590 Tiere (Zoologie)
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Institute
- Biodiversität und Klima Forschungszentrum (BiK-F) (77) (remove)
Active species reintroduction is an important conservation tool when aiming for the restoration of biological communities and ecosystems. The effective monitoring of reintroduction success is a crucial factor in this process. Here, we used a combination of environmental DNA (eDNA) techniques and species distribution models (SDMs) to evaluate the success of recent reintroductions of the freshwater fish Alburnoides bipunctatus in central Germany. We built SDMs without and with eDNA presence data to locate further suitable reintroduction sites and potentially overlooked populations of the species. We successfully detected eDNA of A. bipunctatus at all reintroduction sites, as well as several adjacent sites mostly in downstream direction, which supports the success of reintroduction efforts. eDNA‐based species detection considerably improved SDMs for A. bipunctatus, which allowed to identify species presence in previously unknown localities. Our results confirm the usefulness of eDNA techniques as standard tool to monitor reintroduced fish populations. We propose that combining eDNA with SDMs is a highly effective approach for long‐term monitoring of reintroduction success in aquatic species.
Aim: Predicting future changes in species richness in response to climate change is one of the key challenges in biogeography and conservation ecology. Stacked species distribution models (S‐SDMs) are a commonly used tool to predict current and future species richness. Macroecological models (MEMs), regression models with species richness as response variable, are a less computationally intensive alternative to S‐SDMs. Here, we aim to compare the results of two model types (S‐SDMS and MEMs), for the first time for more than 14,000 species across multiple taxa globally, and to trace the uncertainty in future predictions back to the input data and modelling approach used.
Location: Global land, excluding Antarctica.
Taxon: Amphibians, birds and mammals.
Methods: We fitted S‐SDMs and MEMs using a consistent set of bioclimatic variables and model algorithms and conducted species richness predictions under current and future conditions. For the latter, we used four general circulation models (GCMs) under two representative concentration pathways (RCP2.6 and RCP6.0). Predicted species richness was compared between S‐SDMs and MEMs and for current conditions also to extent‐of‐occurrence (EOO) species richness patterns. For future predictions, we quantified the variance in predicted species richness patterns explained by the choice of model type, model algorithm and GCM using hierarchical cluster analysis and variance partitioning.
Results: Under current conditions, species richness predictions from MEMs and S‐SDMs were strongly correlated with EOO‐based species richness. However, both model types over‐predicted areas with low and under‐predicted areas with high species richness. Outputs from MEMs and S‐SDMs were also highly correlated among each other under current and future conditions. The variance between future predictions was mostly explained by model type.
Main conclusions: Both model types were able to reproduce EOO‐based patterns in global terrestrial vertebrate richness, but produce less collinear predictions of future species richness. Model type by far contributes to most of the variation in the different future species richness predictions, indicating that the two model types should not be used interchangeably. Nevertheless, both model types have their justification, as MEMs can also include species with a restricted range, whereas S‐SDMs are useful for looking at potential species‐specific responses.
Background: The invasive temperate mosquito Aedes japonicus japonicus is a potential vector for various infectious diseases and therefore a target of vector control measures. Even though established in Germany, it is unclear whether the species has already reached its full distribution potential. The possible range of the species, its annual population dynamics, the success of vector control measures and future expansions due to climate change still remain poorly understood. While numerous studies on occurrence have been conducted, they used mainly presence data from relatively few locations. In contrast, we used experimental life history data to model the dynamics of a continuous stage-structured population to infer potential seasonal densities and ask whether stable populations are likely to establish over a period of more than one year. In addition, we used climate change models to infer future ranges. Finally, we evaluated the effectiveness of various stage-specific vector control measures.
Results: Aedes j. japonicus has already established stable populations in the southwest and west of Germany. Our models predict a spread of Ae. j. japonicus beyond the currently observed range, but likely not much further eastwards under current climatic conditions. Climate change models, however, will expand this range substantially and higher annual densities can be expected. Applying vector control measures to oviposition, survival of eggs, larvae or adults showed that application of adulticides for 30 days between late spring and early autumn, while ambient temperatures are above 9 °C, can reduce population density by 75%. Continuous application of larvicide showed similar results in population reduction. Most importantly, we showed that with the consequent application of a mixed strategy, it should be possible to significantly reduce or even extinguish existing populations with reasonable effort.
