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312 results for “ecological model”
Data from: Applying ecological site concepts and state-and-transition models to a grazed riparian rangeland
Ecological sites and state-and-transition models are useful tools for generating and testing hypotheses about drivers of vegetation composition in rangeland systems. These models have been widely implemented in upland rangelands, but comparatively little attention has been given to developing ecological site concepts for rangeland riparian areas, and additional environmental criteria may be necessary to classify riparian ecological sites. Between 2013 and 2016, fifteen study reaches on five creeks were studied at Tejon Ranch in southern California. Data were collected to describe the relationship between riparian vegetation composition, environmental variables, and livestock management; and to explore the utility of ecological sites and state-and-transition models for describing riparian vegetation communities and for creating hypotheses about drivers of vegetation change. Hierarchical cluster analysis was used to classify the environmental and vegetation data (15 stream reaches 4 years) into two ecological sites and eight community phases that comprised three vegetation states. Classification and regression tree (CART) analysis was used to determine the influence of abiotic site variables, annual precipitation, and cattle activity on vegetation clusters. Channel slope explained the greatest amount of variation in vegetation clusters; however, soil texture, geology, watershed size, and elevation were also selected as important predictors of vegetation composition. The classification tree built with this limited set of abiotic predictor variables explained 90% of the observed vegetation clusters. Cattle grazing and annual precipitation were not linked to qualitative differences in vegetation. Abiotic variables explained almost all of the observed riparian vegetation dynamics—and the divisions in the CART analysis corresponded roughly to the ecological sites—suggesting that ecological sites are well-suited for understanding and predicting change in this highly variable system. These findings support continued development of riparian ecological site concepts and state-and-transition models to aid decision making for conservation and management of rangeland riparian areas.
Data from: Seasonal difference in temporal transferability of an ecological model: near-term predictions of lemming outbreak abundances
Ecological models have been criticized for a lack of validation of their temporal transferability. Here we answer this call by investigating the temporal transferability of a dynamic state-space model developed to estimate season-dependent biotic and climatic predictors of spatial variability in outbreak abundance of the Norwegian lemming. Modelled summer and winter dynamics parametrized by spatial trapping data from one cyclic outbreak were validated with data from a subsequent outbreak. There was a distinct difference in model transferability between seasons. Summer dynamics had good temporal transferability, displaying ecological models' potential to be temporally transferable. However, the winter dynamics transferred poorly. This discrepancy is likely due to a temporal inconsistency in the ability of the climate predictor (i.e. elevation) to reflect the winter conditions affecting lemmings both directly and indirectly. We conclude that there is an urgent need for data and models that yield better predictions of winter processes, in particular in face of the expected rapid climate change in the Arctic.
Data from: Long term impacts of selective logging on two Amazonian tree species with contrasting ecological and reproductive characteristics: inferences from Eco-gene model simulations
The impact of logging and subsequent recovery after logging is predicted to vary depending on specific life history traits of the logged species. The Eco-gene simulation model was used to evaluate the long-term impacts of selective logging over 300 years on two contrasting Brazilian Amazon tree species, Dipteryx odorata and Jacaranda copaia. D. odorata (Leguminosae), a slow growing climax tree, occurs at very low densities, whereas J. copaia (Bignoniaceae) is a fast growing pioneer tree that occurs at high densities. Microsatellite multilocus genotypes of the pre-logging populations were used as data inputs for the Eco-gene model and post-logging genetic data was used to verify the output from the simulations. Overall, under current Brazilian forest management regulations, there were neither short nor long-term impacts on J. copaia. By contrast, D. odorata cannot be sustainably logged under current regulations, a sustainable scenario was achieved by increasing the minimum cutting diameter at breast height from 50 to 100 cm over 30-year logging cycles. Genetic parameters were only slightly affected by selective logging, with reductions in the numbers of alleles and single genotypes. In the short term, the loss of alleles seen in J. copaia simulations was the same as in real data, whereas fewer alleles were lost in D. odorata simulations than in the field. The different impacts and periods of recovery for each species support the idea that ecological and genetic information are essential at species, ecological guild or reproductive group levels to help derive sustainable management scenarios for tropical forests.
