The Role of Landscape‐Dependent Disturbance and Dispersal in Metapopulation Persistence.

The fundamental processes that influence metapopulation dynamics (extinction and recolonization) will often depend on landscape structure. Disturbances that increase patch extinction rates will frequently be landscape dependent such that they are spatially aggregated and have an increased likelihood of occurring in some areas. Similarly, landscape structure can influence organism movement, producing asymmetric dispersal between patches. Using a stochastic, spatially explicit model, we examine how landscape‐dependent correlations between dispersal and disturbance rates influence metapopulation dynamics. Habitat patches that are situated in areas where the likelihood of disturbance is low will experience lower extinction rates and will function as partial refuges. We discovered that the presence of partial refuges increases metapopulation viability and that the value of partial refuges was contingent on whether dispersal was also landscape dependent. Somewhat counterintuitively, metapopulation viability was reduced when individuals had a preponderance to disperse away from refuges and was highest when there was biased dispersal toward refuges. Our work demonstrates that landscape structure needs to be incorporated into metapopulation models when there is either empirical data or ecological rationale for extinction and/or dispersal rates being landscape dependent

In pursuit of knowledge: Addressing barriers to effective conservation evaluation

Evaluation, the process of assessing the effectiveness of programs and activities, has gained increasing attention in the conservation sector as programs seek to account for investments, measure their impacts, and adapt interventions to improve future outcomes. We conducted a country-wide evaluation of terrestrial-based conservation programs in Samoa. Though rarely applied, the benefit of evaluating multiple projects at once is that it highlights factors which are persistent and influential across the entire conservation sector. We found mixed success in achieving goals among conservation programs; yet this result is surrounded by uncertainty because of the quality of existing evidence on project outcomes. We explore the role of different components of the conservation management system, i.e., context, planning, inputs, processes, and outputs, in facilitating and/or constraining collection of data on project outcomes, and thereby assessment of whether projects were successful. Our study identified a number of direct and indirect barriers that affected the capacity of projects to carry out informative evaluations and generate knowledge on conservation progress in Samoa. These attributes and mechanisms include: the availability and management of data, design and planning of projects, and systems for reporting among donors and proponents. To overcome these barriers to evaluation, we believe that a shift in institutional approaches to reporting outcomes is needed, from a reflective way of thinking to a more prospective outlook

The effect of resource aggregation at different scales: Optimal foraging behavior of Cotesia rubecula

Copyright is owned by publisher: http://www.press.uchicago.edu/Resources can be aggregated both within and between patches. In this article, we examine how aggregation at these different scales influences the behavior and performance of foragers. We developed an optimal foraging model of the foraging behavior of the parasitoid wasp Cotesia rubecula parasitizing the larvae of the cabbage butterfly Pieris rapae. The optimal behavior was found using stochastic dynamic programming. The most interesting and novel result is that the effect of resource aggregation within and between patches depends on the degree of aggregation both within and between patches as well as on the local host density in the occupied patch, but lifetime reproductive success depends only on aggregation within patches. Our findings have profound implications for the way in which we measure heterogeneity at different scales and model the response of organisms to spatial heterogeneity.Brigitte Tenhumberg, Michael A Keller, Andrew J Tyre and Hugh P Possingha

Population Cycling in Space-Limited Organisms Subject to Density-Dependent Predation

We present a population model with density-dependent disturbance. The model is motivated by, and is illustrated with, data on the percentage of space covered by barnacles on quadrats of rock in the intertidal zone. The autocorrelation function observed indicates population cycling. This autocorrelation function is predicted qualitatively and quantitatively by the detailed model we present. The general version of the model suggests the following rules regarding cycling in space-limited communities subject to density-dependent disturbances. These rules may apply to any space-limited community where a density-dependent disturbance reduces population densities to very low levels, like fire or wind for plant communities. We propose that the period of the cycle will be approximately equal to the time it takes the community to reach a critical density plus the average time between disturbance events when the density is above that critical density. The cycling will only be clear from autocorrelation data if the growth process is relatively consistent, there is a critical density (which the sessile organism reaches and passes) above which the probability of disturbance increases rapidly, and the time to reach the critical density is at least twice the average time between disturbance events

Managing the impact of invasive species: the value of knowing the density–impact curve

