Swimming behavior and performance of the marsh rat Holochilus vulpinus (Brants, 1827) (Cricetidae, Sigmodontinae)

Semiaquatic habits evolved in several Sigmodontinae rodent species, but this issue remains poorly studied. The marsh rat Holochilus vulpinus (Brants, 1827) has been associated with palustrine wetland environments and exhibits several morphological traits related to the semiaquatic habit. However, its swimming behavior and the way its morphological specializations contribute to it have not been evaluated so far in this species. This note focuses on describing and quantifying the swimming behavior and swimming performance of H. vulpinus. In order to address these issues, five individuals of H. vulpinus, four adults and one subadult, were filmed while swimming and their performance was quantified. The obtained results indicate that the swimming mode is bipedal paddling, alternating the stroke of the hind feet. The quantitative indicators also qualify H. vulpinus as a good swimmer compared to other terrestrial and semiaquatic mammals.

Estimating soil moisture using Sentinel-1 and Sentinel-2 sensors for dryland and palustrine wetland areasa

Soil moisture content (SMC) plays an important role in the hydrological functioning of wetlands. Remote sensing shows potential for the quantification and monitoring of the SMC of palustrine wetlands; however, this technique remains to be assessed across a wetland–terrestrial gradient in South Africa. The ability of the Sentinel Synthetic Aperture Radar (SAR) and optical sensors, which are freely available from the European Space Agency, were evaluated to predict SMC for a palustrine wetland and surrounding terrestrial areas in the grassland biome of South Africa. The percentage of volumetric water content (%VWC) was measured across the wetland and terrestrial areas of the Colbyn Wetland Nature Reserve, located in the City of Tshwane Metropolitan Municipality of the Gauteng Province, using a handheld SMT-100 soil moisture meter at a depth of 5 cm during the peak and end of the hydroperiod in 2018. The %VWC was regressed against the Sentinel imagery, using random forest, simple linear and support vector machine regression models. Random forest yielded the highest prediction accuracies in comparison to the other models. The results indicate that the Sentinel images have the potential to be used to predict SMC with a high coefficient of determination (Sentinel-1 SAR = R²>0.9; Sentinel-2 optical = R²>0.9) and a relatively low root mean square error (Sentinel-1 RMSE =<17%; Sentinel-2 optical = RMSE <21%). Predicted maps show higher ranges of SMC for wetlands (> 50%VWC; p<0.05) compared to terrestrial areas, and therefore SMC monitoring may benefit the inventorying of wetlands, as well as monitoring of their extent and ecological condition.