Multilevel modeling of time-series cross-sectional data reveals the dynamic interaction between ecological threats and democratic development
<p>What is the relationship between environment and democracy? The framework of cultural evolution suggests that societal development is an adaptation to ecological threats. Pertinent theories assume that democracy emerges as societies adapt to ecological factors such as higher economic wealth, lower pathogen threats, less demanding climates, and fewer natural disasters. However, previous research confused within-country processes with between-country processes and erroneously interpreted between-country findings as if they generalize to within-country mechanisms. In this article, we analyze a time-series cross-sectional dataset to study the dynamic relationship between environment and democracy (1949-2016), accounting for previous misconceptions in levels of analysis. By separating within-country processes from between-country processes, we find that the relationship between environment and democracy not only differs by countries but also depends on the level of analysis. Economic wealth predicts increasing levels of democracy in between-country comparisons, but within-country comparisons show that democracy declines as countries become wealthier over time. This relationship is only prevalent among historically wealthy countries but not among historically poor countries, whose wealth also increased over time. By contrast, pathogen prevalence predicts lower levels of democracy in both between-country and within-country comparisons. Our longitudinal analyses identifying temporal precedence reveal that not only reductions in pathogen prevalence drive future democracy, but also democracy reduces future pathogen prevalence and increases future wealth. These nuanced results contrast with previous analyses using narrow, cross-sectional data. As a whole, our findings illuminate the dynamic process by which environment and democracy shape each other.</p>
Data from: Using camera trapping and hierarchical occupancy modelling to evaluate the spatial ecology of an African mammal community
Emerging conservation paradigms have shifted from single to multi-species approaches focused on sustaining biodiversity. Multi-species hierarchical occupancy modelling provides a method for assessing biodiversity while accounting for multiple sources of uncertainty. We analysed camera trapping data with multi-species models using a Bayesian approach to estimate the distributions of a terrestrial mammal community in northern Botswana and evaluate community, group, and species-specific responses to human disturbance and environmental variables. Groupings were based on two life-history traits: body size (small, medium, large and extra-large) and diet (carnivore, omnivore and herbivore). We photographed 44 species of mammals over 6607 trap nights. Camera station-specific estimates of species richness ranged from 8 to 27 unique species, and species had a mean occurrence probability of 0·32 (95% credible interval = 0·21–0·45). At the community level, our model revealed species richness was generally greatest in floodplains and grasslands and with increasing distances into protected wildlife areas. Variation among species' responses was explained in part by our species groupings. The positive influence of protected areas was strongest for extra-large species and herbivores, while medium-sized species actually increased in the non-protected areas. The positive effect of grassland/floodplain cover, alternatively, was strongest for large species and carnivores and weakest for small species and herbivores, suggesting herbivore diversity is promoted by habitat heterogeneity. Synthesis and applications. Our results highlight the importance of protected areas and grasslands in maintaining biodiversity in southern Africa. We demonstrate the utility of hierarchical Bayesian models for assessing community, group and individual species' responses to anthropogenic and environmental variables. This framework can be used to map areas of high conservation value and predict impacts of land-use change. Our approach is particularly applicable to the growing number of camera trap studies world-wide, and we suggest broader application globally will likely result in reduced costs, improved efficiency and increased knowledge of wildlife communities.