Conclusion: Our study provides valuable insights into the mechanisms concerning the establishment of stable populations in invasive species. In order to minimise the hazard to public health, we recommend vector control measures to be applied in ‘high risk areas’ which are predicted to allow establishment of stable populations to establish.
Wolves (Canis lupus) are currently showing a remarkable comeback in the highly frag-mented cultural landscapes of Germany. We here show that wolf numbers increasedexponentially between 2000 and 2015 with an annual increase of about 36%. Wedemonstrate that the first territories in each newly colonized region were establishedover long distances from the nearest known reproducing pack on active militarytraining areas (MTAs). We show that MTAs, rather than protected areas, served asstepping-stones for the recolonization of Germany facilitating subsequent spreadingof wolf territories in the surrounding landscape. We did not find any significant differ-ence between MTAs and protected areas with regard to habitat. One possible reasonfor the importance of MTAs may be their lower anthropogenic mortality rates com-pared to protected and other areas. To our knowledge, this is the first documented casewhere MTAs facilitate the recolonization of an endangered species across large areas.
The success of social insects is largely intertwined with their highly advanced chemical communication system that facilitates recognition and discrimination of species and nest-mates, recruitment, and division of labor. Hydrocarbons, which cover the cuticle of insects, not only serve as waterproofing agents but also constitute a major component of this communication system. Two cryptic Crematogaster species, which share their nest with Camponotus ants, show striking diversity in their cuticular hydrocarbon (CHC) profile. This mutualistic system therefore offers a great opportunity to study the genetic basis of CHC divergence between sister species. As a basis for further genome-wide studies high-quality genomes are needed. Here, we present the annotated draft genome for Crematogaster levior A. By combining the three most commonly used sequencing techniques—Illumina, PacBio, and Oxford Nanopore—we constructed a high-quality de novo ant genome. We show that even low coverage of long reads can add significantly to overall genome contiguity. Annotation of desaturase and elongase genes, which play a role in CHC biosynthesis revealed one of the largest repertoires in ants and a higher number of desaturases in general than in other Hymenoptera. This may provide a mechanistic explanation for the high diversity observed in C. levior CHC profiles.
Environmental niche modelling is an acclaimed method for estimating species’ present or future distributions. However, in marine environments the assembly of representative data from reliable and unbiased occurrences is challenging. Here, we aimed to model the environmental niche and distribution of marine, parasitic nematodes from the Pseudoterranova decipiens complex using the software Maxent. The distribution of these potentially zoonotic species is of interest, because they infect the muscle tissue of host species targeted by fisheries. To achieve the best possible model, we used two different approaches. The land distance (LD) model was based on abiotic data, whereas the definitive host distance (DHD) model included species-specific biotic data. To assess whether DHD is a suitable descriptor for Pseudoterranova spp., the niches of the parasites and their respective definitive hosts were analysed using ecospat. The performance of LD and DHD was compared based on the variables’ contribution to the model. The DHD-model clearly outperformed the LD-model. While the LD-model gave an estimate of the parasites’ niches, it only showed the potential distribution. The DHD-model produced an estimate of the species’ realised distribution and indicated that biotic variables can help to improve the modelling of data-poor, marine species.
Climate change forces many species to move their ranges to higher latitudes or elevations. Resulting immigration or emigration of species might lead to functional changes, e.g., in the trait distribution and composition of ecological assemblages. Here, we combined approaches from biogeography (species distribution models; SDMs) and community ecology (functional diversity) to investigate potential effects of climate-driven range changes on frugivorous bird assemblages along a 3000 m elevational gradient in the tropical Andes. We used SDMs to model current and projected future occurrence probabilities of frugivorous bird species from the lowlands to the tree line. SDM-derived probabilities of occurrence were combined with traits relevant for seed dispersal of fleshy-fruited plants to calculate functional dispersion (FDis; a measure of functional diversity) for current and future bird assemblages. Comparisons of FDis between current and projected future assemblages showed consistent results across four dispersal scenarios, five climate models and two representative concentration pathways. Projections indicated a decrease of FDis in the lowlands, an increase of FDis at lower mid-elevations and little changes at high elevations. This suggests that functional dispersion responds differently to global warming at different elevational levels, likely modifying avian seed dispersal functions and plant regeneration in forest ecosystems along tropical mountains.
