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13,064 results for “predictions”
Data from: Functional traits of marine macrophytes predict primary production
The relationship between community structure and the functioning of ecosystems is the subject of ongoing debate. Biological or functional trait-based approaches that capture life strategy, morphology and behavioural characteristics have received far less attention than taxonomic diversity in this context, despite their more intuitive link to ecosystem functioning. Macrophyte primary production underpins aquatic food webs, regulates benthic and pelagic ecosystems and is a key aspect of the global carbon cycle. This study spans a range of aquatic biomes across Europe and aims to examine potential for predicting primary production of macrophyte communities based on the functional traits of species and identify the traits that are the most informative indicators of macrophyte production. Macrophyte primary production was assessed based on the oxygen production of the whole community, linked to biomasses of selected biological traits derived of its component species and analysed using the novel boosted regression trees modelling technique. Results showed that functional traits derived from macrophyte community data explained most of the variation in primary production of macrophyte communities without the need to incorporate environmental data on the habitats. Macrophyte primary production was influenced by a combination of tolerance, morphology and life habit traits; however tolerance traits contributed most of variability in macrophyte primary production when all traits were analysed jointly. This study also showed the existence of trait clustering as the studied trait categories were not fully independent; strong interlinkages between and within trait categories emerged. Our study suggests that functional trait analysis captures different aspects of ecosystem functioning and thereby enables assessing primary production of macrophyte communities over geographically distinct areas without extensive taxonomic and environmental data. This could result in a novel framework through which a simplification of the general procedure of production estimations and comparisons across environmental gradients can be achieved.
Data from: Wintering areas predict age-related breeding phenology in a migratory passerine bird
Understanding connections between breeding, stopover and wintering grounds for long-distance migratory birds can provide important insight into factors influencing demography and the strength of carry-over effects among various periods of the annual cycle. Using previously described, multi-isotope (δ13C, δ15N, δ2H) feather isoscapes for Africa, we identified the most probable wintering areas for house martins (Delichon urbica) breeding at Badajoz in southwestern Spain. We identified two most-probable wintering areas differing in latitude in West Africa. We found that the probability to winter in the northern region was related to age and sex of individuals. Specifically, experienced males (i.e., two years or older) winter in the northern area with a greater probability than experienced females, whereas first-year females winter in the northern area with a greater probability than first-year males. In addition, wintering area was correlated with breeding phenology, with individuals wintering in the northern area initiating their clutches earlier than those wintering in the southern area. For birds wintering in the northern area, there was no relationship between age and clutch initiation date. In contrast, young birds wintering in the southern area initiated their clutches earlier than experienced birds wintering in this area. There was no significant correlation between wintering area and clutch size or the number of fledglings produced. We hypothesize that the relationship among social status, population density and winter habitat quality should be the most important driver of the carry-over effect we found for this population
Data from: Predicting bird song from space
Environmentally imposed selection pressures are well known to shape animal signals. Changes in these signals can result in recognition mismatches between individuals living in different habitats, leading to reproductive divergence and speciation. For example, numerous studies have shown that differences in avian song may be a potent prezygotic isolating mechanism. Typically, however, detailed studies of environmental pressures on variation in animal behavior have been conducted only at small spatial scales. Here, we use remote-sensing data to predict animal behavior, in this case, bird song, across vast spatial scales. We use remotely sensed data to predict the song characteristics of the little greenbul (Andropadus virens), a widely distributed African passerine, found across secondary and mature rainforest habitats and the rainforest-savanna ecotone. Satellite data that captured ecosystem structure and function explained up to 66% of the variation in song characteristics. Song differences observed across habitats, including those between human-altered and mature rainforest, have the potential to lead to reproductive divergence, and highlight the impacts that both natural and anthropogenic change may have on natural populations. Our approach offers a novel means to examine the ecological correlates of animal behavior across large geographic areas with potential applications to both evolutionary and conservation biology.