Do selfing species have greater niche breadth? Support from ecological niche modeling
<p>We explore the relationship between plant mating system (selfing or outcrossing) and niche breadth to gain new insights into processes that drive species distributions. Using a comparative approach with highly selfing versus highly outcrossing sister species, we test the extent to which: (1) species pairs have evolved significant niche divergence and less niche overlap, (2) selfers have wider niche breadths than outcrossers or vice versa, and (3) niches of selfers and outcrossers are defined by significant differences in environmental variables. We applied predictive ecological niche modeling approaches to estimate and contrast niche divergence, overlap and breadth, and to identify key environmental variables associated with each species' niche for seven sister species with divergent mating systems. Data from 4862 geo-referenced herbarium occurrence records were compiled for 14 species in Collinsia and Tonella (Plantaginaceae) and 19 environmental variables associated with each record. We found sister species display significant niche divergence, though not as a function of divergence time, and overall, selfers have significantly wider niche breadths compared to their outcrossing sisters. Our results suggest that a selfing mating system likely contributes to the greater capacity to reach, reproduce, establish, and adapt to new habitats, which increases niche breadth of selfers.</p>
Data from: Contemporary ecological interactions improve models of past trait evolution
Despite the fact that natural selection underlies both traits and interactions, evolutionary models often neglect that ecological interactions may, and in many cases do, influence the evolution of traits. Here, we explore the interdependence of ecological interactions and functional traits in the pollination associations of hawkmoths and flowering plants. Specifically, we develop an adaptation of the Ornstein-Uhlenbeck model of trait evolution that allows us to study the influence of plant corolla depth and observed hawkmoth-plant interactions on the evolution of hawkmoth proboscis length. Across diverse modelling scenarios, we find that the inclusion of contemporary interactions can provide a better description of trait evolution than the null expectation. Moreover, we show that the pollination interactions provide more-likely models of hawkmoth trait evolution when interactions are considered at increasingly fine-scale groups of hawkmoths. Finally, we demonstrate how the results of best-fit modelling approaches can implicitly support the association between interactions and trait evolution that our method explicitly examines. In showing that contemporary interactions can provide insight into the historical evolution of hawkmoth proboscis length, we demonstrate the clear utility of incorporating additional ecological information to models designed to study past trait evolution.
Data from: Combining landscape genomics and ecological modelling to investigate local adaptation of indigenous Ugandan cattle to East Coast fever
East Coast fever (ECF) is a fatal sickness affecting cattle populations of eastern, central, and southern Africa. The disease is transmitted by the tick Rhipicephalus appendiculatus, and caused by the protozoan Theileria parva parva, which invades host lymphocytes and promotes their clonal expansion. Importantly, indigenous cattle show tolerance to infection in ECF-endemically stable areas. Here, the putative genetic bases underlying ECF-tolerance were investigated using molecular data and epidemiological information from 823 indigenous cattle from Uganda. Vector distribution and host infection risk were estimated over the study area and subsequently tested as triggers of local adaptation by means of landscape genomics analysis. We identified 41 and seven candidate adaptive loci for tick resistance and infection tolerance, respectively. Among the genes associated with the candidate adaptive loci are PRKG1 and SLA2. PRKG1 was already described as associated with tick resistance in indigenous South African cattle, due to its role into inflammatory response. SLA2 is part of the regulatory pathways involved into lymphocytes' proliferation. Additionally, local ancestry analysis suggested the zebuine origin of the genomic region candidate for tick resistance.
Data from: Ecological niche modelling for conservation planning of an endemic snail in the verge of becoming a pest in cardamom plantations in the Western Ghats biodiversity hotspot
Conservation managers and policy makers are often confronted with a challenging dilemma of devising suitable strategies to maintain agricultural productivity while conserving endemic species that at the early stages of becoming pests of agricultural crops. Identification of environmental factors conducive to species range expansion for forecasting species distribution patterns will play a central role in devising management strategies to minimize the conflict between the agricultural productivity and biodiversity conservation. Here, we present results of a study that predicts the distribution of Indrella ampulla, a snail endemic to the Western Ghats biodiversity hotspot, which is becoming a pest in cardamom (Ellettaria cardamomum) plantations. We determined the distribution patterns and niche overlap between I. ampulla and Ellettaria cardamomum using maximum entropy (MaxEnt) niche modeling techniques under current and future (2020–2080) climatic scenarios. The results showed that climatic (precipitation of coldest quarter and isothermality) and soil (cation exchange capacity of soil [CEC]) parameters are major factors that determine the distribution of I. ampulla in Western Ghats. The model predicted cardamom cultivation areas in southern Western Ghats are highly sensitive to invasion of I. ampulla under both present and future climatic conditions. While the land area in the central Western Ghats is predicted to become unsuitable for I. ampulla and Ellettaria cardamomum in future, we found 71% of the Western Ghats land area is suitable for Ellettaria cardamomum cultivation and 45% suitable for I. ampulla, with an overlap of 35% between two species. The resulting distribution maps are invaluable for policy makers and conservation managers to design and implement management strategies minimizing the conflicts to sustain agricultural productivity while maintaining biodiversity in the region.