Economic impacts of invasive species worldwide are substantial. Management strategies have been incorporated in population models to assess the effectiveness of management for reducing density, with the implicit assumption that economic impact of the invasive species will also decline. The optimal management effort, however, is that which minimizes the sum of both the management and impact costs. The relationship between population density and economic impact (what we call the “density–impact curve”) is rarely examined in a management context and could take several nonlinear forms. Here we determine the effects of population dynamics and density–impact curves of different shapes on optimal management effort and discover cases where management is either highly effective or a waste of resources. When an inaccurate density–impact curve is used, the increase in total costs due to over- or underinvestment in management can be large. We calculate the increase in total costs incurred if the density–impact curve is incorrect and find that the greater the maximum impact caused by an invasive species, the more important it is not only to reduce its density, but also to know the shape of the density–impact relationship accurately. Lack of information regarding the relationship between density and economic impact causes the most acute problems for invaders that cause high impact at low density, where management typically will be too little, too late. For species that are only problematic at high density, ignorance of the density–impact curve can lead to overinvestment in management with little reduction in impact

Anatomical aspects of grape berry development

The anatomical development of the sultana-grape berry has been followed from anthesis to maturity on material grown under glasshouse and field conditions including field-grown clonal lines differing in final fruit size. Fresh weight, volume, berry dimensions, moisture content and dry weight were measured on whole berries. Pericarp growth was studied at the cell level. Pericarp growth is basically responsible for the overall growth of the berry and this tissue represents 64% of the mature fruit's total volume. The period required for complete berry development (approximately 100 days) falls into two major growth periods separated by a lag phase. Before the lag phase pericarp growth results partly from cell division but mainly from cell enlargement. After the lag phase pericarp growth results entirely from cell enlargement. Cell division in the pericarp ceases about one week before the lag phase. Berry size differences between clonal lines were primarily due to differences in the size of pericarp cells. Berry size differences between fruits grown in the glasshouse and in the field at Merbein were due to differences in both pericarp cell number and cell size

Optimal adaptive management for the translocation of a threatened species

Active adaptive management (AAM) is an approach to wildlife management that acknowledges our imperfect understanding of natural systems and allows for some resolution of our uncertainty. Such learning may be characterized by risky strategies in the short term. Experimentation is only considered acceptable if it is expected to be repaid by increased returns in the long term, generated by an improved understanding of the system. By setting AAM problems within a decision theory framework, we can find this optimal balance between achieving our objectives in the short term and learning for the long term. We apply this approach to managing the translocation of the bridled nailtail wallaby (Onychogalea fraenata), an endangered species from Queensland, Australia. Our task is to allocate captive-bred animals, between two sites or populations to maximize abundance at the end of the translocation project. One population, at the original site of occupancy, has a known growth rate. A population potentially could be established at a second site of suitable habitat, but we can only learn the growth rate of this new population by monitoring translocated animals. We use a mathematical programming technique called stochastic dynamic programming, which determines optimal management decisions for every possible management trajectory. We find optimal strategies under active and passive adaptive management, which enables us to examine the balance between learning and managing directly. Learning is more often optimal when we have less prior information about the uncertain population growth rate at the new site, when the growth rate at the original site is low, and when there is substantial time remaining in the translocation project. Few studies outside the area of optimal harvesting have framed AAM within a decision theory context. This is the first application to threatened species translocation

Applying Decision-Theory Framework to Landscape Planning for Biodiversity: Follow-up to Watson et al

Because socioeconomic factors drive conservation planning, we believe that to be relevant to on-the-ground projects, conservation science should be focused more on formulating problems explicitly and showing how the broad variety of decision-making tools can be used to deliver solutions. Conservation biology cannot operate outside the reality of financial limitations

Theory for designing nature reserves for single species

We examine the question of the optimal number of reserves that should be established to maximize the persistence of a species. We assume that the mean time to extinction of a single population increases as a power of the habitat area, that there is a certain amount of habitat to be reserved, and that the aim is to determine how this habitat is most efficiently divided. The optimal configuration depends on whether the management objective is to maximize the mean time to extinction or minimize the risk of extinction. When maximizing the mean time to extinction, the optimal number of independent reserves does not depend on the amount of available habitat for the reserve system. In contrast, the risk of extinction is minimized when individual reserves are equal to the optimal patch size, making the optimal number of reserves linearly proportional to the amount of available habitat. A model that includes dispersal and correlation in the incidence of extinction demonstrates the importance of considering the relative rate at which these two factors decrease with distance between reserves. A small number of reserves is optimal when the mean time to extinction increases rapidly with habitat area or when risks of extinction are high