Predicting mule deer recruitment from climate oscillations for harvest management on the northern Great Plains

Abstract

We analyzed a unique 51-year time series for a population of mule deer in the North Dakota badlands, USA to examine the effects of seasonal weather on autumn recruitment. Winter weather recorded prior to birth of fawns and weather conditions recorded during spring the previous year (lagged effect), but not during spring or summer after birth, were related to observed patterns in autumn recruitment. When deer density was low (approx. 1 deer/km 2 ) during the 1960s, fawn/female ratios were high ranging from 1.1 to 1.4 when minimum temperatures during the prior winter averaged À168 C and À88 C, respectively. Likewise, during the 2000s, when deer density was high (approx. 3 deer/km 2 ), fawn/female ratios ranged from 0.6 to 0.9 when minimum daily temperatures during the previous winter were À168 C and À88 C, respectively. Large-scale Pacific-based climatic indices (>2,000 km to the Pacific coast) were correlated with local weather and helped explain variability in autumn recruitment. Higher values of the multivariate el niño southern oscillation and Pacific decadal oscillation were correlated with warmer and drier winters in the North Dakota badlands, whereas the North Pacific Index was correlated with colder and snowy winters. The ability to predict recruitment from local weather or from broad-scale climate indices (oscillations) provides greater opportunities for conservation and management, such as adjusting harvest quotas prior to autumn harvest.

Potential Effects of Oil and Natural Gas Development on Mule Deer (Odocoileus hemionus) Survival and Fawn Rearing Resource Selection

“…This result is similar to other studies on mule deer survival in northern latitudes (White et al 1987, Bishop et al 2005, Lomas and Bender 2007, Carnes 2009, Hurley et al 2011, Brodie et al 2013) as well as previous population models on mule deer in western North Dakota (Ciuti et al 2015). I detected a strong negative relationship between mule deer survival and snow depth in spring.…”

Climate information to support wildlife management in the North Central United States

“…One state-level wildlife manager reported using both observed and projected temperature, precipitation, and wind data to better understand impacts on game bird populations in vulnerability analyses and regional conservation decisions. Other agency staff have collaborated with university researchers to examine the impacts of ENSO patterns on deer populations to inform hunting license allocations (Ciuti et al 2014(Ciuti et al , 2015. Understanding the nuanced ways that users engage with and use climate information is one factor which shapes climate information needs and the type of information and guidance needed to help meet them.…”

“…Wildlife biologists at universities and state agencies have collaborated to examine ENSO impacts on precipitation and temperature in the PPR to better understand weather-climate-ecological relationships, and in turn, to inform management decisions. In one study, ENSOrelated anomalies on winter and spring temperatures were correlated with white-tailed deer population numbers in southwest ND, since longer, colder winters negatively impact the health of the doe, which in turn leads to higher fawn mortality that year but lower fawn mortality in the subsequent year (Ciuti et al 2014(Ciuti et al , 2015. Interviewees want to know the strength and reliability of the correlation between ENSO phases and temperatures in the PPR in order to use ENSO outlooks to improve estimates of deer populations and inform decisions about hunting allowances.…”

Pivotal effect of early‐winter temperatures and snowfall on population growth of alpineParnassius smintheusbutterflies

“…One of the challenges of relating climate change to animal population dynamics is the need to identify the components of weather and climate that have the greatest impact on population growth and persistence, whether they be general indices of climate such as the North Atlantic Oscillation (NAO) or Pacific Decadal Oscillation (PDO; Vandenbosch , Ciuti et al. , Pardikes et al. ), or combinations of shorter‐term variables such as growing degree days (Pöyry et al.…”