Impacts of Chronic Anthropogenic Noise from Energy‐Sector Activity on Abundance of Songbirds in the Boreal Forest

Abstract: The effects of human activities in forests are often examined in the context of habitat conversion. Changes in habitat structure and composition are also associated with increases in the activity of people with vehicles and equipment, which results in increases in anthropogenic noise. Anthropogenic noise may reduce habitat quality for many species, particularly those that rely on acoustic signals for communication. We compared the density and occupancy rate of forest passerines close to versus far from noise‐generating compressor stations and noiseless well pads in the boreal forest of Alberta, Canada. Using distance‐based sampling, we found that areas near noiseless energy facilities had a total passerine density 1.5 times higher than areas near noise‐producing energy sites. The White‐throated Sparrow (Zonotrichia albicollis), Yellow‐rumped Warbler (Dendroica coronata), and Red‐eyed Vireo (Vireo olivaceus) were less dense in noisy areas. We used repeat sampling to estimate occupancy rate for 23 additional species. Seven had lower conditional or unconditional occupancy rates near noise‐generating facilities. One‐third of the species examined showed patterns that supported the hypothesis that abundance is influenced by anthropogenic noise. An additional 4 species responded negatively to edge effects. To mitigate existing noise impacts on birds would require approximately $175 million. The merits of such an effort relative to other reclamation actions are discussed. Nevertheless, given the $100 billion energy‐sector investment planned for the boreal forest in the next 10 years, including noise suppression technology at the outset of construction, makes noise mitigation a cost‐effective best‐management practice that might help conserve high‐quality habitat for boreal birds.     

Long‐Term Dynamics of a Fragmented Rainforest Mammal Assemblage

Abstract: Habitat fragmentation is a severe threat to tropical biotas, but its long‐term effects are poorly understood. We evaluated longer‐term changes in the abundance of larger (>1 kg) mammals in fragmented and intact rainforest and in riparian “corridors” in tropical Queensland, with data from 190 spotlighting surveys conducted in 1986–1987 and 2006–2007. In 1986–1987 when most fragments were already 20–50 years old, mammal assemblages differed markedly between fragmented and intact forest. Most vulnerable were lemuroid ringtail possums (Hemibelideus lemuroides), followed by Lumholtz's tree‐kangaroos (Dendrolagus lumholtzi) and Herbert River ringtail possums (Pseudocheirus herbertensis). Further changes were evident 20 years later. Mammal species richness fell significantly in fragments, and the abundances of 4 species, coppery brushtail possums (Trichosurus vulpecula johnstoni), green ringtail possums (Pseudochirops archeri), red‐legged pademelons (Thylogale stigmatica), and tree‐kangaroos, declined significantly. The most surprising finding was that the lemuroid ringtail, a strict rainforest specialist, apparently recolonized one fragment, despite a 99.98% decrease in abundance in fragments and corridors. A combination of factors, including long‐term fragmentation effects, shifts in the surrounding matrix vegetation, and recurring cyclone disturbances, appear to underlie these dynamic changes in mammal assemblages.     

Lichen Conservation in Heavily Managed Boreal Forests

Lichens are an important component of the boreal forest, where they are long lived, tend to accumulate in older stands, and are a major food source for the threatened woodland caribou (Rangifer tarandus caribou). To be fully sustainable, silvicultural practices in the boreal forest must include the conservation of ecological integrity. Dominant forest management practices, however, have short‐term negative effects on lichen diversity, particularly the application of herbicides. To better understand the long‐term effects of forest management, we examined lichen regeneration in 35 mixed black spruce (Picea mariana) and jack pine (Pinus banksiana) forest stands across northern Ontario to determine recovery following logging and postharvest silvicultural practices. Our forest stands were 25–40 years old and had undergone 3 common sivilcultural treatments that included harvested and planted; harvested, planted, and treated with N‐[phosphonomethyl] glycine (glyphosate); and harvested, planted, and treated with 2,4‐dichlorophenoxyacetic acid (2,4‐D). Forest stands with herbicide treatments had lower lichen biomass and higher beta and gamma diversity than planted stands that were not treated chemically or control stands. In northwestern Ontario, planted stands that were not treated chemically had significantly greater (p < 0.05) alpha diversity than stands treated with herbicides or control stands. Our results show that common silvicultural practices do not emulate natural disturbances caused by wildfires in the boreal forest for the lichen community. We suggest a reduction in the amount of chemical application be considered in areas where lichen biomass is likely to be high and where the recovery of woodland caribou is an objective. Conservación de Líquenes en Bosques Boreales Manejados Intensivamente     

Association of extinction risk of saproxylic beetles with ecological degradation of forests in Europe

