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The gradual heterogeneity of climatic factors pose varying selection pressures across geographic distances that leave signatures of clinal variation in the genome. Separating signatures of clinal adaptation from signatures of other evolutionary forces, such as demographic processes, genetic drift, and adaptation to non-clinal conditions of the immediate local environment is a major challenge. Here, we examine climate adaptation in five natural populations of the harlequin fly Chironomus riparius sampled along a climatic gradient across Europe. Our study integrates experimental data, individual genome resequencing, Pool-Seq data, and population genetic modelling. Common-garden experiments revealed a positive correlation of population growth rates corresponding to the population origin along the climate gradient, suggesting thermal adaptation on the phenotypic level. Based on a population genomic analysis, we derived empirical estimates of historical demography and migration. We used an FST outlier approach to infer positive selection across the climate gradient, in combination with an environmental association analysis. In total we identified 162 candidate genes as genomic basis of climate adaptation. Enriched functions among these candidate genes involved the apoptotic process and molecular response to heat, as well as functions identified in other studies of climate adaptation in other insects. Our results show that local climate conditions impose strong selection pressures and lead to genomic adaptation despite strong gene flow. Moreover, these results imply that selection to different climatic conditions seems to converge on a functional level, at least between different insect species.
One of the major problems in evolutionary biology is to elucidate the relationships between historical events and the tempo and mode of lineage divergence. The development of relaxed molecular clock models and the increasing availability of DNA sequences resulted in more accurate estimations of taxa divergence times. However, finding the link between competing historical events and divergence is still challenging. Here we investigate assigning constrained-age priors to nodes of interest in a time-calibrated phylogeny as a means of hypothesis comparison. These priors are equivalent to historic scenarios for lineage origin. The hypothesis that best explains the data can be selected by comparing the likelihood values of the competing hypotheses, modelled with different priors. A simulation approach was taken to evaluate the performance of the prior-based method and to compare it with an unconstrained approach. We explored the effect of DNA sequence length and the temporal placement and span of competing hypotheses (i.e. historic scenarios) on selection of the correct hypothesis and the strength of the inference. Competing hypotheses were compared applying a posterior simulation analogue of the Akaike Information Criterion and Bayes factors (obtained after calculation of the marginal likelihood with three estimators: Harmonic Mean, Stepping Stone and Path Sampling). We illustrate the potential application of the prior-based method on an empirical data set to compare competing geological hypotheses explaining the biogeographic patterns in Pleurodeles newts. The correct hypothesis was selected on average 89% times. The best performance was observed with DNA sequence length of 3500-10000 bp. The prior-based method is most reliable when the hypotheses compared are not temporally too close. The strongest inferences were obtained when using the Stepping Stone and Path Sampling estimators. The prior-based approach proved effective in discriminating between competing hypotheses when used on empirical data. The unconstrained analyses performed well but it probably requires additional computational effort. Researchers applying this approach should rely only on inferences with moderate to strong support. The prior-based approach could be applied on biogeographical and phylogeographical studies where robust methods for historical inferences are still lacking.
Good quality data on precipitation are a prerequisite for applications like short-term weather forecasts, medium-term humanitarian assistance, and long-term climate modelling. In Sub-Saharan Africa, however, the meteorological station networks are frequently insufficient, as in the Cuvelai-Basin in Namibia and Angola. This paper analyses six rainfall products (ARC2.0, CHIRPS2.0, CRU-TS3.23, GPCCv7, PERSIANN-CDR, and TAMSAT) with respect to their performance in a crop model (APSIM) to obtain nutritional scores of a household’s requirements for dietary energy and further macronutrients. All products were calibrated to an observed time series using Quantile Mapping. The crop model output was compared against official yield data. The results show that the products (i) reproduce well the Basin’s spatial patterns, and (ii) temporally agree to station records (r = 0.84). However, differences exist in absolute annual rainfall (range: 154 mm), rainfall intensities, dry spell duration, rainy day counts, and the rainy season onset. Though calibration aligns key characteristics, the remaining differences lead to varying crop model results. While the model well reproduces official yield data using the observed rainfall time series (r = 0.52), the products’ results are heterogeneous (e.g., CHIRPS: r = 0.18). Overall, 97% of a household’s dietary energy demand is met. The study emphasizes the importance of considering the differences among multiple rainfall products when ground measurements are scarce.
