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Article Reference Gekko (Gekko) , a new dark-colored tokay gecko from the Thai-Malay border (Squamata, Gekkonidae)
We describe Gekko dam sp. nov. based on type specimens from a limestone hill in Palian District, Trang Province, southern peninsular Thailand. The new species is also found in Satun Province, southern peninsular Thailand, and in Perlis State, northwestern Peninsular Malaysia. A member of the subgenus Gekko, it differs from all currently recognized Gekko species by the following combination of morphological characters and pattern: maximal known snout-vent length of 149.1 mm, lack of contact between nostrils and rostral, 21–24 interorbital scales between supraciliaries, 72–83 scale rows around midbody, 12–14 dorsal tubercle rows at midbody, 26–28 ventral scale rows at midbody, 22 precloacal pores in males, two postcloacal tubercles on each side of the base of the tail, 14–17 subdigital lamellae on 1st toe and 19–21 on 4th toe, a Y-shaped mark on head, white spots on head, dark grey to black dorsal background with four regular bands of contrasting white spots on dorsum between limb insertions, throat and venter white with orange patches, and a copper iris.
Located in Library / RBINS Staff Publications 2026
Article Reference Gekko (Gekko) emshiva, a new limestone-dwelling gecko from Sa Kaeo Province, eastern Thailand (Squamata, Gekkonidae)
We describe Gekko shiva sp. nov. from limestone cave and hills in Khlong Hat District, Sa Kaeo Province, eastern Thailand, near the border with Cambodia. The new species, a member of the subgenus Gekko, differs from all currently recognized Gekko species by the following combination of morphological characters and pattern: maximal known snout-vent length of 131.9 mm, lack of contact between nostrils and rostral, 28 or 29 interorbital scales between supraciliaries, 80–86 scale rows around midbody, 18 dorsal tubercle rows at midbody, 35–37 ventral scale rows at midbody, 9–12 precloacal pores in males, one or two postcloacal tubercles on each side of the base of the tail, 13–15 subdigital lamellae on 1st toe and 18 or 19 on 4th toe, no Y-shaped mark on head, white spots on head, brown dorsal background with irregular bands of white spots on dorsum, yellow venter, and greenish golden iris.
Located in Library / RBINS Staff Publications 2025
Article Reference GEMAS: Cadmium distribution and its sources in agricultural and grazing land soil of Europe - original data versus clr-transformed data
Located in Library / RBINS Staff Publications 2017
Article Reference GEMAS: Source, distribution patterns and geochemical behaviour of Ge in agricultural and grazing land soils at European continental scale
Located in Library / RBINS Staff Publications 2016
Article Reference Gene Tree Estimation Error with Ultraconserved Elements: An Empirical Study on Pseudapis Bees
Located in Library / RBINS Staff Publications 2021
Article Reference Generality of biodiversity-production relationships in global forests
Located in Library / RBINS Staff Publications 2016
Article Reference D source code Generalized changes of benthic communities after construction of wind farms in the southern North Sea
Located in Library / RBINS Staff Publications 2022 OA
Article Reference Generalized osteosclerotic condition in the skeleton of Nanophoca vitulinoides, a dwarf seal from the Miocene of Belgium
Located in Library / RBINS Staff Publications 2018
Article Reference Generating Hyperspectral Reference Measurements for Surface Reflectance from the LANDHYPERNET and WATERHYPERNET Networks
Located in Library / RBINS Staff Publications 2024
Article Reference Generation of super-resolution gap-free ocean colour satellite products using data-interpolating empirical orthogonal functions (DINEOF)
In this work we present a super-resolution approach for deriving high-spatial-resolution and high-temporal-resolution ocean colour satellite datasets. The technique is based on DINEOF (data-interpolating empirical orthogonal functions), a data-driven method that uses the spatio-temporal coherence of analysed datasets to infer missing information. DINEOF is used here to effectively increase the spatial resolution of satellite data and is applied to a combination of Sentinel-2 and Sentinel-3 datasets. The results show that DINEOF is able to infer the spatial variability observed in the Sentinel-2 data to the Sentinel-3 data while reconstructing missing information due to clouds and reducing the amount of noise in the initial dataset. In order to achieve this, the Sentinel-2 and Sentinel-3 datasets have undergone the same pre-processing, including a comprehensive, region-independent, and pixel-based automatic switching scheme for choosing the most appropriate atmospheric correction and ocean colour algorithm to derive in-water products. The super-resolution DINEOF has been applied to two different variables (turbidity and chlorophyll) and two different domains (Belgian coastal zone and the whole of the North Sea), and the sub-mesoscale variability of the turbidity along the Belgian coastal zone has been studied.
Located in Library / RBINS Staff Publications 2025