Estimation of changes in abundances and densities is essential for the research, management, and conservation of animal populations. Recently, technological advances have facilitated the surveillance of animal populations through the adoption of passive sensors, such as camera traps (CT). Several methods, including the random encounter model (REM), have been developed for estimating densities of unmarked populations but require additional field work. Hierarchical abundance models, such as the N-mixture model (NMM), can estimate densities without performing additional fieldwork but do not explicitly estimate the area effectively sampled. This obscures the interpretation of its densities and requires its users to focus on relative measures of abundance instead. We compare relative trends in density/ abundance for three species (wild boar, red deer, and fox) based on the REM and NMM. The NMM applied here is adapted to overcome two issues potentially leading to poor abundance estimates: (i) we specify a joint observation model, based on a beta distribution, for all species within a community to strengthen the inference on infrequently detected species, and (ii) we model species-specific counts as a Poisson process, relaxing the assumption that each individual can only be detected once per survey. We reveal that NMM and REM provided density estimates in the same order of magnitude for wild boar, but not for foxes and red deer. Assuming a Poisson detection process in the NMM was important to control for inflation of density estimates for frequently detected species. Both methods correctly identified species ranking of abundance/density but did not always agree on relative ranks of yearly estimates within a single population, nor on its linear population trends. Our results suggest that relative population trends are better preserved between NMM and REM compared to absolute densities. Thus practitioners working with counts-only data should resort to relative abundances, rather than absolute densities.

Vairimorpha (=Nosema) ceranae is a widespread pollinator parasite that commonly infects honeybees and wild pollinators, including bumblebees. Honeybees are highly competent V. ceranae hosts and previous work in experimental flight cages suggests V. ceranae can be transmitted during visitation to shared flowers. However, the relationship between floral visitation in the natural environment and the prevalence of V. ceranae among multiple bee species has not been explored. Here, we analyzed the number and duration of pollinator visits to particular components of squash flowers—including the petals, stamen, and nectary—at six farms in southeastern Michigan, USA. We also determined the prevalence of V. ceranae in honeybees and bumblebees at each site. Our results showed that more honeybee flower contacts and longer duration of contacts with pollen and nectar was linked with greater V. ceranae prevalence in bumblebees. Honeybee visitation patterns appear to have a disproportionately large impact on V. ceranae prevalence in bumblebees even though honeybees are not the most frequent flower visitors. Floral visitation by other pollinators was not linked with V. ceranae prevalence in bumblebees. Further, V. ceranae prevalence in honeybees was unaffected by floral visitation behaviors by any pollinator species. These results suggest that honeybee visitation behaviors on shared floral resources may be an important contributor to increased V. ceranae spillover to bumblebees in the field. Understanding how V. ceranae infection risk is influenced by pollinator behavior in the shared floral landscape is critical for reducing parasite spillover into declining native bee populations.

Dispersal is a fundamental process in evolution and ecology. Due to the predominant role of flight in bird movement, their dispersal capabilities can be estimated from their flight morphology. Most predictors of flight efficiency require an estimate of the total wing area, but the existing methods for estimating wing area are multi-stepped and prone to compounding error. Here, we validated a new method for estimating the total wing area that requires only the measurement of the wingspan plus two measurements from the folded wings of study skin specimens: wing length and secondary length. We demonstrate that the new folded-wing method estimates total wing area with high precision across a variety of avian groups and wing shapes. In addition, the new method performs as well as the old method when used to estimate natal dispersal distances of North American birds. The folded-wing method will allow for estimates of the total wing to be readily obtained from thousands of specimens in ornithological collections, thus providing critical information for studies of flight and dispersal in birds.

