Ecological Niche Modeling of Water Lily (Nymphaea L.) Species in Australia under Climate Change to Ascertain Habitat Suitability for Conservation Measures
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ABSTRACT:
SUBMITTER: Nzei J
PROVIDER: S-EPMC9322643 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The enigmatic placozoans, which hold a key position in the metazoan Tree of Life, have attracted substantial attention in many areas of biological and biomedical research. While placozoans have become an emerging model system, their ecology and particularly biogeography remain widely unknown. In this study, we use modelling approaches to explore habitat preferences, and distribution pattern of the placozoans phylum. We provide hypotheses for discrete ecological niche separation between genetic placozoan lineages, which may also help to understand biogeography patterns in other small marine invertebrates. We, here, used maximum entropy modelling to predict placozoan distribution using 20 environmental grids of 9.2 km2 resolution. In addition, we used recently developed metrics of niche overlap to compare habitat suitability models of three genetic clades. The predicted distributions range from 55°N to 44°S and are restricted to regions of intermediate to warm sea surface temperatures. High concentrations of salinity and low nutrient concentrations appear as secondary factors. Tests of niche equivalency reveal the largest differences between placozoan clades I and III. Interestingly, the genetically well-separated clades I and V appear to be ecologically very similar. Our habitat suitability models predict a wider latitudinal distribution for placozoans, than currently described, especially in the northern hemisphere. With respect to biogeography modelling, placozoans show patterns somewhere between higher metazoan taxa and marine microorganisms, with the first group usually showing complex biogeographies and the second usually showing "no biogeography."
| S-EPMC4651326 | biostudies-literature
Project description:BackgroundSuitability of environmental conditions determines a species distribution in space and time. Understanding and modelling the ecological niche of mosquito disease vectors can, therefore, be a powerful predictor of the risk of exposure to the pathogens they transmit. In Africa, five anophelines are responsible for over 95% of total malaria transmission. However, detailed knowledge of the geographic distribution and ecological requirements of these species is to date still inadequate.MethodsIndoor-resting mosquitoes were sampled from 386 villages covering the full range of ecological settings available in Cameroon, Central Africa. Using a predictive species distribution modeling approach based only on presence records, habitat suitability maps were constructed for the five major malaria vectors Anopheles gambiae, Anopheles funestus, Anopheles arabiensis, Anopheles nili and Anopheles moucheti. The influence of 17 climatic, topographic, and land use variables on mosquito geographic distribution was assessed by multivariate regression and ordination techniques.ResultsTwenty-four anopheline species were collected, of which 17 are known to transmit malaria in Africa. Ecological Niche Factor Analysis, Habitat Suitability modeling and Canonical Correspondence Analysis revealed marked differences among the five major malaria vector species, both in terms of ecological requirements and niche breadth. Eco-geographical variables (EGVs) related to human activity had the highest impact on habitat suitability for the five major malaria vectors, with areas of low population density being of marginal or unsuitable habitat quality. Sunlight exposure, rainfall, evapo-transpiration, relative humidity, and wind speed were among the most discriminative EGVs separating "forest" from "savanna" species.ConclusionsThe distribution of major malaria vectors in Cameroon is strongly affected by the impact of humans on the environment, with variables related to proximity to human settings being among the best predictors of habitat suitability. The ecologically more tolerant species An. gambiae and An. funestus were recorded in a wide range of eco-climatic settings. The other three major vectors, An. arabiensis, An. moucheti, and An. nili, were more specialized. Ecological niche and species distribution modelling should help improve malaria vector control interventions by targeting places and times where the impact on vector populations and disease transmission can be optimized.
| S-EPMC2805691 | biostudies-literature
Project description:Ecological niche modeling is a tool used to determine current potential species' distribution or habitat suitability models which can then be used to project suitable areas in time. Projections of suitability into past climates can identify locations of climate refugia, or areas with high climatic stability likely to contain the highest levels of genetic diversity and stable populations when climatic conditions are less suitable in other parts of the range. Modeling habitat suitability for closely related species in recent past can also reveal potential periods and regions of contact and possible admixture. In the east palearctic, there are five Dryophytes (Hylid treefrog) clades belonging to two groups: Dryophytes japonicus group: Clades A and B; and Dryophytes immaculatus group: Dryophytes immaculatus, Dryophytes flaviventris, and Dryophytes suweonensis. We used maximum entropy modeling to determine the suitable ranges of these five clades during the present and projected to the Last Glacial Maximum (LGM) and Last Interglacial (LIG) periods. We also calculated climatic stability for each clade to identify possible areas of climate refugia. Our models indicated suitable range expansion during the LGM for four clades with the exclusion of D. immaculatus. High climatic stability in our models corresponded to areas with the highest numbers of recorded occurrences in the present. The models produced here can additionally serve as baselines for models of suitability under climate change scenarios and indicate species ecological requirements.
