There is a growing concern over change in vegetation dynamics and drought patterns with the increasing climate variability and warming trends in Africa, particularly in the semiarid regions of East Africa. Here, several geospatial techniques and datasets were used to analyze the spatio-temporal vegetation dynamics in response to climate (precipitation and temperature) and drought in Eritrea from 2000 to 2017. A pixel-based trend analysis was performed, and a Pearson correlation coefficient was computed between vegetation indices and climate variables. In addition, vegetation condition index (VCI) and standard precipitation index (SPI) classifications were used to assess drought patterns in the country. The results demonstrated that there was a decreasing NDVI (Normalized Difference Vegetation Index) slope at both annual and seasonal time scales. In the study area, 57.1% of the pixels showed a decreasing annual NDVI trend, while the significance was higher in South-Western Eritrea. In most of the agro-ecological zones, the shrublands and croplands showed decreasing NDVI trends. About 87.16% of the study area had a positive correlation between growing season NDVI and precipitation (39.34%, p < 0.05). The Gash Barka region of the country showed the strongest and most significant correlations between NDVI and precipitation values. The specific drought assessments based on VCI and SPI summarized that Eritrea had been exposed to recurrent droughts of moderate to extreme conditions during the last 18 years. Based on the correlation analysis and drought patterns, this study confirms that low precipitation was mainly attributed to the slowly declining vegetation trends and increased drought conditions in the semi-arid region. Therefore, immediate action is needed to minimize the negative impact of climate variability and increasing aridity in vegetation and ecosystem services.

Aims: Decomposition of manure deposited onto pasture from grazing animals represents an important process for carbon (C) and nitrogen (N) cycles in grassland systems. However, studies investigating manure decomposition are scarce; especially in sub-Saharan Africa (SSA). Methods: In this study, we measured decomposition of three types of animal manure (cattle, sheep, goat) over >1 year using litter bags at four climatically different sites across Kenya. Results Manure dry matter, total C, total N and ammonium concentrations decreased exponentially, with the most rapid decrease occurring during the first few weeks following application, followed by slower changes during the following 2–3 months. Rates of N mineralization were lower than those for C mineralization, resulting in decreasing C/N ratios over time. Generally, cattle manure decomposed faster than sheep or goat manure despite having a higher initial C/N ratio and lower N concentration, with decomposition rates for dry matter ranging from 0.200 to 0.989 k year⁻¹. Cellulose decomposed first, while lignin concentrations increased among all manure types and at all sites. Conclusions: We found that total manure decomposition rates were positively correlated with cumulative precipitation and aridity index, but negatively correlated with mean temperature. Our results show much slower decomposition rates of manures in semi-arid tropical environments of East Africa as compared to the few previous studies in temperate climates.

Global agricultural lands are becoming saline because of human activities that have affected crop production and food security worldwide. In this study, the spatiotemporal variability of soil electrical conductivity (EC) in Central Asia was evaluated based on high-resolution multi-year predicted soil EC data, Moderate Resolution Imaging Spectroradiometer (MODIS) land cover product, precipitation, reference evapotranspiration, population count, and soil moisture datasets. We primarily detected pixel-based soil EC trends over the past three decades and correlated soil EC with potential deriving factors. The results showed an overall increase in salt-affected areas between 1990 and 2018 for different land cover types. The soil EC trend increased by 6.86% (p < 0.05) over Central Asia during 1990–2018. The open shrub lands dominated by woody perennials experienced the highest increasing soil salinity trend, particularly in Uzbekistan and Turkmenistan local areas, while there was a decreasing soil EC trend in the cropland areas, such as in Bukhara and Khorezm (Uzbekistan). The main factors that affect the variability of soil salinity were strongly associated with population pressure and evapotranspiration. This study provides comprehensive soil EC variations and trends from the local to regional scales. Agriculture and land resource managers must tackle the rising land degradation concerns caused by the changing climate in arid lands and utilise geoinformatics.

