A resource selection function (RSF) is any model that yields values proportional to the probability of use of a resource unit. RSF models often are fitted using generalized linear models (GLMs) although a variety of statistical models might be used. Information criteria such as the Akaike Information Criteria (AIC) or Bayesian Information Criteria (BIC) are tools that can be useful for selecting a model from a set of biologically plausible candidates. Statistical inference procedures, such as the likelihood-ratio test, can be used to assess whether models deviate from random null models. But for most applications of RSF models, usefulness is evaluated by how well the model predicts the location of organisms on a landscape. Predictions from RSF models constructed using presence/absence (used/ unused) data can be evaluated using procedures developed for logistic regression, such as confusion matrices, Kappa statistics, and Receiver Operating Characteristic (ROC) curves. However, RSF models estimated from presence/ available data create unique problems for evaluating model predictions. For presence/available models we propose a form of k -fold cross validation for evaluating prediction success. This involves calculating the correlation between RSF ranks and area-adjusted frequencies for a withheld sub-sample of data. A similar approach can be applied to evaluate predictive success for out-of-sample data. Not all RSF models are robust for application in different times or different places due to ecological and behavioral variation of the target organisms. #

The management of landscapes for biological conservation and ecologically sustainable natural resource use are crucial global issues. Research for over two decades has resulted in a large literature, yet there is little consensus on the applicability or even the existence of general principles or broad considerations that could guide landscape conservation. We assess six major themes in the ecology and conservation of landscapes. We identify 13 important issues that need to be considered in developing approaches to landscape conservation. They include recognizing the importance of landscape mosaics (including the integration of terrestrial and aquatic areas), recognizing interactions between vegetation cover and vegetation configuration, using an appropriate landscape conceptual model, maintaining the capacity to recover from disturbance and managing landscapes in an adaptive framework. These considerations are influenced by landscape context, species assemblages and management goals and do not translate directly into on-the-ground management guidelines but they should be recognized by researchers and resource managers when developing guidelines for specific cases. Two crucial overarching issues are: (i) a clearly articulated vision for landscape conservation and (ii) quantifiable objectives that offer unambiguous signposts for measuring progress.

Multi-scale resource selection modeling is used to identify factors that limit species distributions across scales of space and time. This multi-scale nature of habitat suitability complicates the translation of inferences to single, spatial depictions of habitat required for conservation of species. We estimated resource selection functions (RSFs) across three scales for a threatened ungulate, woodland caribou (Rangifer tarandus caribou), with two objectives: (1) to infer the relative effects of two forms of anthropogenic disturbance (forestry and linear features) on woodland caribou distributions at multiple scales and (2) to estimate scale-integrated resource selection functions (SRSFs) that synthesize results across scales for management-oriented habitat suitability mapping. We found a previously undocumented scale-specific switch in woodland caribou response to two forms of anthropogenic disturbance. Caribou avoided forestry cut-blocks at broad scales according to first- and second-order RSFs and avoided linear features at fine scales according to third-order RSFs, corroborating predictions developed according to predator-mediated effects of each disturbance type. Additionally, a single SRSF validated as well as each of three single-scale RSFs when estimating habitat suitability across three different spatial scales of prediction. We demonstrate that a single SRSF can be applied to predict relative habitat suitability at both local and landscape scales in support of critical habitat identification and species recovery.

Summary1. The analysis of large heterogeneous data sets of avian point-count surveys compiled across studies is hindered by a lack of analytical approaches that can deal with detectability and variation in survey protocols. 2. We reformulated removal models of avian singing rates and distance sampling models of the effective detection radius (EDR) to control for the effects of survey protocol and temporal and environmental covariates on detection probabilities. 3. We estimated singing rates and EDR for 75 boreal forest songbird species and found that survey protocol, especially point-count radius, explained most of the variation in detectability. However, environmental and temporal covariates (date, time, vegetation) affected singing rates and EDR for 73% and 59% of species, respectively. 4. Unadjusted survey counts increased by an average of 201% from a 5-min, 50-m radius survey to a 10-min, 100-m radius survey (n = 75 species). This variability was decreased to 8Á5% using detection probabilities estimated from a combination of removal and distance sampling models. 5. Our modelling approach reduced computation when fitting complex models to large data sets and can be used with a wide range of statistical techniques for inference and prediction of avian densities.

