Enggano Island holds high endemic biodiversity, yet pressure on its forests keeps rising. This article examines the community-based monitoring (CBM) carried out by the Enggano indigenous people together with the Enggano Monitoring Team in February and March 2025. The monitoring covered Protection Forest and Limited Production Forest areas of roughly 125 ha spread across six grids. The methods combined ground checks, line transects, bird point counts, feed-plant inventories, resident interviews, and satellite imagery and geographic information system (GIS) analysis through the QField application. The team recorded 43 animal signs, several direct encounters with endemic species such as the Enggano myna and the Enggano imperial pigeon, and a clear dominance of wildlife feed plants and other useful plants. The 2024 land cover data show that forest still covers 55.97 percent of the island. These findings position CBM not merely as a tool for collecting ecological data, but as an instrument for defending customary territory, a means of restoring the relationship between residents and their forest, and a way of preparing a local discourse on multispecies eco-justice. The authors argue that resident-generated data strengthen the bargaining position of the indigenous people in the customary forest recognition process that followed Constitutional Court Decision No. 35/PUU-X/2012, while also building an evidentiary basis for treating nonhuman beings as holders of justice claims.
This study analyzes flood dynamics in the Greater Lome area based on remote sensing and hydrometeorological data analysis. Daily rainfall data from the Lome-Airport synoptic station (2016 and 2020) were collected from the National Meteorological Agency of Togo (ANAMET) during the rainy season (March to October). Daily water levels in the Zio River at Togblekope were collected from the General Directorate of Hydraulics (DGH) during the rainy season (March to October) for the years 2016 and 2020. The time series were subjected to homogeneity tests to identify any artificial breaks in the data collected using RHtests dlyPrcp software. Radar data were processed using SNAP software, while maps were processed in ArcGIS 10.5. During 2016, a peak of 1,608 ha, corresponding to the maximum flooded area, was reached on August 24. At the start of the season, 40.29% of the maximum flooded area was submerged. In 2016, the population was therefore faced with at least thirty consecutive days of rising water levels. Not all districts were affected equally by the floods in 2016. The districts of Abobo, Djagble, and Be-Est were the most severely affected. The intra-annual dynamics of 2020 are similar to those of 2016. During 2020, the peak of 930 ha corresponding to the maximum flooded area was reached on September 2. At the beginning of the season, on June 16, only 11% of the maximum flooded area was submerged. All cantons were unevenly affected by the floods in 2020. The cantons of Abobo, Akepe, Mission Tove, Davie, and Adetikope were the most affected by the phenomenon. The results show a 45% decrease in flooded areas between 2016 and 2020, with a peak of 1,608 hectares reached on August 24, 2016, compared to 930 hectares on September 2, 2020, reflecting earlier and more intense flooding in 2016.
One of the major issues facing in tier-II cities like Tumakuru is the Efficient implementation Of Integrated Municipal Solid Waste Management. In order to choose the best Scientific Waste Treatment Technologies and Management Strategies for Tumakuru city, the amount and Composition of Municipal Solid Waste (MSW) differ considerably over the course of three distinct seasons. In order to ascertain the average per capita waste generation in each of Tumakuru City Corporation's (TCC) thirty-five wards, household data was gathered through a survey. Waste samples from 1050 households in each of the three seasons were recorded in order to calculate the average Household generation for five wards. According to the study's findings, the total amount of waste produced by Tumakuru city's households can be estimated at 110 TPD. And the results show that MSW samples have seasonal variation in Moisture content ranging from 27.52% to 41.2%, with an average of 34.46% which is suitable for composting and Biomethanation. The Calorific value having medium energy recovery potential which is suitable for refuse derived fuel (RDF). The overall results of MSW revealed significant seasonal effects on Moisture content, TOC, and Nutrient Parameters, confirming that climatic conditions strongly influence waste characteristics.
Irregular rainfall limits adequate crop production within the Uromi in south – south agroecological zone of Nigeria. This study was carried out to analyse the rainfall pattern, onset and cessation of rainy season including the length of growing season for agricultural production in Uromi, Edo state. Secondary data collected from NiMET maproom for the period 1991 – 2024 were used. The result revealed a variation in rainfall pattern in the area which led to variation in onset and cessation of rainfall including length of growing season. A very high variability in the onset of rain was observed with a CV of 95%, cessation has a CV of 30.67% indicating a high variability while length of growing season has a low variability with a CV of 3.88%. The trend analysis shows that onset of the rainy season has a negative trend of y = -0.1329x + 9.8556 with an R-squared value of 0.0304. A positive trend was observed for cessation of rain with a best fit line equation y = 0.1134x + 13.369 and a low R 2 of 0.0605 which is discernible trend in the data. The length of growing season has a positive slope (y = 0.2527x + 217.7) and an R 2 of 0.0853. The observed trend in the area may have been triggered off by intrinsic and extrinsic factors. This information is very important to farmers in Uromi in deciding on crop types to be cultivated and on planning sowing dates as a function of observed onset dates. The study recommend Farmers should change/shift their planting period to appropriate time since the onset date has changed in order to avoid crop damage at the early stage, Government should provide the farmers with early matured crop and improved crop varieties, mitigation/adaptation action is highly needed in order to cope with the problem.
Soil temperature is the temperature of the soil at different depths beneath the soil surface and does not only indicate climate change. Agricultural practices are strongly impacted by soil temperature making it a very important variable for soil conditions. Thermal diffusivity is the ratio of thermal conductivity to volumetric heat capacity. It tells how materials conduct thermal energy relative to how they store thermal energy. Soil temperature is strongly affected by thermal diffusivity. Therefore the purpose of this study is to investigate soil temperature variations and thermal diffusivity during the wet and dry seasons in Ibadan, Oyo State, Nigeria. Soil temperature data at depths of 5 cm, 10 cm, and 30 cm were obtained from the Nigeria Mesoscale Experiment (NIMEX) site for the period July to December 2006, covering both wet (July–September) and dry (October–December) seasons. Thermal diffusivity was estimated using the Horton numerical method. Results show clear seasonal and depth-dependent variations in soil temperature, with lower temperatures recorded during the wet season due to increased soil moisture and cloud cover, and higher temperatures during the dry season associated with reduced moisture and increased solar radiation. Temperature amplitude decreased with depth, indicating attenuation of surface thermal signals. Thermal diffusivity exhibited significant variability, with maximum values recorded in September and minimum (including negative) values also occurring within the wet season. The negative diffusivity values are attributed to rapid temporal temperature fluctuations linked to soil moisture dynamics and the sensitivity of the numerical method used. Overall, the study highlights the strong influence of seasonal climatic conditions and soil moisture on soil thermal regimes in tropical environments.