Data from: Correlation between genetic diversity and environmental suitability: taking uncertainty from ecological niche models into account
The hindcast of shifts in the geographical ranges of species as estimated by ecological niche modelling (ENM) has been coupled with phylogeographical patterns, allowing the inference of past processes that drove population differentiation and genetic variability. However, more recently, some studies have suggested that maps of environmental suitability estimated by ENM may be correlated to species' abundance, raising the possibility of using environmental suitability to infer processes related to population demographic dynamics and genetic variability. In both cases, one of the main problems is that there is a wide variation in ENM development methods and climatic models. In this study, we analyse the relationship between heterozygosity (He) and environmental suitability from multiple ENMs for 25 population estimates for Dipteryx alata, a widely distributed, endemic tree species of the Cerrado region of central Brazil. We propose a new approach for generating a statistical distribution of correlations under randomly generated ENM. The confidence intervals from these distributions indicate how model selection with different properties affects the ability to detect a correlation of interest (e.g. the correlation between He and suitability). Additionally, our approach allows us to explore which particular ensemble of ENMs produces the better result for finding an association between environmental suitability and He. Caution is necessary when choosing a method or a climatic data set for modelling geographical distributions, but the new approach proposed here provides a conservative way to evaluate the ability of ensembles to detect patterns of interest.
Data from: Ecological niche modeling for a cultivated plant species: a case study on taro (Colocasia esculenta) in Hawai'i
Under the threat of ongoing and projected climate change, communities in the Pacific Islands face challenges of adapting culture and lifestyle to accommodate a changing landscape. Few models can effectively predict how biocultural livelihoods might be impacted. Here, we examine how environmental and anthropogenic factors influence an ecological niche model (ENM) for the realized niche of cultivated taro (Colocasia esculenta) in Hawai'i. We created and tuned two sets of ENMs: one using only environmental variables, and one using both environmental and cultural characteristics of Hawa'i. These models were projected under two different Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways (RCPs) for 2070. Models were selected and evaluated using average omission rate and area under the receiver operating characteristic curve (AUC). We compared optimal model predictions by comparing the percentage of taro plots predicted present and measured ENM overlap using Schoener's D-statistic. The model including only environmental variables consisted of 19 Worldclim bioclimatic variables, in addition to slope, altitude, distance to perennial streams, soil evaporation, and soil moisture. The optimal model with environmental variables plus anthropogenic features also included a road density variable (which we assumed as a proxy for urbanization) and a variable indicating agricultural lands of importance to the State of Hawai'i. The model including anthropogenic features performed better than the environment-only model based on omission rate, AUC, and review of spatial projections. The two models also differed in spatial projections for taro under anticipated future climate change. Our results demonstrate how ENMs including anthropogenic features can predict which areas might be best suited to plant cultivated species in the future, and how these areas could change under various climate projections. These predictions might inform biocultural conservation priorities and initiatives. In addition, we discuss the incongruences that arise when traditional ENM theory is applied to species whose distribution has been significantly impacted by human intervention, particularly at a local scale relevant to biocultural conservation initiatives.