The accurate knowledge of the groundwater storage variation (ΔGWS) is essential for reliable water resource assessment, particularly in arid and semi-arid environments (e.g., Australia, the North China Plain (NCP)) where water storage is significantly affected by human activities and spatiotemporal climate variations. The large-scale ΔGWS can be simulated from a land surface model (LSM), but the high model uncertainty is a major drawback that reduces the reliability of the estimates. The evaluation of the model estimate is then very important to assess its accuracy. To improve the model performance, the terrestrial water storage variation derived from the Gravity Recovery And Climate Experiment (GRACE) satellite mission is commonly assimilated into LSMs to enhance the accuracy of the ΔGWS estimate. This study assimilates GRACE data into the PCRaster Global Water Balance (PCR-GLOBWB) model. The GRACE data assimilation (DA) is developed based on the three-dimensional ensemble Kalman smoother (EnKS 3D), which considers the statistical correlation of all extents (spatial, temporal, vertical) in the DA process. The ΔGWS estimates from GRACE DA and four LSM simulations (PCR-GLOBWB, the Community Atmosphere Biosphere Land Exchange (CABLE), the Water Global Assessment and Prognosis Global Hydrology Model (WGHM), and World-Wide Water (W3)) are validated against the in situ groundwater data. The evaluation is conducted in terms of temporal correlation, seasonality, long-term trend, and detection of groundwater depletion. The GRACE DA estimate shows a significant improvement in all measures, notably the correlation coefficients (respect to the in situ data) are always higher than the values obtained from model simulations alone (e.g., ~0.15 greater in Australia, and ~0.1 greater in the NCP). GRACE DA also improves the estimation of groundwater depletion that the models cannot accurately capture due to the incorrect information of the groundwater demand (in, e.g., PCR-GLOBWB, WGHM) or the unavailability of a groundwater consumption routine (in, e.g., CABLE, W3). In addition, this study conducts the inter-comparison between four model simulations and reveals that PCR-GLOBWB and CABLE provide a more accurate ΔGWS estimate in Australia (subject to the calibrated parameter) while PCR-GLOBWB and WGHM are more accurate in the NCP (subject to the inclusion of anthropogenic factors). The analysis can be used to declare the status of the ΔGWS estimate, as well as itemize the possible improvements of the future model development.
BIOfid is a specialized information service currently being developed to mobilize biodiversity data dormant in printed historical and modern literature and to offer a platform for open access journals on the science of biodiversity. Our team of librarians, computer scientists and biologists produce high-quality text digitizations, develop new text-mining tools and generate detailed ontologies enabling semantic text analysis and semantic search by means of user-specific queries. In a pilot project we focus on German publications on the distribution and ecology of vascular plants, birds, moths and butterflies extending back to the Linnaeus period about 250 years ago. The three organism groups have been selected according to current demands of the relevant research community in Germany. The text corpus defined for this purpose comprises over 400 volumes with more than 100,000 pages to be digitized and will be complemented by journals from other digitization projects, copyright-free and project-related literature. With TextImager (Natural Language Processing & Text Visualization) and TextAnnotator (Discourse Semantic Annotation) we have already extended and launched tools that focus on the text-analytical section of our project. Furthermore, taxonomic and anatomical ontologies elaborated by us for the taxa prioritized by the project’s target group - German institutions and scientists active in biodiversity research - are constantly improved and expanded to maximize scientific data output. Our poster describes the general workflow of our project ranging from literature acquisition via software development, to data availability on the BIOfid web portal (http://biofid.de/), and the implementation into existing platforms which serve to promote global accessibility of biodiversity data.
