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Dryad

Behavioral responses of a large, heat-sensitive mammal to climatic variation at multiple spatial scales

Cite this dataset

Verzuh, Tana L. et al. (2022). Behavioral responses of a large, heat-sensitive mammal to climatic variation at multiple spatial scales [Dataset]. Dryad. https://doi.org/10.5061/dryad.5tb2rbp7s

Abstract

1. Climate warming creates energetic challenges for endothermic species by increasing metabolic and hydric costs of thermoregulation. Although endotherms can invoke an array of behavioral and physiological strategies for maintaining homeostasis, the relative effectiveness of those strategies in a climate that is becoming both warmer and drier is not well understood.

2. In accordance with the heat dissipation limit theory, which suggests that allocation of energy to growth and reproduction by endotherms is constrained by the ability to dissipate heat, we expected that patterns of habitat use by large, heat-sensitive mammals across multiple scales are critical for behavioral thermoregulation during periods of potential heat stress and that they must invest a large portion of time to maintain heat balance.

3. To test our predictions, we evaluated mechanisms underpinning the effectiveness of bed sites for ameliorating daytime heat loads and potential heat stress across the landscape while accounting for other factors known to affect behavior. We integrated detailed data on microclimate and animal attributes of moose Alces alces, into a biophysical model to quantify costs of thermoregulation at fine and coarse spatial scales.

4. During summer, moose spent an average of 67.8% of daylight hours bedded, and selected bed sites and home ranges that reduced risk of experiencing heat stress. For most of the day, shade could effectively mitigate the risk of experiencing heat stress up to 10°C, but at warmer temperatures (up to 20℃) wet soil was necessary to maintain homeostasis via conductive heat loss. Consistent selection across spatial scales for locations that reduced heat load underscores the importance of the thermal environment as a driver of behavior in this heat-sensitive mammal.

5. Moose in North America have long been characterized as riparian-obligate species because of their dependence on woody plant species for food. Nevertheless, the importance of dissipating endogenous heat loads conductively through wet soil suggests riparian habitats also are critical thermal refuges for moose. Such refuges may be especially important in the face of a warming climate in which both high environmental temperatures and drier conditions will likely exacerbate limits to heat dissipation, especially for large, heat-sensitive animals.

Methods

Bed site data: We placed mini weather stations (Kestrel Instruments 5500 Weather Meter, Boothwyn, PA) at four bed sites at a time, which we randomly selected from bed sites used by an individual moose during the previous two weeks. We collected data on three available sites for each used site (4 used sites with 3 random sites each; 16 total weather stations per day). We defined available bed sites as those at a random distance (values between 15m and 330m sampled uniformly via random number generator) at a random angle (values between 1 and 359 degrees sampled uniformly via random number generator). We set the distance boundary by averaging the daily mean displacement of adult female moose in the Snowy Mountain Range during the summer (June–September) of 2017. Sites were selected based on the physical location determined by distance and angle away from the bed site and in a space large enough to accommodate a bedded moose.

We placed a mini weather station in the approximate center of each used bed site. Available sites did not have matted vegetation; thus, we determined the center of the available bed site by choosing an area in which a moose could bed down. The weather stations collected data on temperature, wind speed, and relative humidity every five minutes and were left in place for at least 24 hours to capture one entire day from sunrise to sunset.  We installed the mini weather stations on small tripods ~30 cm off the ground (approximate center of the core of a bedded moose) on a rotating mount with a wind vane to enable the meter to accurately track wind speed. 

We collected additional data on landcover type, canopy cover, and a qualitative measure of soil moisture at visited bed sites. We measured canopy cover at the four corners of the bed site using a GRS densitometer (Graphic Resource Solutions, Arcata, CA; Paletto & Tosi 2009), resulting in a percentage canopy cover reported in 25% increments.  We measured canopy cover from 0.75-m above the ground to approximate the height of the head of a bedded moose. Landcover type at the bed site and the immediate area was classified as either pine, aspen, wet meadow complex, sagebrush (Artemisia spp.), high-alpine tundra, meadow, or burned area. Roughly 78% of the study area was forested, the majority of which (~65%) was dominated by lodgepole pine (Pinus contorta). Other pine species included Engelmann spruce (Picea engelmanii) and subalpine fir (Abies lasiocarpa). Forests in the study area were heavily affected by a mountain pine beetle (Dendroctonus ponderosae) epidemic in 1996, and many standing dead trees remained (Dillon et al. 2005).  In addition to the dominant conifer species, stands of quaking aspen (Populus tremuloides) accounted for ~3.8% of the land area. Wet meadow complexes (riparian areas) comprised of several willow species (Salix spp.), mountain big sagebrush (Artemisia tridentata ssp. Vaseyana), alpine meadows, and small areas of high-alpine tundra accounted for the remaining 18.2% (Dillon et al. 2005). In July 2018, the northeast corner of the study area burned. Several moose used this area both before and after the fire, and thus we did not censor any data from the fire-affected area.

There were many wet landcover types in the Snowy Mountains ranging from riparian to wet meadows, ponds, fens, or some combination thereof; for our purposes, we refer to them as riparian. Given the limited number of bed sites occurring in some vegetation classes, we combined fire-affected areas, sagebrush, and dry meadows into a category we refer to as other. If the site was in an area of mixed vegetation, we recorded the predominant type. Roughly 78% of the study area was forested, the majority of which (~65%) was dominated by lodgepole pine (Pinus contorta).

For the bed-site analysis, we used microclimate data from the Kestrel weather stations in used and available bed sites in each vegetation class to parameterize the microclimate model. We averaged daily minima and maxima for each variable (i.e., temperature, wind speed, and humidity) over each week of the summer which was then used by the Niche Mapper microclimate submodel to calculate profiles for the “average” day each week.  We used two scenarios for canopy cover to capture the full range of variation: maximum percent canopy cover for the vegetation class in question or the minimum percent canopy cover (averaged from recorded bed site data).

Large weather station data: We installed 5 large weather stations in different landcover types throughout the study area (Snowy Mountain Range, WY, USA) in May of 2018, and stations were left in place through December 2019. We used HOBO micro-station data loggers programmed to record weather data every five minutes continuously throughout the day. We mounted HOBO 12-bit temperature and relative humidity sensors in radiation shields and fit them on a 2-m tripod with a HOBO wind sensor set (measures wind speed and direction) attached to a cross arm at the top of each station. We installed each station in a different landcover type; aspen, intact pine, beetle-killed pine, sagebrush, and wet meadow complex. Data were then averaged over each hour for each climate variable. Minimum and maximum values were also recorded for each hour.

Usage notes

For these purposes, the bed site and large weather station data are uploaded as CSV files that can be opened using Excel.

Funding

Wyoming Game and Fish Department

Wyoming Governor's Big Game License Coalition