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299 results for “niche models”

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dryad36/100

Data from: Occurrence-habitat mismatching and niche truncation when modelling distributions affected by anthropogenic range contractions

Aims: Human-induced pressures such as deforestation cause anthropogenic range contractions (ARCs). Such contractions present dynamic distributions that may engender data misrepresentations within species distribution models. The temporal bias of occurrence data—where occurrences represent distributions before (past bias) or after (recent bias) ARCs—underpins these data misrepresentations. Occurrence-habitat mismatching results when occurrences sampled before contractions are modelled with contemporary anthropogenic variables; niche truncation results when occurrences sampled after contractions are modelled without anthropogenic variables. Our understanding of their independent and interactive effects on model performance remains incomplete but is vital for developing good modelling protocols. Through a virtual ecologist approach, we demonstrate how these data misrepresentations manifest and investigate their effects on model performance. Location: Virtual Southeast Asia Methods: Using 100 virtual species, we simulated ARCs with 100-year land-use data and generated temporally biased (past, recent) occurrence datasets. We modelled datasets with and without a contemporary land-use variable (conventional modelling protocols) and with a temporally dynamic land-use variable. We evaluated each model's ability to predict historical and contemporary distributions. Results: Greater ARC resulted in greater occurrence-habitat mismatching for datasets with past bias and greater niche truncation for datasets with recent bias. Occurrence-habitat mismatching prevented models with the contemporary land-use variable from predicting anthropogenic-related absences, causing overpredictions of contemporary distributions. Although niche truncation caused underpredictions of historical distributions (environmentally suitable habitats), incorporating the contemporary land-use variable resolved these underpredictions, even when mismatching occurred. Models with the temporally dynamic land-use variable consistently outperformed models without. Main conclusions: We showed how these data misrepresentations can degrade model performance, undermining their use for empirical research and conservation science. Given the ubiquity of anthropogenic range contractions, these data misrepresentations are likely inherent to most datasets. Therefore, we present a three-step strategy for handling data misrepresentations: maximise the temporal range of anthropogenic predictors, exclude mismatched occurrences, and test for residual data misrepresentations.

opencc-zeroMay 2022View details →

dryad36/100

Underlying microevolutionary processes parallel macroevolutionary patterns in ancient Neotropical Mountains - Ecological Niche Modeling and Corridors files

Aim Ancient climatic fluctuations are invoked as the main driving force that generates the astonishing biodiversity in ancient mountains. As a result, endemism and spatial turnover are usually high and few species are widespread among entire mountain ranges, precluding the understanding of origins of macroevolutionary patterns. Here, we used a species endemic to, but widespread in, one of the most species-rich ancient mountains on the globe to test how environmental changes acted on them and how their macroevolutionary patterns were shaped. Location Espinhaço Range, Eastern Brazil. Taxon Vriesea oligantha species complex (Bromeliaceae). Methods We compiled data for plastidial regions and nuclear microsatellites to assess genetic diversity, population structure, migration rates and phylogenetic relationships. Using temperature and precipitation variables we modeled suitable areas for the present and the past, estimating corridors between isolated populations. We also implemented Bayesian demographic analyses to estimate ancient populations dynamics. Finally, we tested if population structure is driven by isolation by environment or by distance using a Bayesian modeling approach. Results Our results showed that the intraspecific divergence events of V. oligantha are older than those associated with the latest Pleistocene climatic oscillations, supporting the view that Quaternary climatic fluctuations are key components for understanding its population differentiation processes. Species distribution modeling estimated corridors between populations in the past, as also shown in the demographic analyses, depicting a major spatial reorganization during colder climates. Besides, the high genetic structure estimated results from both models of isolation by distance and by environment. Main conclusions V. oligantha is a remarkable model to test the effects of climatic oscillations over the biological community, since this species originated in the early-Pleistocene, prevailing over several cycles of climatic fluctuations until today. The estimated demographic dynamics of V. oligantha agrees with the species-pump mechanism, suggesting it as the main cause of speciation within the Espinhaço Range. Moreover, the phylogeographic patterns of V. oligantha reflect previously recognized spatial and temporal macroevolutionary patterns in the Espinhaço Range, providing insights into how microevolutionary processes may have given rise to this astonishing mountain biodiversity.