To quantify water flows between groundwater (GW) and surface water (SW) as well as the impact of Abstract. To quantify water flows between groundwater (GW) and surface water (SW) as well as the impact of capillary rise on evapotranspiration by global hydrological models (GHMs), it is necessary to replace the bucket-like linear GW reservoir model typical for hydrological models with a fully integrated gradient-based GW flow model. Linear reservoir models can only simulate GW discharge to SW bodies, provide no information on the location of the GW table and assume that there is no GW flow among grid cells. A gradient-based GW model simulates not only GW storage but also hydraulic head, which together with information on SW table elevation enables the quantification of water flows from GW to SW and vice versa. In addition, hydraulic heads are the basis for calculating lateral GW flow among grid cells and capillary rise.
G³M is a new global gradient-based GW model with a spatial resolution of 5' that will replace the current linear GW reservoir in the 0.5° WaterGAP Global Hydrology Model (WGHM). The newly developed model framework enables inmemory coupling to WGHM while keeping overall runtime relatively low, allowing sensitivity analyses and data assimilation. This paper presents the G³M concept and specific model design decisions together with results under steady-state naturalized conditions, i.e. neglecting GW abstractions. Cell-specific conductances of river beds, which govern GW-SW interaction, were determined based on the 30'' steady-state water table computed by Fan et al. (2013). Together with an appropriate choice for the effective elevation of the SW table within each grid cell, this enables a reasonable simulation of drainage from GW to SW such that, in contrast to the GW model of de Graaf et al. (2015, 2017), no additional drainage based on externally provided values for GW storage above the floodplain is required in G³M. Comparison of simulated hydraulic heads to observations around the world shows better agreement than de Graaf et al. (2015). In addition, G³M output is compared to the output of two established macro-scale models for the Central Valley, California, and the continental United States, respectively. As expected, depth to GW table is highest in mountainous and lowest in flat regions. A first analysis of losing and gaining rivers and lakes/wetlands indicates that GW discharge to rivers is by far the dominant flow, draining diffuse GW recharge, such that lateral flows only become a large fraction of total diffuse and focused recharge in case of losing rivers and some areas with very low GW recharge. G³M does not represent losing rivers in some dry regions. This study presents the first steps towards replacing the linear GW reservoir model in a GHM while improving on recent efforts, demonstrating the feasibility of the approach and the robustness of the newly developed framework.
New geochemical data from the Malawi Rift (Chiwondo Beds, Karonga Basin) fill a major spatial gap in our knowledge of hominin adaptations on a continental scale. Oxygen (δ18O), carbon (δ13C), and clumped (Δ47) isotope data on paleosols, hominins, and selected fauna elucidate an unexpected diversity in the Pleistocene hominin diet in the various habitats of the East African Rift System (EARS). Food sources of early Homo and Paranthropus thriving in relatively cool and wet wooded savanna ecosystems along the western shore of paleolake Malawi contained a large fraction of C3 plant material. Complementary water consumption reconstructions suggest that ca. 2.4 Ma, early Homo (Homo rudolfensis) and Paranthropus (Paranthropus boisei) remained rather stationary near freshwater sources along the lake margins. Time-equivalent Paranthropus aethiopicus from the Eastern Rift further north in the EARS consumed a higher fraction of C4 resources, an adaptation that grew more pronounced with increasing openness of the savanna setting after 2 Ma, while Homo maintained a high versatility. However, southern African Paranthropus robustus had, similar to the Malawi Rift individuals, C3-dominated feeding strategies throughout the Early Pleistocene. Collectively, the stable isotope and faunal data presented here document that early Homo and Paranthropus were dietary opportunists and able to cope with a wide range of paleohabitats, which clearly demonstrates their high behavioral flexibility in the African Early Pleistocene.
