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Plant Composition and Biomass Data
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Boyce, Mark; Jessica Grenke — 2023-05-18 Summary: Vascular plant composition and biomass data collected for the AGGP AMP project. Detailed description of methods available within https://doi.org/10.1111/1365-2664.14181 and below. Composition data collected during 2017-2018, biomass data collected during 2018. To capture plant community responses to AMP grazing relative to regionally typical management, we established 0.5 × 0.5 meter quadrats in which we identified plant community abundances and biomass estimates. As outlined in Grenke et al. (2022), due to our prioritization of sampling many pairs of ranches rather than conducting intensive sampling within each ranch, rarefaction curves for each of our study sites did not saturate. Therefore, plant community measures should be considered on a relative rather than an absolute basis. To determine the potential for specific components of the plant community to influence biomass production we assessed community composition. Composition was sampled by randomly placing five quadrats within each of three landscape positions, for a total of 15 quadrats per study site. Sampling was stratified by topographic landscape position in order to capture potential topographically sourced heterogeneity, with landscape designations representative of relative positioning within the context of each ranch pair. Areas were designated as “low” if they occurred within the bottom third of a local relief, “high” if they occurred within the top third of the local relief, and “medium” if they occurred within the middle third of the landscape relief. To assess how vascular plant species composition may have influenced biomass production we recorded vascular plant species abundance (percent cover) at every site using a 0.5 meter × 0.5 meter quadrat. All non-senesced vascular plants within the quadrat were identified to species (USDA, NRCS 2021). Vascular plant species abundances were collected over two years, during the peak growing seasons of both 2017 and 2018, typically between June 15 and July 15. To reduce variance in our diversity estimates, we pooled data across the two years of sampling. Further details can be found in Grenke et al. (2022). 2.3.2. Plant community biomass estimates We measured plant biomass (aboveground biomass, litter mass, and roots from soil cores) using three randomly selected quadrats from each of the three landscape positions within the ranch (9 quadrats per ranch). Biomass data were taken from a randomly determined half of the plant composition quadrat (0.25 meter × 0.5 meter total). Plant biomass measures were collected during the peak growing season of 2018 at the same time as vascular plant species abundance sampling (June 15-July 15). Litter mass was removed using hand raking, followed by clipping all standing plants to ground level (aboveground biomass). Two soil cores (6 cm diameter, 15 cm deep) were then taken within the same area and pooled within a quadrat, with roots later sieved out and washed. All biomass and litter mass was dried to constant weight at 70°C, weighed, and standardized to g/m². The resulting root biomass measures were lower than would be reasonably expected from these systems (e.g., see Bork et al., 2019). This was likely due to extensive fine-root degradation in transport as well as breakage during the washing process. As such, root biomass measures represent the within-study relative treatment effects, not absolute indicators of total root biomass present. To measure aboveground biomass and biomass removal by livestock, we required approximate measures of plant growth with and without current-year grazing. The adaptive nature of ranch operations at our sites, as well as the geographic breadth of the sampling area, precluded us from systematically placing exclusion cages prior to grazing. Thus, at each plot, we installed an exclosure cage (1 × 1 meter) located 2 meters away from the non-exclosed plot a minimum of 2 weeks before plant community sampling. Biomass (aboveground, litter mass, and soil cores) and vascular plant species composition were sampled at the excluded and non-excluded sites within each pair. Subsequent analysis and discussion of biomass refer to those data collected from exclosure cages to mitigate the confounding influence of short-term grazing.
