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)

Social structure mediates environmental effects on group size in an obligate cooperative breeder, Suricata suricatta

Population dynamics in group-living species can be strongly affected both by features of sociality per se and by resultant population structure. To develop a mechanistic understanding of population dynamics in highly social species we need to investigate how processes within groups, processes linking groups, and external drivers act and interact to produce observed patterns. We model social group dynamics in cooperatively breeding meerkats, Suricata suricatta, paying attention to local demographic as well as dispersal processes. We use generalized additive models to describe the influence of group size, population density, and environmental conditions on demographic rates for each sex and stage, and we combine these models into predictive and individual-based simulation models of group dynamics. Short-term predictions of expected group size and simulated group trajectories over the longer term agree well with observations. Group dynamics are characterized by slow increases during the breeding season and relatively sharp declines during the pre-breeding season, particularly after dry years. We examine the demographic mechanisms responsible for environmental dependence. While individuals appear more prone to emigrate after dry years, seasons of low rainfall also cause reductions in reproductive output that produce adult-biased age distributions in the following dispersal season. Adult subordinates are much more likely to disperse or be evicted than immature individuals, and demographic structure thus contributes to crashes in group size. Our results demonstrate the role of social structure in characterizing a population's response to environmental variation. We discuss the implications of our findings for the population dynamics of cooperative breeders and population dynamics generally

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

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

Identification of the Photoreceptor Transcriptional Co-Repressor SAMD11 as Novel Cause of Autosomal Recessive Retinitis Pigmentosa

Retinitis pigmentosa (RP), the most frequent form of inherited retinal dystrophy is characterized by progressive photoreceptor degeneration. Many genes have been implicated in RP development, but several others remain to be identified. Using a combination of homozygosity mapping, whole-exome and targeted next-generation sequencing, we found a novel homozygous nonsense mutation in SAMD11 in five individuals diagnosed with adult-onset RP from two unrelated consanguineous Spanish families. SAMD11 is ortholog to the mouse major retinal SAM domain (mr-s) protein that is implicated in CRX-mediated transcriptional regulation in the retina. Accordingly, protein-protein network analysis revealed a significant interaction of SAMD11 with CRX. Immunoblotting analysis confirmed strong expression of SAMD11 in human retina. Immunolocalization studies revealed SAMD11 was detected in the three nuclear layers of the human retina and interestingly differential expression between cone and rod photoreceptors was observed. Our study strongly implicates SAMD11 as novel cause of RP playing an important role in the pathogenesis of human degeneration of photoreceptors.This work was supported by several grants from the Spanish Centre for Biomedical Network Research on Rare Diseases (CIBERER)(06/07/0036), Instituto de Salud Carlos III (ISCIII, Spanish Ministry of Health)/FEDER, including FIS (PI013/00226) and RETICS (RD09/0076/00101 and RD12/0034/0010), Ministry of Economy and Competitiveness (MINECO), including FEDER (BFU2012-36845), and BIO2011-27069, Conselleria de Educació of the Valencia Community (PROMETEOII/2014/025), Spanish National Organization of the Blind (ONCE) and the Spanish Fighting Blindness Foundation (FUNDALUCE). M.C. was sponsored by the Miguel Servet Program for Researchers in the Spanish National Health Service (CP12/03256) and RSA by Sara Borrel Postdoctoral Program (CD12/00676), both from the ISCIII/FEDER. A.A-F. was sponsored by CIBERER, RPC is supported by Fundación Conchita Rábago (FCR), L.C is sponsored by RETICS (RD12/0034/0010) from ISCIII and L.d.S. was supported by CAPES Foundation, Ministry of Education of Brazil

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

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