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opencc-by-4.0Jan 2014View details →

Figure 2. Summer core area delineation. The straight line with a in Demographic characteristics, seasonal range and habitat topography of Balkan chamois population in its southernmost limit of its distribution (Giona mountain, Greece)

Figure 2. Summer core area delineation. The straight line with a slope of –1 represents the random use of space within the population seasonal range. The curve that sags below the line of random use represents the clumped use of space. The summer core area can be defined at the point whose tangent has slope –1, e.g. 85%, that is, whose tangent is parallel to the line of random use. This is also the point of the curve that is furthest from the line of random use.

Fig. 4 in Anteaters on the edge: giant and lesser anteaters (Myrmecophaga tridactyla and Tamandua tetradactyla) at their geographic distributional limits in Paraguay

Fig. 4. Capture success (%) of lesser anteater (Tamandua tetradactyla Linnaeus, 1758) and giant anteater (Myrmecophaga tridactyla Linnaeus, 1758) in the Humid Chaco Ecoregion in Paraguay using trap-cameras from November 2016 to March 2018 by forest types: W-RF, Riparian forests associated to wetlands; MXF, Mesoxerophytic semi-deciduous forests dominated by Schinopsis balansae; FSF, Floodable sub-humid forest islets.

Figs 2, 3 in Anteaters on the edge: giant and lesser anteaters (Myrmecophaga tridactyla and Tamandua tetradactyla) at their geographic distributional limits in Paraguay

Figs 2, 3. Photos taken by trap cameras in the Humid Chaco Ecoregion in Paraguay: 2) Giant anteater (Myrmecophaga tridactyla Linnaeus, 1758) on March 20th, 2017; 3) Lesser anteater (Tamandua tetradactyla Linnaeus, 1758) on November 28th, 2017.

Fig. 1 in Anteaters on the edge: giant and lesser anteaters (Myrmecophaga tridactyla and Tamandua tetradactyla) at their geographic distributional limits in Paraguay

Fig. 1. Location of the study area in the Humid Chaco Ecoregion in Paraguay (left) and camera-trap ubications from November 2016 to March 2018. The numbers of the amplified area (right) indicate the date and season in which the trap cameras were placed in the different forests types (see Tab. I).

Fig. 5 in Anteaters on the edge: giant and lesser anteaters (Myrmecophaga tridactyla and Tamandua tetradactyla) at their geographic distributional limits in Paraguay

Fig. 5. Records (%) by hour of the day of giant anteater (Myrmecophaga tridactyla Linnaeus, 1758) and lesser anteater (Tamandua tetradactyla Linnaeus, 1758) in the Humid Chaco Ecoregion in Paraguay using trap-cameras from November 2016 to March 2018.

opencc-by-4.0Oct 2017View details →

Fig. 1 in Interspecific Interactions as a Factor of Limitation of Geographical Distribution: Evidence Obtained by Modeling Home Ranges of Vole Twin Species Microtus Arvalis – M. Levis (Rodentia, Microtidae)

Fig. 1. Potential distribution of the Common vole Microtus arvalis. White circles are georeferenced occurrences of genetically identified individuals; black indicates areas of maximum habitat suitability, white are areas of lowest suitability.

opencc-by-4.0Jul 2022View details →

Fig. 4. Distribution maps. A in A new semi-cryptic Filistata from caves in the Levant with comments on the limits of Filistata insidiatrix (Forsskål, 1775) (Arachnida: Araneae: Filistatidae)

Fig. 4. Distribution maps. A. Filistata insidiatrix (Forsskål, 1775) in the Mediterranean and Middle East (note the species has been recorded from Angola, Venezuela and the islands of Socotra, Azores and Cabo Verde, but these records seem to be introduced); literature records have been taken from Benoit (1968), Brignoli (1982), Marusik & Zonstein (2014), Marusik & Zamani (2015a) and Zonstein & Marusik (2019). B. Filistata insidiatrix (circles) and F. betarif sp. nov. (star) in Israel and Palestine; only specimens examined by us are included in the map. Darker shades of orange are records that include at least one male specimen. C. Other species of Filistata Latreille, 1810 in Israel (except F. insidiatrix).