opencc-zeroMay 2022View details →

dryad36/100

Occurrence datasets, model outputs, and R script for 12 termite species used for niche modeling

The advent of citizen-science databases in conjunction with museum specimen locality information has exponentially increased the power and accuracy of ecological niche modeling (ENM). Increased occurrence data has provided colossal potential to understand the distributions of lesser known or endangered species, including arthropods. Although niche modeling of termites has been conducted in the context of invasive and pest species, few studies have been performed to understand the distribution of basal termite genera. Using specimen records from the American Museum of Natural History (AMNH) as well as locality databases, we generated ecological niche models for 12 basal termite species belonging to six genera and three families. We extracted environmental data from the Worldclim 19 bioclimatic dataset v2, along with SoilGrids datasets and generated models using MaxEnt. We chose Optimal models based on partial Receiving Operating characteristic (pROC) and omission rate criterion and determined variable importance using permutation analysis. We also calculated response curves to understand changes in suitability with changes in environmental variables. Optimal models for our 12 termite species ranged in complexity, but no discernible pattern was noted among genera, families, or geographic range. Permutation analysis revealed that habitat suitability is affected predominantly by seasonal or monthly temperature and precipitation variation. Our findings not only highlight the efficacy of largely citizen-science and museum-based datasets, but our models provide a baseline for predictions of future abundance of lesser-known arthropod species in the face of habitat destruction and climate change.

opencc-zeroJul 2022View details →

zenodo36/100

Supplementary materials for "Modeling the geographical distributions of Chordodes formosanus and its mantis hosts in Taiwan, with considerations for their niche overlaps"

Species distribution model (SDM) has conventionally been used for evaluating the distribution of single species, but comparisons between different SDMs are possible for evaluating the geographic similarity between taxa. Here we used a parasite and host system to infer the geographic overlaps between species with tight biological interaction, e.g. parasites and their obligate host; specifically, we used the horsehair worm Chordodes formosanus and its three different mantis hosts to study the extent of niche overlap. We retrieved presence points for the host species and the parasite and we built the SDMs with MaxEnt implemented in ENMeval by using selected bioclim variables (based on VIF values) at a 30 seconds scale. The models showed that the hosts and parasite do not occur in the high elevation areas in Taiwan, which was expected based on their biology. Interestingly, the predicted parasite distribution included areas without collection records, implying local extinction or sampling bias. We subsequently evaluated niche overlap between hosts and the parasite according to five similarity indices (Schoener’s D, I statistic, relative rank, Pearson correlation coefficient and the rank correlation coefficient rho). Our models showed high similarity of SDM predictions between hosts and the parasite. There were differences among metrics about which host shared the highest similarity with the parasite, but the majority of the results indicated that the Japanese boxing mantis has the highest niche similarity with the horsehair worm. The choice of the niche overlap metric to use can be seen as a way to get informations on the parasite’s ecology, which can be important for endangered species SDMs are reliable tools for host and parasite conservation management and could help to improve biological and ecological knowledge of parasites.

opencc-by-4.0Jul 2022View details →

dryad36/100

VCF datasets and analysis scripts for: The combination of genomic offset and niche modelling provides insights into climate change-driven vulnerability

Global warming is increasingly exacerbating biodiversity loss. Populations locally adapted to spatially heterogeneous environments may respond differentially to climate change, but this intraspecific variation has only recently been considered when modelling vulnerability under climate change. Here, we incorporate intraspecific variation in genomic offset and ecological niche modelling to estimate climate change-driven vulnerability in two bird species in the Sino-Himalayan Mountains. We found that the cold-tolerant populations show higher genomic offset but risk less challenge for niche suitability decline under future climate than the warm-tolerant populations. Based on a genome-niche index estimated by combining genomic offset and niche suitability change, we identified the populations with the least genome-niche interruption as potential donors for evolutionary rescue, i.e., the populations tolerant to climate change. We evaluated potential rescue routes via a landscape genetic analysis. Overall, we demonstrate that the integration of genomic offset, niche suitability modelling, and landscape connectivity can improve climate change-driven vulnerability assessments and facilitate effective conservation management.

opencc-zeroAug 2022View details →

dryad36/100

Data from: Too much of a good thing? Supplementing current species observations with fossil data to assess climate change vulnerability via ecological niche models

