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opencc-by-4.0Dec 2023View details →

Fig. 4 in Reduction Of The Breeding Population Of The Rook, Corvus Frugilegus (Aves, Corvidae), In Ukraine: The Example Of The Eastern Part Of The Kyiv Region

Fig. 4. Standard Deviational Ellipses for the location of rook colonies and their number in the research area in 1983–1985 and 2021.

opencc-by-4.0Dec 2023View details →

Fig. 1 in Reduction Of The Breeding Population Of The Rook, Corvus Frugilegus (Aves, Corvidae), In Ukraine: The Example Of The Eastern Part Of The Kyiv Region

Fig. 1. Geographical location of the study area. The circle is a research territory with an area of 1850 km².

EGMP 2023 Offtake Assessment for Finland and NW Russia / Sweden, Denmark and Germany population of Taiga Bean Goose (former Central MU)

Data and model files for the 2023 EGMP offtake assessment for Finland and NW Russia / Sweden, Denmark and Germany population of Taiga Bean Goose (former Central MU). https://gitlab.com/aewa-egmp/taiga-bean-goose/harvest-assessment-2023

EGMP 2023 Offtake Assessment for the Svalbard Population of Pink-footed Goose

Data and model files for the 2023 EGMP offtake assessment of the Svalbard Population of Pink-footed Goose. https://gitlab.com/aewa-egmp/svalbard-population-of-pink-footed-goose/harvest-assessment-2023

opencc-by-4.0Jun 2023View details →

Data for 'Population density affects sexual selection in an insect model'

Data set (.csv file), analysis code (.R file) and readme (.txt file giving details for dataset and code) accompanying the publication 'Population density affects sexual selection in an insect model' (Winkler L, Eilhardt R, Janicke T, 2023).

opencc-by-4.0May 2020View details →

Abb. 7. Entwicklung der Orthetrum coerulescens-Population des Chuderriets von 2010 bis 2019 in Als Larvenhabitate von Orthetrum coerulescens (Odonata: Libellulidae) im Hinblick auf sporadische Sommertrockenheit optimierte Flachmoorgräben

Abb. 7. Entwicklung der Orthetrum coerulescens-Population des Chuderriets von 2010 bis 2019. Ausgezählt wurden die Grabenabschnitte (Strecken) 1–5 bei insgesamt 113 Kontrollgängen (K) jeweils während der Schlupf- und Flugperiode. BS = Anzahl besiedelte Grabenstrecken, RS =Anzahl Grabenstrecken mit Reproduktionsnachweisen, M × ⅒ = Anzahl territoriale Männchen mal 10–1.

Data from: Partitioning variance in population growth for models with environmental and demographic stochasticity

<ol> <li>How demographic factors lead to variation or change in growth rates can be investigated using life table response experiments (LTRE) based on structured population models. Traditionally, LTREs focused on decomposing the asymptotic growth rate, but more recently decompositions of annual 'realized' growth rates have gained in popularity.</li> <li>Realized LTREs have been used particularly to understand how variation in vital rates translates into variation in growth for populations under long-term study. For these, complete population models may be constructed by combining data in an integrated population model (IPM). IPMs are also used to investigate how temporal variation in environmental drivers affect vital rates. Such investigations have usually come down to estimating covariate coefficients for the effects of environmental variables on vital rates, but formal ways of assessing how they lead to variation in growth rates have been lacking. </li> <li>We extend realized LTREs in two ways. First, we further partition the contributions from vital rates into contributions from temporally varying factors that affect them. The decomposition allows us to compare the resultant effect on the growth rate of different environmental factors that may each act via multiple vital rates. Second, we show how realized growth rates can be decomposed into separate components from environmental and demographic stochasticity. The latter is typically omitted in LTRE analyses.</li> <li>We illustrate how to use the approach in an IPM for data from a 26-year study on northern wheatears (Oenanthe oenanthe), a migratory passerine bird breeding in an agricultural landscape. For this population, consisting of around 50–120 breeding pairs per year, we partition variation in realized growth rates into environmental contributions from temperature, rainfall, population density, and unexplained random variation via multiple vital rates, and from demographic stochasticity.</li> <li>The case study suggests that variation in first-year survival via the random component, and adult survival via temperature are two main factors behind environmental variation in growth rates. More than half of the variation in growth rates is suggested to come from demographic stochasticity, demonstrating the importance of this factor for populations of moderate size.</li> </ol>

Consequences of cross-season demographic correlations for population viability

Demographic correlations are pervasive in wildlife populations and can represent important secondary drivers of population growth. Empirical evidence suggests that correlations are in general positive for long-lived species, but little is known about the degree of variation among spatially segregated populations of the same species in relation to environmental conditions. We assessed the relative importance of two cross-season correlations in survival and productivity, for three Atlantic puffin (Fratercula arctica) populations with contrasting population trajectories and non-overlapping year-round distributions. The two correlations reflected either a relationship between adult survival prior to breeding on productivity or a relationship between productivity and adult survival in the subsequent year. Demographic rates and their correlations were estimated with an integrated population model, and their respective contributions to variation in population growth were calculated using a transient life table response experiment. For all three populations, demographic correlations were positive at both time lags, although their strength differed. Given the difference in year-round distributions of these populations, this variation in the strength of population-level demographic correlations points to environmental conditions as an important driver of demographic variation through life-history constraints. Consequently, the contributions of variances and correlations in demographic rates to population growth rates differed among puffin populations, which has implications for – particularly small – populations' viability under environmental change as positive correlations tend to reduce the stochastic population growth rate.