opencc-zeroOct 2022View details →

Dataset for: Snow limits polecat (Mustela putorius) distribution in Sweden

Many species show range expansions or contractions due to climate-change-induced changes in habitat suitability. In cold climates, many species that are limited by snow are showing range expansions due to reduced winter severity. The European polecat (Mustela putorius) occurs over large parts of Europe with its northern range limit in southern Fennoscandia. However, it is to date unknown what factors limit polecat distribution. We thus investigated whether climate or land-use variables are more important in determining the habitat suitability for polecats in Sweden. We hypothesized that 1) climatic factors, especially the yearly number of snow days, drive habitat suitability for polecats, and that, 2) as the number of snow days is predicted to decline in the near future, habitat suitability in northern Sweden will increase. We used a combination of sightings data and a selection of national maps of environmental factors to test these hypotheses using MaxEnt models. We also used maps of future climate predictions (2021–2050 and 2063–2098) to predict future habitat suitability. The number of snow days was the most important factor, negatively determining habitat suitability for polecats, as expected. Consequently, the predictions showed an increase in suitable habitat both in the current distribution range and in northern Sweden, especially along the coast of the Baltic Sea. Our results suggest that the polecat distribution is limited by snow and that reduced snow cover will likely result in a northward range expansion. However, the exact mechanisms for how snow limits polecats are still poorly understood. Consequently, we expect the Scandinavian polecat population to increase in numbers, in contrast to many populations elsewhere in Europe, where numbers are declining. Due to polecat predation, the expansion of the species might have cascading effects on other wildlife populations.

opencc-zeroMay 2024View details →

Terrain variables used for ensemble distribution modelling of vulnerable marine ecosystems indicator taxa on data-limited seamounts of Cabo Verde (NW Africa)

Aim: Seamounts are conspicuous geological features with an important ecological role and can be considered Vulnerable Marine Ecosystems (VMEs). Since many deep-sea regions remain largely unexplored, investigating the occurrence of VME taxa on seamounts is challenging. Our study aimed to predict the distribution of four cold-water coral (CWC) taxa, indicators for VMEs, in a region where occurrence data is scarce. Location: Seamounts around the Cabo Verde Archipelago (NW Africa). Methods: We used species presence-absence data obtained from Remotely Operated Vehicle (ROV) footage collected during two research expeditions. Terrain variables calculated using a multiscale approach from a 100 m resolution bathymetry grid, as well as physical oceanographical data from the VIKING20X model, at a native resolution of 1/20°, were used as environmental predictors. Two modelling techniques (Generalized Additive Model (GAM) and Random Forest (RF)) were employed and single-model predictions were combined into a final weighted-average ensemble model. Model performance was validated using different metrics through cross-validation. Results: Terrain orientation, at broad-scale, presented one of the highest relative variable contributions to the distribution models of all CWC taxa, suggesting that hydrodynamic-topographic interactions on the seamounts could benefit CWCs by maximizing food supply. However, changes at finer scales in terrain morphology and bottom salinity were important for driving differences in the distribution of specific CWCs. The ensemble model predicted the presence of VME taxa on all seamounts and consistently achieved the highest performance metrics, outperforming individual models. Nonetheless, model extrapolation and uncertainty, measured as the coefficient of variation, were high, particularly, in least surveyed areas across seamounts, highlighting the need to collect more data in future surveys. Main conclusions: Our study shows how data-poor areas may be assessed for the likelihood of VMEs and provides important information to guide future research in Cabo Verde, which is fundamental to advise ongoing conservation planning.

opencc-by-4.0May 2022View details →

Fig. 1 in New records of Tarucus balkanicus at the northern limit of its distribution along the Adriatic coast (Lepidoptera: Papilionoidea, Lycaenidae)

Fig. 1 – Distribution of Tarucus balkanicus in Croatia and Bosnia & Herzegovina based on new and literature records. The distribution of its host plant, Paliurus spina-christi, is shown only for Croatia in accordance with Nikolić (2005-2020).