Ecological niche models (ENMs) are a powerful tool in ecological research and conservation planning. Since ENMs provide probability maps of suitable areas under environmental change, they may assist in designing conservation actions and addressing conservation priorities. However, ENMs are usually implemented by learning the species climatic preferences from their current geographic distribution, which leaves them vulnerable to the issue of niche truncation issues, as if comes with non-climatic limits to the current species distribution posed by e.g. anthropic activities and settlements, and is bound to assume that species are at equilibrium with their environments. These problems might be alleviated by the inclusion of fossil occurrences, which refer to moments during species evolution when such limits were absent, and a larger fraction of the species fundamental niche was probably explored. Here, we combined current and fossil occurrence data for 38 medium-large mammal species of conservation concern to assess the influence of the fossil record on ENM predictions under future climate change scenarios. We found that ignoring or including fossil data yields consistent trends in terms of predicted range increase/decrease. Yet, although adding fossil data invariably results in increased niche width, estimates of range change magnitude improved for just one half only of the species. These results suggest that most species might be in non-equilibrium with their environment, and that the inclusion of fossil data may be crucial to the better understanding of species climatic requirements, hence for designing effective conservation strategies.

opencc-zeroJun 2024View details →

dryad36/100

The niche through time: Considering phenology and demographic stages in plant distribution models

Species distribution models (SDMs) are widely used to infer species-environment relationships, predict spatial distributions, and characterise species' environmental niches. While the importance of space and spatial scales is widely acknowledged in SDM applications, temporal components of the niche are rarely addressed. We discuss how phenology and demographic stages affect model inference in plant SDMs. Ignoring conspicuousness and timing of phenological stages may bias niche estimates through increased observer bias, while ignoring stand age may bias niche estimates through temporal mismatches with environmental variables, especially during times of rapid global warming. We present different methods to consider phenology and demographic stages in plant SDMs, including the selection of causal, spatiotemporally explicit predictors, and the calibration of stage-specific SDMs. Based on a case study with citizen science data, we illustrate how spatiotemporal SDMs provide deeper insights on the coincidence of range and phenological shifts under climate change. The proliferation of digitally available biodiversity and citizen science data increasingly allows considering time explicitly in SDMs. This offers a more mechanistic understanding of plant distributions, and more robust predictions under global change, especially if the reporting of phenological stages and age is facilitated and promoted by relevant data portals.

opencc-zeroJun 2024View details →

dryad36/100

Data from: Integrating niche and occupancy models to infer the distribution of an endemic fossorial snake (Atractus lasallei)

Understanding species distribution and habitat preferences is crucial for effective conservation strategies. However, the lack of information about population responses to environmental change at different scales hinders effective conservation measures. In this study, we estimate the potential and realized distribution of Atractus lasallei, a semi-fossorial snake endemic to the northwestern region of Colombia. We modelled the potential distribution of A. lasallei based on ecological niche theory (using maxent), and habitat use was characterized while accounting for imperfect detection using a single-season occupancy model. Our results suggest that A. lasallei selects areas characterized by slopes below 10°, with high average annual precipitation (>2500mm/year) and herbaceous and shrubby vegetation. Its potential distribution encompasses the northern Central Cordillera and two smaller centers along the Western Cordillera, but its habitat is heavily fragmented within this potential distribution. When the two models are combined, the species' realized distribution sums up to 935 km2, highlighting its vulnerability. We recommend approaches that focus on variability at different spatio-temporal scales to better comprehend the variables that affect species' ranges and identify threats to vulnerable species. Prompt actions are needed to protect herbaceous and shrub vegetation in this region, highly demanded for agriculture and cattle grazing.

opencc-zeroJun 2024View details →

dryad36/100

Modeling data and R code for Chrysodeixis chalcites ecological niche

The golden twin-spot moth, Chrysodeixis chalcites Esper (Lepidoptera: Noctuidae), is a polyphagous, polyvoltine crop pest occurring natively from northern Europe to Mediterranean Africa and the Canary Islands. Larvae feed on a wide variety of naturally occurring plants as well as soybean and other legume crops, short staple cotton, tomato, potato, peppers, tobacco, and banana. Chrysodeixis chalcites has been recorded in agricultural lands in the Ontario peninsula in eastern Canada and in northern counties of Indiana, USA. Given the strong potential for C. chalcites to invade USA crop lands, it is important to identify environments most likely to sustain growing populations of this pest. Though C. chalcites is native to Europe and North Africa, it has invaded sub-Saharan Africa. Using occurrence data form the native and invaded ranges, and environmental predictors including bioclimatic conditions and human disturbance, we trained three ecological niche models to estimate an ensemble prediction of environmental suitability in the contiguous US. Because human impact is potentially a confounding predictor, models were trained both with and without it. High environmental suitability was projected for the Atlantic coast from New England to Florida, the Gulf coast, the lower Midwest, and the Pacific coast and Central Valley of California.