To reduce future loss of biodiversity and to allocate conservation funds effectively, the major drivers behind large‐scale extinction processes must be identified. A promising approach is to link the red‐list status of species and specific traits that connect species of functionally important taxa or guilds to resources they rely on. Such traits can be used to detect the influence of anthropogenic ecosystem changes and conservation efforts on species, which allows for practical recommendations for conservation. We modeled the German Red List categories as an ordinal index of extinction risk of 1025 saproxylic beetles with a proportional‐odds linear mixed‐effects model for ordered categorical responses. In this model, we estimated fixed effects for intrinsic traits characterizing species biology, required resources, and distribution with phylogenetically correlated random intercepts. The model also allowed predictions of extinction risk for species with no red‐list category. Our model revealed a higher extinction risk for lowland and large species as well as for species that rely on wood of large diameter, broad‐leaved trees, or open canopy. These results mirror well the ecological degradation of European forests over the last centuries caused by modern forestry, that is the conversion of natural broad‐leaved forests to dense conifer‐dominated forests and the loss of old growth and dead wood. Therefore, conservation activities aimed at saproxylic beetles in all types of forests in Central and Western Europe should focus on lowlands, and habitat management of forest stands should aim at increasing the amount of dead wood of large diameter, dead wood of broad‐leaved trees, and dead wood in sunny areas.     

Identifying socioeconomic and biophysical factors driving forest loss in protected areas

Protected areas (PAs) are a commonly used strategy to confront forest conversion and biodiversity loss. Although determining drivers of forest loss is central to conservation success, understanding of them is limited by conventional modeling assumptions. We used random forest regression to evaluate potential drivers of deforestation in PAs in Mexico, while accounting for nonlinear relationships and higher order interactions underlying deforestation processes. Socioeconomic drivers (e.g., road density, human population density) and underlying biophysical conditions (e.g., precipitation, distance to water, elevation, slope) were stronger predictors of forest loss than PA characteristics, such as age, type, and management effectiveness. Within PA characteristics, variables reflecting collaborative and equitable management and PA size were the strongest predictors of forest loss, albeit with less explanatory power than socioeconomic and biophysical variables. In contrast to previously used methods, which typically have been based on the assumption of linear relationships, we found that the associations between most predictors and forest loss are nonlinear. Our results can inform decisions on the allocation of PA resources by strengthening management in PAs with the highest risk of deforestation and help preemptively protect key biodiversity areas that may be vulnerable to deforestation in the future.     

Use of an Airborne Lidar System to Model Plant Species Composition and Diversity of Mediterranean Oak Forests

Abstract: Airborne lidar is a remote‐sensing tool of increasing importance in ecological and conservation research due to its ability to characterize three‐dimensional vegetation structure. If different aspects of plant species diversity and composition can be related to vegetation structure, landscape‐level assessments of plant communities may be possible. We examined this possibility for Mediterranean oak forests in southern Portugal, which are rich in biological diversity but also threatened. We compared data from a discrete, first‐and‐last return lidar data set collected for 31 plots of cork oak (Quercus suber) and Algerian oak (Quercus canariensis) forest with field data to test whether lidar can be used to predict the vertical structure of vegetation, diversity of plant species, and community type. Lidar‐ and field‐measured structural data were significantly correlated (up to r= 0.85). Diversity of forest species was significantly associated with lidar‐measured vegetation height (R²= 0.50, p < 0.001). Clustering and ordination of the species data pointed to the presence of 2 main forest classes that could be discriminated with an accuracy of 89% on the basis of lidar data. Lidar can be applied widely for mapping of habitat and assessments of habitat condition (e.g., in support of the European Species and Habitats Directive [92/43/EEC]). However, particular attention needs to be paid to issues of survey design: density of lidar points and geospatial accuracy of ground‐truthing and its timing relative to acquisition of lidar data.     

Using land-use history and multiple baselines to determine bird responses to cocoa agroforestry

Agroforests can play an important role in biodiversity conservation in complex landscapes. A key factor distinguishing among agroforests is land-use history – whether agroforests are established inside forests or on historically forested but currently open lands. The disparity between land-use histories means the appropriate biodiversity baselines may differ, which should be accounted for when assessing the conservation value of agroforests. Specifically, comparisons between multiple baselines in forest and open land could enrich understanding of species’ responses by contextualizing them. We made such comparisons based on data from a recently published meta-analysis of the effects of cocoa (Theobroma cacao) agroforestry on bird diversity. We regrouped rustic, mixed shade cocoa, and low shade cocoa agroforests, based on land-use history, into forest-derived and open-land-derived agroforests and compared bird species diversity (species richness, abundance, and Shannon's index values) between forest and open land, which represented the 2 alternative baselines. Bird diversity was similar in forest-derived agroforests and forests (Hedges’ g* estimate [SE] = -0.3144 [0.3416], p = 0.36). Open-land-derived agroforests were significantly less diverse than forests (g* = 1.4312 [0.6308], p = 0.023) and comparable to open lands (g* = -0.1529 [0.5035], p = 0.76). Our results highlight how land-use history determined the conservation value of cocoa agroforests. Forest-derived cocoa agroforests were comparable to the available – usually already degraded – forest baselines, but entail future degradation risks. In contrast, open-land-derived cocoa agroforestry may offer restoration opportunities. Our results showed that comparisons among multiple baselines may inform relative contributions of agroforestry systems to bird conservation on a landscape scale.     