Total phosphorus (TP) and total nitrogen (TN) reflect the state of eutrophication. However, traditional point-based water quality monitoring methods are time-consuming and labor-intensive, and insufficient to estimate and assess water quality at a large scale. In this paper, we constructed machine learning models for TP and TN inversion using measured data and satellite imagery band reflectance, and verified it by in situ data. Atmospheric correction was performed on the Landsat Top of Atmosphere (TOP) data by removing the effect of the adjacency effect and correcting differences between Landsat sensors. Then, using the established model, the TP and TN patterns in Dongting Lake with a spatial resolution of 30 m from 1996 to 2021 were derived for the first time. The annual and monthly spatio-temporal variation characteristics of TP and TN in Dongting Lake were investigated in details, and the influences of hydrometeorological elements on water quality variations were analyzed. The results show that the established empirical model can accurately estimate TP with coefficient (R²) ≥ 0.70, root mean square error (RMSE) ≤ 0.057 mg/L, mean relative error (MRE) ≤ 0.23 and TN with R² ≥ 0.73, RMSE ≤ 0.48 mg/L and MRE ≤ 0.20. From 1996 to 2021, TP in Dongting Lake showed a downward trend and TN showed an upward trend, while the summer value was much higher than the other seasons. Furthermore, the influencing factors on TP and TN variations were investigated and discussed. Between 1996 and 2003, the main contributors to the change of water quality in Dongting Lake were external inputs such as water level and flow. The significant changes in water quantity and sediment characteristics following the operation of the Three Gorges Dam (TGD) in 2003 also had an impact on the water quality in Dongting Lake.

Background: Ticks are responsible for transmitting several notable pathogens worldwide. Finland lies in a zone where two human-biting tick species co-occur:IxodesricinusandIxodespersulcatus. Tick densities have increased in boreal regions worldwide during past decades, and tick-borne pathogens have been identified as one of the major threats to public health in the face of climate change.Methods: We used species distribution modelling techniques to predict the distributions ofI.ricinusandI.persulcatus,using aggregated historical data from 2014 to 2020 and new tick occurrence data from 2021. By aiming to fill the gaps in tick occurrence data, we created a new sampling strategy across Finland. We also screened for tick-borne encephalitis virus (TBEV) andBorreliafrom the newly collected ticks. Climate, land use and vegetation data, and population densities of the tick hosts were used in various combinations on four data sets to estimate tick species’ distributions across mainland Finland with a 1-km resolution.Results: In the 2021 survey, 89 new locations were sampled of which 25 new presences and 63 absences were found forI.ricinusand one new presence and 88 absences forI.persulcatus. A total of 502 ticks were collected and analysed; no ticks were positive for TBEV, while 56 (47%) of the 120 pools, including adult, nymph, and larva pools, were positive forBorrelia(minimum infection rate 11.2%, respectively). Our prediction results demonstrate that two combined predictor data sets based on ensemble mean models yielded the highest predictive accuracy for bothI.ricinus(AUC = 0.91, 0.94) andI.persulcatus(AUC = 0.93, 0.96). The suitable habitats forI.ricinuswere determined by higher relative humidity, air temperature, precipitation sum, and middle-infrared reflectance levels and higher densities of white-tailed deer, European hare, and red fox. ForI.persulcatus, locations with greater precipitation and air temperature and higher white-tailed deer, roe deer, and mountain hare densities were associated with higher occurrence probabilities. Suitable habitats forI.ricinusranged from southern Finland up to Central Ostrobothnia and North Karelia, excluding areas in Ostrobothnia and Pirkanmaa. ForI.persulcatus, suitable areas were located along the western coast from Ostrobothnia to southern Lapland, in North Karelia, North Savo, Kainuu, and areas in Pirkanmaa and Päijät-Häme.Conclusions: This is the first study conducted in Finland that estimates potential tick species distributions using environmental and host data. Our results can be utilized in vector control strategies, as supporting material in recommendations issued by public health authorities, and as predictor data for modelling the risk for tick-borne diseases.