Fig. 5 in Factors limiting the current distribution of the introduced Java sparrow (Lonchura oryzivora) in Bangkok, Thailand

Fig. 5. Four nest localities of Java sparrow in the study area; nurse dormitory of Bhumipol Hospital (1), Air Force Youth Club (2), Air Force Museum (3) and Phaholyothin 69/1 alley (4). Java sparrows were mostly found nesting in (1) and (3). All sites were located <1.5 km from Don Muang Airport. (1), (2) and (3) were located on the eastern side of Don Muang Airport and (4) was located to the south-west.

Fig. 6. There were 39 in Factors limiting the current distribution of the introduced Java sparrow (Lonchura oryzivora) in Bangkok, Thailand

Fig. 6. There were 39 nest sites at Bhumibol Hospital, 22 sites at the Royal Thai Air Force Museum, 3 at the Thai Air Force Youth Club and 3 at Phahonyothin Soi 69/1. Birds mostly located their nests in cavities in the ceilings of buildings or in openings of air ducts.

Fig. 3. Within the 15 occupied cells, 6 cells had a in Factors limiting the current distribution of the introduced Java sparrow (Lonchura oryzivora) in Bangkok, Thailand

Fig. 3. Within the 15 occupied cells, 6 cells had a percentage of paddyfield cover <1%, 6 cells had 1–20% paddyfield cover and 3 cells had 20–40% paddyfield cover. For the 26 cells with no detections, 16 had a percentage of paddyfield cover <1%, 7 cells had 1–20% paddyfield cover and 3 cells had 20–40% paddyfield cover.

Fig. 2. Forty-one grid cells randomly set within a 10 in Factors limiting the current distribution of the introduced Java sparrow (Lonchura oryzivora) in Bangkok, Thailand

Fig. 2. Forty-one grid cells randomly set within a 10-km radius around Don Muang airport, Bangkok, Thailand, used for surveying Java sparrows. Don Muang was the site where Java sparrows were first recorded in Thailand in 1924. The study area includes three provinces; Bangkok, Pathum Thani, and Nonthaburi. The primary land use was urban, while paddyfields were mostly located on the eastern side of the study area. Different symbols (circles, squares and triangles) represent the number of occasions (out of 5 possible visits to a location) on which the sparrow was detected. Size of symbols of Java sparrow detection points was related to the number of birds detected; smallest size indicated only 1 bird was detected, medium size indicated 2–10 birds were detected, and largest size indicated a group of more than 40 birds was detected.

Fig. 1. 101 in Factors limiting the current distribution of the introduced Java sparrow (Lonchura oryzivora) in Bangkok, Thailand

Fig. 1. 101 grid cells (400 ha each) were overlaid on the study area (40,000 ha). We randomly selected approximately 40% (41) (green) of 98 accessible grid cells in total. Access to three grid cells (red) in the middle of study area including Don Muang International Airport were restricted by the Thai Air Force.

Fig. 4 in Factors limiting the current distribution of the introduced Java sparrow (Lonchura oryzivora) in Bangkok, Thailand

Fig. 4. Number of Java sparrows counted at the two main roosting sites in Bangkok, Thailand, each site was counted once per month from August 2016 to July 2017. Lowest and highest counts (33 and 2132 individuals) were obtained from the Kan Kheha Thung Song Hong (KKTSH) roost (dashed line). Lowest counts at KKTSH were in August–September 2016. The roosting site at Chaeng Wattana (solid line) had a lower number of birds but may have received some birds from KKTSH during the first two months of the count.

publicMay 2024View details →

Terrain variables used for ensemble distribution modelling of vulnerable marine ecosystems indicator taxa on data-limited seamounts of Cabo Verde (NW Africa)

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