Movement and nutritional data of mule deer in Western Wyoming (December 2013–December 2021)
Data files
Sep 18, 2023 version files 145.10 MB
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movementdata.txt
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nutritiondata.csv
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README.md
Abstract
- For species that inhabit environments where resource availability may be unpredictable, balance of resource allocation to life-history traits can have heightened consequences for survival, reproduction, and ultimately, fitness. Acquisition and allocation of energy to maintenance, capital gain, and reproduction should be in tune with the landscape an animal inhabits—environmental severity, food availability, and population size all influence the resources animals have and dictate the ways they should be allocated.
- In seasonal environments, animals that experience periods of extreme resource limitation (e.g., harsh winters) may favor allocation of resources to body reserves to secure their survival at the cost of reproduction (i.e., risk-averse). In contrast, the same accumulation of body reserves may not be necessary to survive in relatively benign landscapes where instead, allocation to reproduction is favored (i.e., risk-prone).
- According to theory of risk-sensitive allocation of resources, when animals are exposed to unprecedented or life-threatening conditions, they may shift resource allocation to favor building capital over allocation in reproduction to preempt against encountering another life-threatening event in the future.
- Using data from a long-term project on a highly site-faithful and long-lived species, mule deer (Odocoileus hemionus), we evaluated how a life-threatening winter and the associated changes in resource availability resulting from a population reduction influenced how animals acquired and allocated energy to survival (i.e., fat accumulation).
- Per capita precipitation, and the associated reduction in population abundance after the severe winter, had a positive influence of accrual of fat over summer. After the extreme physiological stress of a hard winter, deer starting spring with low body reserves accumulated 2.8 percentage points more fat over summer compared with before the experience of a bad winter and had an increased probability of recruiting fewer offspring. Fat stores can interact with environment, life-history, and behavior to influence survival during periods of resource scarcity.
- For a long-lived herbivore, we documented shifts in risk tolerance associated with fat accrual in preparation for winter, supporting the notion that risk-sensitive allocation of resources may be plastic–an essential adaptation for animals to cope with rapidly changing landscapes.
README: Movement and nutritional data of mule deer in Western Wyoming (December 2013–December 2021)
This dataset includes movement and nutrition data of mule deer collected in western Wyoming, USA from December 2013 to December 2021.
Description of the Data and file structure
The movementdata.txt file includes the following columns: id, mst, x, and y. ID represents the unique id for the animal, mst is the collection date (MST) of the movement data, and x and y represent the x and y coordinates of the data. The projection of the data is NAD83 / UTM zone 12N - EPSG:26912. The movement data was saved as a .txt file to not truncate data when opened in Excel because it has > 1,000,000 rows. The first column in the .txt file indicates the row number.
The nutritiondata.csv file includes the following columns: id, year, change, SpringFat, Age, and Recruitment.
- id represents the unique id for the animal.
- Spring Fat represents the ingesta-free body fat of the animal when it was captured in March (unit is % body fat; e.g., 15.7 is 15.7% body fat).
- change represents the over summer change in fat between March and December of a given year (unit is % body fat; e.g., -2 represents an animal lost 2% of body fat over summer and 10 represents an animal that gained 10% body fat over summer).
- Age represents the age of the animal at the December capture event (unit is years; e.g., 7.75 is 7.75 years old).
- Recruitment represents the number of offspring that a female deer raised until the autumn (mid November) of each year (unit is number of offspring; e.g., 1 represents 1 offspring raised to autumn)
Sharing/access Information
Please contact Kevin Monteith (kmonteit@uwyo.edu) or Tayler LaSharr (tlasharr@uwyo.edu) for questions related to the data.
Methods
Animal Capture and Handling
In March 2013, we captured 70 adult, female mule deer using helicopter net gunning. Each year following that initial capture event, we recaptured surviving individuals and captured new individuals to maintain a sample size of 70 animals in mid-March (i.e., spring) and early December (i.e., autumn) until December 2021. At the initial capture of any new animal, we extracted one incisiform canine to estimate age using cementum annuli (LaSharr et al. 2023a). At each capture event, we collected data on nutritional condition, measured body mass, and fit all animals with a GPS radiocollar programmed to take satellite fixes every 2 hours (Advanced Telemetry Systems, Isanti, Minnesota, USA, Telonics, Mesa, Arizona, USA, and Vectronic Aerospace, Berlin, Germany). GPS radiocollars weighed ≤ 2 kg (~3.0% of adult body mass in spring and ~2.6% of adult body mass in autumn).We measured nutritional condition using protocols for mule deer which include measuring subcutaneous rump fat via ultrasonography and body palpation to estimate a body condition score (Stephenson et al. 2002; Cook et al. 2007). Using body mass, body condition score, and maximum thickness of rump fat via ultrasonography, we then estimated ingesta-free body fat (hereafter, ‘body fat’; Cook et al. 2010). We calculated over-summer change in fat by subtracting the body fat of each animal in autumn from their body fat in spring. Each spring capture, we determined pregnancy and fetal number of each animal via ultrasonography (Aikens et al. 2021). All capture and handling were done under compliance with a protocol approved by an Institutional Animal Care and Use Committee at the University of Wyoming (Wyoming Range 20131111KM00040, 20151204KM00135, 20170215KM00260, 20200305KM00412), and were in accordance with guidelines of the American Society of Mammologists (Sikes 2016).
Survival and Recruitment Monitoring
To account for the energetic cost of raising offspring, we determined recruitment status of radiomarked females each autumn. We determined presence and number of dependent young for collared females each autumn (mid – late November). In 2013 and 2014, all recruitment was evaluated using visual observations. We watched marked females for 5–10 minutes using binoculars or spotting scopes to identify recruitment status based on maternal behavior (Monteith et al. 2014). Maternal behaviors included close association, suckling or attempted suckling, and any other evidence of maternal care. Each observation was classified with a confidence level of “low,” “medium,” or “high” based on evidence of maternal behaviors and group dynamics. For observations considered “low” or “medium” confidence, we returned to the site at a later day to make additional observations until the confidence level was “high”. No “low” or “medium” observations were included in our analyses. Additionally, during autumn captures, we validated our observational data by confirming evidence of lactation by palpating the udder (Monteith et al. 2014, Stephenson et al. 2020).
During 2015 – 2021, we collared neonates of collared females each spring as an additional component of the long-term research project. Detailed methodology on capture and handling of neonates can be found elsewhere (Aikens et al. 2021). In instances where all neonates of a marked female were captured and collared (i.e., if a female was pregnant with 2 fetuses and 2 neonates were captured and collared), we used known fate from the juvenile collars to determine recruitment status of adult females each autumn. For any animals in which we were not successful in capturing all neonates in a litter, we used the aforementioned protocol to determine recruitment status.
Environmental Covariates and Population Estimates
To determine the role of population density and habitat on accumulation of capital over summer, we evaluated the influence of moisture, vegetative biomass, and metrics of greenness from NDVI. First, we estimated seasonal home ranges of each animal using Brownian Bridge movement models (Sawyer et al. 2009). We estimated 95% summer home ranges for each animal in each summer from 1 June to 30 August.