opencc-zeroJul 2024View details →

dryad36/100

A greenhouse experiment partially supports inferences of ecogeographic isolation from niche models of Clarkia sister species

Premise: Ecogeographic isolation, or geographic isolation caused by ecological divergence, is thought to be of primary importance in speciation, yet is difficult to demonstrate and quantify. To determine whether distributions are limited by divergent adaptation or historical contingency, the gold standard is to reciprocally transplant taxa between their geographic ranges. Alternatively, ecogeographic isolation is inferred from species distribution models and niche divergence tests based on widely available environmental and occurrence data. Methods: We test for ecogeographic isolation between two sister species of California annual wildflowers, Clarkia concinna and C. breweri, with a hybrid approach. We use niche models to predict water availability as the major axis of ecological divergence and then test that with a greenhouse experiment. Specifically, we manipulate water availability in field soils for two populations of each species and predict higher fitness in conditions representing home habitats to those representing the environment of each's sister species. Key Results: Water availability and soil representing C. concinna generally increased both species' fitness. Thus, water and soil may indeed limit C. concinna from colonizing the range of C. breweri, but not vice versa. We suggest that the competitive environment and pollinator availability, which are not directly captured with either approach, may be key biotic factors correlated with climate that contribute to unexplained ecogeographic isolation for C. breweri. Conclusions: Ours is a valuable approach to assessing ecogeographic isolation, in that it balances feasibility with model validation, and our results have implications for species distribution modeling efforts geared towards predicting climate change responses.

opencc-zeroJul 2021View details →

dryad36/100

Data from: Wallace 2: A shiny app for modeling species niches and distributions redesigned to facilitate expansion via module contributions

These are the occurrence locality datasets used in the example provided in "wallace 2: a shiny app for modeling species niches and distributions redesigned to facilitate expansion via module contributions" published in Ecography (DOI: 10.1111/ecog.06547). The analysis workflow is displayed in the Supporting information of the paper (Fig. S1), and these data are also used in the wallace 2 vignette (<a href="https://wallaceecomod.github.io/wallace/articles/tutorial-v2.html">https://wallaceecomod.github.io/wallace/articles/tutorial-v2.html</a>).

opencc-zeroDec 2022View details →

zenodo36/100

Dataset for the manuscript: "Three-dimensional species distribution modeling reveals the realized spatial niche for coral recruitment on contemporary Caribbean reefs"

