The homogenizing influence of agriculture on forest bird communities at landscape scales

Landscape Ecology - Agricultural expansion is a principal driver of biodiversity loss, but the impacts on community assembly in agro-ecosystems are less clear, especially across regional scales at...     

Mapping dead wood distribution in a temperate hardwood forest using high resolution airborne imagery

Dead wood, in the form of coarse woody debris and standing dead wood, or snags, is an essential structural component of forest ecosystems. It plays a key role in nutrient cycling, ecosystem functions and provision of habitat for a wide variety of species. In order to manage dead wood in a temperate hardwood forest, an understanding of its availability and spatial distribution is important. This research evaluates airborne digital camera remote sensing for mapping temperate forest dead wood across an area within Gatineau Park, Canada. Two approaches were evaluated: (1) direct detection and mapping of canopy dead wood (dead branches and tall snags) through the combination of three techniques in a hybrid classification: ISODATA clustering, object-based classification, and spectral unmixing, and (2) indirect modelling of coarse woody debris and snags using spectral and spatial predictor variables extracted from the imagery. Indirect modelling did not provide useful results while direct detection was successful with field validation showing 94% accuracy for detected canopy level dead wood objects (i.e. 94% of validation sites with canopy dead wood were detected correctly) and 90% accuracy for control sites (i.e. 90% of validation sites with no canopy level dead wood were identified correctly). The procedures presented in this paper are repeatable and could be used to monitor dead wood over time, potentially contributing to applications in forest carbon budget estimation, biodiversity management, and forest inventory.     

Assessing carbon storage and sequestration by Canada's urban forests using high resolution earth observation data

Urban trees are important components of the landscape and offer numerous benefits; both socio-economical and biophysical. Urban trees act as a sink for CO₂, helping to offset carbon emissions from urban areas by removing the greenhouse gas from the atmosphere through photosynthesis. Environment Canada develops estimates of Canada's greenhouse gas emissions and removals which are submitted annually to the United Nations as part of ongoing commitments under the United Nations Framework Convention for Climate Change. As part of these reporting commitments countries are required to develop estimates of emissions and removals of Greenhouse Gas that are the result of direct impact of human activities in the Land-Use, Land-Use Change and Forestry Sector. Here, we present an approach which involves sampling high resolution aerial photographs to determine urban tree coverage across Canada's major urban areas. Our results suggest Canadian urban areas have an estimated tree canopy cover of 27%. This tree cover is estimated to store approximately 34,000 kt C and annually sequester approximately 2500 kt of CO₂. These estimates show significant improvement over previous methods used to provide Canadian estimates. The methods developed here are easily repeatable which allow for temporal changes to be analyzed and assessed over time.     

Optimizing landscape selection for estimating relative effects of landscape variables on ecological responses

Empirical studies of the relative effects of landscape variables may compromise inferential strength with common approaches to landscape selection. We propose a methodology for landscape sample selection that is designed to overcome some common statistical pitfalls that may hamper estimates of relative effects of landscape variables on ecological responses. We illustrate our proposed methodology through an application aimed at quantifying the relationships between farmland heterogeneity and biodiversity. For this project, we required 100 study landscapes that represented the widest possible ranges of compositional and configurational farmland heterogeneity, where these two aspects of heterogeneity were quantified as crop cover diversity (Shannon diversity index) and mean crop field size, respectively. These were calculated at multiple spatial extents from a detailed map of the region derived through satellite image segmentation and classification. Potential study landscapes were then selected in a structured approach such that: (1) they represented the widest possible range of both heterogeneity variables, (2) they were not spatially autocorrelated, and (3) there was independence (no correlation) between the two heterogeneity variables, allowing for more precise estimates of the regression coefficients that reflect their independent effects. All selection criteria were satisfied at multiple extents surrounding the study landscapes, to allow for multi-scale analysis. Our approach to landscape selection should improve the inferential strength of studies estimating the relative effects of landscape variables, particularly those with a view to developing land management guidelines.     

Landscape Fragmentation and Ice Storm Damage in Eastern Ontario Forests

With return times between 20 and 100 years, ice storms are a primary disturbance type for temperate forests of eastern North America. Many studies have been conducted at the forest patch and plot scales to examine relations between damage and variables describing site, composition and structure. This paper presents results from a landscape scale study of fragmentation relations with damage in eastern Ontario forests. Data previously collected for two independent and spatially non-overlapping patch level damage studies were used. A Generalized Linear Model (GLM) was used to analyse relations between damage and fragmentation metrics representing patch isolation, edge density, and the relative size and distribution of patches in the landscape. The metrics were applied using spatial extents of 1 × 1 km and 4 × 4 km, following analyses of the variability of numbers of patches and of the lacunarity of forest patterns over a range of extents. The results showed that patch isolation, as measured by the mean Euclidean distance between patches (ENN) was significantly related to damage.