| S-EPMC8898549 | biostudies-literature
Project description:BackgroundThe Gulf of Mexico (GOM) is a semi-enclosed sea where the waters of the United States, Mexico and Cuba converge. Al least 21 species of cetaceans inhabit it. The only mysticete (baleen whale) is found in the northeast (U.S. waters). The distribution of the 20 species of odontocetes (toothed cetaceans) is well understood in U.S. waters, but practically unknown in Mexican and Cuban waters. In this study we used sighting data from several odontocete species to construct habitat suitability maps in order to identify geographical regions suitable for high diversity throughout the GOM.MethodsHistorical datasets of georeferenced sightings from across the GOM were used to implement the maximum entropy algorithm (MaxEnt) to model the habitat suitability of each species. Five environmental predictors were used, selected for their influence over the occurrence of cetaceans: two oceanographic predictors (sea surface temperature and chlorophyll-a concentration), and three bathymetric predictors (depth, slope, and distance to 200-m isobath). A spatial approach based on the habitat suitability maps was used to identify the suitable regions.ResultsOnly 12 species were modeled, which were the ones with the minimum sample size required. The models performed well, showing good discriminatory power and slight overfitting. Overall, depth, minimum sea surface temperature, and bottom slope were the most contributing predictor in the models. High suitability areas of 10 species were located on the continental slope, and four suitable regions were identified: (1) the Mississippi Canyon and the Louisiana-Texas slope in the northern GOM, (2) the west Florida slope in the east-northeastern GOM, (3) the Rio Grande slope in the west-northwestern GOM, and (4) the Tamaulipas-Veracruz slope in the west-southwestern GOM.ConclusionsWe were able to detect four geographic regions in the GOM where a high diversity of odontocetes is expected, all located on the continental slope. Although the methodology to identify them (spatial overlap) is a very conservative approach, it is useful for conservation and management purposes. The paucity of data did not allow all species to be modeled, which highlights the importance of establishing transboundary monitoring programs.
| S-EPMC7980700 | biostudies-literature
Project description:Globally accelerating frequency and extent of wildfire threatens the persistence of specialist wildlife species through direct loss of habitat and indirect facilitation of exotic invasive species. Habitat specialists may be especially prone to rapidly changing environmental conditions because their ability to adapt lags behind the rate of habitat alteration. As a result, these populations may become increasingly susceptible to ecological traps by returning to suboptimal breeding habitats that were dramatically altered by disturbance. We demonstrate a multistage modeling approach that integrates habitat selection and survival during the key nesting life-stage of a bird species of high conservation concern, the greater sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse). We applied these spatially explicit models to a spatiotemporally robust dataset of sage-grouse nest locations and fates across wildfire-altered sagebrush ecosystems of the Great Basin ecoregion, western United States. Female sage-grouse exhibited intricate habitat selection patterns that varied across regional gradients of ecological productivity among sagebrush communities, but often selected nest sites that disproportionately resulted in nest failure. For example, 23% of nests occurred in wildfire-affected habitats characterized by reduced sagebrush cover and greater composition of invasive annual grasses. We found survival of nests was negatively associated with wildfire-affected areas, but positively associated with higher elevations with increased ruggedness and overall shrub cover. Strong site fidelity likely drove sage-grouse to continue nesting in habitats degraded by wildfire. Hence, increasing frequency and extent of wildfire may contribute disproportionately to reduced reproductive success by creating ecological traps that act as population sinks. Identifying such habitat mismatches between selection and survival facilitates deeper understanding of the mechanisms driving reduced geographic niche space and population decline at broad spatiotemporal scales, while guiding management actions to areas that would be most beneficial to the species.
| S-EPMC7693117 | biostudies-literature
Project description:Pine sawyer beetle species of the genus Monochamus are vectors of the nematode pest Bursaphelenchus xylophilus. The introduction of these species into new habitats is a constant threat for those regions where the forestry industry depends on conifers, and especially on species of Pinus. To obtain information about the potential risk of establishment of these insects in Chile, we performed climate-based niche modeling using data for five North American and four Eurasian Monochamus species using a Maxent approach. The most important variables that account for current distribution of these species are total annual precipitation and annual and seasonal average temperatures, with some differences between North American and Eurasian species. Projections of potential geographic distribution in Chile show that all species could occupy at least 37% of the area between 30° and 53°S, where industrial plantations of P. radiata are concentrated. Our results indicated that Chile seems more suitable for Eurasian than for North American species.
