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Despite lower‐troposphere wind flow being a major control of rainfall in equatorial Africa, no studies have systematically compared winds from multiple reanalyses nor have attempted to validate the wind directions. Therefore, the objectives of this study are to assess differences in wind directions among multiple reanalysis products and compare reanalysis winds with wind measurements made at weather stations. The study region is western Uganda, part of the transition region between western equatorial Africa (WEA) and eastern equatorial Africa (EEA). Four‐times daily (i.e., 0Z, 6Z, 12Z and 18Z) 10‐m and 850‐hPa winds from 1980 to 2021 are obtained for ECMWF Reanalysis v5 (ERA5), Japan Meteorological Agency 55‐year Reanalysis (JRA55), Modern‐Era Retrospective analysis for Research and Applications Version 2 (MERRA2), NCEP‐NCAR Reanalysis 1 (R1) and NCEP/DOE Reanalysis II (R2). Wind measurements at 10 m and 850 hPa are obtained for six weather stations and two weather stations, respectively. Agreements between pairs of products and between measurements and reanalysis estimates are determined. In addition, differences between reanalyses and measurements with respect to wind vectors are calculated. Results show that the majority of reanalyses have western Uganda within the prevailing easterly flow over EEA and east of the prevailing westerly flow over WEA. Ten‐meter wind measurements also show easterly flow being prevalent throughout western Uganda. R1 is unique among the products due to a relatively large number of westerly days. However, much of the westerly flow is likely artificial, based on station data. MERRA2 has large easterly biases. JRA55 is much more accurate than the other products at reproducing the intra‐annual frequencies of wind directions. JRA55 and ERA5 are the least biased products based on the magnitudes of difference vectors. Therefore, it is recommended that JRA55 and ERA5 continue to be used in examinations of winds in western Uganda. [ABSTRACT FROM AUTHOR]

Substantial research on the teleconnections between rainfall and sea surface temperatures (SSTs) has been conducted across equatorial Africa as a whole, but currently no focused examination exists for western Uganda, a rainfall transition zone between eastern equatorial Africa (EEA) and central equatorial Africa (CEA). This study examines correlations between satellite-based rainfall totals in western Uganda and SSTs—and associated indices—across the tropics over 1983–2019. It is found that rainfall throughout western Uganda is teleconnected to SSTs in all tropical oceans but is connected much more strongly to SSTs in the Indian and Pacific Oceans than in the Atlantic Ocean. Increased Indian Ocean SSTs during boreal winter, spring, and autumn and a pattern similar to a positive Indian Ocean dipole during boreal summer are associated with increased rainfall in western Uganda. The most spatially complex teleconnections in western Uganda occur during September–December, with northwestern Uganda being similar to EEA during this period and southwestern Uganda being similar to CEA. During boreal autumn and winter, northwestern Uganda has increased rainfall associated with SST patterns resembling a positive Indian Ocean dipole or El Niño. Southwestern Uganda does not have those teleconnections; in fact, increased rainfall there tends to be more associated with La Niña–like SST patterns. Tropical Atlantic Ocean SSTs also appear to influence rainfall in southwestern Uganda in boreal winter as well as in boreal summer. Overall, western Uganda is a heterogeneous region with respect to rainfall–SST teleconnections; therefore, southwestern Uganda and northwestern Uganda require separate analyses and forecasts, especially during boreal autumn and winter. SIGNIFICANCE STATEMENT: Seasonal rainfall greatly impacts the millions of rural households practicing rain-fed agriculture across equatorial Africa; therefore, understanding the relationship between rainfall and tropical sea surface temperatures (SSTs) can benefit smallholder farmers and other stakeholders. This study examines over the 1983–2019 period the relationships between SSTs and monthly and seasonal rainfall totals in western Uganda. During Northern Hemisphere (boreal) spring and summer, increased SSTs in the Indian Ocean along with La Niña–like SST patterns are generally associated with increased rainfall for the entire region. Rainfall–SST relationships have substantial spatial variability during boreal autumn and winter: only northwestern Uganda has increased rainfall strongly associated with the positive Indian Ocean dipole and El Niño–like SST patterns. These findings have implications for the region-specific forecasts provided to farmers. [ABSTRACT FROM AUTHOR]

Within conservation science and practice, community‐based conservation (CBC) includes policy and management interventions incorporating engagement or participation of local communities and resource users. Evidence across scales points to the importance of supporting local actors and management institutions for better social and ecological outcomes of CBC interventions. However, the institutional and governance processes underlying CBC outcomes remain poorly understood, specifically how institutions respond to opportunities and constraints posed by CBC. In response, this special issue of Conservation Science & Practice solicited contributions investigating adaptation and evolution of institutions and governance in CBC. In this paper, we introduce the special issue and its 13 contributions, representing cases from Africa, Asia, and the Americas across organizational scales and resource systems. We assess the state of knowledge of CBC, identify common themes and lessons learned, and suggest future priorities for research and practice. [ABSTRACT FROM AUTHOR]

Community‐based conservation (CBC) is essential to promoting biodiversity protection and livelihood development. Despite significant financial and institutional investment, performance of CBC interventions is mixed, with shortcomings especially evident in wildlife‐based CBC in Africa. CBC outcomes are typically evaluated through household livelihood gains, or through policy analysis at higher administrative levels such as the central state. Surprisingly, village or local governance capacity is often missing from project assessment. Through a controlled study, we evaluate CBC interventions at multiple scales in Tanzania. Employing Bayesian multilevel latent trait models, we find that CBC participation predicts stronger village governance institutions. Additionally, compared to control villages, CBC villages have more local civic organizations and small business enterprise, but do not experience greater elite capture of public goods. Together, and in the absence of direct CBC benefits provisioned to households or signs of success at the higher level of multi‐village CBC bodies, these findings point to the possibility that village‐level governance institutions can adapt in beneficial ways to prolonged CBC interventions. [ABSTRACT FROM AUTHOR]

Interactions between humans and wildlife resulting in negative impacts are among the most pressing conservation challenges globally. In regions of smallholder livestock and crop production, interactions with wildlife can compromise human well‐being and motivate negative sentiment and retaliation toward wildlife, undermining conservation goals. Although impacts may be unavoidable when human and wildlife land use overlap, scant large‐scale human data exist quantifying the direct costs of wildlife to livelihoods. In a landscape of global importance for wildlife conservation in southern Africa, we quantified costs for people living with wildlife through a fundamental measure of human well‐being, food security, and we tested whether existing livelihood strategies buffer certain households against crop depredation by wildlife, predominantly elephants. To do this, we estimated Bayesian multilevel statistical models based on multicounty household data (n = 711) and interpreted model results in the context of spatial data from participatory land‐use mapping. Reported crop depredation by wildlife was widespread. Over half of the sample households were affected and household food security was reduced significantly (odds ratio 0.37 [0.22, 0.63]). The most food insecure households relied on gathered food sources and welfare programs. In the event of crop depredation by wildlife, these 2 livelihood sources buffered or reduced harmful effects of depredation. The presence of buffering strategies suggests a targeted compensation strategy could benefit the region's most vulnerable people. Such strategies should be combined with dynamic and spatially explicit land‐use planning that may reduce the frequency of negative human–wildlife impacts. Quantifying and mitigating the human costs from wildlife are necessary steps in working toward human–wildlife coexistence. Article Impact statement: Multicounty household data show livelihood costs from wildlife crop depredation. [ABSTRACT FROM AUTHOR]

