Effect of time series length and resolution on abundance‐ and trait‐based early warning signals of population declines

Seasonal environmental conditions shape the behavior and life history of virtually all organisms. Climate change is modifying these seasonal environmental conditions, which threatens to disrupt population dynamics. It is conceivable that climatic changes may be beneficial in one season but result in detrimental conditions in another because life-history strategies vary between these time periods. We analyzed the temporal trends in seasonal survival of yellow-bellied marmots (Marmota flaviventer) and explored the environmental drivers using a 40-y dataset from the Colorado Rocky Mountains (USA). Trends in survival revealed divergent seasonal patterns, which were similar across age-classes. Marmot survival declined during winter but generally increased during summer. Interestingly, different environmental factors appeared to drive survival trends across age-classes. Winter survival was largely driven by conditions during the preceding summer and the effect of continued climate change was likely to be mainly negative, whereas the likely outcome of continued climate change on summer survival was generally positive. This study illustrates that seasonal demographic responses need disentangling to accurately forecast the impacts of climate change on animal population dynamics

How well can body size represent effects of the environment on demographic rates? Disentangling correlated explanatory variables

1. Demographic rates are shaped by the interaction of past and current environments that individuals in a population experience. Past environments shape individual states via selection and plasticity, and fitness-related traits (e.g., individual size) are commonly used in demographic analyses to represent the effect of past22 environments on demographic rates. 2. We quantified how well the size of individuals captures the effects of a population’s past and current environments on demographic rates in a well-studied experimental system of soil mites. We decomposed these interrelated sources of variation with a novel method of multiple regression that is useful for understanding nonlinear relationships between responses and multicollinear explanatory variables. We graphically present the results using area-proportional Venn diagrams. Our novel method was developed by combining existing methods and expanding upon them. 3. We showed that the strength of size as a proxy for the past environment varied widely among vital rates. For instance, in this organism with an income breeding life-history, the environment had more effect on reproduction than individual size, but with substantial overlap indicating that size encompassed some of the effects of the past environment on fecundity. 4. This demonstrates that the strength of size as a proxy for the past environment can vary widely among life-history processes within a species, and this variation should be taken into consideration in trait-based demographic or individual-based approaches that focus on phenotypic traits as state variables. Furthermore, the strength of a proxy will depend on what state variable(s) and what demographic rate is being examined; i.e., different measures of body size (e.g., length, volume, mass, fat stores) will be better or worse proxies for various life-history processes

Disentangling evolutionary, plastic and demographic processes underlying trait dynamics: a review of four frameworks

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.Biologists are increasingly interested in decomposing trait dynamics into underlying processes, such as evolution, plasticity and demography. Four important frameworks that allow for such a decomposition are the quantitative genetic animal model (AM), the ‘Geber’ method (GM), the age-structured Price equation (APE) and the integral projection model (IPM). However, as these frameworks have largely been developed independently, they differ in the assumptions they make, the data they require, as well as their outcomes and interpretation. Here, we evaluate how each framework decomposes trait dynamics into underlying processes. To do so, we apply them to simulated data for a hypothetical animal population. Individual body size was affected by, among others, genes, maternal effects and food intake. We simulated scenarios with and without selection on body size and with high and low heritability. The APE and IPM provided similar results, as did the AM and GM, with important differences between the former and the latter. All frameworks detected positive contributions of selection in the high but not in the low selection scenarios. However, only the AM and GM distinguished between the high and low heritability scenarios. Furthermore, the AM and GM revealed a high contribution of plasticity. The APE and IPM attributed most of the change in body size to ontogenetic growth and inheritance, where the latter captures the combined effects of plasticity, maternal effects and heritability. We show how these apparent discrepancies are mostly due to differences in aims and definitions. For example, the APE and IPM capture selection, whereas the AM and GM focus on the response to selection. Furthermore, the frameworks differ in the processes that are ascribed to plasticity and in how they take into account demography. We conclude that no single framework provides the ‘true’ contributions of evolution, plasticity and demography. Instead, different research questions require different frameworks. A thorough understanding of the different definitions of their components is necessary for selecting the most appropriate framework for the question at hand and for making biologically meaningful inferences. This work thus supports both future analysis and the careful interpretation of existing work.This work was funded by the Swiss NationalScience Foundation project grants (31003A_141110 and 31003A_159462/1 toEP, 31003A_146445 to AO) and an ERC starting grant (#337785 to AO)

The psychology of democracy

What is a democracy? Why do we form democratic systems? Can democracy survive in an age of distrust and polarisation? The Psychology of Democracy explains the psychological underpinnings behind why people engage with and participate in politics. Covering the influence that political campaigns and media play, the book analyses topical and real-world political events including the Arab Spring, Brexit, Black Lives Matter, the US 2020 elections and the Covid-19 pandemic. Lilleker and Ozgul take the reader on a journey to explore the cognitive processes at play when engaging with a political news item all the way through to taking to the streets to protest government policy and action. In an age of post-truth and populism, The Psychology of Democracy shows us how a strong and healthy democracy depends upon the feelings and emotions of its citizens, including trust, belonging, empowerment and representation, as much as on electoral processes

Association of polymorphisms in APOE, p53, and p21 with primary open-angle glaucoma in Turkish patients

