Biology subjects

Wisdom, M.

Publications and source records attributed to Wisdom, M..

4 recordsLinked to original sources

bioRxiv2025

The effects of predator recovery and climate change on the long-term demography of a flagship herbivore

In the western United States, ecosystems are being reshaped from both bottom-up and top-down processes. Widespread carnivore recolonizations after 20th century extirpations have returned top-down pressures to ecosystems, and climate change is reshaping bottom-up forces through shifts in the timing and length of growing seasons, resulting in reduced forage quality and quantity. Large herbivores, such as elk (Cervus canadensis), function as flagship species for conservation and have potential for both top-down and bottom-up forces to shape demography as ecosystems change. To test the roles of top-down (puma density (Puma concolor)) and bottom-up (drought severity and elk density) processes in shaping large herbivore demography, and to tie those effects to population trajectories, we built an integrated population model (IPM) using 36 years of elk data spanning the recolonization of pumas and long-term climate change in eastern Oregon, USA. We tested the effects of top-down and bottom-up forces on elk recruitment, calf survival, and population growth. We also tested effects of bottom-up forces on elk pregnancy rates. Puma recolonization corresponded with declines in mean recruitment from 0.44 to 0.32 calves per female and in calf survival from 0.92 to 0.69, corresponding with a 4% drop in population growth. Drought severity increased over our study period, explaining a decline in mean recruitment from 0.39 to 0.32 calves per female, which corresponds to a 3% reduction in population growth. Drought severity likely acted on recruitment through reduced pregnancy rates. Lactating females showed lower pregnancy rates in drought conditions, while drought from fall breeding periods to the following fall had no effect on recruitment. While both top-down and bottom-up forces explained variation in elk demography over the course of our study, bottom-up forces are likely to be more influential on large herbivores moving forward. Predator populations stabilized following recovery, limiting the top-down contribution to annual variation in vital rates. Climate change-induced drought patterns, however, are accelerating during summer and fall throughout large areas of the interior western U.S. Thus, our results indicate the potential for increasingly strong bottom-up negative effects on herbivores whose performance depends on a narrow period of summer nutrition. Open Research StatementData are not yet provided. Many of the data from Starkey Experimental Forest and Range are already publicly available, and we are currently working to post data for this manuscript on the Forest Service Research Data Archive (FSRDA) linked to the rest of the data from Starkey. Upon acceptance, all data and the relevant code will be archived the FSRDA. Currently, the code for the paper is publicly available on Github at https://github.com/keloonam/starkey_ipm

ecology↗

bioRxiv2024

Variability and correlations among vital rates and their influence on population growth in mule and black-tailed deer

To reverse observed range-wide population declines, managers of mule and black- tailed deer (Odocoileus hemionus) require information on the vital rates and life stages that are most influential to population growth for which to target management actions. We conducted a range-wide literature review and used hierarchical models to provide biological descriptions of mule and black-tailed deer vital rates, their variability, and how they correlate with one another. We then used matrix models and life-stage simulation analysis to determine the individual vital rates that contributed most to lambda, i.e., annual population growth rate. Adult female survival was the vital rate with the greatest ability to predict lambda and explained 62% of the variation in population growth. While annual juvenile survival explained 44% of the variation in lambda, summer and winter juvenile survival by themselves were far less explanatory than adult female survival. Winter fawn:doe ratios, a metric often collected by management agencies, only explained 10% of the variation in lambda. When adult female survival was 0.84, our simulations estimated an equal probability that a population would increase versus decrease, and correspondingly, the estimate of lambda was 1.0 with a 95% credible interval of 0.88-1.14. Simulations suggested that populations with adult survival rates less than 70% would always decline, but as survival increased beyond this value lambda increased linearly and never plateaued. In contrast, the probability of observing a stable lambda plateaued when annual juvenile survival reached approximately 0.5. The mean lambda calculated from all simulated values within the observed range of vital rate values across the species geographical distribution was 0.975, and in 61% of the simulations lambda was < 1. After 20 years, we estimated that this distribution of lambda values would cause populations to decrease in 92% of instances with a mean decrease of 44%. Our results align with the observed declines in mule deer populations throughout their range over recent decades and suggest that these trends will continue until management can improve survival of adult females.

ecology↗

bioRxiv2022

Action prediction error: a value-free dopaminergic teaching signal that drives stable learning

Animals choice behavior is characterized by two main tendencies: taking actions that led to rewards and repeating past actions. Theory suggests these strategies may be reinforced by different types of dopaminergic teaching signals: reward prediction error (RPE) to reinforce value-based associations and movement-based action prediction errors to reinforce value-free repetitive associations. Here we use an auditory-discrimination task in mice to show that movement-related dopamine activity in the tail of the striatum encodes the hypothesized action prediction error signal. Causal manipulations reveal that this prediction error serves as a value-free teaching signal that supports learning by reinforcing repeated associations. Computational modeling and experiments demonstrate that action prediction errors alone cannot support reward-guided learning but when paired with the RPE circuitry they serve to consolidate stable sound-action associations in a value-free manner. Together we show that there are two types of dopaminergic prediction errors that work in tandem to support learning.

neuroscience↗

bioRxiv2020

Integrating spatial capture-recapture models with variable individual identifiability

Spatial capture-recapture (SCR) models have become the preferred tool for estimating densities of carnivores. Within this family of models are variants requiring identification of all individuals in each encounter (SCR), a subset of individuals only (generalized spatial mark-resight, gSMR), or no individual identification (spatial count or spatial presence-absence). Although each technique has been shown through simulation to yield unbiased results, the consistency and relative precision of estimates across methods in real-world settings are seldom considered. We tested a suite of models ranging from those only requiring detections of unmarked individuals to others that integrate remote camera, physical capture, genetic, and global positioning system (GPS) data into a hybrid model, to estimate population densities of black bears, bobcats, cougars, and coyotes. For each species we genotyped fecal DNA collected with detection dogs during a 20-day period. A subset of individuals from each species was affixed with GPS collars bearing unique markings and resighted by remote cameras over 140 days contemporaneous with scat collection. Camera-based gSMR models produced density estimates that differed by less than 10% from genetic SCR for bears, cougars, and coyotes once important sources of variation (sex or behavioral status) were controlled for. For bobcats, SCR estimates were 33% higher than gSMR. The cause of the discrepancies in estimates was likely attributable to challenges designing a study compatible for species with disparate home range sizes and the difficulty of collecting sufficient data in a timeframe in which demographic closure could be assumed. Unmarked models estimated densities that varied greatly from SCR, but estimates became more consistent in models wherein more individuals were identifiable. Hybrid models containing all data sources exhibited the most precise estimates for all species. For studies in which only sparse data can be obtained and the strictest model assumptions are unlikely to be met, we suggest researchers use caution making inference from models lacking individual identity. For best results, we further recommend the use of methods requiring at least a subset of the population is marked and that multiple datasets are incorporated when possible.

ecology↗