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Advancing and retreating fronts in a changing climate: a percolation model of range shifts

Climate change causes considerable shifts in the geographic distribution of species worldwide. Most data on range movements, however, derive from relatively short periods, within which it is difficult to distinguish directional shifts from random fluctuations. For detecting a shift, it is indispensable to delineate the range precisely. We propose a new method for delineation based on percolation theory. We suggest marking the boundary between the connected and fragmented occurrence of the species (the hull). We demonstrate the advantages of this connectivity-based method on simulated examples in which a metapopulation is advancing vs. retreating along an environmental gradient with different velocities. The simulations show that the hull is a fractal and has the same dimension (7/4) even when the front is advancing or retreating relatively fast, compared to the generation time. It is particularly robust in the retreating (trailing) edge. Accordingly, we propose marking the range edge at the mean position of the hull, the 'connectivity limit' of the species. Theoretical considerations suggest that the position of the connectivity limit is statistically more reliable than those limits that are delineated according to the outermost occurrences, and the connectivity-based method is broadly applicable to real-life data.

Morphological variability decreases in populations living in less suitable environments and close to the range edges

Aim: Geographic range expansion depends on ecological and evolutionary processes that may hamper local adaptations in populations living at range edges by constraining phenotypic variability. This study investigates the spatial patterns of the intraspecific variability of skull traits throughout the geographic range of a marsupial from the Brazilian Atlantic Forest. We aimed to answer whether the distance from the range edge and the environmental suitability explain the geographic variation of morphological variability of the species. Location: Atlantic Forest, Brazil. Taxon: Marmosops incanus (Didelphimorphia, Didelphidae). Methods: We analysed adult specimens deposited in the main biological collections in southeastern Brazil. The morphological variability extent and integration within populations were characterised by 13 linear measures of the skull, using a multivariate approach. Environmental suitability for the species' occurrence was estimated by Ecological Niche Models, using climatic and vegetation productivity as predictors and three different modelling methods. Distance from the range edge was calculated based on the minimum linear distance between populations and the closest range limit. We fitted linear regressions and selected the best models that explained the spatial variation of morphological variability based on the Akaike information criterion. Results: The extent of morphological variability of M. incanus is positively correlated with morphological integration and increases with local environmental suitability and distance from the range edges. However, the relationship between morphological variability and environmental suitability depends on the niche modelling method. Main conclusions: Unfavourable environmental conditions constrain morphological variability within populations of the Gray slender opossum and may hamper local adaptation in peripheral populations living in less suitable environments. In addition to environmental conditions, geographic location of populations also plays an important role in phenotypic variability among populations. We stress the boundary effect of the species range on the local adaptation of peripheral populations and its possible consequences for the range expansion dynamics.

Data from: Regional variation in climate change alters the range-wide distribution of colour polymorphism in a wild bird

According to Gloger's rule animal colouration is expected to be darker in wetter and warmer climates. Such environmental clines are predicted to occur in colour polymorphic species and to be shaped by selection if colour morphs represent adaptations to different environments. We studied if the distribution of the colour polymorphic tawny owl (Strix aluco) morphs (a pheomelanic brown and a pale grey) across Europe follow the predictions of Gloger's rule and if there is a temporal change in the geographical patterns corresponding to regional variations in climate change. We used data on tawny owl museum skin specimen collections. First, we investigated long-term spatiotemporal variation in the probability of observing the colour morphs in different climate zones. Second, we studied if the probability of observing the colour morphs was associated with general climatic conditions. Third, we studied if weather fluctuations prior the finding year of an owl explains colour morph in each climate zone. The brown tawny owl morph was historically more common than the grey morph in every studied climate zone. Over time the brown morph has become rarer in the temperate and Mediterranean zone, whereas it has first become rarer but then again more common in the boreal zone. Based on general climatic conditions winter and summer temperature were positively and negatively associated with proportion of brown morph, respectively. Winter precipitation was negatively associated with proportion of brown morph. The effects of five-year means of weather on the probability to observe a brown morph differed between climate zones, indicating region dependent effect of climate change and weather on tawny owl colouration. To conclude, tawny owl colouration does not explicitly follow Gloger's rule, implying a time and space dependent complex system shaped by many factors. We provide novel insights in how the geographic distribution of pheomelanin-based colour polymorphism is changing.