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Aim Species and ecosystems may be unable to keep pace with rapid climate change projected for the 21st century. We evaluated an underexplored dimension of the mismatch between climate and biota: limitations to forest growth and succession affecting habitat suitability. Our objective was to inform continental-scale conservation for boreal songbirds under disequilibria between climate, vegetation and fauna.Location Boreal and southern arctic ecoregions of North America.Methods We used forest inventory and avian survey data to classify 53 species by seral-stage affinity and applied these to generate alternative projections of changes in species' core habitat distributions based on different vegetation lagtime assumptions. We used our seral stage-modified refugia approach and the Zonation algorithm to identify multispecies boreal conservation priorities over the 21st century. We evaluated the sensitivity of land rankings to seral-stage affinity and species' weights and assessed the conservation value of the existing protected areas network compared to Zonation results.Results End-of-century projected changes in songbird distribution were reduced by up to 169% when vegetation lags were considered. Zonation land rankings based on unconstrained climate projections were concentrated at high latitudes, whereas those based on strict and modified refugia scenarios were concentrated in coastal and high-elevation areas, as well as biome transition zones, which were fairly consistent over time and species weights. The existing protected areas network covering 14% of the study area was estimated to conserve 12-14% of baseline avian biodiversity across time periods and scenarios, compared to 16-25% for top-ranked Zonation areas.Main conclusions For some boreal songbirds, limits to forest growth and succession may result in dramatic reductions in suitable habitat over the next century. Our seral stage-adjusted approach provides conservative and efficient boreal conservation priorities anchored around climatic macrorefugia that are robust to century-long climate change and complement the current protected areas network.

In North American boreal forests, wildfire is the dominant agent of natural disturbance. A natural-disturbance model has therefore been promoted as an ecologically based approach to forest harvesting in these systems. Given accelerating resource demands, fire competes with harvest for timber and there is increasing pressure to salvage naturally burned areas. This creates a management paradox: simultaneous promotion of natural disturbance as a guide to sustainability while salvaging forests that have been naturally disturbed. The major drivers of postfire salvage in Canadian boreal forests are societal perceptions, overallocation of forest resources, and economic and policy incentives, and postfire salvage compromisesforest sustainability by diminishing the role of fire as a critical, natural process. These factors might be reconciled through consideration of fire in resource allocations and application of active adaptive management. We provide novel treatment of the role of burn severity in mediating biotic response by examining its influence on the amount, type, and distribution of live, postfire residual material, and we highlight the role of fire in shaping spatial and temporal patterns in forest biodiversity. Maintenance of natural postfire forests is a critical component of an ecosystem-based approach to forest management in boreal systems. Nevertheless, presentpracticesfocus heavily on expediting removal of timber from burned forests, despite increasing evidence that postfire communities differ markedly from postharvest systems, and there is a mismatch between emerging management models and past management practices. Policies that recognize the critical role of fire in these systems and facilitate enhanced understanding of natural system dynamics in support of development of sustainable management practices are urgently needed.

We used binomial distance-sampling models to estimate the effective detection radius (EDR) of point-count surveys across boreal Canada. We evaluated binomial models based on 0-50 m and >50 m distance categories for goodness-of-fit and sensitivities to variation in survey effort and habitats sampled. We also compared binomial EDRs to Partners in Flight's maximum detection distances (MDD) to determine differences in landbird population sizes derived from each. Binomial EDRs had a small positive bias (4%) averaged across 86 species and a large positive bias (30-82%) for two species when compared with EDRs estimated using multinomial distance sampling. Patterns in binomial EDRs were consistent with how bird songs attenuate in relation to their frequencies and transmission through different habitats. EDR varied 12% among habitats and increased 17% when birds were counted to an unlimited distance, compared with a limited distance of 100 m. The EDR did not vary with the duration of surveys, and densities did not differ when using unlimited-distance versus truncated data. Estimated densities, however, increased 19% from 3-to 5-min counts and 25% from 5-to 10-min counts, possibly from increases in the availability, movement, or double counting of birds with longer counts. Thus, investigators should be cautious when comparing distance-sampling results among studies if methods vary. Population sizes estimated using EDR averaged 5 times (0.8-15 times) those estimated with MDD. Survey data from which to estimate binomial EDRs are widely available across North America and could be used as an alternative to MDD when estimating landbird population sizes. Utilisation de modèles binomiaux d'échantillonnages basés sur la distance pour estimer le rayon de détection effectif lors d'inventaires par points d'écoute en région boréale canadienneRésumé.-Nous avons utilisé des modèles binomiaux d'échantillonnages basés sur la distance afin d'estimer le rayon de détection effectif (RDE) des inventaires par points d'écoute en région boréale canadienne. Nous avons évalué des modèles binomiaux basés sur des catégories de distance de 0-50 m et >50 m pour en déterminer l'adéquation et les sensibilités aux variations de l'effort d'inventaire et les habitats échantillonnés. Nous avons aussi comparé les RDE binomiaux aux distances de détection maximales de Partenaires d'envol (DDM) afin de déterminer les différences dans les tailles de populations des oiseaux terrestres estimées. Les RDE binomiaux avaient un léger biais positif (4 %) en moyenne pour 86 espèces et un biais positif élevé (30-82 %) pour deux espèces lorsque comparés aux RDE estimés à l'aide d'un échantillonnage multinomial selon la distance. Les patrons des RDE binomiaux étaient consistants avec la façon dont les chants d'oiseaux s'atténuent en fonction de leur fréquence et de leur transmission à travers différents habitats. Les RDE variaient de 12 % entre les habitats et augmentaient de 17 % lorsque les oiseaux étaient dénombrés à une distance illimitée, comparativement à une distanc...