Data from: A framework for developing ecosystem-specific nutrient criteria: integrating biological thresholds with predictive modeling
We present a novel ecosystem-specific framework for developing nutrient criteria from biological thresholds and predictive modeling (BTPM) and an application of this framework to lakes in Michigan, U.S. The four main components for the BTPM framework are: (1) to predict each ecosystem s expected nutrient concentration in the absence of human effects using a predictive model, (2) to identify important biological thresholds along a nutrient gradient (i.e., biological [BIO] benchmarks), (3) to determine each ecosystem s current nutrient concentration, and (4) to use the above information to derive a nutrient criterion for each ecosystem using the BTPM algorithm. The BTPM framework is extremely flexible in that it can be applied to any aquatic ecosystem type or nutrient and the four components can be implemented in a variety of ways. Our BTPM framework has two additional features: it recognizes that prior to human disturbance, ecosystems varied in their natural nutrient concentrations, and it incorporates risk into the decision-making process. In the simplest scheme, a nutrient criterion is set at a BIO benchmark greater than the expected nutrient concentration. However, to protect ecosystems more conservatively, a criterion is set at current lake nutrient concentrations if current is less than the BIO benchmark. In our application of the BTPM framework, we developed total phosphorus (TP) criteria for a diverse set of 374 lakes in MI. The expected lake TP concentrations in the absence of human effects ranged from 3 µg L-1 to 24 µg L-1, suggesting that a single criterion approach would not be appropriate.We found two predominant benchmarks in the biological data along the TP gradient, one for zooplankton metrics at 8 µg L-1, and one for phytoplankton metrics at 18 µg L-1. We present the sequence of analyses and decisions that could be used to apply this approach in a management context using Michigan lakes as an example.
Data from: The predictability of genomic changes underlying a recent host shift in Melissa blue butterflies
Despite accumulating evidence that evolution can be predictable, studies quantifying the predictability of evolution remain rare. Here, we measured the predictability of genome-wide evolutionary changes associated with a recent host shift in the Melissa blue butterfly (Lycaeides melissa). We asked whether and to what extent genome-wide patterns of evolutionary change in nature could be predicted (1) by comparisons among instances of repeated evolution, and (2) from SNP $\times$ performance associations in a lab experiment. We delineated the genetic loci (SNPs) most strongly associated with host use in two L. melissa lineages that colonized alfalfa. Whereas most SNPs were strongly associated with host use in none or one of these lineages, we detected a ~two-fold excess of SNPs associated with host use in both lineages. Similarly, we found that host-associated SNPs in nature could also be partially predicted from SNP $\times$ performance (survival and weight) associations in a lab rearing experiment. But the extent of overlap, and thus degree of predictability, was somewhat reduced. Although we were able to predict (to a modest extent) the SNPs most strongly associated with host use in nature (in terms of parallelism and from the experiment), we had little to no ability to predict the direction of evolutionary change during the colonization of alfalfa. Our results show that different aspects of evolution associated with recent adaptation can be more or less predictable, and highlight how stochastic and deterministic processes interact to drive patterns of genome-wide evolutionary change
Data from: Efficiency of genomic prediction across two Eucalyptus nitens seed orchards with different selection histories
Genomic selection is expected to enhance the genetic improvement of forest tree species by providing more accurate estimates of breeding values through marker-based relationship matrices compared with pedigree-based methodologies. When adequately robust genomic prediction models are available, an additional increase in genetic gains can be made possible with the shortening of the breeding cycle through elimination of the progeny testing phase and early selection of parental candidates. The potential of genomic selection was investigated in an advanced Eucalyptus nitens breeding population focused on improvement for solid wood production. A high-density SNP chip (EUChip60K) was used to genotype 691 individuals in the breeding population, which represented two seed orchards with different selection histories. Phenotypic records for growth and form traits at age six, and for wood quality traits at age seven were available to build genomic prediction models using GBLUP which were compared to the traditional pedigree-based alternative using BLUP. GBLUP demonstrated that breeding value accuracy would be improved and substantial increases in genetic gains towards solid wood production would be achieved. Cross-validation within and across two different seed orchards indicated that genomic predictions would likely benefit in terms of higher predictive accuracy from increasing the size of the training data sets through higher relatedness and better utilization of LD
Data from: Corridors or risk? movement along, and use of, linear features vary predictably among large mammal predator and prey species
<p>1. Space-use behaviour reflects trade-offs in meeting ecological needs and can have consequences for individual survival and population demographics. The mechanisms underlying space-use can be understood by simultaneously evaluating habitat selection and movement patterns, and fine-resolution locational data are increasing our ability to do so. 2. We use high-resolution location data and an integrated step-selection analysis to evaluate caribou, moose, bear, and wolf habitat selection and movement behavior in response to anthropogenic habitat modification, though caribou data were limited. Space-use response to anthropogenic linear features (LFs) by predators and prey are hypothesized to increase predator hunting efficiency and are thus believed to be a leading factor in woodland caribou declines in western Canada. 3. We found that all species moved faster while on LFs. Wolves and bears were also attracted towards LFs, whereas prey species avoided them. Predators and prey responded less strongly and consistently to natural features such as streams, rivers and lakeshores. These findings are consistent with the hypothesis that LFs facilitate predator movement and increase hunting efficiency, while prey perceive such features as risky. 4. Understanding the behavioural mechanisms underlying space-use patterns is important in understanding how future land-use may impact predator-prey interactions. Explicitly linking behaviour to fitness and demography will be important to fully understand the implications of management strategies.</p>