Data from: A test of the central-marginal hypothesis using population genetics and ecological niche modelling in an endemic salamander (Ambystoma barbouri)
The central-marginal hypothesis (CMH) predicts that population size, genetic diversity, and genetic connectivity are highest at the core and decrease near the edges of species' geographic distributions. We provide a test of the CMH using three replicated core-to-edge transects that encompass nearly the entire geographic range of the endemic streamside salamander (Ambystoma barbouri). We confirmed that the mapped core of the distribution was the most suitable habitat using ecological niche modelling (ENM) and via genetic estimates of effective population sizes. As predicted by the CMH, we found statistical support for decreased genetic diversity, effective population size, and genetic connectivity from core to edge in western and northern transects, yet not along a southern transect. Based on our niche model, habitat suitability is lower towards the southern range edge, presumably leading to conflicting core-to-edge genetic patterns. These results suggest that multiple processes may influence a species' distribution based on the heterogeneity of habitat across a species' range and that replicated sampling may be needed to accurately test the CMH. Our work also emphasizes the importance of identifying the geographic range core with methods other than using the Euclidean center on a map, which may help to explain discrepancies among other empirical tests of the CMH. Assessing core to edge population genetic patterns across an entire species' range accompanied with ENM can inform our general understanding of the mechanisms leading to species' geographic range limits.
Data from: Environmental filtering improves ecological niche models across multiple scales
1. A clear challenge for ecological niche modeling is determining how to best mitigate the effects of sampling bias from commonly collected biodiversity data. Recent approaches have focused on filtering occurrences in overrepresented regions based on geographic or environmental proximity. 2. We tested the efficacy of filtering in geographic and environmental space using occurrence data from four species. Our evaluation strategies examined 14 distance measures in geographic and environmental spaces and eight combinations of environmental variables and their ordinations. This resulted in 78 datasets for each species, which we evaluated using area under the curve (AUC), the difference between training and testing AUC, omission rate, the true skill statistic, and Schoener's D to examine the effects of different filtering schemes. 3. The degree of change produced by filtering on predicted suitability and evaluation statistics increased with increasing range size. Environmental filtering resulted in higher model fit at larger extents and retained more occurrences than geographic filtering. 4. Our results indicate that models should be evaluated using multiple evaluation statistics at multiple thresholds. The use of bin sizes when filtering in environmental space allows for simple comparison between species and filter types and makes for an easily reportable and repeatable distance metric. We specifically recommend that ecological niche models using natural history collection data filter in environmental space with variables derived from permutation importance or the first few axes of a principal components ordination.
Data from: MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling
Species Distribution Models (SDMs) combine information on the geographic occurrence of species with environmental layers to estimate distributional ranges and have been extensively implemented to answer a wide array of applied ecological questions. Unfortunately, most global datasets available to parameterize SDMs consist of spatially interpolated climate surfaces obtained from ground weather station data and have omitted the Antarctic continent, a landmass covering c. 20% of the Southern Hemisphere and increasingly showing biological effects of global change. Here we introduce MERRAclim, a global set of satellite-based bioclimatic variables including Antarctica for the first time. MERRAclim consists of three datasets of 19 bioclimatic variables that have been built for each of the last three decades (1980s, 1990s and 2000s) using hourly data of 2 m temperature and specific humidity. We provide MERRAclim at three spatial resolutions (10 arc-minutes, 5 arc-minutes and 2.5 arc-minutes). These reanalysed data are comparable to widely used datasets based on ground station interpolations, but allow extending their geographical reach and SDM building in previously uncovered regions of the globe.