All giraffe (Giraffa) were previously assigned to a single species (G. camelopardalis) and nine subspecies. However, multi‐locus analyses of all subspecies have shown that there are four genetically distinct clades and suggest four giraffe species. This conclusion might not be fully accepted due to limited data and lack of explicit gene flow analyses. Here, we present an extended study based on 21 independent nuclear loci from 137 individuals. Explicit gene flow analyses identify less than one migrant per generation, including between the closely related northern and reticulated giraffe. Thus, gene flow analyses and population genetics of the extended dataset confirm four genetically distinct giraffe clades and support four independent giraffe species. The new findings support a revision of the IUCN classification of giraffe taxonomy. Three of the four species are threatened with extinction, and mostly occurring in politically unstable regions, and as such, require the highest conservation support possible.
Plant pathogenic smut fungi in the broader sense can be divided into the Ustilaginomycetes, which cause classical smut symptoms with masses of blackish spores being produced in a variety of angiosperms, and the Exobasidiomycetes, which are often less conspicuous, as many do not shed large amounts of blackish spores. The leaf-spot causing members of the genus Entyloma (Entylomatales, Exobasidiomycetes) belong to the latter group. Currently, 172 species that all infect eudicots are included in the genus. Vánky (2012) recognised five Entyloma species on species of Ranunculus s.lat. Two have been reported only from Ficaria verna s.lat., while three, E. microsporum, E. ranunculi-repentis, E. verruculosum, have been reported to have a broad host range, encompassing 30, 26, and 5 species of Ranunculus, respectively. This broad host range is in contrast to the generally high host specificity assumed for species of Entyloma, indicating that they may represent complexes of specialised species. The aim of this study was to investigate Entyloma on Ranunculus s.lat. using multigene phylogenies and morphological comparisons. Phylogenetic analyses on the basis of up to four loci (ITS, atp2, ssc1, and map) showed a clustering of Entyloma specimens according to host species. For some of these Entyloma lineages, names not currently in use were available and reinstated. In addition, Entyloma microsporum s.str. is neotypified. Six novel species are described in this study, namely, Entyloma jolantae on Ranunculus oreophilus, E. klenkei on R. marginatus, E. kochmanii on R. lanuginosus, E. piepenbringiae on R. polyanthemos subsp. nemorosus (type host) and R. repens, E. savchenkoi on R. paludosus, and E. thielii on R. montanus. For all species diagnostic bases and morphological characteristics are provided. The results in this study once more highlight the importance of detailed re-investigation of broad host-range pathogens of otherwise specialised plant pathogen groups.
Don't poke the bear : using tracking data to quantify behavioural syndromes in elusive wildlife
(2018)
Animal personality traits and the emergence of behavioural syndromes, i.e. between-individual correlation of behaviours, are commonly quantified from behavioural observations in controlled environments. Subjecting large and elusive wildlife to controlled test situations is, however, rarely possible, suggesting that ecologists should exploit alternative measures of behaviours for quantifying differences between individuals. Our goal was to test whether movement and space use data can be used to quantify behavioural syndromes in the wild. We quantified six behaviours from GPS and dual motion sensor tracking devices of 46 adult female brown bears followed in southcentral Sweden over the summer and early autumn. As well as daily travel distance, an indicator for activity, and daily displacement, an indicator for exploration, we quantified four behaviours that increase a bear's likelihood of encountering humans and could thus serve as indicators for boldness: diurnality, selection for roads and selection for two open habitat types, bogs and clearcuts, with low lateral cover. We tested (1) whether behaviours showed repeatable between-individual variation (animal personality) and (2) whether behaviours were correlated between individuals and thus formed a behavioural syndrome. Repeatability of behaviours ranged from 0.16 to 0.61 confirming between-individual variation in movement, activity and space use. A multivariate mixed model revealed significant positive correlations between travel distance, displacement and diurnality, suggesting the existence of an activity–exploration and potentially partial boldness syndrome in our bear population. Selection for exposed or human-frequented habitats were uncorrelated with the activity–exploration syndrome and with each other, albeit there was a trend for stronger road avoidance by bears that readily used clearcuts. We show that large tracking data sets can be used to quantify between-individual correlation in spatial behaviours. We suggest that delineating behavioural types from wildlife tracking data will be of increasing interest because of the importance of animal personality for ecological processes, wildlife conservation and human–wildlife coexistence.