A world dataset on the geographic distributions of Solenidae razor clams (Mollusca: Bivalvia)
(2019)
Background: Using this dataset, we examined the global geographical distributions of Solenidae species in relation to their endemicity, species richness and latitudinal ranges and then predicted their distributions under future climate change using species distribution modelling techniques (Saeedi et al. 2016a, Saeedi et al. 2016b). We found that the global latitudinal species richness in Solenidae is bi-modal, dipping at the equator most likely derived by high sea surface temperature (Saeedi et al. 2016b). We also found that most of the Solenidae species will shift their distribution ranges polewards due to global warming (Saeedi et al. 2016a). We also provided a comprehensive review of the taxon to test whether the latitudinal gradient in species richness was uni-modal with a peak in the tropics or northern hemisphere or asymmetric and bimodal as proposed previously (Chaudhary et al. 2016).
New information: This paper presents an integrated global geographic distribution dataset for 77 Solenidae taxa, including 3,034 geographic distribution records. This dataset was compiled after a careful data-collection and cleaning procedure over four years. Data were collected using field sampling, literature and from open-access databases. Then all the records went through quality control procedures such as validating the taxonomy of the species by examining and re-identifying the specimens in museum collections and using taxonomic and geographic data quality control tools in the World Register of Marine Species (WoRMS) and the r-OBIS package (Provoost and Bosch 2017). This dataset can thus be further used for taxonomical and biogeographical studies of Solenidae.
Abstract
Divergence is mostly viewed as a progressive process often initiated by selection targeting individual loci, ultimately resulting in ever increasing genomic isolation due to linkage. However, recent studies show that this process may stall at intermediate stable equilibrium states without achieving complete genomic isolation. We tested the extent of genomic isolation between two recurrently hybridizing nonbiting midge sister taxa, Chironomus riparius and Chironomus piger, by analyzing the divergence landscape. Using a principal component‐based method, we estimated that only about 28.44% of the genomes were mutually isolated, whereas the rest was still exchanged. The divergence landscape was fragmented into isolated regions of on average 30 kb, distributed throughout the genome. Selection and divergence time strongly influenced lengths of isolated regions, whereas local recombination rate only had minor impact. Comparison of divergence time distributions obtained from several coalescence‐simulated divergence scenarios with the observed divergence time estimates in an approximate Bayesian computation framework favored a short and concluded divergence event in the past. Most divergence happened during a short time span about 4.5 million generations ago, followed by a stable equilibrium between mutual gene flow through ongoing hybridization for the larger part of the genome and isolation in some regions due to rapid purifying selection of introgression, supported by high effective population sizes and recombination rates.
Impact Summary
The process of speciation has fascinated biologists from early on. Prevailing theory suggested that gene flow among populations is the main obstacle for their divergence. Recently, it became clear that speciation with gene flow is possible under certain circumstances. However, it remains unclear how the divergence process proceeds in time, how widespread the phenomenon is, and whether it always and inevitably leads to complete isolation. Comparing the genomes of individuals of two regularly hybridizing sister taxa of nonbiting midges, we could show that they diverged during a short period millions of generations ago. Their divergence process apparently ceased before the entire genome was mutually isolated. The taxa remain distinct since, even though they share most of their genome. Our findings thus extend our view of the nature of species and the temporal dynamics of their divergence and describe novel approaches to analyze both current and past divergence processes.
