Avian relationships with wildfire at two dry forest locations with different historical fire regimes

Avian Response to Wildfire Severity in a Northern Boreal Region

Research Highlights: The effects of fire on birds in the most northern parts of the boreal forest are understudied. We found distinct differences in bird communities with increasing fire severity in two vegetation types with naturally different burn severity. The highest severity burns tended to have communities dominated by generalist species, regardless of the original vegetation type. Background and Objectives: Wildfire is the primary natural disturbance in the boreal ecosystems of northwestern Canada. Increased wildfire frequency, extent, and severity are expected with climate change in this region. In particular, the proportion of burns that are high severity and the area of peatlands burned are increasing, and how this influences birds is poorly understood. Materials and Methods: We quantified the effects of burn severity (low, moderate, and high severity) in uplands and peatlands on occupancy, density, richness, community composition, and functional diversity using point counts (n = 1158) from the first two years post-fire for two large fires in the Northwest Territories, Canada. Results: Burn severity had a significant effect on the occupancy and density of 86% of our focal species (n = 20). Responses to burn severity depended on vegetation type for four of the 18 species using occupancy and seven of the 18 using density, but were typically in a similar direction. Species richness and functional diversity were lower in areas of high severity burns than unburned areas and low severity burns in peatlands. Richness was not related to severity in uplands, but functional diversity was. Peatlands had higher species richness than uplands in all burn severities, but as burn severity increased the upland and peatland communities became more similar. Conclusions: Our results suggest that high severity burns in both vegetation types support five generalist species and two fire specialists that may benefit from alterations in vegetation structure as a result of climate induced changes to fire regimes. However, eight species avoided burns, particularly birds preferring peatlands, and are likely to be more susceptible to fire-driven changes to their habitat caused by climate change. Understanding the long-term risks to these species from climate change requires additional efforts that link fire to bird populations.

Dry conifer forest restoration benefits Colorado Front Range avian communities

Fire suppression has increased stand density and risk of severe, stand-replacing wildfire in lower elevation dry conifer forests of western North America, threatening ecological function. The U.S. Forest Service's Collaborative Forest Landscape Restoration Program (CFLRP) aims to mitigate impacts to ecological function, while mandating effectiveness monitoring to verify restoration success. Expected benefits include improved conditions for biodiversity, but relatively few empirical studies evaluate restoration effects on biodiversity. We applied the Integrated Monitoring in Bird Conservation Regions program to survey birds in relation to CFLRP treatments along the Colorado Front Range in 2015-2017. We employed hierarchical models to analyze species occupancy and richness at 1972 points nested within 141 1-km² grid cells. Our objectives were to investigate (1) species occupancy relationships with treatments at local (point) and landscape (grid) spatial scales, (2) potential mechanisms for treatment relationships considering species and treatment relationships with forest structure and composition (i.e., habitat relationships), and (3) treatment and habitat relationships with species richness. The data supported positive and negative point-level treatment relationships, suggesting uneven species distributions between treated and untreated points. At the grid scale, however, we only found positive species relationships with percent area treated, and accordingly, grid-level species richness increased with treatment extent. Potential mechanisms for treatment relationships included treatments generating foraging opportunities for aerial insectivores by opening the canopy, improving conditions for ground-associated species by increasing herbaceous growth, and limiting opportunities for shrub-nesting species by reducing shrub cover. Landscape-scale patterns suggest CFLRP treatments can benefit avian communities by generating habitat for open-forest species without necessarily eliminating habitat for closed-forest species. Our results provide evidence for a commonly expected but rarely verified pattern of increased species richness with forest heterogeneity. We suggest restoration treatments will most benefit forest bird diversity by reducing canopy cover, encouraging herbaceous ground cover, limiting ladder fuel species, and encouraging shrub diversity in canopy openings, while maintaining some dense forest stands on the landscape.

An integration framework for linking avifauna niche and forest landscape models

Avian cavity nesters (ACN) are viable indicators of forest structure, composition, and diversity. Utilizing these species responses in multi-disciplinary climate-avian-forest modeling can improve climate adaptive management. We propose a framework for integrating and evaluating climate-avian-forest models by linking two ACN niche models with a forest landscape model (FLM), LANDIS-II. The framework facilitates the selection of available ACN models for integration, evaluation of model transferability, and evaluation of successful integration of ACN models with a FLM. We found selecting a model for integration depended on its transferability to the study area (Northern Rockies Ecoregion of Idaho in the United States), which limited the species and model types available for transfer. However, transfer evaluation of the tested ACN models indicated a good fit for the study area. Several niche model variables (canopy cover, snag density, and forest cover type) were not directly informed by the LANDIS-II model, which required secondary modeling (Random Forest) to derive values from the FLM outputs. In instances where the Random Forest models performed with a moderate classification accuracy, the overall effect on niche predictions was negligible. Predictions based on LANDIS-II simulations performed similarly to predictions based on the niche model’s original training input types. This supported the conclusion that the proposed framework is viable for informing avian niche models with FLM simulations. Even models that poorly approximate habitat suitability, due to the inherent constraints of predicting spatial niche use of irruptive species produced informative results by identifying areas of management focus. This is primarily because LANDIS-II estimates spatially explicit variables that were unavailable over large spatial extents from alternative datasets. Thus, without integration, one of the ACN niche models was not applicable to the study area. The framework will be useful for integrating avifauna niche and forest ecosystem models, which can inform management of contemporary and future landscapes under differing management and climate scenarios.

Precision gain versus effort with joint models using detection/non-detection and banding data

Capture-recapture techniques provide valuable information, but are often more cost-prohibitive at large spatial and temporal scales than less-intensive sampling techniques. Model development combining multiple data sources to leverage data source strengths and for improved parameter precision has increased, but with limited discussion on precision gain versus effort. We present a general framework for evaluating trade-offs between precision gained and costs associated with acquiring multiple data sources, useful for designing future or new phases of current studies.We illustrated how Bayesian hierarchical joint models using detection/non-detection and banding data can improve abundance, survival, and recruitment inference, and quantified data source costs in a northern Arizona, USA, western bluebird (Sialia mexicana) population. We used an 8-year detection/non-detection (distributed across the landscape) and banding (subset of locations within landscape) data set to estimate parameters. We constructed separate models using detection/non-detection and banding data, and a joint model using both data types to evaluate parameter precision gain relative to effort.Joint model parameter estimates were more precise than single data model estimates, but parameter precision varied (apparent survival > abundance > recruitment). Banding provided greater apparent survival precision than detection/non-detection data. Therefore, little precision was gained when detection/non-detection data were added to banding data. Additional costs were minimal; however, additional spatial coverage and ability to estimate abundance and recruitment improved inference. Conversely, more precision was gained when adding banding to detection/non-detection data at higher cost. Spatial coverage was identical, yet survival and abundance estimates were more precise. Justification of increased costs associated with additional data types depends on project objectives.We illustrate a general framework for evaluating precision gain relative to effort, applicable to joint data models with any data type combination. This framework evaluates costs and benefits from and effort levels between multiple data types, thus improving population monitoring designs.