Geology topics

Lori Pruitt

Publications and source records attributed to Lori Pruitt.

4 recordsLinked to original sources

USGS2017

Experts correctly describe demography associated with historical decline of the endangered Indiana bat, but not recent period of stationarity

Demographic characteristics of bats are often insufficiently described for modeling populations. In data poor situations, experts are often relied upon for characterizing ecological systems. In concert with the development of a matrix model describing Indiana bat ( Myotis sodalis ) demography, we elicited estimates for parameterizing this model from 12 experts. We conducted this elicitation in two stages, requesting expert values for 12 demographic rates. These rates were adult and juvenile seasonal (winter, summer, fall) survival rates, pup survival in fall, and propensity and success at breeding. Experts were most in agreement about adult fall survival (3% Coefficient of Variation) and least in agreement about propensity of juveniles to breed (37% CV). The experts showed greater concordance for adult ( mean CV, adult = 6.2%) than for juvenile parameters ( mean CV, juvenile = 16.4%), and slightly more agreement for survival (mean CV, survival = 9.8%) compared to reproductive rates ( mean CV, reproduction = 15.1%). However, survival and reproduction were negatively and positively biased, respectively, relative to a stationary dynamic. Despite the species exhibiting near stationary dynamics for two decades prior to the onset of a potential extinction-causing agent, white-nose syndrome, expert estimates indicated a population decline of -11% per year (95% CI = -2%, -20%); quasi-extinction was predicted within a century ( mean = 61 years to QE, range = 32, 97) by 10 of the 12 experts. Were we to use these expert estimates in our modeling efforts, we would have errantly trained our models to a rapidly declining demography asymptomatic of recent demographic behavior. While experts are sometimes the only source of information, a clear understanding of the temporal and spatial context of the information being elicited is necessary to guard against wayward predictions.

PeerJ↗

USGS2013

White-nose syndrome is likely to extirpate the endangered Indiana bat over large parts of its range

White-nose syndrome, a novel fungal pathogen spreading quickly through cave-hibernating bat species in east and central North America, is responsible for killing millions of bats. We developed a stochastic, stage-based population model to forecast the population dynamics of the endangered Indiana bat (Myotis sodalis) subject to white-nose syndrome. Our population model explicitly incorporated environmentally imposed annual variability in survival and reproductive rates and demographic stochasticity in predictions of extinction. With observed rates of disease spread, >90% of wintering populations were predicted to experience white-nose syndrome within 20 years, causing the proportion of populations at the quasi-extinction threshold of less than 250 females to increase by 33.9% over 50 years. At the species’ lowest median population level, ca. year 2022, we predicted 13.7% of the initial population to remain, totaling 28,958 females (95% CI = 13,330; 92,335). By 2022, only 12 of the initial 52 wintering populations were expected to possess wintering populations of >250 females. If the species can acquire immunity to the disease, we predict 3.7% of wintering populations to be above 250 females after 50 years (year 2057) after a 69% decline in abundance (from 210,741 to 64,768 [95% CI = 49,386; 85,360] females). At the nadir of projections, we predicted regional quasi-extirpation of wintering populations in 2 of 4 Recovery Units while in a third region, where the species is currently most abundant, >95% of the wintering populations were predicted to be below 250 females. Our modeling suggests white-nose syndrome is capable of bringing about severe numerical reduction in population size and local and regional extirpation of the Indiana bat.

Biological Conservation↗

USGS2012

Population-level impact of white-nose syndrome on the endangered Indiana bat

Establishing status and trend for an endangered species is critical to recovery, especially when it is faced with a nascent extinction agent. We calculated, with hierarchical log-linear change-point models, hibernaculum-level population trends between 1983 and 2009 for the endangered Indiana bat ( Myotis sodalis ) now subjected to the fast-spreading fungal disease white-nose syndrome. We combined trends from 222 wintering populations before and after onset of the disease to determine trend for clusters of interacting wintering populations, recovery units, and the species. Before onset of the disease, a west-to-east gradient in trends existed, with westernmost populations declining and easternmost populations increasing in abundance. The species as a whole, however, was stationary between 1983 and 2005 (-0.5% mean annual change; 95% confidence interval [ CI ] = -2.8, +1.8%). Estimated mean population size in 2009 was 377,124 bats (195,398-957,348), with large variance apparently caused by white-nose syndrome. With the onset of white-nose syndrome (2006-2009), the species exhibited a 10.3% annual decline (95% CI = -21.1, +2.0%). White-nose syndrome is having an appreciable influence on the status and trends of Indiana bat populations, stalling and in some cases reversing population gains made in recent years.

Journal of Mammalogy↗

USGS2012

Space-time models for a panzootic in bats, with a focus on the endangered Indiana bat

Knowledge of current trends of quickly spreading infectious wildlife diseases is vital to efficient and effective management. We developed space-time mixed-effects logistic regressions to characterize a disease, white-nose syndrome (WNS), quickly spreading among endangered Indiana bats ( Myotis sodalis ) in eastern North America. Our goal was to calculate and map the risk probability faced by uninfected colonies of hibernating Indiana bats. Model covariates included annual distance from and direction to nearest sources of infection, geolocational information, size of the Indiana bat populations within each wintering population, and total annual size of populations known or suspected to be affected by WNS. We considered temporal, spatial, and spatiotemporal formulae through the use of random effects for year, complex (a collection of interacting hibernacula), and yearxcomplex. Since first documented in 2006, WNS has spread across much of the range of the Indiana bat. No sizeable wintering population now occurs outside of the migrational distance of an infected source. Annual rates of newly affected wintering Indiana bat populations between winter 2007 to 2008 and 2010 to 2011 were 4, 6, 8, and 12%; this rate increased each year at a rate of 3%. If this increasing rate of newly affected populations continues, all wintering populations may be affected by 2016. Our models indicated the probability of a wintering population exhibiting infection was a linear function of proximity to affected Indiana bat populations and size of the at-risk population. Geographic location was also important, suggesting broad-scale influences. For every 50-km increase in distance from a WNS-affected population, risk of disease declined by 6% (95% CI=5.2-5.7%); for every increase of 1,000 Indiana bats, there was an 8% (95% CI = 1-21%) increase in disease risk. The increasing rate of infection seems to be associated with the movement of this disease into the core of the Indiana bat range. Our spatially explicit estimates of disease risk may aid managers in prioritizing surveillance and management for wintering populations of Indiana bats and help understand the risk faced by other hibernating bat species.

Journal of Wildlife Diseases↗