Social insects dominate arthropod communities worldwide due to cooperation and division of labor in their societies. This, however, makes them vulnerable to exploitation by social parasites, such as slave‐making ants. Slave‐making ant workers pillage brood from neighboring nests of related host ant species. After emergence, host workers take over all nonreproductive colony tasks, whereas slavemakers have lost the ability to care for themselves and their offspring. Here, we compared transcriptomes of different developmental stages (larvae, pupae, and adults), castes (queens and workers), and sexes of two related ant species, the slavemaker Temnothorax americanus and its host Temnothorax longispinosus. Our aim was to investigate commonalities and differences in group‐specific transcriptomes, whereupon across‐species differences possibly can be explained by their divergent lifestyles. Larvae and pupae showed the highest similarity between the two species and upregulated genes with enriched functions of translation and chitin metabolism, respectively. Workers commonly upregulated oxidation‐reduction genes, possibly indicative of their active lifestyle. Host workers, but not workers of the slavemaker, upregulated a “social behavior” gene. In slavemaker queens and workers, genes associated with the regulation of transposable elements were upregulated. Queens of both species showed transcriptomic signals of anti‐aging mechanisms, with hosts upregulating various DNA repair pathways and slavemaker queens investing in trehalose metabolism. The transcriptomes of males showed enriched functions for quite general terms realized in different genes and pathways in each species. In summary, the strong interspecific commonalities in larvae, pupae, and workers were reflected in the same enriched Gene Ontology (GO) terms. Less commonalities occurred in the transcriptomes of queens and males, which apparently utilize different pathways to achieve a long life and sperm production, respectively. We found that all analyzed groups in this study show characteristic GO terms, with similar patterns in both species.
Animal tracking and biologging devices record large amounts of data on individual movement behaviors in natural environments. In these data, movement ecologists often view unexplained variation around the mean as “noise” when studying patterns at the population level. In the field of behavioral ecology, however, focus has shifted from population means to the biological underpinnings of variation around means. Specifically, behavioral ecologists use repeated measures of individual behavior to partition behavioral variability into intrinsic among-individual variation and reversible behavioral plasticity and to quantify: a) individual variation in behavioral types (i.e. different average behavioral expression), b) individual variation in behavioral plasticity (i.e. different responsiveness of individuals to environmental gradients), c) individual variation in behavioral predictability (i.e. different residual within-individual variability of behavior around the mean), and d) correlations among these components and correlations in suites of behaviors, called ‘behavioral syndromes’. We here suggest that partitioning behavioral variability in animal movements will further the integration of movement ecology with other fields of behavioral ecology. We provide a literature review illustrating that individual differences in movement behaviors are insightful for wildlife and conservation studies and give recommendations regarding the data required for addressing such questions. In the accompanying R tutorial we provide a guide to the statistical approaches quantifying the different aspects of among-individual variation. We use movement data from 35 African elephants and show that elephants differ in a) their average behavior for three common movement behaviors, b) the rate at which they adjusted movement over a temporal gradient, and c) their behavioral predictability (ranging from more to less predictable individuals). Finally, two of the three movement behaviors were correlated into a behavioral syndrome (d), with farther moving individuals having shorter mean residence times. Though not explicitly tested here, individual differences in movement and predictability can affect an individual’s risk to be hunted or poached and could therefore open new avenues for conservation biologists to assess population viability. We hope that this review, tutorial, and worked example will encourage movement ecologists to examine the biology of individual variation in animal movements hidden behind the population mean.
1. Recent research highlights the ecological importance of individual variation in behavioural predictability. Individuals may not only differ in their average expression of a behavioural trait (their behavioural type) and in their ability to adjust behaviour to changing environmental conditions (individual plasticity), but also in their variability around their average behaviour (predictability). However, quantifying behavioural predictability in the wild has been challenging due to limitations of acquiring sufficient repeated behavioural measures.
2. We here demonstrate how common biologging data can be used to detect individual variation in behavioural predictability in the wild and reveal the coexistence of highly predictable individuals along with unpredictable individuals within the same population.
3. We repeatedly quantified two behaviours—daily movement distance and diurnal activity—in 62 female brown bears Ursus arctos tracked across 187 monitoring years. We calculated behavioural predictability over the short term (50 consecutive monitoring days within 1 year) and long term (across monitoring years) as the residual intra-individual variability (rIIV) of behaviour around the behavioural reaction norm. We tested whether predictability varies systematically across average behavioural types and whether it is correlated across functionally distinct behaviours, that is, daily movement distance and amount of diurnal activity.
4. Brown bears showed individual variation in behavioural predictability from predictable to unpredictable individuals. For example, the standard deviation around the average daily movement distance within one monitoring year varied up to fivefold from 1.1 to 5.5 km across individuals. Individual predictability for both daily movement distance and diurnality was conserved across monitoring years. Individual predictability was correlated with behavioural type where individuals which were on average more diurnal and mobile were also more unpredictable in their behaviour. In contrast, more nocturnal individuals moved less and were more predictable in their behaviour. Finally, individual predictability in daily movement distance and diurnality was positively correlated, suggesting that individual predictability may be a quantitative trait in its own regard that could evolve and is underpinned by genetic variation.
