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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.

opencc-zeroDec 2017View details →

Data from: Species distribution models of the Spotted Wing Drosophila (Drosophila suzukii, Diptera: Drosophilidae) in its native and invasive range reveal an ecological niche shift

The Spotted Wing Drosophila (Drosophila suzukii) is native to Southeast Asia. Since its first detection in 2008 in Europe and North America, it has been a pest to the fruit production industry as it feeds and oviposits on ripening fruit. Here we aim to model the potential geographical distribution of D. suzukii. We performed an extensive literature review to map the current records. In total, 517 documented occurrences (96 native and 421 invasive) were identified spanning 52 countries. Next, we constructed three species distribution models (SDMs) based on occurrence records in: 1) the native range (SDMnative), 2) the invasive range in Europe (SDMEurope) and 3) a global model of all records (SDMglobal). The models aimed to investigate, whether this species will be able to occupy additional ecological niches beyond its native range and expand its current geographic distribution both globally and in Europe. The SDMs were generated using Maximum Entropy algorithms (Maxent) based on present occurrence records and bioclimatic variables (WorldClim). Predictions of habitat suitability vary greatly depending on the origins of occurrence records. According to all models, precipitation and low temperatures were key limiting factors for the distribution of D. suzukii, which suggests that this species requires a humid environment with mild winters in order to establish a permanent population in its invasive range. Several regions in the invasive range, not presently occupied by this species, were predicted highly suitable, especially in northern Europe, suggesting that D. suzukii is not occupying its full fundamental niche yet. Synthesis and applications. Based on these models of potential geographic distribution of the Spotted Wing Drosophila (Drosophila suzukii), we show a shift in the ecological niche in D. suzukii populations, emphasizing the importance of using presence and local environmental data. Further investigation regarding new occurrences is recommended to secure optimal pest management. Despite a continuing expansion, many countries still lack proper surveillance schemes, and we urge policymakers to initiate appropriate management programs.

opencc-zeroNov 2023View details →

Data from: Integrated species distribution models to account for sampling biases and improve range wide occurrence predictions

Aim Species distribution models (SDMs) that integrate presence-only and presence-absence data offer a promising avenue to improve information on species' geographic distributions. The use of such 'integrated SDMs' on a species range-wide extent has been constrained by the often-limited presence-absence data and by the heterogeneous sampling of the presence-only data. Here, we evaluate integrated SDMs for studying species ranges with a novel expert range map-based evaluation. We build a new understanding about how integrated SDMs address issues of estimation accuracy and data deficiency and thereby offer advantages over traditional SDMs. Location South and Central America. Time period 1979-2017. Major taxa studied Hummingbirds. Methods We build integrated SDMs by linking two observation models – one for each data type – to the same underlying spatial process. We validate SDMs with two schemes: i) cross-validation with presence-absence data and ii) comparison with respect to the species' whole range as defined with IUCN range maps. We also compare models relative to the estimated response curves and compute the association between the benefit of the data integration and the number of presence records in each data set. Results The integrated SDM accounting for the spatially varying sampling intensity of the presence-only data was one of the top-performing models in both model validation schemes. Presence-only data alleviated overly large niche estimates, and data integration was beneficial compared to modelling solely presence-only data for species that had few presence points when predicting the species' whole range. On the community level, integrated models improved the species richness prediction. Main conclusions Integrated SDMs combining presence-only and presence-absence data are successfully able to borrow strengths from both data types and offer improved predictions of species' ranges. Integrated SDMs can potentially alleviate the impacts of taxonomically and geographically uneven sampling and to leverage the detailed sampling information in presence-absence data.

opencc-zeroJan 2024View details →

Combining camera trap surveys and IUCN range maps to improve knowledge of species distributions

