Cumulative weather effects can impact across the whole life cycle

Contrasted impacts of weather conditions in species sensitive to both survival and fecundity: A montane bird case study

There is growing evidence that the Earth's climate is undergoing profound changes that are affecting biodiversity worldwide. This gives rise to the pressing need to develop robust predictions on how species will respond in order to inform conservation strategies and allow managers to adapt mitigation measures accordingly. While predictions have begun to emerge on how species at the extremes of the so-called slow-fast continuum might respond to climate change, empirical studies for species for which all demographic traits contribute relatively equally to population dynamics are lacking. Yet, climate change is expected to strongly affect them throughout their entire lifecycle. We built a 21-year integrated population model to characterize the population dynamics of the rock partridge (Alectoris graeca) in France, and tested the influence of nine weather covariates on demographic parameters. As predicted, both annual survival and breeding success were affected by weather covariates. Thick snow cover during winter was associated with low survival and small brood size the following breeding season. Brood size was higher with intermediate winter temperatures and snowmelt timing, positively correlated to breeding period temperature, but negatively correlated to temperature during the coldest fortnight and precipitation during the breeding period. Survival was positively correlated to winter temperature, but negatively to breeding period precipitation. Large-scale indices indicated that cold and wet winters were associated with small brood size the following breeding season but with high survival. Expected changes of weather conditions due to climate change are likely to impact demographic traits of the rock partridge both positively and negatively depending on the traits and on the affected weather variables. Future population dynamics will thus depend on the magnitude of these different impacts. Our study illustrates the difficulty to make strong predictions about how species with a population dynamic influenced by both survival and fecundity will respond to climate change.

Genetic variance in fitness indicates rapid contemporary adaptive evolution in wild animals

The rate of adaptive evolution, the contribution of selection to genetic changes that increase mean fitness, is determined by the additive genetic variance in individual relative fitness. To date, there are few robust estimates of this parameter for natural populations, and it is therefore unclear whether adaptive evolution can play a meaningful role in short-term population dynamics. We developed and applied quantitative genetic methods to long-term datasets from 19 wild bird and mammal populations and found that, while estimates vary between populations, additive genetic variance in relative fitness is often substantial and, on average, twice that of previous estimates. We show that these rates of contemporary adaptive evolution can affect population dynamics and hence that natural selection has the potential to partly mitigate effects of current environmental change.

Using genomic prediction to detect microevolutionary change of a quantitative trait

Detecting microevolutionary responses to natural selection by observing temporal changes in individual breeding values is challenging. The collection of suitable datasets can take many years and disentangling the contributions of the environment and genetics to phenotypic change is not trivial. Furthermore, pedigree-based methods of obtaining individual breeding values have known biases. Here, we apply a genomic prediction approach to estimate breeding values of adult weight in a 35-year dataset of Soay sheep (Ovis aries). Comparisons are made with a traditional pedigree-based approach. During the study period, adult body weight decreased, but the underlying genetic component of body weight increased, at a rate that is unlikely to be attributable to genetic drift. Thus cryptic microevolution of greater adult body weight has probably occurred. Genomic and pedigree-based approaches gave largely consistent results. Thus, using genomic prediction to study microevolution in wild populations can remove the requirement for pedigree data, potentially opening up new study systems for similar research.

Adverse weather during in utero development is linked to higher rates of later-life herpesvirus reactivation in adult European badgers, Meles meles

Maternal immune and/or metabolic conditions relating to stress or nutritional status can affect in utero development among offspring with subsequent implications for later-life responses to infections. We used free-ranging European badgers as a host-pathogen model to investigate how prenatal weather conditions affect later-life herpesvirus genital tract reactivation. We applied a sliding window analysis of weather conditions to 164 samples collected in 2018 from 95 individuals born between 2005-2016. We test if the monthly mean and variation in rainfall and temperature experienced by their mother during the 12 months of delayed implantation and gestation prior to parturition subsequently affected individual herpes reactivation rates among these offspring. We identified four influential prenatal seasonal weather windows that corresponded with previously identified critical climatic conditions affecting badger survival, fecundity and body condition. These all occurred during the pre-implantation rather than the post-implantation period. We conclude that environmental cues during the in utero period of delayed implantation may result in changes that affect an individual's developmental programming against infection or viral reactivation later in life. This illustrates how prenatal adversity caused by environmental factors, such as climate change, can impact wildlife health and population dynamics-an interaction largely overlooked in wildlife management and conservation programmes.

Lagged and dormant season climate better predict plant vital rates than climate during the growing season

Understanding the effects of climate on the vital rates (e.g., survival, development, reproduction) and dynamics of natural populations is a long-standing quest in ecology, with ever-increasing relevance in the face of climate change. However, linking climate drivers to demographic processes requires identifying the appropriate time windows during which climate influences vital rates. Researchers often do not have access to the long-term data required to test a large number of windows, and are thus forced to make a priori choices. In this study, we first synthesize the literature to assess current a priori choices employed in studies performed on 104 plant species that link climate drivers with demographic responses. Second, we use a sliding-window approach to investigate which combination of climate drivers and temporal window have the best predictive ability for vital rates of four perennial plant species that each have over a decade of demographic data (Helianthella quinquenervis, Frasera speciosa, Cylindriopuntia imbricata, and Cryptantha flava). Our literature review shows that most studies consider time windows in only the year preceding the measurement of the vital rate(s) of interest, and focus on annual or growing season temporal scales. In contrast, our sliding-window analysis shows that in only four out of 13 vital rates the selected climate drivers have time windows that align with, or are similar to, the growing season. For many vital rates, the best window lagged more than 1 year and up to 4 years before the measurement of the vital rate. Our results demonstrate that for the vital rates of these four species, climate drivers that are lagged or outside of the growing season are the norm. Our study suggests that considering climatic predictors that fall outside of the most recent growing season will improve our understanding of how climate affects population dynamics.

Assessing seasonal demographic covariation to understand environmental-change impacts on a hibernating mammal

Natural populations are exposed to seasonal variation in environmental factors that simultaneously affect several demographic rates (survival, development and reproduction). The resulting covariation in these rates determines population dynamics, but accounting for its numerous biotic and abiotic drivers is a significant challenge. Here, we use a factor-analytic approach to capture partially unobserved drivers of seasonal population dynamics. We use 40 years of individual-based demography from yellow-bellied marmots (Marmota flaviventer) to fit and project population models that account for seasonal demographic covariation using a latent variable. We show that this latent variable, by producing positive covariation among winter demographic rates, depicts a measure of environmental quality. Simultaneously, negative responses of winter survival and reproductive-status change to declining environmental quality result in a higher risk of population quasi-extinction, regardless of summer demography where recruitment takes place. We demonstrate how complex environmental processes can be summarized to understand population persistence in seasonal environments.