in the absence of further habitat loss. For 11 out of 12 networks, minimum areas of habitat needed for 95% persistence of metapopulation simulations after 100 years ranged from 80 to 142 ha (approximately 5-9% of land area), depending on the spatial location of habitat. The area of habitat exceeded the estimated minimum viable metapopulation size (MVM) in only two of the six extant metapopulations, and even then by only 20%. The remaining four extant networks were expected to suffer extinction in 15-126 years. MVM was consistently estimated as approximately 5% of land area based on a sensitivity analysis of IFM parameters and was reduced only marginally (to approximately 4%) by modeling the potential impact of long-distance colonization over wider landscapes. The results suggest a widespread extinction debt among extant metapopulations of a declining species, necessitating conservation management or reserve designation even in apparent strongholds. For threatened species, metapopulation modeling is a potential means to identify landscapes near to extinction thresholds, to which conservation measures can be targeted for the best chance of success.     

Effects of uncertainty and variability on population declines and IUCN Red List classifications

The International Union for Conservation of Nature (IUCN) Red List Categories and Criteria is a quantitative framework for classifying species according to extinction risk. Population models may be used to estimate extinction risk or population declines. Uncertainty and variability arise in threat classifications through measurement and process error in empirical data and uncertainty in the models used to estimate extinction risk and population declines. Furthermore, species traits are known to affect extinction risk. We investigated the effects of measurement and process error, model type, population growth rate, and age at first reproduction on the reliability of risk classifications based on projected population declines on IUCN Red List classifications. We used an age‐structured population model to simulate true population trajectories with different growth rates, reproductive ages and levels of variation, and subjected them to measurement error. We evaluated the ability of scalar and matrix models parameterized with these simulated time series to accurately capture the IUCN Red List classification generated with true population declines. Under all levels of measurement error tested and low process error, classifications were reasonably accurate; scalar and matrix models yielded roughly the same rate of misclassifications, but the distribution of errors differed; matrix models led to greater overestimation of extinction risk than underestimations; process error tended to contribute to misclassifications to a greater extent than measurement error; and more misclassifications occurred for fast, rather than slow, life histories. These results indicate that classifications of highly threatened taxa (i.e., taxa with low growth rates) under criterion A are more likely to be reliable than for less threatened taxa when assessed with population models. Greater scrutiny needs to be placed on data used to parameterize population models for species with high growth rates, particularly when available evidence indicates a potential transition to higher risk categories.     

A formal model for consensus and negotiation in environmental management

Environmental management decisions typically lie at the interface of science and public policy. Consequently, these decisions involve a number of stakeholders with competing agendas and vested interests in the ultimate decision. In such cases, it is appropriate to adopt formal methods for consensus building to ensure transparent and repeatable decisions. In this paper, we use an environmental management case study to demonstrate the utility of a mathematical consensus convergence model in aggregating values (or weights) across groups. Consensus models are applicable when all parties agree to negotiate in order to resolve conflict. The advantage of this method is that it does not require that all members of the group reach agreement, often an impossible task in group decision making. Instead, it uses philosophical foundations in consensus building to aggregate group members' values in a way that guarantees convergence towards a single consensual value that summarizes the group position. We highlight current problems with ad hoc consensus and negotiation methods, provide justification for the adoption of formal consensus convergence models and compare the consensus convergence model with currently used methods for aggregating values across a group in a decision making context. The model provides a simple and transparent decision support tool for group decision making that is straightforward to implement.     

The response of the woodpigeon (Columba palumbus) to relaxation of intraspecific competition: A hybrid modelling approach

The recent rapid growth of the woodpigeon population in the British Isles is a cause for concern for environmental managers. It is unclear what has driven their increase in abundance. Using a mathematical model, we explored two possible mechanisms, reduced intraspecific competition for food and increased reproductive success. We developed an age-structured hybrid model consisting of a system of ordinary differential equations that describes density-dependent mortality and a discrete component, which represents the birth-pulse. We investigated equilibrium population dynamics using our model. The two hypotheses predict contrasting population age profiles at equilibrium. We adapted the model to examine the impacts of control measures. We showed that an annual shooting season that follows the period of density-dependent mortality is the most effective control strategy because it simultaneously removes adult and juvenile woodpigeons. The model is a first step towards understanding the processes that influence the dynamics of woodpigeon populations.     

Continuous high-frequency monitoring of estuarine water quality as a decision support tool: a Dublin Port case study

High-frequency, continuous monitoring using in situ sensors offers a comprehensive and improved insight into the temporal and spatial variability of any water body. In this paper, we describe a 7-month exploratory monitoring programme in Dublin Port, demonstrating the value of high-frequency data in enhancing knowledge of processes, informing discrete sampling, and ultimately increasing the efficiency of port and environmental management. Kruskal–Wallis and Mann–Whitney tests were used to show that shipping operating in Dublin Port has a small–medium effect on turbidity readings collected by in situ sensors. Turbidity events are largely related to vessel activity in Dublin Port, caused by re-suspension of sediments by vessel propulsion systems. The magnitudes of such events are strongly related to water level and tidal state at vessel arrival times. Crucially, measurements of Escherichia coli and enterococci contamination from discrete samples taken at key periods related to detected turbidity events were up to nine times higher after vessel arrival than prior to disturbance. Daily in situ turbidity patterns revealed time-dependent water quality “hot spots” during a 24-h period. We demonstrate conclusively that if representative environmental assessment of water quality is to be performed at such sites, sampling times, informed by continous monitoring data, should take into account these daily variations. This work outlines the potential of sensor technologies and continuous monitoring, to act as a decision support tool in both environmental and port management.