Data from: Ecological interactions and coexistence are predicted by gene expression similarity in freshwater green algae
Phenotypic variation controls the species interactions which determine whether or not species coexist. Long-standing hypotheses in ecology and evolution posit that phenotypic differentiation enables coexistence by increasing the size of niche differentiation. This hypothesis has only been tested using macroscopic traits to date, but niche differentiation, particularly of microscopic organisms, also occurs at the molecular and metabolic level. We examined how phenotypic variation that arises at the level of gene expression over evolutionary time affects phytoplankton species interactions and coexistence. We predicted that similarity in gene expression among species would decline with phylogenetic distance, and that reduced similarity in gene expression would weaken competition, increase facilitation and promote coexistence. To test this, we grew eight species of freshwater green algae in monocultures and bicultures for 46 days in a laboratory microcosm experiment. We quantified the strength of species interactions by: (i) fitting Lotka–Volterra models to time-series densities and estimating interaction coefficients, and (ii) calculating relative densities that compare species' steady-state densities in biculture to those in monoculture. We used Illumina high throughput sequencing to quantify the expression of 1253 families of homologous genes, including a set of 17 candidate genes that we hypothesized a priori to be involved in competition or facilitation. Synthesis. We found that closely related species had greater similarity in gene expression than did distantly related species, but as gene expression became more similar, species experienced weaker competition or greater facilitation, and were more likely to coexist. We identified gene functional categories that were uniquely differentially regulated in association with particular species interaction types. Contrary to common thinking in ecology and evolution, similarity in gene expression, and not differentiation, was associated with weaker competition, facilitation and coexistence.
Data from: Paleo-drainage basin connectivity predicts evolutionary relationships across three southeast Asian biodiversity hotspots
Understanding factors driving diversity across biodiversity hotspots is critical for formulating conservation priorities in the face of ongoing and escalating environmental deterioration. While biodiversity hotspots encompass a small fraction of Earth's land surface, more than half the world's plants and two-thirds of terrestrial vertebrate species are endemic to these hotspots. Tropical Southeast Asia displays extraordinary species richness, encompassing four biodiversity hotspots, though disentangling multiple potential drivers of species richness is confounded by the region's dynamic geological and climatic history. Here, we use multi-locus molecular genetic data from dense multi-species sampling of freshwater fishes across three biodiversity hotspots, to test the effect of Quaternary climate change and resulting drainage rearrangements on aquatic faunal diversification. While Cenozoic geological processes have clearly shaped evolutionary history in Southeast Asian halfbeak fishes, we show that paleo-drainage re-arrangements resulting from Quaternary climate change played a significant role in the spatiotemporal evolution of lowland aquatic taxa, and provides priorities for conservation efforts.
Data from: An extensive suite of functional traits distinguishes wet and dry Hawaiian forests and enables prediction of species vital rates
1. The application of functional traits to predict and explain plant species' distributions and vital rates has been a major direction in functional ecology for decades, yet numerous physiological traits have not yet been incorporated into the approach. 2. Using commonly measured traits such as leaf mass per area (LMA) and wood density (WD), and additional traits related to water transport, gas exchange and resource economics, including leaf vein, stomatal, and wilting traits, we tested hypotheses for Hawaiian wet montane and lowland dry forests (MWF and LDF respectively): (1) forests would differ in a wide range of traits as expected from contrasting adaptation; (2) trait values would be more convergent among dry than wet forest species due to the stronger environmental filtering; (3) traits would be inter-correlated within "modules" supporting given functions; (4) relative growth rate (RGR) and mortality rate (m) would correlate with a number of specific traits, with (5) stronger relationships when stratifying by tree size, and (6) RGR and m can be strongly explained from trait-based models. 3. The MWF species' traits were associated with adaptation to high soil moisture and nutrient supply and greater shade tolerance whereas the LDF species' traits were associated with drought tolerance. Thus, on average, MWF species achieved higher maximum heights than LDF species and had leaves with larger epidermal cells, higher maximum stomatal conductance and CO2 assimilation rate, lower vein lengths per area, higher saturated water content and greater shrinkage when dry, lower dry matter content, higher phosphorus concentration, lower nitrogen to phosphorus ratio, high chlorophyll to nitrogen ratio, high carbon isotope discrimination, high stomatal conductance to nitrogen ratio, less negative turgor loss point, and lower WD. Functional traits were more variable in the MWF than LDF, were correlated within modules, and predicted species' RGR and m across forests, with stronger relationships when stratifying by tree size. Models based on multiple traits predicted vital rates across forests (R2 = 0.70-0.72; P < 0.01). 4. Our findings are consistent with a powerful role of broad suites of functional traits in contributing to forest species' distributions, integrated plant design, and vital rates.