The Potential for Species Conservation in Tropical Secondary Forests

Abstract: In the wake of widespread loss of old‐growth forests throughout the tropics, secondary forests will likely play a growing role in the conservation of forest biodiversity. We considered a complex hierarchy of factors that interact in space and time to determine the conservation potential of tropical secondary forests. Beyond the characteristics of local forest patches, spatial and temporal landscape dynamics influence the establishment, species composition, and persistence of secondary forests. Prospects for conservation of old‐growth species in secondary forests are maximized in regions where the ratio of secondary to old‐growth forest area is relatively low, older secondary forests have persisted, anthropogenic disturbance after abandonment is relatively low, seed‐dispersing fauna are present, and old‐growth forests are close to abandoned sites. The conservation value of a secondary forest is expected to increase over time, as species arriving from remaining old‐growth forest patches accumulate. Many studies are poorly replicated, which limits robust assessments of the number and abundance of old‐growth species present in secondary forests. Older secondary forests are not often studied and few long‐term studies are conducted in secondary forests. Available data indicate that both old‐growth and second‐growth forests are important to the persistence of forest species in tropical, human‐modified landscapes.     

The Future of Scattered Trees in Agricultural Landscapes

Abstract: Mature trees scattered throughout agricultural landscapes are critical habitat for some biota and provide a range of ecosystem services. These trees are declining in intensively managed agricultural landscapes globally. We developed a simulation model to predict the rates at which these trees are declining, identified the key variables that can be manipulated to mitigate this decline, and compared alternative management proposals. We used the initial numbers of trees in the stand, the predicted ages of these trees, their rate of growth, the number of recruits established, the frequency of recruitment, and the rate of tree mortality to simulate the dynamics of scattered trees in agricultural landscapes. We applied this simulation model to case studies from Spain, United States, Australia, and Costa Rica. We predicted that mature trees would be lost from these landscapes in 90–180 years under current management. Existing management recommendations for these landscapes—which focus on increasing recruitment—would not reverse this trend. The loss of scattered mature trees was most sensitive to tree mortality, stand age, number of recruits, and frequency of recruitment. We predicted that perpetuating mature trees in agricultural landscapes at or above existing densities requires a strategy that keeps mortality among established trees below around 0.5% per year, recruits new trees at a rate that is higher than the number of existing trees, and recruits new trees at a frequency in years equivalent to around 15% of the maximum life expectancy of trees. Numbers of mature trees in landscapes represented by the case studies will decline before they increase, even if strategies of this type are implemented immediately. This decline will be greater if a management response is delayed.     

Effects of spatial autocorrelation and sampling design on estimates of protected area effectiveness

Estimating the effectiveness of protected areas (PAs) in reducing deforestation is useful to support decisions on whether to invest in better management of areas already protected or to create new ones. Statistical matching is commonly used to assess this effectiveness, but spatial autocorrelation and regional differences in protection effectiveness are frequently overlooked. Using Colombia as a case study, we employed statistical matching to account for confounding factors in park location and accounted for for spatial autocorrelation to determine statistical significance. We compared the performance of different matching procedures—ways of generating matching pairs at different scales—in estimating PA effectiveness. Differences in matching procedures affected covariate similarity between matched pairs (balance) and estimates of PA effectiveness in reducing deforestation. Independent matching yielded the greatest balance. On average 95% of variables in each region were balanced with independent matching, whereas 33% of variables were balanced when using the method that performed worst. The best estimates suggested that average deforestation inside protected areas in Colombia was 40% lower than in matched sites. Protection significantly reduced deforestation, but PA effectiveness differed among regions. Protected areas in Caribe were the most effective, whereas those in Orinoco and Pacific were least effective. Our results demonstrate that accounting for spatial autocorrelation and using independent matching for each subset of data is needed to infer the effectiveness of protection in reducing deforestation. Not accounting for spatial autocorrelation can distort the assessment of protection effectiveness, increasing type I and II errors and inflating effect size. Our method allowed improved estimates of protection effectiveness across scales and under different conditions and can be applied to other regions to effectively assess PA performance.