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Enzyme Data
Borealis
Boyce, Mark — 2023-06-05 READ ME: Soil sampling for the AGGP AMP study during 2018. A detailed description of methods used to derive the data is below. Further questions can be directed to kaliaska@ualberta.ca Soil sampling Soil sampling was done three times in 2018: June 11 – 18 (it took a week to complete the sampling of all the ranches at each sampling time), July 23 – 30, and September 4 – 11, representing spring, mid-summer and fall, respectively. At each sampling, four soil cores (5 cm diameter x 15 cm deep) were collected from two lower and two upper slope positions within each ranch; slopes were randomly selected within the area. Thereafter, soil samples from the same slope position were combined and two composite soil samples (one upper and one lower slope) per ranch were placed on ice and transported to the lab for further processing. Once at the lab, samples were immediately sieved through a 2 mm sieve, refrigerated at -4 °C for 24 hours, and stored at -20 °C until used in further analyses. Soil properties Soil pH, NO3-, NH4+, microbial biomass C (MBC), and microbial biomass N (MBN) were analysed for the soil samples. To determine soil pH, a soil:water solution (10 g:50 mL) was tested using a pH meter (Orion, Thermo Fisher Scientific Inc., Beverly, MA, USA) (Robertson et al., 1999). Soil moisture content was analyzed by comparing weights before and after oven drying (105 °C). For determining soil available N (AN), 10 g of soil was mixed with 0.5M K2SO4 solution in a ratio of 1:5 (air-dried equivalent soil sample weight:K2SO4 solution). The MBC and MBN were determined by ethanol-free chloroform fumigation, from one sub-sample (10 g of oven-dry equivalent) as described previously from a mixture of soil and 0.5 M K2SO4 solution (10 g:50 mL); while the other sub-sample was fumigated for 24 hours. Next, 50 mL of 0.5 M K2SO4 solution was added to fumigated soil subsamples, shaking for 1 hr at 180 rpm and filtered. Fumigated and unfumigated soil extracts were run on a Shimadzu TOC-VCSN analyser (Shimadzu, Kyoto, Japan). MBC and MBN were calculated by dividing the difference in C and N content between unfumigated and fumigated samples (Brookes et al., 1985). Extracellular Enzyme Assays To assess EEA, a standard fluorometric method was used with 96-well microplates described by Sinsabaugh et al. (2003) with acetate buffer solution (pH 5.0). One gram of fresh soil and 125 mL of buffer were mixed to make a soil solution and 200 μL of the solution pipetted into each well of the microplate. Microplates with soil solutions and enzyme substrates were incubated depending on enzyme type for two (phosphotase), three (β-glucosidase, N-acetylglucosaminidase), four (xylosidase), or seven hours (Cello) at 25 °C. After incubation, microplates were read on a Biotek Synergy HT (Bio Tek Instruments, Inc, Vermont, USA) with 360 nm excitation and 460 nm emission. Resulting EEA rates were expressed in μmol per hour per gram oven-dry soil (μmol g soil−1 h−1) using the following equation (Sinsabaugh et al., 2003). For the urease activity assay, we followed the methodology used by Sinsabaugh et al. (2000).
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3 Year Greenhouse Gas data (collected in field)
Borealis
Boyce, Mark — 2023-06-07 Read me: Publication: Soil greenhouse gas emissions and grazing management in northern temperate grasslands Contact Details: Please contact Ma Zilong at mazlong@mail.sysu.edu.cn and Bharat Shrestha at shresthabm@gmail.com if you have any further questions Methods: Growing season GHG fluxes were measured in the field bi-weekly from mid-August to mid-October in 2017, early May to mid-October in 2018, and early May to early September in 2019 using dark static chambers (65.5 × 17 × 15.5 cm height) at six random sampling points within a representative area of each study ranch. Ambient air samples (20 mL) were collected prior to placing the chamber-lids over the static chambers (ambient condition, t = 0) and again at 10, 20, and 30 min after placing the chamber-lid over the static chamber, using an airtight syringe (Norm-Ject, Henke Sass Wolf, Tuttlingen, Germany) through a rubber septum. Samples were then stored in pre-evacuated 12 mL soda glass Isomass Exetainers (Labco Limited, Lampeter, Wales, UK) to provide a positive pressure in the Exetainer. Collected gas samples were transported in dark boxes to the Forest Soil Laboratory at the University of Alberta, Edmonton, and were analyzed using a Varian CP-3800 gas chromatograph (Varian Canada, Mississauga, Canada) equipped with a thermal conductivity detector, a flame ionization detector and an electron capture detector for determining the CO2, CH4, and N2O concentrations, respectively.