5. Unpredictable individuals may cope better with stochastic events and unpredictability may hence be an adaptive behavioural response to increased predation risk.
The Culex pipiens complex encompasses five species and subspecies of the genus Culex. Over time, a multitude of morphologically indistinguishable species has been assigned to this complex with several species being classified as important vectors for different diseases. Some species of this complex hibernate in subterranean habitats, and it has been proven that viruses can survive this phase of hibernation. However, studies focusing on the environmental requirements, ecology and spatial and temporal distribution patterns of mosquitos in underground habitats are sparse. Here, we investigate the main environmental factors and dependencies of Culex, considering the number of individuals and survival probabilities in underground habitats during the winter months. Methods. Since the State of Hesse, Germany harbors about 3500 to 4000 subterranean shelters ample availability of subterranean habitats there provides a good opportunity to conduct detailed investigations of the Culex pipiens complex. In this study, we identified a sample of 727 specimens of overwintering females within the Culex pipiens complex from 52 different underground sites collected over a period of 23 years using qPCR. A complete data set of samplings of hibernating mosquitos from 698 subterranean habitats in Central Germany over the same period was available to study the spatial and temporal patterns and the effect of temperature and precipitation conditions on these hibernating populations using a generalized linear model (GLM). Results. Our qPCR-results show, similar to aboveground studies of mosquitos, that Culex pipiens pipiens and Culex torrentium occur sympatrically. On the other hand, Culex pipiens molestus occurred very rarely. The GLM revealed no shifts in species composition over time, but different preferences for subterranean hibernacula, chemical effects on overwintering populations as well as effects of annual and seasonal mean temperature and precipitation during the active phase from March to November. Cx. p. pipiens and Cx. torrentium are the most common species within Hessian caves and other underground habitats during winter. They co-occur with different frequency without any patterns in species composition. Weather conditions influence the number of overwintering mosquitos during the activity phase. Depending on cave parameters, the number of mosquitos decreases during the winter months.
A tale of two seasons: The link between seasonal migration and climatic niches in passerine birds
(2020)
The question of whether migratory birds track a specific climatic niche by seasonal movements has important implications for understanding the evolution of migration, the factors affecting species' distributions, and the responses of migrants to climate change. Despite much research, previous studies of bird migration have produced mixed results. However, whether migrants track climate is only one half of the question, the other being why residents remain in the same geographic range year-round. We provide a literature overview and test the hypothesis of seasonal niche tracking by evaluating seasonal climatic niche overlap across 437 migratory and resident species from eight clades of passerine birds. Seasonal climatic niches were based on a new global dataset of breeding and nonbreeding ranges. Overlap between climatic niches was quantified using ordination methods. We compared niche overlap of migratory species to two null expectations, (a) a scenario in which they do not migrate and (b) in comparison with the overlap experienced by closely related resident species, while controlling for breeding location and range size. Partly in accordance with the hypothesis of niche tracking, we found that the overlap of breeding versus nonbreeding climatic conditions in migratory species was greater than the overlap they would experience if they did not migrate. However, this was only true for migrants breeding outside the tropics and only relative to the overlap species would experience if they stayed in the breeding range year-round. In contrast to the hypothesis of niche tracking, migratory species experienced lower seasonal climatic niche overlap than resident species, with significant differences between tropical and nontropical species. Our study suggests that in seasonal nontropical environments migration away from the breeding range may serve to avoid seasonally harsh climate; however, different factors may drive seasonal movements in the climatically more stable tropical regions.
Mosquito species belonging to the genus Aedes have attracted the interest of scientists and public health officers for their invasive species traits and efficient capacity of transmitting viruses affecting humans. Some of these species were brought outside their native range by human activities such as trade and tourism, and colonised new regions thanks to a unique combination of eco-physiological traits.
Considering mosquito physiological and behavioural traits to understand and predict the spatial and temporal population dynamics is thus a crucial step to develop strategies to mitigate the local densities of invasive Aedes populations.
