Dataset Information

Habitat suitability analysis reveals high ecological flexibility in a "strict" forest primate.

ABSTRACT: Background:Research 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. Results:Estimated 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. Conclusions:Our 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.

SUBMITTER: Hansen MF

PROVIDER: S-EPMC7027213 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Habitat suitability analysis reveals high ecological flexibility in a "strict" forest primate.

Hansen Malene Friis MF Nawangsari Ventie Angelia VA van Beest Floris M FM Schmidt Niels Martin NM Stelvig Mikkel M Dabelsteen Torben T Nijman Vincent V

Frontiers in zoology 20200218

<h4>Background</h4>Research of many mammal species tends to focus on single habitats, reducing knowledge of ecological flexibility. The Javan lutung (<i>Trachypithecus auratus</i>) 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 ...[more]

PMID: 32095154

Similar Datasets

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.

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.

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.

Project description:Salvage logging in burned forests can negatively affect habitat for white-headed woodpeckers (Dryobates albolarvatus), a species of conservation concern, but also meets socioeconomic demands for timber and human safety. Habitat suitability index (HSI) models can inform forest management activities to help meet habitat conservation objectives. Informing post-fire forest management, however, involves model application at new locations as wildfires occur, requiring evaluation of predictive performance across locations. We developed HSI models for white-headed woodpeckers using nest sites from two burned-forest locations in Oregon, the Toolbox (2002) and Canyon Creek (2015) fires. We measured predictive performance by developing one model at each of the two locations and quantifying discrimination of nest from reference sites at two other wildfire locations where the model had not been developed (either Toolbox or Canyon Creek, and the Barry Point Fire [2011]). We developed and evaluated Maxent models based on remotely sensed environmental metrics to support habitat mapping, and weighted logistic regression (WLR) models that combined remotely sensed and field-collected metrics to inform management prescriptions. Both Maxent and WLR models developed either at Canyon Creek or Toolbox performed adequately to inform management when applied at the alternate Toolbox or Canyon Creek location, respectively (area under the receiver-operating-characteristic curve [AUC] range = 0.61-0.72) but poorly when applied at Barry Point (AUC = 0.53-0.57). The final HSI models fitted to Toolbox and Canyon Creek data quantified suitable nesting habitat as severely burned or open sites adjacent to lower severity and closed canopy sites, where foraging presumably occurs. We suggest these models are applicable at locations similar to development locations but not at locations resembling Barry Point, which were characterized by more (pre-fire) canopy openings, larger diameter trees, less ponderosa pine (Pinus ponderosa), and more juniper (Juniperus occidentalis). Considering our results, we recommend caution when applying HSI models developed at individual wildfire locations to inform post-fire management at new locations without first evaluating predictive performance.

Dataset Information

Habitat suitability analysis reveals high ecological flexibility in a "strict" forest primate.

Publications

Habitat suitability analysis reveals high ecological flexibility in a "strict" forest primate.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets