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These data were collected to explore the capacity of Alnus alnobetula (green alder) shrub patches to modify the habitat and composition of the local plant community at the taiga-tundra ecotone near Trail Valley Creek Research Station in the Northwest Territories. To do this we selected ten sites on south facing slopes with both alder shrub patches and adjacent shrub-free tundra and established quadrats in each habitat and across topographic positions. Within each of these quadrats we selected two sub-quadrats for vegetation community composition and birch height observations. We also measured a suite of environmental variables within 50 cm of each larger quadrat. For detailed description of methods see Wallace and Baltzer (2019), https://doi.org/10.1007/s10021-019-00435-0. (2019-09-16) See also: www.gwfnet.net/MetadataEditor/Record/T-2020-08-10-I1yI3Npg414kI2Ee2I2n3zPI1Eg
Indigenous youth-focused, on-the-land (OTL) camps are being delivered with communities in the Dehcho region, which involve traditional activities led by various Elders and knowledge keepers, and hands-on science-based learning activities led by graduate students and scientists. For this project, I am working with Dehcho First Nations to help lead their OTL camps, while delivering a photovoice project with the youth participants and building an evaluation framework to assess camp programming. This project will explore: (R1) How do OTL camps in the NWT create a space for Indigenous youth to apply local Indigenous Knowledge and Western science to protect the Land? (R2) What are the concerns and priorities of local Indigenous youth regarding environmental and socio-cultural changes in the Dehcho? How can their concerns and priorities be addressed to build more resilient and sustainable LBE programming in the NWT more broadly? Using a Community-Based, Participatory Action Research (CBPAR) approach, this research is responsive to the practical concerns of partner communities through active collaboration and co-learning. This methodology values Indigenous Knowledges, worldviews, cultures and experiences. My research involves the use of mixed-methods and activities at five youth-focused, week-long camps (N=20-30 youth) with partners in the Dehcho region. Opportunities for additional camps are being explored. I will use four integrated methods: (M1) Youth will participate in an immersive, iterative photovoice project, capturing photographs throughout the camp with daily focus groups. We will create photobooks and displays of their photographs and stories to share with their families and communities. (M2) Focus groups will be held at the beginning and end of the camps as an evaluative method for the youth to share their priorities and concerns for LBE. (M3) Participant observation will be used at the camps to understand the context and dynamics of LBE. (M4) Semi-structured interviews (N=20) will be conducted with 25 youth camp participants.
The Ensemble Meteorological Dataset for North America (EMDNA) contains daily precipitation, mean daily temperature, and daily temperature range at the 0.1-degree resolution from 1979 to 2018. Minimum and maximum temperature can be calculated from mean temperature and temperature range. EMDNA merges station observations and reanalysis model outputs to improve the quality of estimates. The dataset is expected to be useful for hydrological and meteorological applications in North America. Two types of datasets are provided by EMDNA, including the probabilistic dataset and the deterministic dataset. The probabilistic dataset has 100 equally plausible ensemble members, which can be used to evaluate the impact of the uncertainties in a myriad of applications. The deterministic dataset is generated during the production of ensemble members and can be applied in studies that do not need uncertainty estimation. See also: www.gwfnet.net/MetadataEditor/Record/T-2020-11-25-i1Fwxi32sBMU2GDhUZ6gAJEg
These data were collected to address the need for a hydroecological monitoring program, with focus on metals of concern, in the Peace-Athabasca Delta (PAD). To do so, we deployed artificial substrate samplers in ~60 lakes for the duration of the ice-free seasons of 2017 and 2018. We assessed the accrued biofilm-sediment mixtures for enrichment of metals of concern above pre-industrial levels determined from analyses of sediment cores in the PAD. We also related metals enrichment to periphytic algae community composition, inferred from diagnostic algal pigments, to explore taxa-specific rates of active biological uptake of metals of concern.
Hydrologic, geomorphological, invertebrate samples, and water quality data was collected from three rivers in the Greater Toronto Area: Ganatsekiagon Creek (Durham), Wilket Creek (York), and Morningside Creek (Scarborough). In all three sites, continuous water level data has been recorded between June 2015 and August 2018 at intervals ranging from 1–5 minutes during the active field season (April–December), and 7–10 minutes during the winter season. Repeated topographical surveys of 150–200 m length reaches have also been conducted at various resolutions. Approximately 3–6 repeat surveys have been completed in each site comprising of planform geometry and bathymetric data. Finally, bedload sediment has been monitored using Radio Frequency Identification tracer stones. A total of 300 tracers, in three sizes, have been seeded in each site. Tracer positions were recorded after each major rainfall event during the active field season each year, resulting in a total of 10, 12, and 13 recoveries in Ganatsekiagon Creek, Wilket Creek, and Morningside Creek, respectively. Invertebrates were collected using the Travelling Kick and Sweep Method outlined in the Ontario Benthos Biomonitoring Network Protocol at each site. Invertebrate samples were collected 16 times between 2015-2018, typically once a month from May–September. Water quality (dissolved oxygen, pH, water temperature) was measured during each invertebrate sampling event, and water samples were collected to measure for nitrates, soluble reactive phosphates, chlorides, conductivity, turbidity, total suspended solids, and sulfates. All water quality tests were conducted in the Ecology Lab (EV1-134) at the University of Waterloo.