Data for: Defining usual oral temperature ranges in outpatients using an unsupervised learning algorithm

Importance: Although oral temperature is commonly assessed in medical examinations, the range of usual or "normal" temperature is poorly defined. Objective: To determine normal oral temperature ranges by age, sex, height, weight and time of day. Design: We applied a filtering algorithm (LIMIT) to 10 years of outpatient temperature measurements. LIMIT iteratively removed encounters with primary diagnoses overrepresented in the tails of the temperature distribution, leaving only those diagnoses unrelated to temperature. Mixed effects modeling was applied to the remaining temperature measurements to identify independent predictors of normal oral temperature and to generate individualized normal temperature ranges. Setting: Single large medical care system, divisions of Internal Medicine and Family Medicine. Participants: All adult outpatient encounters that included temperature measurements, April 2008 - June 2017. Exposures: Primary diagnoses and medications, age, sex, height, weight, time of day and month, abstracted from each outpatient encounter. Main outcomes and measures: Normal temperature ranges by age, sex, height, weight, and time of day. Results: From 618,306 encounters, 36% were removed by LIMIT because they included diagnoses or medications that fell disproportionately in the tails of the temperature distribution. The encounters removed due to overrepresentation in the upper tail were primarily linked to infectious diseases (76.81% of all removed encounters); type 2 diabetes mellitus was the only diagnosis removed for over-representation in the lower tail (15.71% of all removed encounters). Prior to running LIMIT, the mean overall oral temperature was 36.71°C (±0.43); following LIMIT, the mean temperature was 36.64°C (±0.35). Using mixed effects modeling, age, sex, height, weight and time of day accounted for 6.86% (overall) and up to 25.52% (per subject) of the observed variability in temperature. Mean normal oral temperature did not reach 37°C for any subgroup; the upper 99th percentile ranged from 36.8°C (tall underweight old men in the morning) to 37.9°C (short obese young women in the afternoon). Conclusion and relevance: Normal oral temperature varies in a predictable manner based on sex, age, height, weight and time of day, allowing individualized normal temperature ranges to be established.

Parasitism rate differs between herbivore generations in the univoltine, but not bivoltine, range

With climate change, plant-feeding insects might increase their number of annual generations (voltinism). However, to what degree the emergence of a new herbivore generation affects the parasitism rate has not been explored. We performed a field experiment to test whether the parasitism rate differs between the first and the second generation of a specialist leaf miner (Tischeria ekebladella), both in the naturally univoltine and bivoltine parts of the leaf miner's distribution. We found an interactive effect between herbivore generation and geographical range on the parasitism rate. The parasitism rate was higher in the first compared to the second host generation in the part of the range that is naturally univoltine, whereas it did not differ between generations in the bivoltine range. Our experiment highlights that shifts in herbivore voltinism might release top-down control, with major consequences for natural and applied systems.

opencc-by-4.0Jul 2023View details →

Germination of range-wide Quercus suber L. populations

This database contains the individual germination times and rates of cork oak acorns under controlled conditions. Acorns were collected in 2021 from 9 natural populations comprising 10 mother trees per population in France, Italy, Portugal and Spain. The acorns were weighed per mother tree before being sown under controlled conditions at 15, 20 and 25°C. The final size of this database is 718 individual entries which include seed mass, germination rates and timing, and the emergence of the first leaf. The populations from which the acorns were collected are geo-referenced and the mother trees are identified by their circumference and dbh.

opencc-by-4.0Jul 2023View details →

Raw Data Examples for Close-Range Photogrammetry of Replicative Experiments on Ground Stone Tools

The data presented in this study pertains to the experimental collection built to verify the applicability of close-range photogrammetry to ground stone tools (GSTs). GS17 is a sandstone slab collected from the Fiora River in Manciano, Italy, where sandstone of Miocene formation outcrops. This stone is primarily composed of quartz grains embedded in abundant carbonate cement. It was utilized as a GST in replicative experiments, paired with an active tool from the same provenience, and subjected to 2 hours of Rumex crispus achenes grinding. Photogrammetric techniques based on Structure-from-Motion and Multi-View Stereo reconstruction were employed to generate the 3D models of the tool at different stages of the replicative use. We recorded the geometry of the GST before (referred to as T0) and after use (T4) to later compare and assess the change in object geometry during the transformation of vegetal resources, thereby facilitating our understanding of archaeological tools. This dataset comprises the pictures required for the elaboration of the GS17 models at T0 and T4, as well as the data necessary for calibration.

