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.

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.