Heavy browsing pressure from large ungulates is a multicontinent phenomenon that causes regeneration failure of many palatable tree species and induces important socioeconomic and ecological impacts in forest ecosystems. The development of forest management practices that address adequately this issue, however, remains scarce and challenging because (1) large herbivores are both a resource and a source of disturbance; (2) the management of forests and ungulate populations remains largely disconnected in practice; and (3) we still lack a good understanding of the role of critical factors, especially deer densities, vegetation attributes, and their interactions, on the magnitude of browsing damages on forest regeneration. We bring new insights into these challenging issues by critically reviewing the current methods used by managers and conservationists to mitigate deer impacts on forest regeneration, emphasizing the spatial scale at which these methods are undertaken. Specifically, we review management actions at multiple scales on both deer populations (e.g., hunting) and vegetation (e.g., silvicultural treatments) that are common to most deer–forest systems and, for that reason, deserve priority investigation. We identify strengths and limitations of current management actions and highlight the main research gaps. Based on this review, we propose a new integrated management scheme that explicitly addresses: (1) the integration and prioritization of management actions, (2) the development of adaptive management plans, and (3) the participation of stakeholders. Conflicting demands by different stakeholders have challenged the effectiveness of management strategies in deer–forest systems. To reverse this situation, we advocate for a shift of paradigm and the development of integrated strategies that (1) bridge the gap between management actions and the design of in situ experiments and (2) coordinate actions at multiple spatial scales on both deer populations and forests. We propose a new framework informed by key objectives and grounded in the adaptive management paradigm to support this transition, and suggest a research agenda for the next decade(s).

For over three decades, the importance of taxon sampling curves for comparative biodiversity studies has been repeatedly stated. However, many entomologists (both within Canada and worldwide) continue to publish studies without standardizing their data to take sampling effort into account. We present a case study to illustrate the importance of such standardization, using the collection of spiders (Araneae) by pitfall traps as model data. Data were analyzed using rarefaction to represent one example of a taxon sampling curve, and by a variety of traditional diversity indices to describe alpha diversity. Raw species richness and single-index diversity measures (Shannon–Wiener, Simpson's, and Fisher's α) provided contradictory results. Rarefied species richness standardized to the number of individuals collected enabled more accurate comparisons of diversity and revealed when sampling was insufficient. Focusing on arthropods occurring in forested ecosystems, we also examined the use of taxon sampling curves in current literature by reviewing 133 published articles from 14 journals. Only 26% of the published articles in our review used a taxon sampling curve, and raw species richness and the Shannon–Wiener index of diversity were the most commonly used estimates. There is clearly a need to modify how alpha diversity is measured and compared for arthropod biodiversity studies. We recommend the abandonment of both raw species richness and single-index measures of diversity, and reiterate the need to use rarefaction or a related technique that allows for meaningful comparisons of species richness while taking into account sampling effort.

Summary: 1. Spatial analysis of ecological data is central to many interesting questions in ecology. Bayesian implementation of spatially explicit models has received increasing attention from ecologists as Monte Carlo Markov Chain (MCMC) methods have become freely accessible. MCMC simulations offer a flexible framework for modelling extensive ecological data, but they also come with a wide range of problems regarding convergence, processing time and implementation.2. We introduce to ecologists an alternative procedure for fitting Bayesian hierarchical spatial models (BHSM) with quite general spatial covariance structures. This procedure uses integrated nested Laplace approximations (INLA) as an alternative to MCMC.3. We show, using a case study of species distribution model with binary areal data, that implementing BHSM with INLA does not require advanced programming skills, yields accurate results compared with MCMC and is rapid (e.g. a few seconds with small to moderate data sets). BHSMs efficiently removed spatial autocorrelation in the residuals and fairly evaluated uncertainty in parameter estimates and predictions.4. The rapidity of INLA significantly decreased the processing time and allowed both sensitivity analyses on priors and cross‐validation tests to be performed within a reasonable amount of time, which ultimately increased model transparency.

Many deer populations have recently increased worldwide leading to strong direct and indirect ecological and socioeconomical impacts on the composition, dynamic, and functions of forest ecosystems. Deer directly modify the composition and structure of vegetation communities, but they also indirectly affect other species of the ecosystem by modifying the structure of the vegetation. Here we review the results of a research program on overabundant white-tailed deer (Odocoileus virginianus) in the boreal forest of Anticosti Island (Québec, Canada) aimed at identifying deer densities compatible with forest regeneration. Various silvicultural systems and treatments failed to regenerate deer habitat at high deer densities, but planting size-adapted seedlings could be effective at moderate densities. Using a controlled deer density experiment, we found vegetation recovery at deer densities ≤ 15 deer/km². The same experiment revealed that other groups of organisms such as insects and birds responded favorably to a reduction of deer density. We also found that alternative successional trajectories may occur after a certain period of heavy browsing during early succession. We conclude that one of the most important remaining research gaps is the need to identify habitat-specific threshold densities at which deer impacts occur and then to design effective wildlife and forest management strategies to limit deer impacts and sustain ecosystem integrity.