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Effects of industry on wolverine (Gulo gulo) ecology in the boreal forest of northern Alberta
Borealis
Scrafford, Matthew; Boyce, Mark — 2023-03-01 The wolverine is valued by both the trapping and conservation communities for their symbolization of wilderness. In Canada, wolverines are considered a species of Special Concern. In Alberta, wolverines are functionally extinct from central and southeast regions while populations that remain in the north and west May be at Risk. The uncertainty in Alberta’s current risk assessment is because wolverines are Data Deficient in the province. Conducting research on wolverines that will contribute to updating ecological risk assessments is critical for the conservation of the species. One of the greatest ecological threats to wolverines in northern Alberta and British Columbia is displacement and mortality caused by resource extraction and human access. This PhD research is focused on the effects of the oil/gas and forestry industries on wolverine ecology. Specifically, patterns of industrial traffic and land use influence wolverine movements and wolverine food habits and den-site selection were of interest. We evaluated wolverine ecology along a gradient of industrial disturbances represented in both Rainbow Lake and Bistcho Lake, Alberta starting in the fall of 2013. These data will facilitate improved population management by Alberta’s industrial and conservation stakeholders. Major project partners include the Dene Tha First Nation, Alberta Conservation Association, Alberta Trappers Association, Husky Oil, Strategic Oil, Wildlife Conservation Society Canada, TD Friends of the Environment Foundation, Safari Club International – Northern Alberta Chapter, Daishowa-Marubeni International Ltd. (DMI), and The Wolverine Foundation. Wolverines were trapped using log live-traps, GPS radiocollars were attached, and their movements were tracked spatially and temporally to traffic volumes and habitats. We monitored industrial traffic levels with a combination of road counts, motion-sensor cameras, and traffic data available from local industry. We also quantified variability in snow condition and its effects on wolverine movement with stations spread throughout the region. Den-site selection will be investigated by ground and air to understand small and large scale habitat requirements.
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Duck nest data from Bashaw and Viking, Alberta, from 2015 - 2017
Borealis
Boyce, Mark; Blythe, Emily — 2020-09-08 Data from nests found by nest-searching and monitored until hatch or failure. Data collected at two study areas, near the communities of Bashaw, and Viking, Alberta. Data collection occurred between May 1 and July 31 of 2015, 2016, and 2017. Predator removal was occuring at half of the study sites. These data are associated with the thesis "Trappings of Success: Predator Removal & Habitat Associations with Dabbling Duck Nest Survival in Alberta Parklands" by Emily Blythe (2019).
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Extracellular Enzyme Activity data
Borealis
Boyce, Mark — 2023-06-07 Read me: Measurement of Extracellular Enzyme Activity data in the soil incubation study in summer 2018. A detailed description of methods used to derive the data is below. Further questions can be directed to shresthabm@gmail.com Publication : Adaptive Multi-Paddock Grazing Lowers Soil Greenhouse Gas Emission Potential by Altering Extracellular Enzyme Activity Authors: Shrestha, Bharat M.; Bork, Edward W.; Chang, Scott X.; Carlyle; Cameron N.; Ma, Zilong, Döbert, Timm F.; Kaliaskar, Dauren; Boyce, Mark S. Published in: Agronomy DOI: doi:10.3390/agronomy10111781 Methods: Measurements of microbial activities and soil parameters A parallel set of soils at the same moisture level were prepared by placing 50 g of oven-dry equivalent air-dried soil in 200 mL conical flasks for measuring extracellular enzyme activities (EEAs), microbial biomass C (MBC) and N (MBN), and reactive N (available-N), on day 1 (start), day 13, and day 102 (end) of the incubation period. Activities of select extracellular enzymes involved in C (xylosidase: Xylo, β-glucosidase: BG, cellobiosidase: Cello) and N (N-acetyl-β glucosaminidase: NAC) cycling in soil were analyzed. To assess the EEA, a standard fluorometric method was used with 96-well microplates (see Sinsabaugh et al. [46]) with acetate buffer solution (pH 5.0). One gram of fresh soil and 125 mL of buffer were mixed to make a soil solution and 200 µL of the solution was pipetted into each well of the microplate. Depending on the enzyme type, microplates with soil solutions and enzyme substrates were incubated for three (BG, NAC), four (Xylo), or seven hours (Cello) at 25 °C. After incubation, microplates were read on a Biotek Synergy HT (BioTek Instruments, Inc., Vermont, USA) with 360 nm excitation and 460 nm emission [47]. Substrates used in this experiment were 4-MUF-β-D-glucopyranoside, 4-MUF-β-D-cellobioside, 4-MUF-β-D-xyloside, and 4-MUF-N-acetyl-β-glucosaminide. Soil MBC and MBN were analyzed by the chloroform fumigation-extraction method [48,49]. For fumigation, 10 g of moist soil sample was fumigated with chloroform in a desiccator for 24 h. Soil extracts were obtained by mixing 10 g of moist soil with 50 mL of 0.5 mol L−1 K2SO4 solution, shaking for 1 h in a reciprocating shaker (250 rpm) and filtering through Q2 filter papers. Soil extractions were analyzed for MBC and MBN by a TOC-V analyzer connected to a TN module (Shimadzu Corporation, Kyoto, Japan). The MBC and MBN were calculated as the difference between the C and N extracted from fumigated and non-fumigated soil samples, respectively. Soil NO3- and NH4+ were determined using the colorimetric method in soil solution. The vanadium oxidation method was used for NO3- [50], and the indophenol blue method was used for NH4+ [51] and analyzed on a spectrophotometer (GENESYS™ 10S UV-Vis Spectrophotometer, ThermoFisher Scientific, USA ). The sum of NH4+-N and NO3--N was expressed as total available N (avail-N). The MBC, MBN and avail-N on each sampling day were calculated per unit mass of soil (mg kg-1 soil).
