ORCID Profile
0000-0002-0049-9767
Current Organisation
Norwegian University of Science and Technology
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Publisher: Wiley
Date: 26-09-2023
Publisher: Wiley
Date: 27-10-2021
Abstract: An increasing number of empirical studies aim to quantify in idual variation in demographic parameters because these patterns are key for evolutionary and ecological processes. Advanced approaches to estimate in idual heterogeneity are now using a multivariate normal distribution with correlated in idual random effects to account for the latent correlations among different demographic parameters occurring within in iduals. Despite the frequent use of multivariate mixed models, we lack an assessment of their reliability when applied to Bernoulli variables. Using simulations, we estimated the reliability of multivariate mixed effect models for estimating correlated fixed in idual heterogeneity in demographic parameters modelled with a Bernoulli distribution. We evaluated both bias and precision of the estimates across a range of scenarios that investigate the effects of life‐history strategy, levels of in idual heterogeneity and presence of temporal variation and state dependence. We also compared estimates across different s ling designs to assess the importance of study duration, number of in iduals monitored and detection probability. In many simulated scenarios, the estimates for the correlated random effects were biased and imprecise, which highlight the challenge in estimating correlated random effects for Bernoulli variables. The amount of fixed among‐in idual heterogeneity was frequently overestimated, and the absolute value of the correlation between random effects was almost always underestimated. Simulations also showed contrasting performances of mixed models depending on the scenario considered. Generally, estimation bias decreases and precision increases with slower pace of life, large fixed in idual heterogeneity and large s le size. We provide guidelines for the empirical investigation of in idual heterogeneity using correlated random effects according to the life‐history strategy of the species, as well as, the volume and structure of the data available to the researcher. Caution is warranted when interpreting results regarding correlated in idual random effects in demographic parameters modelled with a Bernoulli distribution. Because bias varies with s ling design and life history, comparisons of in idual heterogeneity among species is challenging. The issue addressed here is not specific to demography, making this warning relevant for all research areas, including behavioural and evolutionary studies.
Publisher: Wiley
Date: 04-12-2020
Abstract: The integration and synthesis of the data in different areas of science is drastically slowed and hindered by a lack of standards and networking programmes. Long‐term studies of in idually marked animals are not an exception. These studies are especially important as instrumental for understanding evolutionary and ecological processes in the wild. Furthermore, their number and global distribution provides a unique opportunity to assess the generality of patterns and to address broad‐scale global issues (e.g. climate change). To solve data integration issues and enable a new scale of ecological and evolutionary research based on long‐term studies of birds, we have created the SPI‐Birds Network and Database ( www.spibirds.org )—a large‐scale initiative that connects data from, and researchers working on, studies of wild populations of in idually recognizable (usually ringed) birds. Within year and a half since the establishment, SPI‐Birds has recruited over 120 members, and currently hosts data on almost 1.5 million in idual birds collected in 80 populations over 2,000 cumulative years, and counting. SPI‐Birds acts as a data hub and a catalogue of studied populations. It prevents data loss, secures easy data finding, use and integration and thus facilitates collaboration and synthesis. We provide community‐derived data and meta‐data standards and improve data integrity guided by the principles of Findable, Accessible, Interoperable and Reusable (FAIR), and aligned with the existing metadata languages (e.g. ecological meta‐data language). The encouraging community involvement stems from SPI‐Bird's decentralized approach: research groups retain full control over data use and their way of data management, while SPI‐Birds creates tailored pipelines to convert each unique data format into a standard format. We outline the lessons learned, so that other communities (e.g. those working on other taxa) can adapt our successful model. Creating community‐specific hubs (such as ours, COMADRE for animal demography, etc.) will aid much‐needed large‐scale ecological data integration.
Publisher: Wiley
Date: 24-05-2022
DOI: 10.1111/ELE.14026
Abstract: Temporal correlations among demographic parameters can strongly influence population dynamics. Our empirical knowledge, however, is very limited regarding the direction and the magnitude of these correlations and how they vary among demographic parameters and species’ life histories. Here, we use long‐term demographic data from 15 bird and mammal species with contrasting pace of life to quantify correlation patterns among five key demographic parameters: juvenile and adult survival, reproductive probability, reproductive success and productivity. Correlations among demographic parameters were ubiquitous, more frequently positive than negative, but strongly differed across species. Correlations did not markedly change along the slow‐fast continuum of life histories, suggesting that they were more strongly driven by ecological than evolutionary factors. As positive temporal demographic correlations decrease the mean of the long‐run population growth rate, the common practice of ignoring temporal correlations in population models could lead to the underestimation of extinction risks in most species.
Publisher: Wiley
Date: 22-02-2023
DOI: 10.1111/JEB.14164
Abstract: An organism's energy budget is strongly related to resource consumption, performance, and fitness. Hence, understanding the evolution of key energetic traits, such as basal metabolic rate (BMR), in natural populations is central for understanding life‐history evolution and ecological processes. Here we used quantitative genetic analyses to study evolutionary potential of BMR in two insular populations of the house sparrow ( Passer domesticus ). We obtained measurements of BMR and body mass ( M b ) from 911 house sparrows on the islands of Leka and Vega along the coast of Norway. These two populations were the source populations for translocations to create an additional third, admixed ‘common garden’ population in 2012. With the use of a novel genetic group animal model concomitant with a genetically determined pedigree, we differentiate genetic and environmental sources of variation, thereby providing insight into the effects of spatial population structure on evolutionary potential. We found that the evolutionary potential of BMR was similar in the two source populations, whereas the Vega population had a somewhat higher evolutionary potential of M b than the Leka population. BMR was genetically correlated with M b in both populations, and the conditional evolutionary potential of BMR (independent of body mass) was 41% (Leka) and 53% (Vega) lower than unconditional estimates. Overall, our results show that there is potential for BMR to evolve independently of M b , but that selection on BMR and/or M b may have different evolutionary consequences in different populations of the same species.
Publisher: Wiley
Date: 21-12-2022
DOI: 10.1002/ECY.3908
Abstract: Identifying the environmental drivers of variation in fitness‐related traits is a central objective in ecology and evolutionary biology. Temporal fluctuations of these environmental drivers are often synchronized at large spatial scales. Yet, whether synchronous environmental conditions can generate spatial synchrony in fitness‐related trait values (i.e., correlated temporal trait fluctuations across populations) is poorly understood. Using data from long‐term monitored populations of blue tits ( Cyanistes caeruleus , n = 31), great tits ( Parus major , n = 35), and pied flycatchers ( Ficedula hypoleuca , n = 20) across Europe, we assessed the influence of two local climatic variables (mean temperature and mean precipitation in February–May) on spatial synchrony in three fitness‐related traits: laying date, clutch size, and fledgling number. We found a high degree of spatial synchrony in laying date but a lower degree in clutch size and fledgling number for each species. Temperature strongly influenced spatial synchrony in laying date for resident blue tits and great tits but not for migratory pied flycatchers. This is a relevant finding in the context of environmental impacts on populations because spatial synchrony in fitness‐related trait values among populations may influence fluctuations in vital rates or population abundances. If environmentally induced spatial synchrony in fitness‐related traits increases the spatial synchrony in vital rates or population abundances, this will ultimately increase the risk of extinction for populations and species. Assessing how environmental conditions influence spatiotemporal variation in trait values improves our mechanistic understanding of environmental impacts on populations.
No related grants have been discovered for Bernt-Erik Sæther.