opencc-zeroAug 2023View details →

How to select appropriate hue ranges for sequential color schemes on choropleth maps? A quantitative evaluation using map reading experiments

We propose map reading experiments to quantitatively evaluate the selection of hue ranges for sequential color schemes on choropleth maps. In these experiments, 60 sequential color schemes with six base hues and ten hue ranges were employed as experimental color schemes, and a total of 414 college students were invited to complete identification, comparison, and ranking tasks. Both controlled and real-map experiments were performed, each involving a web-based survey and an eye-tracking experiment. In the controlled experiments, the shapes of the map objects were relatively regular, and attribute data were randomized. In contrast, the shapes were complex in real-map experiments, and real data were employed. Our findings show that widely used color schemes with a hue range of 0º yield poor performance in all tasks; 15º hue ranges yield good performance in the comparison and ranking tasks but poor performance in the identification task. For large hue ranges of 120-360º, participants showed good performance in the identification task but poor performance in the comparison and ranking tasks. For 30-60º hue ranges, participants achieved excellent performance in the comparison and ranking tasks and acceptable performance in the identification task. We also found that the ratings of 0-60º ranges were high.

opencc-zeroSep 2023View details →

Data from: Assessing the local adaptative changes associated with range expansion of the pink stem borer

Understanding the genetic basis of adaptive evolution following habitat expansion can have important implications for pest management. The pink stem borer (PSB), Sesamia inferens (Walker), is a destructive pest of rice that historically restricted to regions south of N34° latitude in China. However, with changes in global climate and farming practices, the distribution of this moth has progressively exceeded its traditional limit of 34° N and encompassed most regions in North China. However, the evolutionary processes and local adaptative changes of this species, are not yet fully understood. Here, we employed genome resequencing to genotype over 1 million of high‐quality SNPs and 20,000 SVs from 14 geographical populations across China. Three highly differentiated genetic groups were formed, corresponding to Northern, Southern China regions and Yunnan-Guizhou Plateau. The pairwise genetic distance between locations was highly correlated with geographic and environmental distance. Our estimates of evolutionary history indicate asymmetric migration with varying population sizes across three genetic groups. Selective sweep analyses highlight the strong selected insect cuticle GRP genes enhanced desiccation adaptability of the northern group and SETMAR gene associated with range expansion and local adaptation in Shandong population. Based on an integrated analysis of transcriptome and enGWAS, we also identified the CYP321A7 gene was involved in the PSB adaption to desiccation climates. Our findings revealed the phylogeography, demographic dynamics and evolutionary forces of PSB and identified potential candidate genes to explore the genetic adaptation to novel environments, which have significant implications for the development of effective strategies to control this pest.

opencc-zeroSep 2023View details →

Data for: Climate change alone cannot explain boreal caribou range recession in Quebec since 1850

The contraction of species range is one of the most significant symptoms of biodiversity loss worldwide. While anthropogenic activities and habitat alteration are major threats for several species, climate change has not been overlooked either. For species at risk, differentiating the effects of human disturbances and climate change on past and current range transformations is an important step towards improved conservation strategies. We paired historical range maps with global atmospheric reanalyses from different sources (ERA5, CERA-20C, 20CRv3) to assess the potential effects of recent climate change on the observed northward contraction of the distribution range of boreal populations of woodland caribou (Rangifer tarandus caribou) in Quebec (Canada) since 1850. We quantified these effects by highlighting the discrepancies between different southern limits of the caribou's range (used as references) observed in the past and reconstitutions obtained through the hindcasting of the climate conditions within which caribou are currently found. Hindcasted southern limits moved ~105 km north over time under all reanalysis datasets, a trend drastically different from the ~620 km reported for observed southern limits since 1850. The differences in latitudinal shift through time between the observed and hindcasted southern limits of distribution suggest that caribou range recession should have been only 17% of what has been observed since 1850 if recent climate change had been the only disturbance driver. This limited impact of climate reinforces the scientific consensus stating that caribou range recession in Quebec is mainly caused by anthropogenic drivers (i.e. logging, development of the road network, agriculture, urbanization) that have modified the structure and composition of the forest over the past 160 years, paving the way for habitat-mediated apparent competition and overharvesting. Our results also call for a better consideration of past distribution ranges in models aiming at projecting future distributions, especially for endangered species.