Hybridization is a natural process whereby two diverging evolutionary lineages reproduce and create offspring of mixed ancestry. Differences in mating systems (e.g., self-fertilization and outcrossing) are expected to affect the direction and extent of hybridization and introgression in hybrid zones. Among other factors, selfers and outcrossers are expected to differ in their mutation loads. This has been studied both theoretically and empirically; however, conflicting predictions have been made on the effects mutation loads of parental species with different mating systems can have on the genomic composition of hybrids. Here we develop a multi-locus, selective model to study how the different mutation load built up in selfers and outcrossers as a result of selective interference and homozygosity impact the long-term genetic composition of hybrid populations. Notably, our results emphasize that genes from the parental population with lesser mutation load get rapidly over-represented in hybrid genomes, regardless of the hybrids own mating system. When recombination tends to be more important than mutation, outcrossers’ genomes tend to be of higher quality and prevail. When recombination is small, however, selfers’ genomes may reach higher quality than outcrossers’ genomes and prevail. Taken together these results provide concrete insights into one of the multiple factors influencing hybrid genome composition and introgression patterns in hybrid zones with species containing species with different mating systems.

Rising ocean temperatures are threatening marine species and populations worldwide, and ectothermic taxa are particularly vulnerable to warming. Echinoderms are an ecologically important phylum of marine ectotherms and shifts in their population dynamics can have profound impacts on the marine environment. The effects of warming on echinoderms are highly variable across controlled laboratory-based studies. Accordingly, synthesis of these studies will facilitate the better understanding of broad patterns in responses of echinoderms to ocean warming. Herein, a meta-analysis incorporating the results of 85 studies (710 individual responses) is presented, exploring the effects of warming on various performance predictors. The mean responses of echinoderms to all magnitudes of warming were compared across multiple biological responses, ontogenetic life stages, taxonomic classes, and regions, facilitated by multivariate linear mixed effects models. Further models were conducted which only incorporated responses to warming greater than the projected end-of-century mean annual temperatures at the collection sites. This meta-analysis provides evidence that ocean warming will generally accelerate metabolic rate (+ 32%) and reduce survival (– 35%) in echinoderms, and echinoderms from sub-tropical (– 9%) and tropical (– 8%) regions will be the most vulnerable. The relatively high vulnerability of echinoderm larvae to warming (– 20%) indicates that this life stage may be a significant developmental bottleneck in the near-future, likely reducing successful recruitment into populations. Furthermore, asteroids appear to be the class of echinoderms that are most negatively affected by elevated temperature (– 30%). When considering only responses to magnitudes of warming representative of end-of-century climate change projections, the negative impacts on asteroids, tropical species and juveniles were exacerbated (– 51%, – 34%, and – 40% respectively). The results of these analyses enable better predictions of how keystone and invasive echinoderm species may perform in a warmer ocean, and the possible consequences for populations, communities, and ecosystems.

Soil fungal community plays an important role in forest ecosystems, and forest secondary succession is a crucial driver of soil fungal community. However, the driving factors of fungal community and function during temperate forest succession and their potential impact on succession processes are poorly understood. In this study, we investigated the dynamics of the soil fungal community in three temperate forest secondary successional stages (shrublands, coniferous forests, and deciduous broadleaf forests) using high-throughput DNA sequencing coupled with functional prediction via the FUNGuild database. We found that fungal community richness, α-diversity, and evenness decreased significantly during the succession process. Soil available phosphorus and nitrate nitrogen decreased significantly after initial succession occurred, and redundancy analysis showed that both were significant predictors of soil fungal community structure. Among functional groups, fungal saprotrophs as well as pathotrophs represented by plant pathogens were significantly enriched in the early-successional stage, while fungal symbiotrophs represented by ectomycorrhiza were significantly increased in the late-successional stage. The abundance of both saprotroph and pathotroph fungal guilds was positively correlated with soil nitrate nitrogen and available phosphorus content. Ectomycorrhizal fungi were negatively correlated with nitrate nitrogen and available phosphorus content and positively correlated with ammonium nitrogen content. These results indicated that the dynamics of fungal community and function reflected the changes in nitrogen and phosphorus availability caused by the secondary succession of temperate forests. The fungal plant pathogen accumulated in the early-successional stage and ectomycorrhizal fungi accumulated in the late-successional stage may have a potential role in promoting forest succession. These findings contribute to a better understanding of the response of soil fungal communities to the secondary forest succession process and highlight the importance of fungal communities during temperate forest succession.

