Valuing wildlife: a review of methods

The paper analyses the costs and benefits of conserving wildlife and reports part of a wider research project which aims to estimate the benefits of certain ecological types and habitats, and to compare the outcome of different techniques used to value wildlife. The authors outline a range of philosophical, technical and methodological problems in deriving cardinal measures of costs and benefits.     

Linking life history to landscape for threatened species conservation in a multiuse region

Landscape-scale conservation that considers metapopulation dynamics will be essential for preventing declines of species facing multiple threats to their survival. Toward this end, we developed a novel approach that combines occurrence records, spatial–environmental data, and genetic information to model habitat, connectivity, and patterns of genetic structure and link spatial attributes to underlying ecological mechanisms. Using the threatened northern quoll (Dasyurus hallucatus) as a case study, we applied this approach to address the need for conservation decision-making tools that promote resilient metapopulations of this threatened species in the Pilbara, Western Australia, a multiuse landscape that is a hotspot for biodiversity and mining. Habitat and connectivity were predicted by different landscape characteristics. Whereas habitat suitability was overwhelmingly driven by terrain ruggedness, dispersal was facilitated by proximity to watercourses. Although there is limited evidence for major physical barriers in the Pilbara, areas with high silt and clay content (i.e., alluvial and hardpan plains) showed high resistance to dispersal. Climate subtlety shaped distributions and patterns of genetic turnover, suggesting the potential for local adaptation. By understanding these spatial–environmental associations and linking them to life-history and metapopulation dynamics, we highlight opportunities to provide targeted species management. To support this, we have created habitat, connectivity, and genetic uniqueness maps for conservation decision-making in the region. These tools have the potential to provide a more holistic approach to conservation in multiuse landscapes globally.     

Use of three monitoring approaches to manage a major <Emphasis Type="Italic">Chrysosporum ovalisporum</Emphasis> bloom in the Murray River,Australia, 2016

An unusual bloom of Chrysosporum ovalisporum (basionym Aphanizomenon ovalisporum) occurred for the first time in the Murray River and distributary rivers in New South Wales, Australia, from mid-February to early June 2016. At its greatest extent, it contaminated a combined river length of ca. 2360 km. Chrysosporum ovalisporum usually comprised >99% of the total bloom biovolume at most locations sampled, which at times exceeded 40 mm³ l^?1. The origins of the bloom were most likely reservoirs on the upper Murray River, with cyanobacterial-infested water released from them contaminating the river systems downstream. An integrated approach using three analytical methods: (1) identification and enumeration by microscopy, (2) multiplex quantitative polymerase chain reaction (qPCR), and (3) toxin analysis, was used to obtain data for the assessment of risk to water users and management of the bloom. qPCR indicated some cyrA and stxA genes responsible for cylindrospermopsin and saxitoxin biosynthesis respectively were present, but mostly below the level of quantification. No mcyE genes for microcystin biosynthesis were detected. Toxin analysis also revealed that cylindrospermopsin, saxitoxin and microcystin were all below detection. Lack of measurable toxicity in a species usually considered a cylindrospermopsin producer elsewhere meant the possibility of relaxing management guidelines; however, high (Red) alerts needed to be maintained due to risk to water users from other biohazards potentially produced by the cyanobacteria such as contact irritants. A three-tiered monitoring strategy is suggested for monitoring cyanobacterial blooms to provide enhanced data for bloom management.