Data from: Seasonally varying predation behaviour and climate shifts are predicted to affect predator-prey cycles
The functional response of some predator species changes from a pattern characteristic for a generalist to that for a specialist according to seasonally varying prey availability. Current theory does not address the dynamic consequences of this phenomenon. Since season length correlates strongly with altitude and latitude and is predicted to change under future climate scenarios, including this phenomenon in theoretical models seems essential for correct prediction of future ecosystem dynamics. We develop and analyze a two-season model for the great horned owl (Bubo virginialis) and snowshoe hare (Lepus americanus). These species form a predator-prey system in which the generalist to specialist shift in predation pattern has been documented empirically. We study the qualitative behavior of this predator-prey model community as summer season length changes. We find that relatively small changes in summer season length can have a profound impact on the system. In particular, when the predator has sufficient alternative resources available during the summer season, it can drive the prey to extinction, there can be coexisting stable states, and there can be stable large-amplitude limit cycles coexisting with a stable steady state. Our results illustrate that the impacts of global change on local ecosystems can be driven by internal system dynamics and can potentially have catastrophic consequences.
Data from: Selective logging intensity in an East African rain forest predicts reductions in ant diversity
As natural forest ecosystems increasingly face pressure from deforestation, it is ever more important to understand the impacts of habitat fragmentation and degradation on biodiversity. Most studies of anthropogenic change in the tropics come from Southeast Asia and South America, and impacts of habitat modification are often taxon-specific. Here we empirically assessed the impact of habitat fragmentation and recent (within 25 years) and historic (>25 years ago) selective logging on the diversity of ants in the Kakamega rain forest in western Kenya, and asked whether these forms of degradation interact as multiple stressors. We found that the severity of recent selective logging was negatively related to overall species richness and abundance as well as the richness and abundance of forest specialists, but found no detrimental effect of past selective logging or habitat fragmentation on ant diversity, although habitat fragment size was correlated with estimated species richness. There was also no effect of any form of habitat degradation on the richness or abundance of open habitat specialists, even though these species often exploit niches created in disturbed environments. Ultimately, this study reveals the detrimental impact of even moderate forms of habitat degradation on insect biodiversity in the understudied African rain forests.
Data from: Differences in offspring size predict the direction of isolation asymmetry between populations of a placental fish
Crosses between populations or species often display an asymmetry in the fitness of reciprocal F1 hybrids. This pattern, referred to as isolation asymmetry or Darwin's Corollary to Haldane's rule, has been observed in taxa from plants to vertebrates, yet we still know little about which factors determine its magnitude and direction. Here we show that differences in offspring size predict the direction of isolation asymmetry observed in crosses between populations of a placental fish, Heterandria formosa. In crosses between populations with differences in offspring size, high rates of hybrid inviability occur only when the mother is from a population characterized by small offspring. Crosses between populations that display similarly sized offspring, whether large or small, do not result in high levels of hybrid inviability in either direction. We suggest this asymmetric pattern of reproductive isolation is due to a disruption of parent-offspring coadaptation that emerges from selection for differently sized offspring in different populations.