opencc-by-4.0Jan 2021View details →

FIGURE 1 Ptomaphagus thebeatles n in Ptomaphagus thebeatles n. sp., a previously unrecognized beetle from Europe, with remarks on urban taxonomy and recent range expansion (Coleoptera: Leiodidae)

FIGURE 1 Ptomaphagus thebeatles n. sp., habitus. Drawing by Erik-Jan Bosch.

opencc-by-4.0Oct 2014View details →

Fig. 1 in Distributional range of the South African maritime spider-egg parasitoid wasp, Echthrodesis lamorali (Hymenoptera: Platygastridae: Scelioninae)

Fig. 1. Lateral view of the habitus of a female Echthrodesis lamorali Masner specimen.

opencc-zeroSep 2023View details →

Effect of climate-change-induced increases on the range of rice-barley double cultivation on the intermediate egret

Intensification of cultivation methods and land use types, particularly in the face of climate change, has steadily weakened the habitat function of rice fields for waterbirds. Intermediate egrets (Ardea intermedia) are highly dependent on rice field habitats. Here, we examine the effect of a shift from rice monoculture to rice–barley double cultivation on the use of rice fields by intermediate egrets in South Korea. Rice-barley double cultivation has been increasing steadily in the southern region of South Korea due to changes in the rice growth period under climate change and maximization of economic benefits. We studied rice fields to determine the effect of the rice-barely double cultivation area on the abundance of intermediate egrets on the regional scale and their potential distribution pattern in response to double cultivation in relation to climate change using national-scale climate, altitude, and land cover data from May 1 to June 23, 2018. Compared to the irrigation practices used for rice monoculture, irrigation was stopped for some time in rice-barley double cultivation prior to planting, compromising the role of rice fields as a food ground for intermediate egrets. The potential abundance of intermediate egrets rapidly decreased by half when the double cultivation area increased to >40% of the total rice-field area, and was less than one individual if the area increased to >80%. Furthermore, according to climate change projections, by 2100, the double cultivation area would account for 75.74% of the predicted range of intermediate egret foraging ground. Synthesis and applications. Double cultivation areas should be <40% of existing rice fields to minimize the impact of the change in cultivation practices. This approach can also convert rice fields to other types of land use. Consequently, appropriate conservation and management measures may be developed to maintain suitable habitats despite rapidly changing cultivation practices resulting from climate change.

Data from: Divergent mechanisms of reduced growth performance in Betula ermanii saplings from high-altitude and low-latitude range edges

The reduced growth performance of individuals from range edges is a common phenomenon in various taxa, and considered to be an evolutionary factor that limits the species' range. However, most studies did not distinguish between two mechanisms that can lead to this reduction: genetic load and adaptive selection to harsh conditions. This study investigated the climatic and genetic factors underlying the growth performance of Betula ermanii saplings transplanted from 11 populations including high-altitude edge and low-latitude edge population using RAD-seq analysis. For 11 B. ermanii populations in wide-latitude range of Japan, we estimated gene diversity, nucleotide diversity, the coefficients of linkage disequilibrium, genetic differentiation between populations, population structure as well as the relatedness coefficient from SNPs. As a result, the low-latitude edge population exhibited a high level of linkage disequilibrium, low genetic diversity, a distinct genetic composition from the other populations, and a high relatedness coefficient. This data contains two SNPs datas (vcf files) used in these analysis. We analyzed SNPs data separately for 8 planting sites. Then each tarball contains 8 separate vcf files. One tarball named "vcfAfterFiltering" contains vcf files after SNP filtering steps used for the calculation of the coefficients of linkage disequilibrium. Another tarball named "vcfAfterLDPruning" contains vcf files after SNP filtering and before LD-based pruning used for the calculation of other genetic parameters.

