Panel VIIIA: A Landscape Perspective on Sustainability: Connectivity and Landcover
Landscape fragmentation and connectivity are fundamental concepts in the study of wildlife movement and population dynamics. They are relevant to conservation efforts and investigations into the effects of anthropogenic landscape change and climate change. Fragmentation has been increasing at a rapid pace in many parts of Canada due to anthropogenic land conversion for urban development, road construction, and agriculture. Remaining unfragmented areas of the landscape are becoming smaller and smaller, negatively affecting wildlife populations by reducing habitat amount and quality and subdividing populations into smaller and more vulnerable fractions. Due to the intrinsic association of landscape fragmentation and landscape connectivity, it is important to recognise how exactly the methods for measuring these concepts are related. In general, the concept of fragmentation implies a reduction in connectivity in the remaining ecological network. However, depending on the approach used to quantify these concepts, differing and contradictory conclusions can be made about how fragmentation and connectivity are related. Our literature review has shown that it is often not clear what these concepts mean exactly. We are analysing a selection of quantification approaches in order to clarify the relationship between “connectivity”, “fragmentation”, and “fragmentation per se”. In particular, this study clarifies the role of within-patch connectivity and its relation to landscape fragmentation, allowing for more informative monitoring and more accurate time-series analysis of landscape change in the future. We are assessing which methods available for measuring landscape connectivity include within-patch connectivity and which ones do not. We also assess how the lack of consideration of within-patch connectivity may conclude with misleading results. Both within-patch connectivity and between-patch connectivity need to be considered when measuring landscape connectivity.
Despite overwhelming evidence that biodiversity and ecosystems are under mounting stress, many countries have not yet integrated measures to preserve ecological connectivity into environmental assessment (EA) legislation. Using Canada as a case study, this project aims to critically assess the inclusion of ecological connectivity within the EA process, to identify and characterize existing performance gaps, and to highlight the need for improvement. We assessed past environmental impact statements (EIS) of completed projects available from the registry on the Impact Assessment Agency of Canada website. All EISs were evaluated using a comprehensive set of both review questions and evaluation criteria based on the landscape
ecology literature. We have found that consideration of ecological connectivity is largely absent within EISs. To slow down biodiversity loss and maintain ecosystem resilience, ecological connectivity urgently needs to be integrated and prioritized within the EA process. Tools for assessing and conserving ecological connectivity need to become integrated into environmental
legislation including EA guidelines. Synthesizing existing knowledge on best practices for measuring, assessing, and protecting ecological connectivity will be necessary to build knowledge and capacity among EA practitioners regarding best practices.
Plant phenology is the study of cyclical plant development phases (e.g. bud burst, leaf out, and leaf fall) and is an important indicator of climate change. Variations of plant traits at the maturity stage of development provide evidence of environmental factors limiting plant growth and carbon sequestration. Satellite remote sensing can be used to study plant phenology at regional and global scales and enables the extraction of continuous spatial and temporal information. The objective of this study was to identify robust satellite derived vegetation indices (VIs) for monitoring of the maturity or peak of season (POS) phenological phase of forests and grasslands in North America, between 2002 and 2015. The study investigated the performance of four satellite derived VIs, namely, the green chromatic coordinate (GCC) index, the normalized difference vegetation index (NDVI), the normalized difference water index (NDWI), and the simple ratio (SR) index, each with their own intrinsic capacity to measure various vegetation traits (greenness, photosynthetic activity, water content, and structure, respectively). Ground measurements of POS were derived from GCC time-series that were obtained from near-earth digital repeat photography from the PhenoCam Network. For each PhenoCam site, time-series of the four VIs were extracted from Landsat 7 images using Google Earth Engine’s cloud-based platform. POS was derived from each of the time-series and the robustness of the satellite derived VIs was assessed by the relationships between the satellite derived POS and the ground derived POS across multiple climate zones (i.e. Köppen-Geiger zones af, bwk, cfa, cfb, csa, csb, bsk, dfa, dfb, and dfc). All VIs, with the exception of NDWI, performed well when study sites were stratified by ecosystem (i.e. forest and grassland) and climate zone. NDWI performance was enhanced when the data was masked for snow. GCC, NDVI, and SR performed best for deciduous broadleaf forest sites in the dfb climate zone with R2 of 0.83 - 0.86 (p<.001). NDVI and NDWI performed best for grassland sites in the dfb climate zone with R2 of 0.85 (p<.001). GCC and SR performed well for grassland sites in the dfb climate zone with R2 of 0.70 – 0.75 (p<.001). The findings suggest the need for ecosystem and climate stratification when using Landsat 7 VIs to monitor the plant maturity phenology phase of forests and grasslands.
Roads and traffic significantly increase mortality rates in wildlife populations and act as movement barriers blocking access to important resources for many species. We designed, tested and implemented a standardized protocol to collect road mortality data along Highway 10 that runs between Montreal and Sherbrook through the Northern Green Mountain linkage of the Northern Appalachian-Acadian ecoregion. We conducted 82 road mortality surveys along this high-traffic 4-lane highway to assess the range of species affected, quantify the amount of road mortality, identify roadkill hotspots and coldspots, evaluate their relationship with the location of wildlife corridors, and propose priority locations for road mitigation measures. One driver and two observers surveyed the 40 km study area driving 30 km/hr in sessions of 10 consecutive days, alternating between morning and evening surveys between May 14th and August 29th of 2019. They recorded GPS coordinates for 212 animal carcasses and measured their sizes. It was possible to identify the species of 192 of the carcasses found, including 83 medium sized mammals, 59 birds, 22 amphibians, 16 reptiles, 22 small mammals, and 10 large mammals. The roadkill locations were clustered for most species. We will present road mortality hotspots and coldspots, compare them to existing wildlife corridors across the highway, and suggest potential road mitigation measures. Once road mitigation efforts will be established, future research will be able to evaluate the success of these efforts using the protocol we developed for collecting road mortality data along autoroute 10 in a BACI study design (Before-After-Control-Impact). The results of this study will help guide future investments towards mitigating road mortality and re-establishing connectivity between wildlife populations north and south of the highway.
This event is brought to you by the Loyola College for Diversity and Sustainability and the Loyola Sustainability Research Centre with the support of the Office of the Vice-President, Research and Graduate Studies; the Faculty of Arts and Science; the Canada Excellence Research Chair in Smart, Sustainable and Resilient Communities and Cities; the John Molson School of Business; and the Departments of Biology; Communication Studies; Economics; Geography, Planning and Environment; Management; and Political Science at Concordia University.