Long‐term trends in equatorial African rainfall have proven difficult to determine because of a dearth in ground‐measured rainfall data. Multiple, satellite‐based products now provide daily rainfall estimates from 1983 to the present at relatively fine spatial resolutions, but in order to assess trends in rainfall, they must be validated alongside ground‐based measurements. The purpose of this paper is twofold: (a) to assess the accuracy of four rainfall products covering the past several decades in western Uganda; and (b) to ascertain recent, multi‐decadal trends in annual rainfall for the region. The four products are African Rainfall Climatology Version 2 (ARC2), Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN‐CDR), and TAMSAT African Rainfall Climatology And Timeseries (TARCAT). The bias and accuracy of 10‐day, monthly, and seasonal rainfall totals of the four products were assessed using approximately 10 years of data from 10 rain gauges. The homogeneity of the products over multiple time periods was assessed using change‐point analysis. The accuracy of the four products increased with an increase in temporal scale, and CHIRPS was the only product that could be considered sufficiently accurate at estimating seasonal rainfall totals throughout most of the region. TARCAT tended to underestimate totals, and ARC2 and PERSIANN were in general the least accurate products. Only annual rainfall estimates from CHIRPS and TARCAT were significantly correlated with ground‐measured rainfall totals. TARCAT was the most homogeneous product, while ARC2, CHIRPS, and PERSIANN had significant negative change points that caused a drying bias over the 1983–2016 period. After adjusting the satellite‐based rainfall estimates based on the timing and magnitude of the change points, annual rainfall totals derived from all four products indicated that western Uganda experienced significantly increasing rainfall from 1983 to 2016. [ABSTRACT FROM AUTHOR]

Smallholder farmers and livestock keepers in sub-Saharan Africa are on the frontlines of climate variability and change. Yet, in many regions, a paucity of weather and climate data has prevented rigorous assessment of recent climate trends and their causes, thereby limiting the effectiveness of forecasts and other services for climate adaptation. In rainfed systems, farmer perceptions of changing rainfall and weather patterns are important precursors for annual cropping decisions. Here, we propose that combining such farmer perceptions of trends in seasonal rainfall with satellite-based rainfall estimates and climate station data can reduce uncertainties regarding regional climatic trends. In western Uganda, a rural and climatically complex transition zone between eastern and central equatorial Africa, data from 980 smallholder households suggest distinct changes in seasonal bimodal rainfall over recent decades, specifically wetter rainy seasons and drier dry seasons. Data from three satellite-based rainfall products beginning in 1983 largely corroborate respondent perceptions over the last 10–20 years, particularly in the southernmost sites near Queen Elizabeth National Park. In addition, combining all three information sources suggests an increasing trend in annual rainfall, most prominently in the north near Murchison Falls National Park over the past two decades; this runs counter to recent research asserting the presence of a drying trend in the region. Our study is unique in evaluating and cross-validating these multiple data sources to identify climatic change affecting people in a poorly understood region, while providing insights into regional-scale climate controls. [ABSTRACT FROM AUTHOR]

Largely absent from the current scientific dialog is recognition of which voices should contribute to decisions on the future of Africa's elephants, particularly those living in the Kavango‐Zambezi Transfrontier Conservation Area. We argue that elephant conservation policy must take into account the voices of the people bearing the cost of living with wildlife, as well as the nations with the responsibility of hosting elephant populations. Southern African elephant conservation is a 'wicked problem', which is best addressed through small wins approaches. Specifically, research on changes in local political and governance dynamics resulting from community conservation programs is needed, to identify new modalities for community level engagement. Additionally, research into policy implications, as well as seasonal resource needs of humans and wildlife, from zoning and corridor development to facilitate landscape level movement is needed. A modular approach to research for ensuring functional social–ecological landscapes within the KAZA context could help sustain both wildlife and communities in the region. [ABSTRACT FROM AUTHOR]

