About

Dan Doak is a Professor and the Byers Family Chair in Environmental Studies at the University of Colorado Boulder. His research focuses on the ecology and management of rare species and habitats, biodiversity protection and management, population and community ecology, and the effects of climate change on ecological systems. He is involved in understanding how ecological systems are impacted by environmental changes and works on strategies for conserving biodiversity. Dan Doak's work is conducted through the Doak Lab, and he is based in the Department of Environmental Studies at the University of Colorado Boulder.

Research topics

• Demography
• Biology
• Ecology
• Geography
• Computer Science
• Mathematics
• Algorithm
• Statistics
• Econometrics
• Virology
• Medicine
• Environmental health
• Environmental science

Selected publications

• Behavioral shifts mask the success of legislation and outreach for endangered species recovery

  Nature Communications · 2026-03-18

  articleOpen access

  A fundamental challenge in conservation is assessing the efficacy of recovery actions to optimize endangered species management. Considerable recent attention has focused on effective measures to counter the endangerment of avian scavengers, which have declined worldwide, primarily due to poisoning. One iconic example is efforts to recover the critically endangered California condor (Gymnogyps californianus), whose leading cause of death is poisoning from ingesting lead-based ammunition in carcasses. Despite enormous resources expended in California, USA, including implementation of public outreach campaigns and two legislative bans on lead ammunition, lead-related mortality of condors has increased. Here we show that two types of behavioral shifts explain the observed increases in condor lead exposure: wilder foraging and ranging by condors and increased shooting of wild pigs (Sus scrofa) by humans. After accounting for these trends, we show that both lead ammunition bans and public outreach efforts have significantly reduced condor blood lead levels in California, lowering mortality. Our analyses uncover a dynamic in which changing ecological conditions mask the true efficacy of legislation and outreach. Given rapid global change, such dynamics are likely operating in many settings, underscoring the importance of comprehensive evaluations of recovery actions, which can be obscured by shifting behaviors and threats.

  PublisherOA PDFDOI

• Dynamic and context-dependent keystone species effects in kelp forests

  Proceedings of the National Academy of Sciences · 2025-03-03 · 6 citations

  articleOpen accessSenior author

  Sea otters are an iconic keystone predator that can maintain kelp forests by preying on grazing invertebrates such as sea urchins. However, the effects of sea otters on kelp forests vary over their geographic range. Here, we analyze two 30-y datasets on kelp forest communities during the reintroduction of sea otters along the west coast of Vancouver Island, BC, Canada, and around San Nicolas Island, CA. We developed a community model to estimate species interactions as dynamic rates, varying with community state. We find evidence of a classic trophic cascade off Vancouver Island; the arrival of otters quickly led to depletion of urchins and recovery of kelp. However, this cascade was muted around San Nicolas Island, with otters, urchins, and kelp all coexisting at intermediate densities for multiple years. Our models show that this difference came from a pulse of strong otter impacts on urchins following recolonization off Vancouver Island, but not off San Nicolas Island. The mean effects of otters on urchins and urchins on kelp were not stronger in the north, indicating that interaction dynamics and not average interaction strength are key to explaining differences in community trajectories. We also find stronger multistep interaction chains in the south, arising from competitive interactions that indirectly buffered otter effects. These findings shed light on long-standing hypotheses about how interspecific interactions can alter the function of keystone species across community contexts. More broadly, we show how community change can be more accurately predicted by considering dynamic interaction strengths.

  PublisherOA PDFDOI

• What Is Demographic Lability and When Might We Expect to See It?