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Greenhouse Gas Data ( collected in lab)
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Boyce, Mark — 2023-06-07 Read me: Greenhouse gas data collection and measurement in 2018. A detailed description of methods used to derive the data is below. Further questions can be directed to shresthabm@gmail.com Methods: Soil preparation, incubation, gas sampling, and analysis Water holding capacity of sieved soils at different matric potentials was determined using the pressure-plate method [41]. Sub-samples of air-dried soils were first placed in O-rings on porous ceramic plates and saturated for 24 h. Saturated soils were then pressurized at 0.1, 0.5, 1.0, 5.0, and 15.0 bars for 72 h, after which the moisture content at each pressure level was quantified by drying at 105 ºC for 27 h to a constant mass and reweighing. Water content at 15 bar was considered the permanent wilting point (PWP), while 0.1 bar was the field capacity (FC) of sandy soils [42] and 0.33 bar the FC of clayey soils [41]. Water content at 0.33 bar was estimated by linear extrapolation of water contents at 0.1, 0.5, and 1.0 bar. The moisture content of air-dried sieved soil was also determined following the oven-dry method (described above) to help maintain the desired soil moisture level throughout the subsequent incubation experiment. For each grassland investigated, 100 g of oven-dry equivalent air-dried soil was placed in each of six 500 mL Mason jars for the incubation experiment. Sufficient water was added (with a dilute 0.005 M CaSO4 to protect micro-aggregates from disruption) to bring these soils to a moisture level of either FC, 40% FC, or PWP [43]. One set of Mason jars with soil from each moisture treatment was placed in an incubator at 5 ºC, while the other set was placed in another incubator at 25 ºC. The tops of all jars were covered with perforated aluminum foil for five consecutive days to stabilize microbial activity. On the fifth day (collection day 0), initial GHG samples were collected from the headspace air of the jars immediately after closing them using a lid equipped with a rubber septum. Soils were further incubated for 24 h with the lids closed, and then headspace samples were collected again to determine the change in GHG concentrations. Subsequent sampling of GHGs occurred on days 1, 2, 4, 7, 10, 13, 18, 23, 28, 35, 42, 52, 62, 72, 82, 92 and 102. The change in gas concentration between the 0 and 24 h headspace samples on each sampling day was used to calculate daily GHG flux per unit dry mass of soil. Soil moisture levels were maintained throughout the incubation period by tracking water loss by weighing the jars and replenishing the water at least 3 days prior to each gas sampling event. Headspace air samples were collected with an air-tight 20 mL syringe (Norm-Ject, Henke Sass Wolf, Tuttlingen, Germany) and injected into 12 mL pre-vacuumed soda glass Isomass Exetainers (Labco Limited, Lampeter, Wales, UK). Greenhouse gas samples were analyzed with a Varian CP 3800 gas chromatograph (Varian Canada, Mississauga, Canada) containing three detectors. A thermal conductivity detector (TCD) and flame ionization detector (FID) simultaneously determined the concentration of CO2 and CH4, respectively [44], while the electron capture detector (ECD) determined the concentration of N2O [45]. Standard curves were generated using mixtures of gases at standard concentrations of CO2 (360 ppm), CH4 (1.6 ppm) and N2O (1.0 ppm) (Praxair) and used to calculate the headspace concentrations of respective gases.
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Greater sage-grouse (Centrocercus urophasianus) morphology, parasitology, lek behaviour and abundance, and genotyping in Wyoming from 1987 to 1990.