Seasonal roost selection of wild turkeys at their northern range edge

Wild turkeys (Meleagris gallopavo) are diurnally active birds that spend the dark hours roosting in trees. We tested the hypothesis that multiple benefits exist for roost tree selection by wild turkeys, including thermoregulation, resource acquisition, and protection from predators. We compared 48 roost trees used by eastern wild turkeys (M. g. silvestris) in Ontario, Canada to 48 non-roost trees sampled contemporaneously during 2017-2019 to determine roost site selection between seasons. Mean (± SE) roost tree height (21.4 ± 0.8 m) was taller than non-roost trees (18.2 ± 0.8 m), and roost trees were also larger in diameter at breast height (58.1 ± 5.5 cm versus 38.7 ± 3.1 cm). Using ibuttons to collect microclimate temperatures at the tree, we found that mean temperature (± SE) of a deciduous roost (14.5 ± 0.1°C) was higher than temperature at either a coniferous roost (13.9 ± 0.1°C) or ambient temperature (13.2 ± 0.1°C) during the summer months. In winter however, we did not find any relationship between temperature and tree type. Roosts were closer to buildings (150.8 ± 26.0 m) in the winter compared to summer and year-round roosts, and winter roosts were also farther away from crops (395.2 ± 63.7 m) compared to roost sites used year-round. Summer roosts were closer to roads (143 ± 36.3 m) than the roosts in the winter and roosts used year-round. Our data suggest that thermoregulation is not the driving force behind roost selection; instead, predator avoidance appears to play the most important role, with some weaker evidence in support of proximity to resources.

opencc-by-4.0Oct 2023View details →

HYPHOP: a tool for high-altitude, long-range monitoring of hydrogen peroxide and higher organic peroxides in the atmosphere

We provide here the supporting dataset for our study on measurement performance of the HYPHOP monitor during the CAFE-Brazil aircraft campaign in 2022/23.

opencc-by-4.0Oct 2023View details →

Data for "Nishimori's cat: stable long-range entanglement from finite-depth unitaries and weak measurements"

Open the record for dataset details and reuse information.

Understanding habitat selection of range-expanding populations of large carnivores: 20 years of grey wolves (Canis lupus) recolonizing Germany

Aim: The non-stationarity in habitat selection of expanding populations poses a significant challenge for spatial forecasting. Focusing on the grey wolf (Canis lupus) natural recolonization of Germany, we compared the performance of different distribution modelling approaches for predicting habitat suitability in unoccupied areas. Furthermore, we analysed whether grey wolf showed non-stationarity in habitat selection in newly colonized areas, which will impact the predictions for potential habitat. Location: Germany Methods: Using telemetry data as presence points, we compared the predictive performance of five modelling approaches based on combinations of distribution modelling algorithms –GLMM, MaxEnt, and ensemble modelling– and two background point selection strategies. We used a homogeneous Poisson point process to draw background points from either the minimum convex polygons derived from telemetry or the whole area known to be occupied by wolves. Models were fit to the data of the first years and validated against independent data representing the expansion of the species. The best-performing approach was then used to further investigate non-stationarity in the species' response in spatiotemporal restricted datasets that represented different colonization steps. Results: Whilst all approaches performed similarly when evaluated against a subset of the data used to fit the models, the ensemble model based on integrated data performed best when predicting range expansion. Models for subsequent colonization steps differed substantially from the global model, highlighting the non-stationarity of wolf habitat selection towards human disturbance during the colonization process. Main conclusions: While telemetry-only data overfitted the models, using all available datasets increased the reliability of the range expansion forecasts. The non-stationarity in habitat selection pointed to wolves settling in the best areas first, and filling in nearby lower-quality habitat as the population increases. Our results caution against spatial extrapolation and space-for-time substitutions in habitat models, at least with expanding species.

Machine learning suggests small size is a key determinant of plasmid host range

Plasmids mediate gene exchange across taxonomic barriers through conjugation, shaping bacterial evolution for billions of years. While plasmid mobility can be harnessed for genetic engineering and drug-delivery applications, rapid plasmid-mediated spread of resistance genes has rendered most clinical antibiotics useless, posing an existential threat to human society. To solve this urgent problem, we must understand how plasmids spread across bacterial communities. Here, we applied machine-learning models to identify features that determine plasmid host range. We assembled an up-to-date dataset of more than thirty thousand bacterial plasmids, separated them into 1125 clusters, and assigned a distribution possibility score, which takes host distribution of each taxonomic rank and the sampling bias of the existing sequencing data into account, for each cluster. Using this score and an optimized plasmid feature pool, we built a model stack consisting of DecisionTreeRegressor, EvoTreeRegressor, and LGBMRegressor as base models and LinearRegressor as a meta-learner. Our analysis reveals that a short sequence length is most important for successful plasmid spread, followed by P-loop NTPases, mobility factors, and β-lactamases. Ours and other recent results suggest that small plasmids broaden their range by evading host defenses and using alternative modes of transfer instead of autonomous conjugation.