  The American Naturalist · 2025-07-25 · 1 citations

  articleSenior author

  AbstractWhen vital rates are convex functions of environmental drivers, temporal variation in those vital rates could increase long-term stochastic fitness (so-called demographic lability). Yet no empirical cases of this phenomenon have yet been documented. We first outline three necessary steps to document lability: estimate how vital rates change with environmental drivers, quantify driver distributions, and compare the fitness effects of variation to a "no-variation" baseline driver value (typically its mean). We then review articles that presented evidence for lability and find that none fully documented it. In addition, we examine for the first time when natural selection would produce adaptive lability de novo, rather than other adaptations to stochastic environments, and we suggest that selection to better exploit the most frequent environmental states may often erode lability. Finally, we consider conditions (including life history "speed," shape of vital rate/environment relationships, and type of environmental driver) that might support lability. We argue that lability is less likely in response to abiotic than biotic drivers but question whether fast and slow life histories differ in their propensity for lability. Our principal aim is to suggest research directions that would put the intriguing idea of demographic lability on a firmer foundation.

  PublisherDOI

• Sampling design and estimates of observation error greatly reduce quasi-extinction probability in plant populations

  Biological Conservation · 2025-04-08

  articleOpen access

  Estimates of population dynamics and risk of extinction are sensitive to both mean rates of annual change and also the variation in these rates caused by environmental stochasticity. The analytical machinery to incorporate the latter into estimates of long-term stochastic growth and quasi-extinction risk are well developed for count-based population data. However, analytical methods rarely account for the effects of observation error during the sampling process, which can inflate apparent stochasticity and thus alter estimates of population behavior. Here, we applied a Bayesian stochastic population model to estimate the growth rates and quasi-extinction risk of over 157 plant populations monitored through a collaborative science program in NE Spain, and calculated the effect of incorporating direct measures of the observation error into our estimates. We found that including the observation error into models reduced the estimated temporal variation of all populations, which in turn resulted in modest increases in estimated long-term growth rates but considerable reductions in quasi-extinction risk. In this study we show how adjusting sampling designs to the size, detectability and density of plant populations, and repeating surveys in one or more years substantially improves estimates of population growth and viability, thus contributing to guide a better conservation practice. • Observation error can account for a great part of the temporal variation in population growth rates. • Choice of sampling method can help reduce observation error in plant population monitoring programs. • Simple measures of observation error improve model fit and reduce estimates of population variance. • Improved estimates lead to reduced probabilities of extinction in plant populations • Better estimates of population viability and extinction risk can guide conservation efforts.

  PublisherDOI

• Author response for "Nonlinear life table response experiment analysis: Decomposing nonlinear and nonadditive population growth responses to changes in environmental drivers"

  2024-02-19

  peer-review
  PublisherDOI

• Density, Climate, and Stochasticity Shape Four Centuries of Population Dynamics for Two Long‐Lived Tree Species

  Ecology and Evolution · 2024-12-01

  articleOpen accessSenior author

  The dynamics of colonizing populations may be strongly influenced by both extrinsic (e.g., climate and competition) and intrinsic (e.g., density) forces as well as demographic and environmental stochasticity. Understanding the impacts of these effects is crucial for predicting range expansions, trailing edge dynamics, and the viability of rare species, but the general importance of each of these forces remains unclear. Here, we assemble establishment time and spatial locations of most individuals that have reached maturity in six isolated, establishing populations of two pine species. These data allow us to quantify the relative importance of multiple factors in controlling growth of these populations. We found that climate, density, site, and demographic stochasticity were of varying importance both within and across species, but that no driver appeared to dominate dynamics across all populations and time periods. Indeed, exclusion of any one of these effects greatly reduced predictive power of our population growth models. Given the similarity in the abiotic characteristics of these sites, the varying importance of these classes of effects was surprising but speaks to the need to consider multiple effects when predicting the dynamics of small and colonizing populations.

  PublisherOA PDFDOI

• Practical models to guide the transition of California condors from a conservation-reliant to a self-sustaining species

  Biological Conservation · 2024-02-15 · 8 citations

  article
  PublisherDOI

• Temporal variability and predictability predict alpine plant community composition and distribution patterns