Herbivore phenology can predict response to changes in plant quality by livestock grazing
<p>Livestock grazing can have a strong impact on herbivore abundance, distribution and community. However, not all species of herbivores respond the same way to livestock grazing, and we still have a poor understanding of the underlying mechanisms driving these differential responses. Here, we investigate the effect of light intensity cattle grazing on the abundance of two grasshoppers (<i>Euchorthippus cheui</i> and <i>E. unicolor</i>) that co-occur in the same grasslands and feed on the same food plant (the dominant grass <i>Leymus chinensis</i>). The two grasshopper species differ in phenology so that their peak abundances are separated into early- and late-growing seasons. We used an exclosure experiment to monitor grasshopper abundance and food quality in the field under grazed and ungrazed conditions, and performed feeding trials to examine grasshopper preference for grazed or ungrazed food plants in the laboratory. We found that the nitrogen content of <i>L. chinensis</i> leaves continuously declined in the ungrazed areas, but was significantly enhanced by cattle grazing over the growing season. Cattle grazing facilitated the early-season grasshopper <i>E. cheui, </i>whereas it suppressed<i> </i>the late-season grasshopper <i>E. unicolor</i>. Moreover, feeding trials showed that <i>E. cheui</i> preferred <i>L. chinensis</i> from grazed plots, while <i>E. unicolor</i> preferred the leaves from ungrazed plots. We conclude that livestock grazing has opposite effects on the two grasshopper species, and that these effects may be driven by grazing-induced chagnes in plant nutrient content and the unique nutritional niches of the grasshoppers. These results suggest that insects that belong to the same guild can have opposite nutrient requirements, related to their distinct phenologies, and that this can ultimately affect their response to cattle grazing. Our results show that phenology may link insect physiological needs to local resource availabilities, and should be given more attention in future work on interactions between large herbivores and insects.</p>
Data from: Stronger social bonds do not always predict greater longevity in a gregarious primate
In group-living species, individuals often have preferred affiliative social partners, with whom ties or bonds can confer advantages that correspond with greater fitness. For example, in adult female baboons and juvenile horses, individuals with stronger or more social ties experience greater survival. We used detailed behavioral and life history records to explore the relationship between tie quality and survival in a gregarious monkey (Cercopithecus mitis stuhlmanni), while controlling for dominance rank, group size, and life history strategy. We used Cox proportional hazards regressions to model the cumulative (multi-year) and current (single-year) relationships of social ties and the hazard of mortality in 83 wild adult females of known age, observed 2–8 years each (437 subject-years) in eight social groups. The strength of bonds with close partners was associated with increased mortality risk under certain conditions: Females that had strong bonds with close partners that were inconsistent over multiple years had a higher risk of mortality than females adopting any other social strategy. Within a given year, females had a higher risk of death if they were strongly bonded with partners that changed from the previous year versus with partners that remained consistent. Dominance rank, number of adult female groupmates, and age at first reproduction did not predict the risk of death. This study demonstrates that costs and benefits of strong social bonds can be context-dependent, relating to the consistency of social partners over time.
Data from: Is evolution predictable? quantitative genetics under complex genotype-phenotype maps
<p>A fundamental aim of post-genomic 21st century biology is to understand the genotype-phenotype map (GPM) or how specific genetic variation relates to specific phenotypic variation. Quantitative genetics approximates such maps using linear models, and has developed methods to predict the response to selection in a population. The other major field of research concerned with the GPM, developmental evolutionary biology or evo-devo, has found the GPM to be highly nonlinear and complex. Here we quantify how the predictions of quantitative genetics are affected by the complex, nonlinear maps found in developmental biology. We found that the disagreements between predicted and observed responses to selection are common, roughly in a third of generations, systematic and due to nonlinear nature of the genotype-phenotype map. They occur at all time scales, even from one generation to the next. Our results are a step towards integrating the fields studying the GPM.</p>
Data from: Historical citizen science to understand and predict climate-driven trout decline
Historical species records offer an excellent opportunity to test the predictive ability of range forecasts under climate change, but researchers often consider that historical records are scarce and unreliable, besides the datasets collected by renowned naturalists. Here, we demonstrate the relevance of biodiversity records developed through citizen-science initiatives generated outside the natural sciences academia. We used a Spanish geographical dictionary from the mid-nineteenth century to compile over 10 000 freshwater fish records, including almost 4 000 brown trout (Salmo trutta) citations, and constructed a historical presence–absence dataset covering over 2 000 10 × 10 km cells, which is comparable to present-day data. There has been a clear reduction in trout range in the past 150 years, coinciding with a generalized warming. We show that current trout distribution can be accurately predicted based on historical records and past and present values of three air temperature variables. The models indicate a consistent decline of average suitability of around 25% between 1850s and 2000s, which is expected to surpass 40% by the 2050s. We stress the largely unexplored potential of historical species records from non-academic sources to open new pathways for long-term global change science.