Variation in fitness components can be linked in some cases to variation of key traits. Metric traits that lie at the intersection of development, defense, and ecological interactions may be expected to experience strong environmental selection, informing our understanding of evolutionary and ecological processes. Here, we use quantitative genetic and population genomic methods to investigate disease dynamics in hybrid and non-hybrid populations. We focus our investigation on morphological and ecophysiological traits which inform our understanding of physiology, growth, and defense against a pathogen. In particular, we investigate stomata, microscopic pores on the surface of a leaf which regulate gas exhange during photosynthesis and are sites of entry for various plant pathogens. Stomatal patterning traits were highly predictive of disease risk. Admixture mapping identified a polygenic basis of disease resistance. Candidate genes for stomatal and disease resistance map to the same genomic regions, and are experienceing positive selection. Genes with functions for guard cell homeostasis, the plant immune system, components of constitutive defenses, and growth related transcription factors were identified. Our results indicate positive selection is filtering genetic variance from one of the parental species maladpated to a novel pathogen, and changing suites of stomatal traits which contribute to disease variation in natural populations.

Climate change and shifting environmental conditions can allow pathogens to spread into previously unburdened areas. For plant pathogens, this dynamic has the potential to disrupt natural ecosystem equilibria and human agriculture, making predicting plant pathogen range shifts an increasingly important enterprise. Although such predictions will hinge on an accurate understanding of the determinants of pathogen range – namely the environmental, geographical, and host range characteristics that modulate local pathogen habitation – few studies to date have probed these in natural plant populations. Here, we characterize range determinants for the model system of Lewis flax (Linum Lewisii) and its pathogen, flax rust (Melamspora lini), in the Rocky Mountains. Transect surveys were performed to assess three relationships: i) the effect of geographical features – elevation, slope aspect, slope grade, and land-cover – on flax presence and density, ii) the effect of geographical features on flax rust presence and prevalence, and iii) the effects of flax’s local population density and metapopulation structure on flax rust presence and prevalence. We found that flax population density, but not host metapopulation structure, influences the distribution of flax rust. Additionally, we showed that, while the distribution of flax was broadly constrained to a relatively narrow range of geographical and resulting environmental features, flax rust was evenly distributed across the full range of settings measured. These results indicate that a warming environment, which is expected to modulate such features, may restrict the optimal range of the plant more so than that of its pathogen. Importantly, our results also suggest that even if flax shifts its spatial range to escape increasing climatic pressures, flax rust will not face any significant barriers to track this movement.

Illumination of species diversity and their distribution is key to evolution, genetics and conservation. The genus of Sibynophis is a group of rare snakes with less attentions. Based on more extensive sampling, we use both mitochondrial fragments and nuclear gene to explore the species diversity of the species of Sibynophis occurring in China. The results showed that S. c. miyiensis is a synonym of S. c. grahami, and S. c. grahami should be gave a specific rank as S. graham. Sibynophis triangularis was uncovered to be new to China and Myanmar. On basis of our specimens and molecular phylogeny results, the species distribution boundaries of each Chinese species were redefined.

Interdisciplinary teams are on the rise as scientists attempt to address complex environmental issues. While the benefits of Team Science approaches are clear, researchers often struggle with its implementation, particularly for new team members. The challenges of large projects often weigh on the most vulnerable members of a team: trainees, including undergraduate students, graduate students, and post-doctoral researchers. Trainees on big projects have to navigate their role on the team, with learning project policies, procedures, and goals, all while also training in key scientific tasks such as co-authoring papers. To address these challenges, we created and participated in a project-specific, graduate-level Team Science course. The purposes of this course were to: (1) introduce students to the goals of the project, (2) build trainees’ understanding of how big projects operate, and (3) allow trainees to explore how their research interests dovetailed with the overall project. Additionally, trainees received training regarding: (1) diversity, equity & inclusion, (2) giving and receiving feedback, and (3) effective communication. Onboarding through the Team Science course cultivated psychological safety and a collaborative student community across disciplines and institutions. Thus, we recommend a Team Science course for onboarding students to big projects to help students establish the skills necessary for collaborative research. Project-based Team Science classes can benefit student advancement, enhance the productivity of the project, and accelerate the discovery of solutions to ecological issues.