EuroSAT Model Zoo: A Dataset of Diverse Populations of Neural Network Models - EuroSAT

Abstract In the last years, neural networks have evolved from laboratory environments to the state-of-the-art for many real-world problems. Our hypothesis is that neural network models (i.e., their weights and biases) evolve on unique, smooth trajectories in weight space during training. Following, a population of such neural network models (refereed to as “model zoo”) would form topological structures in weight space. We think that the geometry, curvature and smoothness of these structures contain information about the state of training and can be reveal latent properties of individual models. With such zoos, one could investigate novel approaches for (i) model analysis, (ii) discover unknown learning dynamics, (iii) learn rich representations of such populations, or (iv) exploit the model zoos for generative modelling of neural network weights and biases. Unfortunately, the lack of standardized model zoos and available benchmarks significantly increases the friction for further research about populations of neural networks. With this work, we publish a novel dataset of model zoos containing systematically generated and diverse populations of neural network models for further research. In total the proposed model zoo dataset is based on six image datasets, consist of 27 model zoos with varying hyperparameter combinations are generated and includes 50’360 unique neural network models resulting in over 2’585’360 collected model states. Additionally, to the model zoo data we provide an in-depth analysis of the zoos and provide benchmarks for multiple downstream tasks as mentioned before. Dataset This dataset is part of a larger collection of model zoos and contains the zoos trained on EuroSAT. All zoos with extensive information and code can be found at <a href="http://www.modelzoos.cc">www.modelzoos.cc</a>. This repository contains two types of model populations: the base model zoo ("eurosat_cnn_kaiming_uniform.zip"), as well as a collection of sparsified model zoos (filenames ending in "magn_XX.zip" or "ard.zip"). Zoos are trained with CNN models in configurations varying the seed only (seed), and sparsification is done through magnitude-based weight pruning ("magn_XX.zip") or  varational dropout ("ard.zip"). For more information on the zoos and code to access and use the zoos, please see <a href="http://www.modelzoos.cc">www.modelzoos.cc</a>.

Godard et al. D. antillarum populations STJ 2017-2023

Average number of diadema antillarum/m2 at nine fringing reef sites and three mangrove sites in STJ 2017-2023

Fig. 7 in Comparative analysis of the population structure of Crematogaster subdentata and Lasius neglectus in the primary and secondary ranges (Hymenoptera: Formicidae)

Fig. 7 – Comparison of the sizes of foraging areas of polycalic colonies and supercolonies of Crematogaster subdentata and Lasius neglectus in the primary and secondary ranges: a, Crimea, b, – Rostov-on-Don, c, Tashkent.

Fig. 6 in Comparative analysis of the population structure of Crematogaster subdentata and Lasius neglectus in the primary and secondary ranges (Hymenoptera: Formicidae)

Fig. 6 – Average values of the average size of the foraging areas of Crematogaster subdentata (a) and Lasius neglectus (b) in the primary and secondary ranges. C – Crimea, T – Tashkent, R – Rostov-on-Don.

Fig. 5 in Comparative analysis of the population structure of Crematogaster subdentata and Lasius neglectus in the primary and secondary ranges (Hymenoptera: Formicidae)

Fig. 5 – Relation of tree and shrub species visited by Crematogaster subdentata (a, Crimea, b, Rostov-on-Don, c, Tashkent) and Lasius neglectus (d, – Crimea, e, – Rostov-on-Don, f, – Tashkent). Trees: Ac – Acer sp., Ah – Aesculus hippocastanum, Aj – Albizia julibrissin, Al – Ailanthus altissima, An – Acer negundo, Cl – Cedrus libani, Co – Cydonia oblonga, Cs – Cupressus sempervirens, Ea – Elaeagnus angustifolia, Fe – Fraxinus excelsior, Fr – Fraxinus sp., Gl – Gleditsia triacanta, Jr – Juglans regia, M – Morus sp., Md – Malus domestica, Mn – Morus nigra, Pa – Prunus americana, Pb - Pinus brutia, Pc – Prunus cerasus, Pd – Prunus domestica, Pi – Pinus pallasiana, Pp – Populus niger, Po – Populus alba, Pr – Prunus cerasifera, Ps – Prunus spinosa, Py - Populus pyramidalis, Ra – Robinia pseudoacacia, Sa – Salix sp., Sj – Styphnolobium japonicum, Tl – Tilia sp., Ul – Ulmus sp., Us – Ulmus laevis.