Borealis
Black, Emily; Boyce, Mark — 2023-07-17 Greater sage-grouse (<i>Centrocercus urophasianus</i>) is a charismatic North American prairie bird species. The greater sage-grouse engages in a unique breeding behaviour called lekking, where males participate in communal breeding displays on historic breeding grounds called leks. These breeding behaviours have led to exaggerated sexual selection, and the development of male secondary sexual characteristics such as brightly coloured combs above the eye, noisy mating dances (aka struts), and large inflatable air sacs on the male’s chests. However, parasites such as lice (<i>Lagopoecus gibsoni</i>, <i>Goniodes centrocerci)</i> and avian malaria (<i>Plasmodium pediocetii</i>) have been known to affect the reproductive success of males by decreasing strutting frequency and affecting female mate choice. This makes the greater sage-grouse an intriguing species in which to explore the relationship between sexual selection and host-parasite dynamics. <br> From 1987-1990, several graduate students in the Dr. Mark Boyce lab at the University of Wyoming conducted field experiments to assess the effects of morphology, secondary sexual characteristics, and parasites on the strutting and mating success of greater sage-grouse, as well as auxiliary experiments investigating sage-grouse egg and chick development, and genotyping. Juvenile and adult grouse were captured on the lek, body measurements and characteristics were recorded, and blood, fecal, ectoparasite, and cecal samples were taken to assess the condition of the grouse. Grouse were also observed displaying on the lek, and lek attendance and strutting and copulation frequency was recorded. These data were stored on binders and floppy disks until they were modernized in 2023 as part of the Living Data Project Data Rescue. Included in the rescued data are lek observations and attendance, strutting frequency, and copulations from 1987-1990, morphology and parasite load of captured grouse from 1987-1990, egg and chick development from wild and captive populations in 1990, and genotyping performed using grouse blood samples collected during captures. The data are cleaned and standardized using tidy data principles and are in .csv format.
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Replication Data for Elk harvests
Borealis
Boyce, Mark — 2022-08-23 Trump, T., K. Knopff, A. T. Morehouse, and M. S. Boyce. 2022. Sustainable elk harvests in Alberta with increasing predator populations. PLoS ONE (revision submitted).
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Cypress Hills Cougar Data
Borealis
Boyce, Mark — 2023-02-27 1) GPS collar data from cougars caught in Cypress Hills- the alpha numeric prefix is the cougar’s ID based on the province of capture (Alberta or Saskatchewan) and order it was captured (1,2,3…) 2) Database of GPS clusters that were searched for cougar kill sites.
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Replication Data for: Industrial development alters wolf spatial distribution mediated by prey availability
Borealis
Fisher, Jason; Ladle, Andrew; Boczkulak, Hannah; Boucher, Nicole; Boyce, Mark — 2023-05-26 Increasing resource extraction and human activity are reshaping species’ spatial distributions in human-altered landscape and consequently impacting the dynamics of interspecific interactions, such as between predators and prey. To evaluate the effects of industrial features and human activity on the occurrence of wolves (Canis lupus), we deployed an array of 122 remote wildlife camera traps in Alberta's Rocky Mountains and foothills near Hinton, Canada in 2014. Using generalized linear models, we compared the occurrence frequency of wolves at camera sites to natural land cover, industrial disturbance (forestry and oil/gas exploration), human activity (motorized and non-motorized), and prey availability (moose, Alces alces; elk, Cervus canadensis; mule deer, Odocoileus hemionus; and white-tailed deer, Odocoileus virginianus). Industrial block features (well sites and cutblocks) and prey (elk and mule deer) availability interacted to influence wolf occurrences, but models including motorized and non-motorized human activity were not strongly supported. Wolves occurred infrequently at sites with high densities of well sites and cutblocks, except when elk or mule deer were frequently detected. Our results suggest that wolves risk using industrial block features when prey occur frequently to increase predation opportunities, but otherwise avoid them due to risk of human encounters. Effective management of wolves in anthropogenically-altered landscapes thus requires the simultaneous consideration of industrial block features and populations of elk and mule deer.
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Data and R Code from Granados et al. 2023, Mammalian predator and prey responses to recreation and land use across multiple scales provide limited support for the human shield hypothesis, Ecology and Evolution.
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Granados, Alys; Sun, Catherine; Fisher, Jason T.; Ladle, Andrew; Dawe, Kimberly; Beirne, Christopher; Boyce, Mark; Chow, Emily; Heim, Nicole; Fennell, Mitchell; Klees van Bommel, Joana; Naidoo, Robin; Procko, Michael; Stewart, Frances; Burton, Cole — 2023 Data from Granados et al. 2023 Mammalian predator and prey responses to recreation and land use across multiple scales provide limited support for the human shield hypothesis, Ecology and Evolution https://creativecommons.org/licenses/by/4.0/legalcode

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