  Ecology · 2024-10-26 · 2 citations

  article

  One of the most reliable features of natural systems is that they change through time. Theory predicts that temporally fluctuating conditions shape community composition, species distribution patterns, and life history variation, yet features of temporal variability are rarely incorporated into studies of species-environment associations. In this study, we evaluated how two components of temporal environmental variation-variability and predictability-impact plant community composition and species distribution patterns in the alpine tundra of the Southern Rocky Mountains in Colorado (USA). Using the Sensor Network Array at the Niwot Ridge Long-Term Ecological Research site, we used in situ, high-resolution temporal measurements of soil moisture and temperature from 13 locations ("nodes") distributed throughout an alpine catchment to characterize the annual mean, variability, and predictability in these variables in each of four consecutive years. We combined these data with annual vegetation surveys at each node to evaluate whether variability over short (within-day) and seasonal (2- to 4-month) timescales could predict patterns in plant community composition, species distributions, and species abundances better than models that considered average annual conditions alone. We found that metrics for variability and predictability in soil moisture and soil temperature, at both daily and seasonal timescales, improved our ability to explain spatial variation in alpine plant community composition. Daily variability in soil moisture and temperature, along with seasonal predictability in soil moisture, was particularly important in predicting community composition and species occurrences. These results indicate that the magnitude and patterns of fluctuations in soil moisture and temperature are important predictors of community composition and plant distribution patterns in alpine plant communities. More broadly, these results highlight that components of temporal change provide important niche axes that can partition species with different growth and life history strategies along environmental gradients in heterogeneous landscapes.

  PublisherDOI

• Optimizing demographic analysis in the face of missing data years to improve conservation of threatened species

  Biological Conservation · 2024-11-24

  articleOpen accessSenior author

  Quantification of population dynamics and predictions of species viability rely on estimates of vital rates and an understanding of the ecological drivers of these rates. Most standard methods for assessing impacts of drivers, such as climate, on vital rates require annual demographic data for many individuals over multiple years. However, many real studies have either planned or unplanned data gaps. Vital rates are usually estimated over annual transitions, therefore one year of missing data results in two missing estimates. Additionally, relating annual climate variation to changes in vital rates is challenging if studies do not collect data annually. To avoid this loss of information due to missing data, we developed and then tested a Bayesian modeling approach for a dataset with missing years. Using an 18-year study of the rare plant Eriogonum brandegeei we estimate vital rates, their relationship to annual climate, and stochastic population growth. By comparing model performance across data subsets, as well as in tests using simulated data, we find that the approach works well with missing years of demographic data and removes the need to ignore information from multi-year transitions. This generalizable approach increases the useability of available data to study species dynamics despite patchy demographic data.

  PublisherDOI

• Author response for "Nonlinear life table response experiment analysis: Decomposing nonlinear and nonadditive population growth responses to changes in environmental drivers"

  2024-01-12

  peer-review
  PublisherDOI

Recent grants

• Collaborative Research: Controls over Prairie Plant Range Distributions under Future Climate Change

  NSF · $416k · 2014–2020

• LTER Cross-site: Collaborative Research - Assessing the Geographic and Temporal Consistency of Life History and Demographic Patterns: A Long-term, Multi-site Comparison

  NSF · $240k · 2000–2007

• Collaborative Research: Interactions Among Keystone Species: Effects of Termites and Ungulates on Biodiversity in East African Savannas.

  NSF · $97k · 2007–2011

• DISSERTATION RESEARCH:Ecological interactions mediate the effects of climatic stress on populations: dissecting the direct and indirect effects of climate on plants

  NSF · $18k · 2013–2015

• LTREB RENEWAL: Collaborative Research: Population- and community-level mechanisms of range limitation in a variable and changing environment

  NSF · $260k · 2012–2018

Frequent coauthors

• William F. Morris

  Duke University

  49 shared

• Todd M. Palmer

  University of Cape Town

  44 shared

• James A. Estes

  University of California, Santa Cruz

  44 shared

• Jacob R. Goheen

  Wyoming Department of Education

  34 shared

• Allison M. Louthan

  Kansas State University

  34 shared

• Terrie M. Williams

  University of California, Santa Cruz

  30 shared

• Robert M. Pringle

  Princeton University

  29 shared

• Joaquim Garrabou

  Institut Català de Ciències del Clima

  22 shared