| S-EPMC4097063 | biostudies-other
Project description:BackgroundResearch of many mammal species tends to focus on single habitats, reducing knowledge of ecological flexibility. The Javan lutung (Trachypithecus auratus) is considered a strict forest primate, and little is known about populations living in savannah. In 2017-2018, we investigated the density and distribution of Javan lutung in Baluran National Park, Indonesia. We conducted ad libitum follows and line transect distance sampling with habitat suitability analysis of Javan lutung.ResultsEstimated density was 14.91 individuals km- 2 (95% CI 7.91-28.08), and estimated population size was 3727 individuals (95% CI 1979 - 7019). Long-tailed macaque (Macaca fascicularis) habitat suitability was the main driver of lutung habitat suitability as the probability of lutung occurrence increased greatly with macaque habitat suitability. Distance to roads, and distance to secondary forest had a negative relationship with lutung occurrence. Lutung habitat suitability decreased with increasing elevation, however, Mt Baluran and the primary forest on Mt Baluran was under-sampled due to treacherous conditions. Follows of six focus groups revealed considerable use of savannah, with terrestrial travel. The follows also revealed polyspecific associations with long-tailed macaques through shared sleeping sites and inter-specific vocalisations.ConclusionsOur study provides new knowledge on the general ecology of Javan lutung, such as use of savannah habitats, underlining our need to branch out in our study sites to understand the flexibility and adaptability of our study species. Another undocumented behaviour is the polyspecific association with long-tailed macaques. We encourage more research on this subject.
| S-EPMC7027213 | biostudies-literature
Project description: Not available
| S-EPMC11243989 | biostudies-literature
Project description:Invasive wildlife often causes serious damage to the economy and agriculture as well as environmental, human and animal health. Habitat models can fill knowledge gaps about species distributions and assist planning to mitigate impacts. Yet, model accuracy and utility may be compromised by small study areas and limited integration of species ecology or temporal variability. Here we modelled seasonal habitat suitability for wild pigs, a widespread and harmful invader, in northern Australia. We developed a resource-based, spatially-explicit and regional-scale approach using Bayesian networks and spatial pattern suitability analysis. We integrated important ecological factors such as variability in environmental conditions, breeding requirements and home range movements. The habitat model was parameterized during a structured, iterative expert elicitation process and applied to a wet season and a dry season scenario. Model performance and uncertainty was evaluated against independent distributional data sets. Validation results showed that an expert-averaged model accurately predicted empirical wild pig presences in northern Australia for both seasonal scenarios. Model uncertainty was largely associated with different expert assumptions about wild pigs' resource-seeking home range movements. Habitat suitability varied considerably between seasons, retracting to resource-abundant rainforest, wetland and agricultural refuge areas during the dry season and expanding widely into surrounding grassland floodplains, savanna woodlands and coastal shrubs during the wet season. Overall, our model suggested that suitable wild pig habitat is less widely available in northern Australia than previously thought. Mapped results may be used to quantify impacts, assess risks, justify management investments and target control activities. Our methods are applicable to other wide-ranging species, especially in data-poor situations.
| S-EPMC5417638 | biostudies-literature
Project description:BackgroundCryptosporidiosis is a zoonotic intestinal infectious disease caused by Cryptosporidium spp., and its transmission is highly influenced by climate factors. In the present study, the potential spatial distribution of Cryptosporidium in China was predicted based on ecological niche models for cryptosporidiosis epidemic risk warning and prevention and control.MethodsThe applicability of existing Cryptosporidium presence points in ENM analysis was investigated based on data from monitoring sites in 2011-2019. Cryptosporidium occurrence data for China and neighboring countries were extracted and used to construct the ENMs, namely Maxent, Bioclim, Domain, and Garp. Models were evaluated based on Receiver Operating Characteristic curve, Kappa, and True Skill Statistic coefficients. The best model was constructed using Cryptosporidium data and climate variables during 1986‒2010, and used to analyze the effects of climate factors on Cryptosporidium distribution. The climate variables for the period 2011‒2100 were projected to the simulation results to predict the ecological adaptability and potential distribution of Cryptosporidium in future in China.ResultsThe Maxent model (AUC = 0.95, maximum Kappa = 0.91, maximum TSS = 1.00) fit better than the other three models and was thus considered the best ENM for predicting Cryptosporidium habitat suitability. The major suitable habitats for human-derived Cryptosporidium in China were located in some high-population density areas, especially in the middle and lower reaches of the Yangtze River, the lower reaches of the Yellow River, and the Huai and the Pearl River Basins (cloglog value of habitat suitability > 0.9). Under future climate change, non-suitable habitats for Cryptosporidium will shrink, while highly suitable habitats will expand significantly (χ2 = 76.641, P < 0.01; χ2 = 86.836, P < 0.01), and the main changes will likely be concentrated in the northeastern, southwestern, and northwestern regions.ConclusionsThe Maxent model is applicable in prediction of Cryptosporidium habitat suitability and can achieve excellent simulation results. These results suggest a current high risk of transmission and significant pressure for cryptosporidiosis prevention and control in China. Against a future climate change background, Cryptosporidium may gain more suitable habitats within China. Constructing a national surveillance network could facilitate further elucidation of the epidemiological trends and transmission patterns of cryptosporidiosis, and mitigate the associated epidemic and outbreak risks.
| S-EPMC10088348 | biostudies-literature