Fig. 1 in Comparative analysis of the population structure of Crematogaster subdentata and Lasius neglectus in the primary and secondary ranges (Hymenoptera: Formicidae)

Fig. 1 – Distribution of Crematogaster subdentata and Lasius neglectus in Tashkent C. subdentata, polycalic colonies, C. subdentata, monocalic colonies, L. neglectus,> 20 nests per 100 m, L. neglectus, 10-20 nests per 100 m, L. neglectus, <10 nests per 100 m.

Fig. 2 in Comparative analysis of the population structure of Crematogaster subdentata and Lasius neglectus in the primary and secondary ranges (Hymenoptera: Formicidae)

Fig. 2 – Scheme of the foraging areas of Lasius neglectus in Rostov-on-Don species; trees: Pc – Prunus cerasus, Ps – Prunus spinosa, Ul – Ulmus sp.

Fig. 4 in Comparative analysis of the population structure of Crematogaster subdentata and Lasius neglectus in the primary and secondary ranges (Hymenoptera: Formicidae)

Fig. 4 – Scheme of the foraging areas of Crematogaster subdentata in Crimea (A) and Tashkent (B) large accessible nests of C. subdentata in buildings and outside; inaccessible nests of C. subdentata in buildings; trees: Co – Cydonia oblonga, Jr – Juglans regia, M – Morus sp., Md – Malus domestica, Mn – Morus nigra, Pa – Prunus americana, Pd – Prunus domestica.

Data and codes from "How does dispersal shape the genetic structure of animal populations in European cities? A simulation approach"

Codes and data used for "Savary et al. How does dispersal shape the genetic structure of animal populations in European cities? A simulation approach".

All data for the preprint Population genetics of Glossina palpalis gambiensis in the sleeping sickness focus of Boffa (Guinea) before and after eight years of vector control: no effect of control despite a significant decrease of human exposure to the disease

Data set for the paper titled "Population genetics of Glossina palpalis gambiensis in the sleeping sickness focus of Boffa (Guinea) before and after eight years of vector control: no effect of control despite a significant decrease of human exposure to the disease"

Data from: Personality determines population-level effects of microplastics consumption in a modelled population of stream-dwelling rainbow trout (Oncorhynchus mykiss)

Microplastics in freshwater habitats are consumed by fish, including stream-dwelling salmonids, which can alter food consumption or negatively affect swimming and foraging behaviour. As population-level effects are largely unknown, a simulated population of stream-dwelling rainbow trout (Oncorhynchus mykiss) was created using the agent-based model 'inSTREAM 7' to model population-level effects (biomass) of behavioural changes caused by microplastics consumption. Individual fish were assigned all possible combinations of two personality traits (dominance, boldness/shyness), and consumed microplastics while foraging, while their abundance, body size, and microplastics consumption were tracked for three different life stages (fry, juvenile, adult) for a 10-year simulation period. Three additive scenarios were explored: a low-impact scenario with decreased food consumption, a medium-impact scenario with added lower swimming speed, and a high-impact scenario with added reductions in prey capture efficiency. Each was tested with microplastics concentrations of 0%, 1% (i.e., current levels), and 3% (i.e., future levels) of drift food. Overall, microplastics consumption did not strongly affect trout population abundance. Dominant adult trout consumed disproportionally more microplastics than all other fish, especially with higher microplastics concentrations. Different personality types were affected differently in the three scenarios: dominant and bold adults were smaller when food consumption was reduced, shy and subordinate adults were smaller when swimming speed was lowered, and all dominant adults, regardless of boldness, were smaller when foraging efficiency was impeded, with dominant and bold fry also less abundant in this scenario. However, effects on fish body size were only found with microplastic concentrations of 3%, indicating these outcomes can be prevented, as current levels of microplastics pollution are unlikely to affect salmonid body size. Nevertheless, microplastics ingestion represents an additional stressor that may potentially interact with a myriad of anthropogenic impacts that already affect wild salmonid populations.

Population demographic history and evolutionary rescue: Influence of a bottleneck event

Rapid environmental change presents a significant challenge to the persistence of natural populations. Rapid adaptation that increases population growth, enabling populations that declined following severe environmental change to grow and avoid extinction, is called evolutionary rescue. Numerous studies have shown that evolutionary rescue can indeed prevent extinction. Here, we extend those results by considering the demographic history of populations. To evaluate how demographic history influences evolutionary rescue, we created 80 populations of red flour beetle, Tribolium castaneum, with three classes of demographic history: diverse populations that did not experience a bottleneck, and populations that experienced either an intermediate or a strong bottleneck. We subjected these populations to a new and challenging environment for six discrete generations and tracked extinction and population size. Populations that did not experience a bottleneck in their demographic history avoided extinction entirely, while more than 20% of populations that experienced an intermediate or strong bottleneck went extinct. Similarly, among the extant populations at the end of the experiment, adaptation increased the growth rate in the novel environment the most for populations that had not experienced a bottleneck in their history. Taken together, these results highlight the importance of considering the demographic history of populations to make useful and effective conservation decisions and management strategies for populations experiencing environmental change that pushes them toward extinction.