Whether the three-dimensional (3D) structure of habitats influences and partition recruitment niches of corals is unknown. We developed a new method that combined Species Distribution Modeling and Structure from Motion to characterize and map the three-dimensional recruitment niches of two ecosystem engineers on Caribbean coral reefs, scleractinian corals and octocorals.  In this repository, we include 48 3D models of small areas of the reef (i.e., within ~ 0.25 m2 quadrats) reconstructed with Structure-from-Motion, as well as the geospatial data used to characterize and map the realized recruitment niche for scleractinian corals and octocorals on Caribbean coral reefs. We conducted the study at two shallow, fringing reefs off the south shore of St. John, US Virgin Islands, named Grootpan and Europa Bays (18° 18.360’N, 64° 43.140’W, and 18° 19.016’N, 64° 43.798’W, respectively). Within each 0.25 m2 quadrat, we counted and marked all recruits (octocorals ≤ 5 cm height, and scleractinians ≤ 4 cm wide). DATASET DESCRIPTIONS: <ul> <li>"Quadname_data.zip": In each of this folders we included all the data calculated within a quadrat: <ul> <li>ASCII files (.txt).</li> <li>The annotated dense point cloud (.las) for each quadrat.</li> <li>The quadrat 3D model texture (.jpg).</li> <li>The quadrat 3D polygon mesh (.ply).</li> <li>The quadrat 2.5D Digital Elevation Model (i.e., DEM; .tif).</li> <li>Shape files with recruits local coordinates within each quadrat (.dbf, .prj, .shp, .shx).</li> </ul> </li> <li>"datawide.rds": This is the file needed to run the analyses performed in Martínez-Quintana et al., 2023. This file is obtained after processing all the raw data calculated within each quadrat.  All code associated with the workflow used to obtain the datawide.rds file and run the analyses performed in Martínez-Quintana et al., 2023 is available at <a href="https://github.com/AdamWilsonLab/meshSDM">github.com/AdamWilsonLab/meshSDM</a>.</li> </ul> IMPORTANT NOTES: <ul> <li>Quadrat names starting with the letters “eu” indicate the data were collected at Europa Bay, whereas those starting with the letters “ec” indicate that data were collected at Grootpan Bay (commonly named East Cabritte).</li> <li>Each ASCII file (quadname_ASCII_subsampled_X.txt) contains the slope and roughness of the quadrat calculated on the point cloud at 5, 10, 20, and 100 mm scales, and the smooth point cloud used to calculate the topographic exposure index (TEI) described in Martínez-Quintana et al., 2023. Calculations were performed and ASCII files were created with CloudCompare.</li> <li>Each dense point cloud, mesh, texture, and DEM were calculated with Agisoft Metashape.</li> <li>Agisoft Metashape allows the user to classify and annotate groups of points in the dense point cloud. However, the list of classes provided by the software corresponds to the standard list used for terrestrial LiDAR data; these classes cannot be renamed within the software. Thus, for the present study, we coded the automatic semantic classifications available in Metashape as follows: <ul> <li>Ground = Calcareous rock.</li> <li>Building = Igneous rock.</li> <li>High noise = Sand.</li> <li>Low vegetation = Adult Scleractinian corals.</li> <li>Medium vegetation = Adult Octocoral base.</li> <li>High vegetation = Sponge.</li> <li>Water = Octocoral recruit (named also ocr).</li> <li>Road Surface = Scleractinian recruit (named also scr).</li> <li>Unclassified = created points but never classified (excluded from the analyses).</li> <li>Low Point = noise (unreliable points).</li> <li>Transmission tower and Rail = Points outside the quadrat and excluded from the analysis.</li> </ul> </li> </ul>

opencc-by-4.0Jan 2023View details →

dryad36/100

Evaluating niche changes during invasion with seasonal models in Capsella bursa‐pastoris

Premise Researchers often use ecological niche models to predict where species might establish and persist under future or novel climate conditions. However, these predictive methods assume species have stable niches across time and space. Furthermore, ignoring the time of occurrence data can obscure important information about species reproduction and ultimately fitness. Here, we assess and compare ecological niche models generated from full-year averages to seasonal models Methods In this study, we generate full-year and monthly ecological niche models for Capsella bursa-pastoris in Europe and North America to see if we can detect changes in the seasonal niche of the species after long-distance dispersal. Key Results We find full-year ecological niche models have low transferability across continents and there are continental differences in the climate conditions that influence the distribution of C. bursa-pastoris. Monthly models have greater predictive accuracy than full-year models in cooler seasons but no monthly models are able to predict North American summer occurrences very well. Conclusions The relative predictive ability of European monthly models compared to North American monthly models suggests a change in the seasonal timing between the native range to the non-native range. These results highlight the utility of ecological niche models at finer temporal scales in predicting species distributions and unmasking subtle patterns of evolution.

opencc-zeroFeb 2023View details →

dryad36/100

Data from: Integrating ecological niche and hydrological connectivity models to assess the impacts of hydropower plants on an endemic and imperiled freshwater turtle

We built this dataset to assess the impacts of hydropower plants on the distribution of an endemic and imperiled freshwater turtle with very unique ecological requirements, the Williams' side-necked turtle (Phrynops williamsi). To prevent and mitigate impacts, we prioritized sites for species conservation by classifying planned HPP locations according to their predicted adverse effects on species distribution. The dataset has two files: i) species occurrence records and ii) hydropower plant data. The first dataset was fully built by the authors and the second was modified from the Brazilian Electricity Regulatory Agency (ANEEL) georeferenced data system.

opencc-zeroMay 2023View details →

dryad36/100