Data from: Genome assembly and annotation of Arabidopsis halleri, a model for heavy metal hyperaccumulation and evolutionary ecology
The self-incompatible species Arabidopsis halleri is a close relative of the self-compatible model plant Arabidopsis thaliana. The broad European and Asian distribution and heavy metal hyperaccumulation ability make A. halleri a useful model for ecological genomics studies. We used long-insert mate-pair libraries to improve the genome assembly of the A. halleri ssp. gemmifera Tada mine genotype (W302) collected from a site with high contamination by heavy metals in Japan. After five rounds of forced selfing, heterozygosity was reduced to 0.04%, which facilitated subsequent genome assembly. Our assembly now covers 196 Mb or 78% of the estimated genome size and achieved scaffold N50 length of 712 kb. To validate assembly and annotation, we used synteny of A. halleri Tada mine with a previously published high-quality reference assembly of a closely related species, Arabidopsis lyrata. Further validation of the assembly quality comes from synteny and phylogenetic analysis of the HEAVY METAL ATPASE4 (HMA4) and METAL TOLERANCE PROTEIN1 (MTP1) regions using published sequences from European A. halleri for comparison. Three tandemly duplicated copies of HMA4, key gene involved in cadmium and zinc hyperaccumulation, were assembled on a single scaffold. The assembly will enhance the genomewide studies of A. halleri as well as the allopolyploid Arabidopsis kamchatica derived from A. lyrata and A. halleri.
Data from: Combining human acceptance and habitat suitability in a unified socio-ecological suitability model: a case study of the wolf in Switzerland
Habitat suitability models (HSMs) are commonly used in conservation practise to assess the potential of an area to be occupied and colonised. A major limitation of these models, however, is the omission of spatially explicit understanding of human acceptance towards the focal species. As wildlife is more and more subject to human-dominated landscapes, ignoring the sociological component will result in misrepresentation of the observed processes and inappropriate management. We distributed 10 000 questionnaires across Switzerland and identified key socio-demographical factors correlated with human acceptance of the wolf. We then created a spatially explicit acceptance model based on geo-referenced socio-demographical, social and geographical information. Finally, we combined our acceptance model with a HSM to obtain a unified socio-ecological suitability model, which included human and ecological components. We showed that the key factors associated with human acceptance were perception of how harmful the wolf is, interest in wolf-related issues, need for livestock protection, and fear of the wolf. Perceived harmfulness was in turn correlated with direct and indirect experience with the wolf, and level of education. Our acceptance map predicted decreasing acceptance with increasing altitude of residency and proximity to locations of confirmed wolf presence. This resulted in the overall opposition to the wolf for the Alpine region, albeit substantial regional differences. We found little spatial overlap (6% of Switzerland) between areas where the wolf was accepted and areas of suitable habitat. These areas of socio-ecological suitability were concentrated in the Jura Mountains and in the eastern and southern Alps, and were absent in the western and central Alps. Particularly in the Jura region, which is yet to be colonised, management of human acceptance will be a crucial conservation target. Synthesis and applications. We developed an integrative, socio-ecological approach that allowed us to accurately reproduce recent wolf recolonisation. We anticipate our framework to be a powerful tool to reliably evaluate overall suitable habitats and predict short to medium-term range expansion for species whose distribution is also dependent on human attitudes. Because our approach is sensitive to both the ecological and human component, it is ideally suited to identify key regions where proactive and targeted socio-ecological management plans are needed.
Figure 3 in Natural history and ecological niche modelling of coastal Atyphella Olliff Larvae (Lampyridae: Luciolinae) in Vanuatu
Figure 3. Distributions of pronotal widths and resulting predicted instars in two species of coastal Atyphella.
Figure 2 in Natural history and ecological niche modelling of coastal Atyphella Olliff Larvae (Lampyridae: Luciolinae) in Vanuatu
Figure 2. (a) Collection site of coastal Atyphella. Yellow dots indicate locations specimens were collected in 2018. (b) Predictive model for possible localities of coastal Atyphella in Vanuatu. White squares indicate locations Atyphella was collected in 2018.
Figure 1 in Natural history and ecological niche modelling of coastal Atyphella Olliff Larvae (Lampyridae: Luciolinae) in Vanuatu
Figure 1. (a) Typical habitat of coastal Atyphella (Efate, Vanuatu). (b) Typical habitat of coastal Atyphella (Malekula, Vanuatu). (c) Experimental setup of submersion experiment. (d) Captive coastal Atyphella feeding on snail.
Data for : Ecological associations distribution modelling of marine plankton at global scale
<p>Git repository : https://gitlab.univ-nantes.fr/combi-ls2n/adm</p>
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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.