The Neretva dwarf goby Orsinigobius croaticus (Gobiiformes, Gobionellidae) is an endemic fish native to the freshwaters of the Adriatic Basin in Croatia and Bosnia and Herzegovina. Due to its limited distribution range, specific karst habitat and endangered status, laboratory studies on reproductive biology are scarce. We investigated the sound production and acoustic behaviour of this species during reproductive intersexual laboratory encounters. We performed dissection and micro-computed tomography (μCT) scanning of the pectoral girdle to explore the anatomy of its putative sound producing mechanism. To study interspecific acoustic differences and determine whether acoustic features can discriminate among species, comparative analysis was conducted on sounds produced by closely related soniferous sand gobies. Our results indicate that males of the O. croaticus emit pulsatile sounds composed of a variable number of short (~ 15 ms) consecutive pulses when interacting with females, usually during the pre-spawning phase in the nest, but also during courtship outside the nest. Pulsatile sounds were low-frequency and short pulse trains (~ 140 Hz, < 1000 ms), and spectro-temporal parameters were correlated with physical traits and water temperature. Male visual behaviour rate was higher when co-occurring with sounds and females entered the male’s nest significantly more frequently when sounds were present. Male sound production was accompanied by movements such as head thrust and fin spreading. μCT scans and dissections suggest that O. croaticus shares certain anatomical similarities of the pectoral girdle (osseous elements and arrangement of levator pectoralis muscles) to previously studied sand gobies. Multivariate comparisons, using sounds produced by eight soniferous European sand gobies, effectively distinguished soniferous (and sympatric) species based on acoustic properties. Discrimination success decreased when temperature-dependent features (sound duration and pulse repetition rate) were excluded from analysis. Therefore, we suggest both spectral and temporal features are important for acoustic differentiation of sand gobies.

The plants’ geographical distribution is affected by natural or human-induced climate change. Numerous studies at both the global and regional level currently focus on the potential changes in plant distribution areas. Ecological niche modeling can help predict the likely distribution of species according to environmental variables under different climate scenarios. In this study, we predicted the potential geographic distributions of Quercus ilex L. (holm oak), a keystone species of the Mediterranean ecosystem, for the Last Interglacial period (LIG: ~120 Ka), the Last Glacial Maximum (LGM: ~22 Ka), mid-Holocene (MH: ~6 Ka), and future climate scenarios (Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios) for years 2050-2070 obtained from CCSM4 and MIROC-ESM global climate scenarios respectively. The models were produced with algorithms from the R-package “biomod2” and assessed by AUC of the Receiver Operating Characteristic plot and True Skill Statistics. Apart from BIOCLIM (SRE), all model algorithms performed similarly and produced projections that are supported by good evaluation scores, although Random Forest (RF) slightly outperformed all the others. Additionally, distribution maps generated for the past period were validated through a comparison with pollen data acquired from the Neotoma Pollen Database. The results revealed that southern areas of the Mediterranean Basin, particularly coastal regions, served as long-term refugia for Q. ilex, which was supported by fossil pollen data. Furthermore, the models suggest long term refugia role for Anatolia and we argue that Anatolia may have served as a founding population for the species. Future climate scenarios indicated that Q. ilex distribution varied by region, with some areas experiencing range contractions and others range expands. This study provides significant insights into the vulnerability of the Q. ilex to future climate change in the Mediterranean ecosystem and highlights the crucial role of Anatolia in the species’ historical distribution.

