Geology topics

William F. Morris

Publications and source records attributed to William F. Morris.

5 recordsLinked to original sources

USGS2022

Climate change weakens the impact of disturbance interval on the growth rate of natural populations of Venus flytrap

Disturbances elicit both positive and negative effects on organisms; these effects vary in their strength and their timing. Effects of disturbance interval (i.e., the length of time between disturbances) on population growth will depend on both the timing and strength of positive and negative effects of disturbances. Climate change can modify the relative strengths of these positive and negative effects, leading to altered optimal disturbance intervals (the disturbance interval at which population growth rate is highest) and changes in the sensitivity of population growth rate to disturbance interval. While we know that climate may alter impacts of disturbance in some systems, we have a poor understanding of which effects of disturbance and which vital rates might drive an altered response to disturbance interval in a changing climate. We use demographic monitoring of natural populations of Dionaea muscipula , the Venus flytrap, that have experienced natural and managed fires, combined with realistic past and future climate projections, to construct climate- and fire-driven integral projection models (IPMs). We use these IPMs to compare the effect of fire return interval (FRI) on population growth rate in past and future climates. To dissect the mechanisms driving FRI response, we then construct IPMs with demographic data from an experimental manipulation of fire effects (ash addition, neighbor removal) and an accidental fire. Our results show that an FRI of 10 years is optimal for D. muscipula in past climate conditions, but a longer FRI (12 years) is optimal in future climate conditions. Further, deviations from optimal FRI reduce population growth rate dramatically in the past climate, but this reduction is muted in a future climate (future minus past sensitivity = 0.006, 95% CI [0.002, 0.011]). Finally, our experimental work suggests that fire effects are driven in part by positive, additive effects of competitor removal and ash addition immediately following a fire; for one population, both these treatments significantly increased population growth rate. Our work suggests that climate change can alter the response of populations to disturbance, highlighting the need to consider the interacting effects of multiple abiotic drivers when projecting future population growth and geographical distributions.

North Carolina↗

USGS2022

Shifting precipitation regimes alter the phenology and population dynamics of low latitude ectotherms

Predicting how species respond to changes in climate is critical to conserving biodiversity. Modeling efforts to date have largely centered on predicting the effects of warming temperatures on temperate species phenology. In and near the tropics, the effects of a warming planet on species phenology are more likely to be driven by changes in the seasonal precipitation cycle rather than temperature. To demonstrate the importance of considering precipitation-driven phenology in ecological studies, we present a case study wherein we construct a mechanistic population model for a rare subtropical butterfly (Miami blue butterfly, Cyclargus thomasi bethunebakeri ) and use a suite of global climate models to project butterfly populations into the future. Across all iterations of the model, the trajectory of Miami blue populations is uncertain. We identify both biological uncertainty (unknown diapause survival rate) and climate uncertainty (ambiguity in the sign of precipitation change across climate models), and their interaction as key factors that determine persistence vs. extinction. Despite uncertainty, the most optimistic iteration of the model predicts that Miami blue butterfly populations will decline under the higher emissions scenario (RCP 8.5). The lack of climate model agreement across the projection ensemble suggests that investigations into the effect of climate change on precipitation-driven phenology require a higher level of rigor in the uncertainty analysis compared to analogous studies of temperature. For tropical species, a mechanistic approach that incorporates both biological and climate uncertainty is the best path forward to understand the effect shifting precipitation regimes have on phenology and population dynamics.

Florida↗

USGS2021

Shifting correlations among multiple aspects of weather complicate predicting future demography of a threatened species

Most studies of the ecological effects of climate change consider only a limited number of weather drivers that could affect populations, though we know that multiple weather drivers can simultaneously affect population growth rate. Multiple drivers could simultaneously increase/decrease one vital rate, or one may increase a vital rate while another decreases the same vital rate. Considering the impact of multiple weather drivers on vital rates is particularly important in a changing climate, in which correlations among drivers may not be preserved in the future. We used a long-term dataset on the endangered red-cockaded woodpecker ( Dryobates borealis ) to understand how multiple weather drivers jointly affect survival and reproductive vital rates and then assessed the contributions of individual weather drivers to historical trends in vital rates over time. We found that vital rates were often influenced by more than one weather driver and that weather drivers most commonly exerted opposing effects. For instance, some weather drivers increased vital rates over time, while others acted in the opposite direction, decreasing vital rates over time. Importantly, the historical correlations among weather drivers are almost always projected to change in the future climate, such that future trends in vital rates may not match historical trends. For example, we do not find historical trends in adult survival, but changing correlations among weather drivers could generate future trends in this vital rate. Our work provides an example of how multiple weather drivers can control a variety of vital rates and also illustrates how changes in the correlation structure of weather drivers through time might substantially affect future trends in individual and population performance.

Ecosphere↗

USGS2013

Ability of matrix models to explain the past and predict the future of plant populations.

Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage-based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts' 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data-collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk-averse decisions than to expect precise forecasts from models.

Conservation Biology↗

USGS2012

Matrix population models from 20 studies of perennial plant populations

Demographic transition matrices are one of the most commonly applied population models for both basic and applied ecological research. The relatively simple framework of these models and simple, easily interpretable summary statistics they produce have prompted the wide use of these models across an exceptionally broad range of taxa. Here, we provide annual transition matrices and observed stage structures/population sizes for 20 perennial plant species which have been the focal species for long-term demographic monitoring. These data were assembled as part of the "Testing Matrix Models" working group through the National Center for Ecological Analysis and Synthesis (NCEAS). In sum, these data represent 82 populations with >460 total population-years of data. It is our hope that making these data available will help promote and improve our ability to monitor and understand plant population dynamics.

Ecology↗