Data will consist of perceptions of “good” and “bad” water and how each impacts upon individual and community health. They will be collected through surveys and Elder interviews. While Indigenous communities recognise western science (WS) standards for drinking water quality, potability as a concept is not sufficient to address the Indigenous concepts of “good” or “bad” in relation to water. The purpose of this collaborative research project is to develop Traditional Knowledge (TK) indicators of “good” and “bad” water in order to explore the similarities and differences between the WS concept of “safe to drink” and the TK concept of “good to drink”. This will be achieved through an exploration of water-related health, how human health (encompassing physical, spiritual, mental, and emotional health) is affected by “good” and “bad” water, development of appropriate TK indicators, and community case studies. Through this process and its outcomes, communities will be able to better understand and assess water-related health in Indigenous communities through a TK system and be able to share this with government agencies currently responsible for water management, remediation, and quality monitoring. See also: www.gwfnet.net/MetadataEditor/Record/T-2020-12-16-M1uFcYiOM310C6nM2dmLLZ8tw
Snow depth, air and soil temperature, and soil moisture were downloaded for five locations from the United States Department of Agriculture Soil Climate Analysis Network (SCAN) (https://www.wcc.nrcs.usda.gov/scan/). These locations were selected for the following reasons: 1) because of their proximity to specific landscape types, and 2) they have consistent data from 2009-2015. For each selected station and winter season, the daily time series data were downloaded for the corresponding ‘Water Year.’ A ‘Water Year’ is defined as October 1st of the previous year to September 30th of the specified year. For example, the 2009/2010 winter season is within the 2010 Water Year. Snow depth measurements were converted from inches to centimetres. All analysis and plots where done using Microsoft Office Excel for each selected station and winter season.
Soil moisture and snow depth data will be retrieved from a Global Navigation Satellite System Reflectometry (GNSS-R) instrument onboard a unmanned aerial vehicle (UAV). These data will be compared with ground measurements taken coincidentally with the flight.
The dataset contributes to work packages 1.2, or A(i), under Phase II of Prairie Water, “analyzing future climate and land use change using Virtual Watershed modelling”. The dataset aims to assess hydrological sensitivity of Canadian Prairie catchments to climate with seven temperature scenarios and five precipitation scenarios, and contribute to our understanding of the hydrological, biogeochemical, and ecological response of prairie watersheds to climate and land management changes. The dataset is comprised of inputs to and outputs from the Cold Regions Hydrological Model (CRHM) when it was run as a virtual model of two classes of Canadian Prairie watersheds, as defined by Wolfe et al. (2019). These classes are Pothole Till and High Elevation Grasslands. These watersheds represented typified prairie watersheds based on physiogeography and coherent response to environmental change.Model parameters were informed by the results of Wolfe et al. (2019). The .prj files necessary to run the virtual models are included in the dataset. Climate forcing data are from the Adjusted and Homogenized Canadian Climate Dataset from a cohort of stations contained within each watershed class and cover a period from 1960-2006. There are a series of climate sensitivity scenarios that include applying a delta method to the original climate data (i.e., 1°C increments of warming, and -20%, +10%, +20% and +30% of precipitation). The .prj and .obs files for the baseline and each sensitivity scenario are included in the dataset. Model output includes hourly catchment outflow, snow water equivalent, and surface storage for the baseline and each scenario. In addition, virtual model outputs where linked to biogeochemical and biological models to calclate nutrient loading and biodiversity indicators. Nutrient load information is calculated using stream concentrations from the Pothole Till watershed class. Using the stream concentration-flow relationship, the hydrological data from the CRHM simulations were fed into these equations to estimate changes in nutrient loading. Wetland bird abundance and bird species richness are calculated using calculated pond areas that are modified from the CRHM outputs. See also: www.gwfnet.net/MetadataEditor?q=T-2020-11-30-I1NSFev5tUUSEKgex5I3xmCw
Data was collected from three rivers in the Greater Toronto Area of Southern Ontario: Ganatsekiagon Creek (City of Pickering), Wilket Creek (City of Toronto), and Morningside Creek (City of Toronto). The grain size distribution at each site was calculated using a Wolman Pebble count with a 200-stone sample size. Bedload transport was monitored over three years using Radio Frequency Identification (RFID) tracer stones, and periodic topographic surveys were conducted. A total of 300 tracers in 3 size classes were seeded in each site in August 2015. Tracer positions were recorded after each major rainfall event during the active field season each year, resulting in a total of 10, 12, and 13 recoveries in Ganatsekiagon Creek, Wilket Creek, and Morningside Creek, respectively. With each recovery, the travel distance of each tracer since its last known position is calculated. Detailed topographic surveys of the channel bed were conducted in the summers of 2016 and 2018 using a total station. Surveys were used to create DEM of Difference (DOD) at each site after a Triangular Irregular Network interpolation.