A general reaction norm model of any order can be formulated as a linear mixed model. From this follows that estimates of mean phenotypic traits in a population (fixed effects), and predictions of individual additive genetic deviations from mean reaction norm parameter values (random effects), can be found from the best linear unbiased predictions (BLUP) equation in matrix form. The resulting BLUP model is dynamical in the sense that the incidence matrix varies with time. This leads to a straightforward and multivariate alternative to infinite-dimensional and random regression modeling of reaction norms. Based on such a BLUP model, the within-generation changes in predicted mean reaction norm parameter values can be found by use of the Robertson-Price identity, applied on the predicted random effects. From this follows that the between-generation change in the mean values are found from Robertson’s secondary theorem of natural selection, applied on the predicted random effects. This explains why and to which extent the variances of BLUP random effects are underestimated, which is a well-known observation. The dynamical BLUP model will thus produce the mean reaction norms over time, which makes it possible to disentangle the microevolutionary and plasticity components in for example climate change responses. The BLUP responses will depend on the additive genetic relationship matrix A_t. When A_t is an identity matrix, the results will be identical to the results from a variant of the multivariate breeder’s equation, based on the selection gradient with respect to the individual phenotypic trait values. Parameters are assumed to be known and constant, but it is discussed how they can be estimated by means of a prediction error method. Generations are assumed to be non-overlapping, but adjustments for overlapping generations can easily be done.

Bioclimatic variables (BCVs) are the most widely used predictors within the field of ecological niche modeling. However, recent studies indicate that BCVs alone are not sufficient to describe these limits and more (bio)climatological variables should be considered. Unfortunately, the most popular database WorldClim offers only a limited selection of predictors; thus, other gridded station-based observations or reanalysis (GSOR) datasets should be taken into account. In the present study, we investigate how well the BCVs are represented by different GSOR datasets for the extended Mediterranean area within the period 1970-2020, how deviations among the datasets differ regionally and how different calculation schemes affect the representation of BCVs. We consider different calculation schemes for quarters/months, the annual mean temperature and the maximum temperature of the warmest month and show the effects on the respective BCV. Differences resulting from different calculation schemes are presented for ERA5-Land. Selected BCVs are analyzed to show differences between WorldClim, ERA5-Land, E-OBS and CRU. Our results show that (a) deviations between the two calculation schemes for annual mean temperature (maximum temperature of the warmest month) diminish (increase) when the temporal resolution is decreased; (b) with respect to the definition of the respective month/quarter, temporal shifts can have substantially different effects on the BCVs, depending on region; (c) overall, all datasets represent the different BCVs similarly, but with partly large differences in some subregions; (d) the largest differences occur when specific month/quarters are defined by the seasonal cycle of precipitation. In summary, (a) since the definition of BCVs matches different calculation schemes, a transparent communication of the BCVs calculation schemes is inevitable; (b) the calculation, integration or elimination of BCVs has to be examined carefully for each dataset, region, period or species; (c) the GSOR-Data provide, except some subregions, a consistent representation of BCVs within the extended Mediterranean region.

The interactions between different species in an ecosystem, such as predation and herbivory, are crucial for maintaining the ecosystem’s functioning, including pest control and nutrient cycling. Unfortunately, human activities are increasingly affecting these trophic relationships, contributing to the current decline in biodiversity, particularly due to urbanization and climate change. The intensity of trophic interactions is also affected by latitudinal gradients, which may be further impacted by urbanization, such as the urban island heat effect. This study aimed to investigate the hypothesis that the impact of human pressure on trophic interactions varies across different latitudes. To test this hypothesis, we selected 18 study sites at two latitudes (i.e., ~53°N and ~50°N) with varying human population density. We used artificial caterpillars placed on European beech branches to assess bird predation and took standardized pictures of the leaves to estimate insect herbivory. Remote sensing techniques were used to estimate human pressure. We found that the intensity of both bird predation and insect herbivory varied in response to human pressure, with opposite trends observed depending on the latitude. At the upper latitude, bird predation increased with human impact, while the opposite was observed at the lower latitude. All types of herbivory in both latitudes increased with urbanization. Moreover, at lower latitudes, species may face a disadvantage due to the urban heat island effect, as they tend to be relatively sensitive to temperature changes. Conversely, at higher latitudes, some species may benefit from a softer winter. Overall, this study highlights the complex and dynamic nature of trophic relationships in the face of human-driven changes to ecosystems. It also emphasizes the importance of considering both human pressure and latitudinal gradients when assessing the ecological consequences of future climate change scenarios, particularly in urban environments.

