Elephant crop-raiding and human-elephant conflict in Cambodia: crop selection and seasonal timings of raids

Elephants are threatened globally by habitat loss, poaching and accelerating levels of human-elephant conflict. For Elephas maximus in Cambodia, crop raiding underlies this conflict. Understanding the timing of raids and selection of crops can help design locally appropriate mitigation and management strategies. This study, using a 4-year database of events, investigated the most frequently raided crops and patterns of raids, over time and seasons and by location. Damage frequency varied significantly by crop, with rice, banana, cassava, sugar cane and papaya most frequently raided. Considering raid events per unit crop area, banana, sugar cane and pineapple were raided more than would be expected based on their availability. There were differences in both crop-raiding events and crop-damage frequencies over study years and there was a peak raiding season in October-December. Nationally, significant differences were found among provinces but not between years. Rates of damage decreased after mitigation strategies such as observation towers, deterrents and fences were implemented. We suggest further mechanisms to improve human-elephant conflict monitoring in relation to crop choice and availability

Patch - Occupancy Survey of Elephant (Loxodonta africana) Surrounding Livingstone, Zambia

Wild elephants represent the biggest human–wildlife conflict issue in Livingstone, Zambia. However, little is known about their movements. This survey investigated elephants’ habitat use outside a core protected and fenced zone that forms part of Mosi-oa-Tunya National Park, Zambia. Using ‘patch-occupancy’ methodology, indications of elephant presence (feeding behaviour, dung and tracks) were surveyed. The survey aimed to assist proposed future monitoring exercises by defining the geographical extent that should be considered to improve accuracy in species abundance estimates. Results were supplemented using collected indications of elephant presence from prior monitoring exercises, and during this survey. Elephant presence was confirmed up to 8 km from the boundary of the protected core habitat, focussed in: (1) an unfenced zone of the national park, (2) along a road leading from the national park to the Dambwa Forest to the north and (3) along two rivers located to the west (Sinde River) and east (Maramba River) of the core area. Detection probability of elephant presence was high using these methods, and we recommend regular sampling to determine changes in habitat use by elephants, as humans continue to modify land-use patterns. Conservation implications: Identification of elephant ranging behaviour up to 8 km outside of the Mosi-oa-Tunya National Park in southern Zambia will assist in managing human– elephant conflict in the area, as well as in assessing this seasonal population’s abundance

Driver determination of increased cyanobacterial activity within the waters of the Okavango Delta

The data consists of multiple different files which include data on the Land Use and Land Cover and their change within the region, as well as locally collected precipitation and temperature data, NDCI and GLH data showcasing algal bloom activity, and vegetation indices. Most of the data was collected remotely using Satellite data, this data was collected during the Summer of 2021 and consists of monthly data points for the 2017-2020 time period, covering the greater Okavango Delta region. The weather data was collected locally on a monthly basis for the same 2017-2020 time period near the Kasane airport in Northern Botswana. The data was collected to determine the driving landscape and climate factors behind the increased algal and toxic cyanobacterial activity within the waters of the Okavango Delta. As mentioned earlier, the bulk of the data used was remote satellite data, specifically Sentinel-2 data. Sentinel-2 data is freely available . The data was collected using Google Earth Engine and the Copernicus website (https://scihub.copernicus.eu/dhus/# /home), and worked with in both SNAP and ERDAS Imagine software. The LULC maps were created using ERDAS Imagine unsupervised classification. The weather data was locally collected using a meteorological station located on the Kasane airport