Data from: Contemporary evolution of sea urchin gamete-recognition proteins: experimental evidence of density-dependent gamete performance predicts shifts in allele frequencies over time
Species whose reproductive strategies evolved at one density regime might be poorly adapted to other regimes. Field and laboratory experiments on the sea urchin Strongylocentrotus franciscanus examined the influences of the two most common sperm bindin alleles, which differ at two amino acid sites, on fertilization success. In the field experiment, the Arginine/Glycine (RG) genotype performed best at low densities and the Glycine/Arginine (GR) genotype at high densities. In the lab experiment, the RG genotype had a higher affinity with available eggs, whereas the GR genotype was less likely to induce polyspermy. These sea urchins can reach 200 years of age. The RG allele dominates in old sea urchins, whereas younger sea urchins have near equal RG and GR allele frequencies. A latitudinal cline in RG and GR genotypes is consistent with longer survival of sea urchins in the north and with predominance of RG genotypes in older individuals. The oldest sea urchins were likely conceived at low densities, before sea-urchin predators, like sea otters, were overharvested and sea urchin densities exploded off the west coast. Contemporary evolution of gamete-recognition proteins might allow species to adapt to shifts in abundances and reduces the risk of reproductive failure in altered populations.
Data from: Testing species assemblage predictions from stacked and joint species distribution models
Aim: Predicting the spatial distribution of species assemblages remains an important challenge in biogeography. Recently, it has been proposed to extend correlative species distribution models (SDMs) by taking into account (a) covariance between species occurrences in so-called joint species distribution models (JSDMs) and (b) ecological assembly rules within the SESAM (spatially explicit species assemblage modelling) framework. Yet, little guidance exists on how these approaches could be combined. We, thus, aim to compare the accuracy of assemblage predictions derived from stacked and from joint SDMs. Location: Switzerland Taxon Birds, tree species Methods: Based on two monitoring schemes (national forest inventory and Swiss breeding bird atlas), we built SDMs and JSDMs for tree species (at 100m resolution) and forest birds (at 1km resolution). We tested accuracy of species assemblage and richness predictions on holdout data using different stacking procedures and ecological assembly rules. Results Despite minor differences, results were consistent between birds and tree species. Cross-validated species-level model performance was generally higher in SDMs than JSDMs. Differences in species richness and assemblage predictions were larger between stacking procedures and ecological assembly rules than between stacked SDMs and JSDMs. On average, predictions were slightly better for stacked SDMs compared to JSDMs, probabilistic stacks outperformed binary stacks, and ecological assembly rules yielded best predictions. Main conclusions: When predicting the composition of species assemblages, the choice of stacking procedure and ecological assembly rule seems more decisive than differences in underlying model type (SDM vs. JSDM). JSDMs do not seem to improve community predictions compared to SDMs or improve predictions for rare species. Still, JSDMs may provide additional insights into community assembly and may help deriving hypotheses about prevailing biotic interactions in the system. We provide simple rules of thumb for choosing appropriate modelling pathways. Future studies should test these preliminary guidelines for other taxa and biogeographic realms as well as for other JSDM algorithms.
Data from: Predicting species occurrences with habitat network models
1. Biodiversity conservation requires modelling tools capable of predicting the presence or absence (i.e. occurrence-state) of species in habitat patches. Local habitat characteristics of a patch (lh), the cost of traversing the landscape matrix between patches (weighted connectivity; (wc), and the position of the patch in the habitat network topology (nt) all influence occurrence-state. Existing models are data demanding or consider only local habitat characteristics. We address these shortcomings and present a network-based modelling approach, which aims to predict species occurrence-state in habitat patches using readily available presence-only records. 2. For the tree frog Hyla arborea on the Swiss Plateau, we delineated habitat network nodes from an ensemble habitat suitability model, and used different cost surfaces to generate the edges of three networks: one limited only by dispersal distance (Uniform), another incorporating traffic, and a third based on inverse habitat suitability. For each network, we calculated explanatory variables representing the three categories (lh, wc and nt). The response variable, occurrence-state, was parametrized by a sampling-intensity procedure assessing observations of comparable species over a threshold of patch visits. The explanatory variables from the three networks and an additional non-topological model were related to the response variable with boosted regression trees. 3. The habitat network models had a similar fit; they all outperformed the non-topological model. Habitat suitability index ((lh) was the most important predictor in all networks, followed by third-order neighborhood (nt). Patch size (lh) was unimportant in all three networks. 4. We found that topological variables of habitat networks are relevant for the prediction of species occurrence-state, a step-forward from models considering only local habitat characteristics. For any habitat patch, occurrence-state is most prominently influenced by its habitat suitability, and then by the number of patches in a wide neighborhood. Our approach is generic and can be applied to multiple species in different habitats.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.