No abstract

We investigated the ranging patterns of elephants in the Marsabit protected area, north eastern Kenya, to ascertain the range of bachelor and female family herds in different seasons, and to identify corridor and noncorridor areas. Data were acquired for five bachelor and four female family herds equipped with satellite‐linked geographical positioning system collars, and monitored from December 2005 to December 2007. Distinct dry (about 260 km2) and wet seasons (about 910 km2) ranges were observed, with connecting corridors (north‐eastern corridor: about 90 km long, about 2‐7 km wide; southern corridors: about 10‐20 km long, about 2‐3 km wide). The dry season range corresponded with Marsabit evergreen forest, while the wet season range matched with dry deciduous lowland shrubs. The ranging elephants moved at speed of about 0.2‐20 kmh−1. Bachelor herds moved faster than female family herds. Elephants moved fast during the intermediate and wet seasons than during the dry season. The speed of ranging elephants was over 1 kmh−1 in the corridor areas and about 0.2 to less than 1 kmh−1 in the non‐corridor areas. Expansion of settlements towards corridor areas needs to be controlled to avoid future blocking of connectivity between wet and dry season elephant ranges.

Summary African swine fever (ASF) is a transcontinental, contagious, fatal virus disease of pig with devastating socioeconomic impacts. Interaction between infected wild boar and domestic pig may spread the virus. The disease is spreading fast from the west of Eurasia towards ASF‐free China. Consequently, prediction of the distribution of ASF along the Sino‐Russian‐Korean borders is urgent. Our area of interest is Northeast China. The reported ASF‐locations in 11 contiguous countries from the Baltic to the Russian Federation were extracted from the archive of the World Organization for Animal Health from July 19, 2007 to March 27, 2017. The locational records of the wild boar were obtained from literature. The environmental predictor variables were downloaded from the WorldClim website. Spatial rarefication and pair‐wise geographic distance comparison were applied to minimize spatial autocorrelation of presence points. Principal component analysis (PCA) was used to minimize multi‐collinearity among predictor variables. We selected the maximum entropy algorithm for spatial modelling of ASF and wild boar separately, combined the wild boar prediction with the domestic pig census in a single map of suids and overlaid the ASF with the suids map. The accuracy of the models was assessed by the AUC. PCA delivered five components accounting for 95.7% of the variance. Spatial autocorrelation was shown to be insignificant for both ASF and wild boar records. The spatial models showed high mean AUC (0.92 and 0.97) combined with low standard deviations (0.003 and 0.006) for ASF and wild boar, respectively. The overlay of the ASF and suids maps suggests that a relatively short sector of the Sino‐Russian border has a high probability entry point of ASF at current conditions. Two sectors of the Sino‐Korean border present an elevated risk.

Highlights • Mediterranean oaks are endangered by infection with an invasive alien oomycete. • Forecasts based on SDM showed an expansion of the plant pathogen within Andalusia. • Our SDMs verified the known environmental suitability and provided new insights. • Phytosanitary management zones may be set from the current and future distribution.