Search for: All records

Life table response experiments (LTREs) decompose differences in population growth rate between environments into separate contributions from each underlying demographic rate. However, most LTRE analyses make the unrealistic assumption that the relationships between demographic rates and environmental drivers are linear and independent, which may result in diminished accuracy when these assumptions are violated. We extend regression LTREs to incorporate nonlinear (second‐order) terms and compare the accuracy of both approaches for three previously published demographic datasets. We show that the second‐order approach equals or outperforms the linear approach for all three case studies, even when all of the underlying vital rate functions are linear. Nonlinear vital rate responses to driver changes contributed most to population growth rate responses, but life history changes also made substantial contributions. Our results suggest that moving from linear to second‐order LTRE analyses could improve our understanding of population responses to changing environments.

 

Danthonia californicaBolander (Poaceae)is a native perennial bunchgrass commonly used in the restoration of prairie ecosystems in the western United States. Plants of this species simultaneously produce both chasmogamous (potentially outcrossed) and cleistogamous (obligately self‐fertilized) seeds. Restoration practitioners almost exclusively use chasmogamous seeds for outplanting, which are predicted to perform better in novel environments due to their greater genetic diversity. Meanwhile, cleistogamous seeds may exhibit greater local adaptation to the conditions in which the maternal plant exists. We performed a common garden experiment at two sites in the Willamette Valley, Oregon, to assess the influence of seed type and source population (eight populations from a latitudinal gradient) on seedling emergence and found no evidence of local adaptation for either seed type. Cleistogamous seeds outperformed chasmogamous seeds, regardless of whether seeds were sourced directly from the common gardens (local seeds) or other populations (nonlocal seeds). Furthermore, average seed weight had a strong positive effect on seedling emergence, despite the fact that chasmogamous seeds had significantly greater mass than cleistogamous seeds. At one common garden, we observed that seeds of both types sourced from north of our planting site performed significantly better than local or southern‐sourced seeds. We also found a significant seed type and distance‐dependent interaction, with cleistogamous seedling emergence peaking approximately 125 km from the garden. These results suggest that cleistogamous seeds should be considered for greater use inD. californicarestoration.

 

Multiple, simultaneous environmental changes, in climatic/abiotic factors, interacting species, and direct human influences, are impacting natural populations and thus biodiversity, ecosystem services, and evolutionary trajectories. Determining whether the magnitudes of the population impacts of abiotic, biotic, and anthropogenic drivers differ, accounting for their direct effects and effects mediated through other drivers, would allow us to better predict population fates and design mitigation strategies. We compiled 644 paired values of the population growth rate ( λ ) from high and low levels of an identified driver from demographic studies of terrestrial plants. Among abiotic drivers, natural disturbance (not climate), and among biotic drivers, interactions with neighboring plants had the strongest effects on λ . However, when drivers were combined into the 3 main types, their average effects on λ did not differ. For the subset of studies that measured both the average and variability of the driver, λ was marginally more sensitive to 1 SD of change in abiotic drivers relative to biotic drivers, but sensitivity to biotic drivers was still substantial. Similar impact magnitudes for abiotic/biotic/anthropogenic drivers hold for plants of different growth forms, for different latitudinal zones, and for biomes characterized by harsher or milder abiotic conditions, suggesting that all 3 drivers have equivalent impacts across a variety of contexts. Thus, the best available information about the integrated effects of drivers on all demographic rates provides no justification for ignoring drivers of any of these 3 types when projecting ecological and evolutionary responses of populations and of biodiversity to environmental changes. 

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.

 

Populations of many species are genetically adapted to local historical climate conditions. Yet most forecasts of species’ distributions under climate change have ignored local adaptation (LA), which may paint a false picture of how species will respond across their geographic ranges. We review recent studies that have incorporated intraspecific variation, a potential proxy for LA, into distribution forecasts, assess their strengths and weaknesses, and make recommendations for how to improve forecasts in the face of LA. The three methods used so far (species distribution models, response functions, and mechanistic models) reflect a trade‐off between data availability and the ability to rigorously demonstrate LA to climate. We identify key considerations for incorporating LA into distribution forecasts that are currently missing from many published studies, including testing the spatial scale and pattern of LA, the confounding effects of LA to nonclimatic or biotic drivers, and the need to incorporate empirically based dispersal or gene flow processes. We suggest approaches to better evaluate these aspects of LA and their effects on species‐level forecasts. In particular, we highlight demographic and dynamic evolutionary models as promising approaches to better integrate LA into forecasts, and emphasize the importance of independent model validation. Finally, we urge closer examination of how LA will alter the responses of central vs. marginal populations to allow stronger generalizations about changes in distribution and abundance in the face of LA.