High probability areas for ASF infection in China along the Russian and Korean borders.

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.

Eutrophication of mangroves linked to depletion of foliar and soil base cations.

There is growing concern that increasing eutrophication causes degradation of coastal ecosystems. Studies in terrestrial ecosystems have shown that increasing the concentration of nitrogen in soils contributes to the acidification process, which leads to leaching of base cations. To test the effects of eutrophication on the availability of base cations in mangroves, we compared paired leaf and soil nutrient levels sampled in Nypa fruticans and Rhizophora spp. on a severely disturbed, i.e. nutrient loaded, site (Mahakam delta) with samples from an undisturbed, near-pristine site (Berau delta) in East Kalimantan, Indonesia. The findings indicate that under pristine conditions, the availability of base cations in mangrove soils is determined largely by salinity. Anthropogenic disturbances on the Mahakam site have resulted in eutrophication, which is related to lower levels of foliar and soil base cations. Path analysis suggests that increasing soil nitrogen reduces soil pH, which in turn reduces the levels of foliar and soil base cations in mangroves.

Reduced dependence of Crested Ibis on winter-flooded rice fields: implications for their conservation.

The Crested Ibis Nipponia nippon was once thought to be extinct in the wild until seven birds were discovered in a remote mountain village in China in 1981. Studies suggested that winter-flooded rice fields play an essential role in nest site selection by the Crested Ibis and hence in their survival. Considerable efforts were therefore made to conserve the winter-flooded rice fields, but these have caused conflicts between the agricultural and conservation communities. The population and geographical range of the wild Crested Ibis has expanded greatly since 1981, but there is no spatial information on the winter-flooded rice fields, nor on the current association of nest sites and winter-flooded rice fields. We mapped winter-flooded rice fields across the entire current range of Crested Ibis using innovative remote sensing and geographical information systems (GIS) techniques. The spatial relationships between the nest site clusters and winter-flooded rice fields were quantified using Ward's hierarchical clustering method and Ripley's K-function. We show that both have significantly clumped distribution patterns and that they are positively associated. However, the dependence of Crested Ibis on the winter-flooded rice fields varied significantly among the nest site clusters and has decreased over the years, indicating the absence of winter-flooded rice fields is not constraining their recovery and population expansion. We therefore recommend that efforts should be made to protect the existing winter-flooded rice fields and to restore the functionality of natural and semi-natural wetlands, to encourage both in-situ conservation and the re-introduction of the Crested Ibis. In addition, we recommend that caution should be exercised when interpreting the habitat requirements of species with a narrow distribution, particularly when that interpretation is based only on their current habitat.

Smallholder farms as stepping stone corridors for crop-raiding elephant in northern Tanzania: integration of Bayesian expert system and network simulator.

Crop-raiding elephants affect local livelihoods, undermining conservation efforts. Yet, crop-raiding patterns are poorly understood, making prediction and protection difficult. We hypothesized that raiding elephants use corridors between daytime refuges and farmland. Elephant counts, crop-raiding records, household surveys, Bayesian expert system, and least-cost path simulation were used to predict four alternative categories of daily corridors: (1) footpaths, (2) dry river beds, (3) stepping stones along scattered small farms, and (4) trajectories of shortest distance to refuges. The corridor alignments were compared in terms of their minimum cumulative resistance to elephant movement and related to crop-raiding zones quantified by a kernel density function. The "stepping stone" corridors predicted the crop-raiding patterns. Elephant presence was confirmed along these corridors, demonstrating that small farms located between refuges and contiguous farmland increase habitat connectivity for elephant. Our analysis successfully predicted elephant occurrence in farmland where daytime counts failed to detect nocturnal presence. These results have conservation management implications.

Shrimp pond effluent dominates foliar nitrogen in disturbed mangroves as mapped using hyperspectral imagery.

Conversion of mangroves to shrimp ponds creates fragmentation and eutrophication. Detection of the spatial variation of foliar nitrogen is essential for understanding the effect of eutrophication on mangroves. We aim (i) to estimate nitrogen variability across mangrove landscapes of the Mahakam delta using airborne hyperspectral remote sensing (HyMap) and (ii) to investigate links between the variation of foliar nitrogen mapped and local environmental variables. In this study, multivariate prediction models achieved a higher level of accuracy than narrow-band vegetation indices, making multivariate modeling the best choice for mapping. The variation of foliar nitrogen concentration in mangroves was significantly influenced by the local environment: (1) position of mangroves (seaward/landward), (2) distance to the shrimp ponds, and (3) predominant mangrove species. The findings suggest that anthropogenic disturbances, in this case shrimp ponds, influence nitrogen variation in mangroves. Mangroves closer to the shrimp ponds had higher foliar nitrogen concentrations.

What drives conversion of tropical forest in Carrasco Province, Bolivia?

The conversion of closed forest (CCF) in Carrasco Province, Bolivia, was monitored using a series of four midresolution satellite images from 1986 to 2002. The conversion of forests into nonforests from 1986 to 2002 was 1.5% annually. Inclusion of conversions into open forest doubles the annual CCF rate to 3.1%. Five predictors of CCF were tested in a spatial model: land tenure regime, distance from roads, distance from settlements, topography, and soil suitability for farming. Only three out of the five predictors tested were found to be reliable predictors of CCF: land tenure regime, distance from roads, and distance from settlements. University reserve and indigenous land show substantially less CCF than national park and untitled land. In addition the spatial model shows that the greater the distance of forest from roads or settlements, the less CCF. Topography and soil suitability for farming lack predictive power for CCF and are therefore excluded from the spatial model.