Monitoring is a prerequisite for evidence-based wildlife management, yet conventional monitoring approaches are often ineffective for species occurring at low densities. However, some species such as large mammals are often observed by lay people and this information can be leveraged through citizen science monitoring schemes. Assessing the quantity, quality, and potential biases of such data sources is crucial before making inferences at scale. For Eurasian moose (Alces alces), a species currently reoccurring in north-eastern Germany in low numbers, we compared three different citizen science tools: a mail/email report system, a smartphone application, and a webpage. Among these monitoring tools, the mail/email report system yielded the greatest number of moose reports in absolute and in standardized (corrected for time effort) terms. The reported moose were predominantly identified as single, adult, male individuals, and reports occurred mostly during late summer. Overlaying citizen science data with independently generated habitat suitability and connectivity maps showed that members of the public detected moose in suitable habitats but not necessarily in movement corridors. Also, moose detections were often recorded near roads, suggestive of spatial bias in sampling effort. Our results suggest that citizen science-based data collection can be facilitated by brief, intuitive digital reporting systems. However, inference from the resulting data can be limited due to unquantified and possibly biased sampling effort. To overcome these challenges, we offer specific recommendations such as engaging outdoor enthusiasts in suitable moose habitats, for improving quantity, quality and analysis of citizen science-based data for making robust inferences about wildlife populations.

1. Grassy ecosystems cover ~40% of the global land surface and are an integral component of the global carbon cycle. Grass litter decomposes via a combination of ultraviolet radiation degradation (which returns carbon to the atmosphere rapidly) and biological decomposition (a slower carbon pathway). As such, decomposition and carbon storage in grasslands may vary with climate and exposure to solar radiation. We investigated rates of grass litter decomposition in Australian temperate grasslands along a climate gradient to uncouple the relative importance of UV radiation and climate on decomposition. 2. Litterbags containing two common native grass species were deployed at six grassland sites across a precipitation gradient (380-890 mm) in south-eastern Australia. Bags were retrieved over 39 weeks to measure mass loss from decomposition. We used shade treatments to partition UV degradation from biological decomposition. 3. The shade treatment consistently reduced the rate of decomposition relative to full-sun treatments at all sites; there was no significant difference in the effect size of the shade treatment among sites. The rate of decomposition was positively correlated with rainfall midway through the experiment, but there were no significant differences in total decomposition among sites after 39 weeks. In general, the shape of decomposition curves was more linear than has typically been observed in global decomposition studies. 4. Synthesis: We found that UV exposure was a strong contributor to litter decomposition in temperate Australian grasslands. This effect was not influenced by climatic variables and may be related to a period of photopriming prior to further biotic decomposition. This study highlights the importance of litter composition and UV exposure in our understanding of how decomposition patterns contribute to global carbon cycling.

The molluscan feeding structure is the radula, a chitinous membrane with teeth, which are highly adapted to the food and the substrate. In Polyplacophora and Patellogastropoda, the handling of hard ingesta can be facilitated by high content of chemical compounds containing Fe or Si in the tooth cusps. Other taxa, however, possess teeth that are less mineralized, even though animals have to avoid structural failure or high wear during feeding as well. Here, we investigated the gastropod Gastropteron rubrum, feeding on hard Foraminifera, diatoms and Porifera. Tooth morphologies and wear were documented by scanning electron microscopy and their mechanical properties were tested by nanoindentation. We determined, that gradients of hard- and stiffness run along each tooth, decreasing from cusp to basis. We also found, that inner lateral teeth are harder and stiffer than the outer ones. These findings allowed us to propose hypotheses about the radula-ingesta interaction. In search for the origins of the gradients, teeth were visualized using confocal laser scanning microscopy, to determine the degree of tanning, and analyzed with energy-dispersive X-ray spectroscopy, to test the elemental composition. We found that the mechanical gradients probably have their origin in the degree of tanning, as the teeth did not contain high proportions of metals or other minerals. However, in the tooth surfaces, which interact with the ingesta, high Si and Ca content was determined, which is likely an adaptation to reduce wear.