Reliable maps of species distributions are fundamental for biodiversity research and conservation. Range maps created by the International Union for Conservation of Nature (IUCN) Red List are often considered authoritative but may not match species occurrence data. We tested concordance between occurrences from camera trap surveys and predicted occurrence from IUCN maps for 510 medium- to large-bodied mammalian species in 80 camera-trap sampling areas. Across all areas, cameras detected 39% of the species that were expected to occur based on IUCN ranges. The probability of mismatches between camera traps and IUCN range maps was significantly higher for smaller-bodied mammals and habitat specialists in the Neotropics and Indomalaya, and in areas with shorter canopy forests. Our results indicate that in many areas within their range map distributions species may be rare or absent. We suggest that combining range map data with accumulating data from ground-based biodiversity sensors, such as camera traps, acoustic recorders, and eDNA surveys, provides a richer knowledge base for conservation mapping and planning.

opencc-zeroMar 2024View details →

Resources for: Spatio-temporal integrated Bayesian species distribution models reveal lack of broad relationships between traits and range shifts

Aim: Climate change and habitat loss or degradation are some of the greatest threats that species face today, often resulting in range shifts. Species traits have been discussed as important predictors of range shifts, with the identification of general trends being of great interest for conservation efforts. However, studies reviewing relationships between traits and range shifts have questioned the existence of such generalized trends, due to mixed results and weak correlations, as well as analytical shortcomings. The aim of this study was to test this relationship empirically, using analytical approaches that account for common sources of bias when assessing range trends. Location: Tanzania, East Africa. Time period: 1980-1999 and 2000-2020. Major taxa studied: 57 savannah specialist birds found in Tanzania, belonging to 26 families and 11 orders. Methods: We applied recently developed integrated spatio-temporal species distribution models in R-INLA, combining citizen science and bird atlas data to estimate ranges of species, quantify range shifts, and test the predictive power of traditional trait groups, as well as exposure-related and sensitivity traits. We based our study on 40 years of bird observations in East African savannahs, a biome that has experienced increasing climatic and non-climatic pressures over recent decades. We correlated patterns of change with species traits. Results: We find indications of relationships identified by previous research, but low average explanatory power of traits from an ecological perspective, confirming the lack of meaningful general associations. However, our analysis finds compelling species-specific results. Main conclusions: We highlight the importance of individual assessments, while demonstrating the usefulness of our analytical approach for analyses of range shifts.

Fig. 3 in Distributional Range Extension of the Shallow Water Scorpionfish Parascorpaena poseidon (Perciformes: Scorpaenidae), with a Revised Diagnosis of the Species

Fig. 3. Lateral (A) and dorsal (B) views of head of Parascorpaena poseidon (NSMT-P 17865, 97.8 mm SL). Bars indicate 5 mm.

Fig. 4 in Distributional Range Extension of the Shallow Water Scorpionfish Parascorpaena poseidon (Perciformes: Scorpaenidae), with a Revised Diagnosis of the Species

Fig. 4. Relationships between body width (A); head width (B); snout length (C); interorbital width at vertical midline of eye (D); upper-jaw length (E); maxilla depth (F); postorbital length (G); orbit diameter (H); and separation between opercular spine tips (I) (all as % of SL) and standard length (mm) in Parascorpaena poseidon, showing ontogenetic changes. Star indicates holotype [except for snout length, interorbital width at vertical midline of eye, and upper-jaw length—see text regarding measurements by Chou and Liao (2022)].

Fig. 2 in Distributional Range Extension of the Shallow Water Scorpionfish Parascorpaena poseidon (Perciformes: Scorpaenidae), with a Revised Diagnosis of the Species

Fig. 2. Variously-sized preserved specimens of Parascorpaena poseidon. A, FMNH 75818, 1 of 27 specimens, 35.3 mm SL, Galle, Sri Lanka; B, FMNH 75818, 1 of 27 specimens, 65.3 mm SL, Galle, Sri Lanka; C, NSMT-P 17865, 97.8 mm SL, Yaku-shima Island, Osumi Islands, Kagoshima, Japan; D, BPBM 27680, 1 of 2 specimens, 115.4 mm SL, Kovalam, Kerala India.

Fig. 1 in Distributional Range Extension of the Shallow Water Scorpionfish Parascorpaena poseidon (Perciformes: Scorpaenidae), with a Revised Diagnosis of the Species

Fig. 1. Fresh specimen of Parascorpaena poseidon from Kovalam, Kerala, India (BPBM 27680, 1 of 2 specimens, 115.4 mm SL). Photo by J. E. Randall (BPBM).

