Summary Model selection is difficult. Even in the apparently straightforward case of choosing between standard linear regression models, there does not yet appear to be consensus in the statistical ecology literature as to the right approach. We review recent works on model selection in ecology and subsequently focus on one aspect in particular: the use of the Akaike Information Criterion (AIC) or its small‐sample equivalent, AICC. We create a novel framework for simulation studies and use this to study model selection from simulated data sets with a range of properties, which differ in terms of degree of unobserved heterogeneity. We use the results of the simulation study to suggest an approach for model selection based on ideas from information criteria but requiring simulation. We find that the relative predictive performance of model selection by different information criteria is heavily dependent on the degree of unobserved heterogeneity between data sets. When heterogeneity is small, AIC or AICC are likely to perform well, but if heterogeneity is large, the Bayesian Information Criterion (BIC) will often perform better, due to the stronger penalty afforded. Our conclusion is that the choice of information criterion (or more broadly, the strength of likelihood penalty) should ideally be based upon hypothesized (or estimated from previous data) properties of the population of data sets from which a given data set could have arisen. Relying on a single form of information criterion is unlikely to be universally successful.

ABSTRACT1. The feasibility of using River Habitat Survey (RHS) data to describe freshwater pearl mussel (Margaritifera margaritifera) macrohabitat in the River Spey, north-east Scotland, was investigated.2. Mussels were found to be positively associated with a number of RHS variables. These included: boulder/cobble river bed substrates, broken/unbroken standing waves (channel flow types), aquatic liverworts/mosses/lichens and broadleaf/mixed woodland/bankside tree cover. Negative associations with gravel-pebble/silt substrates and emergent reeds/sedges/herbs were also found.3. Two binary logistic regression models, based on seven and four variables, respectively, were constructed in order to predict the presence/absence of mussels at any given site. Predictive success rates of 83% and 78% were achieved.4. Another binary logistic regression model, based on four variables, was constructed in order to predict the occurrence of 'optimal' M. margaritifera habitat (overall mussel densities 51 m À2 ). A predictive success rate of 83% was achieved.5. The results indicate two potentially important applications of RHS for the conservation management of M. margaritifera: (1) for monitoring the effects of physical changes on extant mussel beds (and predicting their effects on mussel populations), and (2) for determining the habitat suitability of historically occupied sites for re-introductions.

Whilst a number of studies have examined the effects of biodiversity conservation on the delivery of ecosystem services, they are often limited in the scope of the ecosystem services (ES) assessed and can suffer from confounding spatial issues. This paper examines the impacts of nature conservation on the delivery of a full suite of ES across nine case studies in the UK, using expert opinion. The case studies covered a range of habitats and explore the delivery of ES from a 'protected site' and a comparable 'non-protected' site. By conducting pair-wise comparisons of ES delivery between comparable sites our study attempts to mitigate confounding cause and effect factors in relation to spatial context in correlative studies. The analysis showed that protected sites deliver higher levels of ecosystem services than non-protected sites, with the main differences being in the cultural and regulating ecosystem services. Against expectations, there was no consistent negative impact of protection on provisioning services across these case studies. Whilst the analysis demonstrated general patterns in ES delivery between protected and non-protected sites, the individual responses in each case study highlights the importance of the local social, biophysical, economic and temporal context of individual protected areas and the associated management.

The freshwater pearl mussel (Margaritifera margaritifera) is an endangered species in Europe, protected nationally and internationally, but with a steadily declining range and abundance owing to pressures such as pollution, river engineering, and illegal exploitation. Despite this, no consistent approaches have been developed around Europe for monitoring pearl mussel populations and their habitats. To address this need, experts on pearl mussel ecology from 11 countries met at a series of workshops in order to develop a protocol for monitoring, published under the auspices of the European Committee for Standardization (CEN). This standard is unique, as it is the first CEN standard dedicated to a single species of conservation concern. The standard is aimed at scientists, conservation bodies, and environmental regulators, and can be used for designing national monitoring programmes as well as reporting on the conservation status of pearl mussel populations under the European Habitats Directive. It contains guidance at the individual site level to determine why populations are failing to recruit, but also addresses the need for a wider‐scale approach to ensure that catchment developments do not have adverse impacts on rivers containing pearl mussels. A pearl mussel monitoring programme needs to investigate the size and viability of populations, as well as the fish hosts (Atlantic salmon, Salmo salar, or brown trout, Salmo trutta) on which pearl mussel larvae depend. Water quality, including variables such as dissolved oxygen, acid–base chemistry, and nutrient levels, is also an essential monitoring component, together with the physical features of the river bed, river flow regimes, and sediment dynamics. It is hoped that this pan‐European approach will improve the ability to compare data across many countries, and will ultimately ensure that the results of monitoring are translated into measures for improving the conservation status of the freshwater pearl mussel throughout its range.

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Catchment management in the developed world is undergoing a fundamental reconfiguration in which top-down governance is being challenged by local organisations promoting collaborative decisionmaking. Local, participation-based organisations are emerging as mediators of relations between governments and publics. These organisations, defined here as participatory catchment organisations (PCOs), are emergent at a time when developed world catchment management is itself undergoing substantial change. Through in-depth engagement with four PCOs, and using six case studies, we identify the principles associated with successful problem resolution. The findings illustrate the importance of PCOs as two-way bridges between publics and governments. We identify three principles shared by these organisations that show how, through participatory approaches founded on trust, complicated problems can be resolved in ways that do not unduly punish groups or individuals. In conclusion, we identify four questions that highlight the need to consider the practicality of evolving relations amongst governments, publics, and the organisations that have come to mediate catchment management.

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Nature-based solutions are widely advocated for freshwater ecosystem conservation and restoration. As increasing amounts of river restoration are undertaken, the need to understand the ecological response to different measures and where measures are best applied becomes more pressing. It is essential that appraisal methods follow a sound scientific approach. Here, experienced restoration appraisal experts review current best practice and academic knowledge to make recommendations and provide guidance that will enable practitioners to gather and analyse meaningful data, using scientific rigor to appraise restoration success. What should be monitored depends on the river type and the type and scale of intervention. By understanding how habitats are likely to change we can anticipate what species, life stages, and communities are likely to be affected. Monitoring should therefore be integrated and include both environmental/habitat and biota assessments. A robust scientific approach to monitoring and appraisal is resource intensive. We recommend that appraisal efforts be directed to where they will provide the greatest evidence, including ‘flagship’ restoration schemes for detailed long-term monitoring. Such an approach will provide the evidence needed to understand which restoration measures work where and ensure that they can be applied with confidence elsewhere.