We examine why demographic models should be used cautiously in Population Viability Analysis (PVA) with endangered species. We review the structure, data requirements, and outputs of analytical, deterministic single-population, stochastic single-population, metapopulation, and spatially explicit models. We believe predictions from quantitative models for endangered species are unreliable due to poor quality of demographic data used in most applications, difficulties in estimating variance in demographic rates, and lack of information on dispersal (distances, ages, mortality, movement patterns). Unreliable estimates also arise because stochastic models are difficult to validate, environmental trends and periodic fluctuations are rarely considered, the form of density dependence is frequently unknown but greatly affects model outcomes, and alternative model structures can result in very different predicted effects of management regimes. We suggest that PVA (1) evaluate relative rather than absolute rates of extinction, (2) emphasize short-time periods for making projections, (3) start with simple models and choose an approach that data can support, (4) use models cautiously to diagnose causes of decline and examine potential routes to recovery, (5) evaluate cumulative ending functions and alternative reference points rather than extinction rates, (6) examine all feasible scenarios, and (7) mix genetic and demographic currencies sparingly. Links between recovery options and PVA models should be established by conducting field tests of model assumptions and field validation of secondary model predictions.

Invasive alien species (IAS) exact large biodiversity and economic costs and are a significant component of human-induced, global environmental change. Previous studies looking at the variation in alien species across regions have been limited geographically or taxonomically or have not considered economics. We used a global invasive species database to regress IAS per-country on a suite of socioeconomic, ecological, and biogeographical variables. We varied the countries included in the regression tree analyses, in order to explore whether certain outliers were biasing the results, and in most of the cases, merchandise imports was the most important explanatory variable. The greater the degree of international trade, the higher the number of IAS. We also found a positive relationship between species richness and the number of invasives, in accord with other investigations at large spatial scales. Island status (overall), country area, latitude, continental position (New World versus Old World) or other measures of human disturbance (e.g., GDP per capita, population density) were not found to be important determinants of a country's degree of biological invasion, contrary to previous studies. Our findings also provide support to the idea that more resources for combating IAS should be directed at the introduction stage and that novel trade instruments need to be explored to account for this environmental externality.

No abstract

No abstract

Although the aim of conservation planning is the persistence of biodiversity, current methods trade-off ecological realism at a species level in favour of including multiple species and landscape features. For conservation planning to be relevant, the impact of landscape configuration on population processes and the viability of species needs to be considered. We present a novel method for selecting reserve systems that maximize persistence across multiple species, subject to a conservation budget. We use a spatially explicit metapopulation model to estimate extinction risk, a function of the ecology of the species and the amount, quality and configuration of habitat. We compare our new method with more traditional, area-based reserve selection methods, using a ten-species case study, and find that the expected loss of species is reduced 20-fold. Unlike previous methods, we avoid designating arbitrary weightings between reserve size and configuration; rather, our method is based on population processes and is grounded in ecological theory.

Abstract. A decision theory framework can be a powerful technique to derive optimal management decisions for endangered species. We built a spatially realistic stochastic metapopulation model for the Mount Lofty Ranges Southern Emu-wren (Stipiturus malachurus intermedius), a critically endangered Australian bird. Using discrete-time Markov chains to describe the dynamics of a metapopulation and stochastic dynamic programming (SDP) to find optimal solutions, we evaluated the following different management decisions: enlarging existing patches, linking patches via corridors, and creating a new patch. This is the first application of SDP to optimal landscape reconstruction and one of the few times that landscape reconstruction dynamics have been integrated with population dynamics. SDP is a powerful tool that has advantages over standard Monte Carlo simulation methods because it can give the exact optimal strategy for every landscape configuration (combination of patch areas and presence of corridors) and pattern of metapopulation occupancy, as well as a trajectory of strategies. It is useful when a sequence of management actions can be performed over a given time horizon, as is the case for many endangered species recovery programs, where only fixed amounts of resources are available in each time step. However, it is generally limited by computational constraints to rather small networks of patches. The model shows that optimal metapopulation management decisions depend greatly on the current state of the metapopulation, and there is no strategy that is universally the best. The extinction probability over 30 yr for the optimal state-dependent management actions is 50-80% better than no management, whereas the best fixed state-independent sets of strategies are only 30% better than no management. This highlights the advantages of using a decision theory tool to investigate conservation strategies for metapopulations. It is clear from these results that the sequence of management actions is critical, and this can only be effectively derived from stochastic dynamic programming. The model illustrates the underlying difficulty in determining simple rules of thumb for the sequence of management actions for a metapopulation. This use of a decision theory framework extends the capacity of population viability analysis (PVA) to manage threatened species.

a Cyclic pseudo-peptides derived from marine metabolites of the genus Lissoclinum bistratum and Lissoclinum patella have attracted scientific interest in the last two decades. Their structural properties and solution dynamics have been analyzed in detail, elaborate synthetic procedures for the natural products and synthetic derivatives developed, the biosynthetic pathways studied and it now is possible to produce them biosynthetically. Initially, these macrocyclic ligands were studied due to their medicinal and pharmaceutical potential -some of the isolated cyclic pseudo-peptides show high cytotoxic and antiviral activity.A major focus in the last decade has been on their Cu II coordination chemistry, as a number of studies have indicated that dinuclear Cu II complexes of cyclic peptides may be involved in the ascidians' metabolism, and this is the focus of the present review.

No abstract