Fig. 5 in Distributional Range Extension of the Shallow Water Scorpionfish Parascorpaena poseidon (Perciformes: Scorpaenidae), with a Revised Diagnosis of the Species

Fig. 5. Distributional records of Parascorpaena poseidon, based on original description (triangles and star), literature record as P. mossambica (closed circle), and present study (open circles). Star indicates type locality.

opencc-by-4.0Dec 2014View details →

Fig. 2 in On The Geographic Distribution Of Nemognatha Plaumanni Borchmann, 1942 (Coleoptera: Meloidae): New Records From Venezuela, With A 4500 Km Range Extension

Fig. 2. Latero-dorsalvieWofaspecimenof Nemognathaplaumanni BorcHmann, 1942, from tHeCordilleradelaCostaintHeStateofAragua (Venezuela), locatedabout 4500 kmnortH

opencc-by-4.0Nov 2018View details →

Fig. 1 in Distributional Range Extension of Xeniamia atrithorax (Perciformes: Apogonidae) in the northern South China Sea

Fig. 1. Fresh specimens of Xeniamia atrithorax, collected off Dong-gang, Pingtung, Taiwan. (A, B) KAUM–I. 109976, 29.9 mm SL; (C, D) KAUM–I. 110317, 28.1 mm SL.

opencc-by-4.0Nov 2017View details →

Fig. 4 in Distributional Range Extension and Live Coloration of the Indo-Pacific Deepwater Cardinalfish Ostorhinchus cheni (Perciformes: Apogonidae)

Fig. 4. Distributional records of Ostorhinchus cheni. ★ based on specimens examined in the present study; ▲ based on underwater photograph; ● literature records.

opencc-by-4.0Nov 2017View details →

Fig. 1 in Distributional Range Extension and Live Coloration of the Indo-Pacific Deepwater Cardinalfish Ostorhinchus cheni (Perciformes: Apogonidae)

Fig. 1. Fresh specimen of Ostorhinchus cheni. KAUM–I. 69457, 115.4 mm SL, off Miagao, Panay Island, Philippines.

opencc-by-4.0Nov 2017View details →

Fig. 3 in Distributional Range Extension and Live Coloration of the Indo-Pacific Deepwater Cardinalfish Ostorhinchus cheni (Perciformes: Apogonidae)

Fig. 3. Underwater photograph of Ostorhinchus cheni. Tulamben, Bali, Indonesia, 70–80 m, 18 June 2016 (Photo by T. Shiraishi).

opencc-by-4.0Nov 2016View details →

Fig. 3 in Distribution Range Extensions of Parapercis bicoloripes and P. diplospilus (Perciformes: Pinguipedidae) in the South China Sea and the Adjacent Waters, with Notes on Ontogenetic Changes in P. bicoloripes

Fig. 3. Ontogenetic changes in relationship of snout length (circles) and fleshy orbit diameter (triangles) as percentage of standard length to standard length (mm) in Parapercis bicoloripes.

opencc-by-4.0Nov 2016View details →

Fig. 2 in Distribution Range Extensions of Parapercis bicoloripes and P. diplospilus (Perciformes: Pinguipedidae) in the South China Sea and the Adjacent Waters, with Notes on Ontogenetic Changes in P. bicoloripes

Fig. 2. Distribution of Parapercis bicoloripes (triangles) and P. diplospilus (circles). Closed and open symbols indicate previously known and new records, respectively.

opencc-by-4.0Nov 2016View details →

Fig. 1 in Distribution Range Extensions of Parapercis bicoloripes and P. diplospilus (Perciformes: Pinguipedidae) in the South China Sea and the Adjacent Waters, with Notes on Ontogenetic Changes in P. bicoloripes

Fig. 1. Fresh specimens of Parapercis bicoloripes from Malaysia (A–B) and the Philippines (C). A, KAUM–I. 79754, 136.0 mm SL, off Kuala Terengganu; B, KAUM–I. 16935, 120.4 mm SL, off Kuala Terengganu; C, KAUM–I. 69435, 66.1 mm SL, off Miagao, Iloilo, Panay Island.

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.