Here, we synthesised the life cycle of four invasive Aedes species (Ae. aegypti, Ae. albopictus, Ae. japonicus and Ae. koreicus) in a single multi-scale stochastic modelling framework which we coded in the R package dynamAedes. We designed a stage-based and time-discrete stochastic model driven by temperature, photo-period and inter-specific larval competition that can be applied to three different spatial scales: punctual, local and regional. These spatial scales consider different degrees of spatial complexity and data availability, by accounting for both active and passive dispersal of mosquito species as well as for the heterogeneity of the input temperature data.
Our overarching aim was to provide a flexible, open-source and user-friendly tool rooted in the most updated knowledge on species biology which could be applied to the management of invasive Aedes populations as well as for more theoretical ecological inquiries.
The most basic behavioural states of animals can be described as active or passive. However, while high-resolution observations of activity patterns can provide insights into the ecology of animal species, few methods are able to measure the activity of individuals of small taxa in their natural environment. We present a novel approach in which the automated VHF radio-tracking of small vertebrates fitted with lightweight transmitters (< 0.2 g) is used to distinguish between active and passive behavioural states.
A dataset containing > 3 million VHF signals was used to train and test a random forest model in the assignment of either active or passive behaviour to individuals from two forest-dwelling bat species (Myotis bechsteinii (n = 50) and Nyctalus leisleri (n = 20)). The applicability of the model to other taxonomic groups was demonstrated by recording and classifying the behaviour of a tagged bird and by simulating the effect of different types of vertebrate activity with the help of humans carrying transmitters. The random forest model successfully classified the activity states of bats as well as those of birds and humans, although the latter were not included in model training (F-score 0.96–0.98).
The utility of the model in tackling ecologically relevant questions was demonstrated in a study of the differences in the daily activity patterns of the two bat species. The analysis showed a pronounced bimodal activity distribution of N. leisleri over the course of the night while the night-time activity of M. bechsteinii was relatively constant. These results show that significant differences in the timing of species activity according to ecological preferences or seasonality can be distinguished using our method.
Our approach enables the assignment of VHF signal patterns to fundamental behavioural states with high precision and is applicable to different terrestrial and flying vertebrates. To encourage the broader use of our radio-tracking method, we provide the trained random forest models together with an R-package that includes all necessary data-processing functionalities. In combination with state-of-the-art open-source automated radio-tracking, this toolset can be used by the scientific community to investigate the activity patterns of small vertebrates with high temporal resolution, even in dense vegetation.
he most basic behavioural states of animals can be described as active or passive. While high-resolution observations of activity patterns can provide insights into the ecology of animal species, few methods are able to measure the activity of individuals of small taxa in their natural environment. We present a novel approach in which a combination of automatic radiotracking and machine learning is used to distinguish between active and passive behaviour in small vertebrates fitted with lightweight transmitters (<0.4 g).
We used a dataset containing >3 million signals from very-high-frequency (VHF) telemetry from two forest-dwelling bat species (Myotis bechsteinii [n = 52] and Nyctalus leisleri [n = 20]) to train and test a random forest model in assigning either active or passive behaviour to VHF-tagged individuals. The generalisability of the model was demonstrated by recording and classifying the behaviour of tagged birds and by simulating the effect of different activity levels with the help of humans carrying transmitters. The model successfully classified the activity states of bats as well as those of birds and humans, although the latter were not included in model training (F1 0.96–0.98).
We provide an ecological case-study demonstrating the potential of this automated monitoring tool. We used the trained models to compare differences in the daily activity patterns of two bat species. The analysis showed a pronounced bimodal activity distribution of N. leisleri over the course of the night while the night-time activity of M. bechsteinii was relatively constant. These results show that subtle differences in the timing of species' activity can be distinguished using our method.
Our approach can classify VHF-signal patterns into fundamental behavioural states with high precision and is applicable to different terrestrial and flying vertebrates. To encourage the broader use of our radiotracking method, we provide the trained random forest models together with an R package that includes all necessary data processing functionalities. In combination with state-of-the-art open-source automated radiotracking, this toolset can be used by the scientific community to investigate the activity patterns of small vertebrates with high temporal resolution, even in dense vegetation.