Purpose To investigate the association between Apolipoprotein E (APOE), tumor suppressor protein p53 (p53), and cyclin-dependent kinase inhibitor 1A (p21) genes and primary open-angle glaucoma (POAG) in a cohort of Turkish subjects. Methods Seventy-five POAG patients (49 women, 26 men) and 119 healthy subjects (67 women, 52 men) were genotyped with polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Allele and genotype frequencies between healthy subjects and glaucoma patients were compared by the χ2 test, and intraocular pressure (IOP), cup/disc ratio (C/D) and visual field indices (MD and PSD) were compared among different APOE, p53, and p21 genotypes in POAG group. A p value 0.05). POAG subjects with the ε2ε3 genotype had a worse PSD value (median=2.2) than those with the ε3ε4 genotype (median=1.77; p=0.01) and POAG subjects with the ε3ε3 genotype had worse MD and PSD values (median= -7.4 and 3.4, respectively) than those with the ε3ε4 genotype (median= -4.1 and 1.77, respectively; p=0.034 and 0.028, respectively). Conclusions Our study found no link between polymorphisms in APOE, p53, and p21 genes and POAG in Turkish patients, although a larger sample is required to elucidate the role of these polymorphisms in the pathogenesis and course of glaucoma

Modeling adaptive and non-adaptive responses to environmental change

Understanding how the natural world will be impacted by environmental change over the coming decades is one of the most pressing challenges facing humanity. Addressing this challenge is difficult because environmental change can generate both population level plastic and evolutionary responses, with plastic responses being either adaptive or non-adaptive. We develop an approach that links quantitative genetic theory with data-driven structured models to allow prediction of population responses to environmental change via plasticity and adaptive evolution. After introducing general new theory, we construct a number of example models to demonstrate that evolutionary responses to environmental change over the short-term will be considerably slower than plastic responses, and that the rate of adaptive evolution to a new environment depends upon whether plastic responses are adaptive or non-adaptive. Parameterization of the models we develop requires information on genetic and phenotypic variation and demography that will not always be available, meaning that simpler models will often be required to predict responses to environmental change. We consequently develop a method to examine whether the full machinery of the evolutionarily explicit models we develop will be needed to predict responses to environmental change, or whether simpler non-evolutionary models that are now widely constructed may be sufficient

Why disease ecology needs life-history theory: a host perspective

When facing an emerging infectious disease of conservation concern, we often have little information on the nature of the host-parasite interaction to inform management decisions. However, it is becoming increasingly clear that the life-history strategies of host species can be predictive of individual- and population-level responses to infectious disease, even without detailed knowledge on the specifics of the host-parasite interaction. Here, we argue that a deeper integration of life-history theory into disease ecology is timely and necessary to improve our capacity to understand, predict and mitigate the impact of endemic and emerging infectious diseases in wild populations. Using wild vertebrates as an example, we show that host life-history characteristics influence host responses to parasitism at different levels of organisation, from individuals to communities. We also highlight knowledge gaps and future directions for the study of life-history and host responses to parasitism. We conclude by illustrating how this theoretical insight can inform the monitoring and control of infectious diseases in wildlife

"Medicine is still against Black people": Mapping and visualising intersections of social inequalities, community mistrust, and vaccine hesitancy in online and physical spaces in the UK and US

Funded by the British Academy, this report is part of a research project entitled “Mapping and visualising intersections of social inequalities, community mistrust, and vaccine hesitancy in online and physical spaces in the UK and US”. The report investigates social, cultural, and political factors underlying vaccine hesitant beliefs and ideas among minoritised communities in the United Kingdom (UK) and the United States of America (US). The data is collected through interviews and focus groups with vaccine-hesitant individuals within various religiously, ethnically, and racially minoritised communities, interviews with medical practitioners, and through thematic analysis of vaccine communication in Twitter and Telegram during the COVID-19 pandemic

Chromosome-level genome assembly for the Aldabra giant tortoise enables insights into the genetic health of a threatened population

The Aldabra giant tortoise (Aldabrachelys gigantea) is one of only two giant tortoise species left in the world. The species is endemic to Aldabra Atoll in Seychelles and is considered vulnerable due to its limited distribution and threats posed by climate change. Genomic resources for A. gigantea are lacking, hampering conservation efforts focused on both wild and ex-situ populations. A high-quality genome would also open avenues to investigate the genetic basis of the exceptionally long lifespan. Here, we produced the first chromosome-level de novo genome assembly of A. gigantea using PacBio High-Fidelity sequencing and high-throughput chromosome conformation capture (Hi-C). We produced a 2.37 Gbp assembly with a scaffold N50 of 148.6 Mbp and a resolution into 26 chromosomes. RNAseq-assisted gene model prediction identified 23,953 protein-coding genes and 1.1 Gbp of repetitive sequences. Synteny analyses among turtle genomes revealed high levels of chromosomal collinearity even among distantly related taxa. We also performed a low-coverage re-sequencing of 30 individuals from wild populations and two zoo individuals. Our genome-wide population structure analyses detected genetic population structure in the wild and identified the most likely origin of the zoo-housed individuals. The high-quality chromosome-level reference genome for A. gigantea is one of the most complete turtle genomes available. It is a powerful tool to assess the population structure in the wild population and reveal the geographic origins of ex-situ individuals relevant for genetic diversity management and rewilding efforts