Smallholder farmers in Sub-Saharan Africa (SSA) are not only dealing with decreased production from land degradation, but are also impacted heavily by climate variability. Farmers perceive decreased rainfall or shortened rainy seasons throughout SSA; however, the link between perceptions and climate variability is complex, especially in areas with increasing land degradation. Moreover, little is known about climate variability and farmers' perceptions in central equatorial Africa. The purpose of this study is to quantify interannual rainfall variability from 1983 to 2014 in western Uganda and to relate the rainfall variability and associated changes in soil moisture to perceptions and coping strategies of local farmers. Surveys of 308 farming households and 14 group interviews were conducted near Kibale National Park, and daily satellite-based rainfall data for the region were extracted from the African Rainfall Climatology version 2 database. Results indicate a decrease in the long rains by approximately 3 weeks throughout much of the region; thus, soil-water deficits have intensified. Farmers perceived later onsets of both the short rains and long rains, while also reporting decreasing soil fertility and crop yields. Therefore, farmers' perceptions of rainfall variability in the Kibale region may reflect more the decrease in soil fertility than the shortened rainy seasons and decreased soil moisture. Expanding croplands has been the farmers' most prevalent coping strategy to decreased yields; however, nearly all the unfarmed land in western Uganda is now in protected areas. Consequently, western Uganda is facing a crisis at the nexus of population growth, land use change, and climate change. [ABSTRACT FROM AUTHOR]

Characterizing compositional and structural aspects of vegetation is critical to effectively assessing land function. When priorities are placed on ecological integrity, remotely sensed estimates of fractional vegetation components (FVCs) are useful for measuring landscape-level habitat structure and function. In this study, we address whether FVC estimates, stratified by dominant vegetation type, vary with different classification approaches applied to very-high-resolution small unoccupied aerial system (UAS)-derived imagery. Using Parrot Sequoia imagery, flown on a DJI Mavic Pro micro-quadcopter, we compare pixel- and segment-based random forest classifiers alongside a vegetation height-threshold model for characterizing the FVC in a southern African dryland savanna. Results show differences in agreement between each classification method, with the most disagreement in shrub-dominated sites. When compared to vegetation classes chosen by visual identification, the pixel-based random forest classifier had the highest overall agreement and was the only classifier not to differ significantly from the hand-delineated FVC estimation. However, when separating out woody biomass components of tree and shrub, the vegetation height-threshold performed better than both random-forest approaches. These findings underscore the utility and challenges represented by very-high-resolution multispectral UAS-derived data (~10 cm ground resolution) and their uses to estimate FVC. Semi-automated approaches statistically differ from by-hand estimation in most cases; however, we present insights for approaches that are applicable across varying vegetation types and structural conditions. Importantly, characterization of savanna land function cannot rely only on a "greenness" measure but also requires a structural vegetation component. Underscoring these insights is that the spatial heterogeneity of vegetation structure on the landscape broadly informs land management, from land allocation, wildlife habitat use, natural resource collection, and as an indicator of overall ecosystem function. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Systems (UAS) represent an important niche platform for measuring vegetation health, structure, and productivity; metrics that directly inform sustainable conservation and development initiatives in rural African savannas. Products derived from UAS imagery have much finer spatial resolutions than traditional satellite or aircraft imagery, allowing the spectral and structural heterogeneity of vegetation to be mapped and monitored with more detail, an advantage especially useful for challenging environments such as dryland savannas. This study uses UAS-captured imagery to assess the efficacy of UAS for monitoring structural characteristics of vegetation in a mixed savanna woodland. The main objective was to compare multiple approaches for extracting woody vegetation structure from UAS imagery and assess correlations between in situ field measurements and UAS estimates. We compare different sensor types to determine whether multispectral data improve estimates of vegetation structure at the expense of spatial resolution. Results indicate that leveraging multispectral reflectance information, particularly in the near-infrared portion of the spectrum, aids in crown delineation, areal estimates, and fractional cover of woody and non-woody vegetation within the study area. We also compare two image segmentation techniques for crown delineation and found that all techniques perform best in grassy savanna sites where trees and shrubs are easily distinguishable. Overall, a region-growing technique consistently exhibits highest levels of agreement with in situ height and crown area measurements, while a simple height threshold is best for determining fractional coverage of structural classes present. Findings from this work contribute to the advancement for applying high spatial resolution, UAS-derived methods in remote sensing analyses with specific consideration towards autonomous crown delineation and resource management initiatives in dryland systems. Lastly, data-informed analyses, as presented here, provide robust scientific evidence that contribute to informing environmental management decisions when considering the use of UAS technology in conservation and wildlife management across Africa. [ABSTRACT FROM AUTHOR]