Archetypes of remnant West African forest patches, their main characteristics and geographical distribution

Remnant West African forest patches provide crucial ecosystem functions and services while contributing to sustaining the livelihoods of vast numbers of people. The vast majority lie outside of protected areas, although relatively few are managed as sacred forests, which limits their access and use. This lack of protection, together with a growing demand for arable land and forest resources, have accentuated their fragmentation, degradation, and deforestation. There is therefore an urgent need to generate knowledge on their social-ecological characteristics and change pressures to support their conservation. This study investigates what are i) the main biophysical and social-ecological characteristics of remnant forest patches, and ii) the potential change pressures and drivers. Within this scope, we apply archetype analysis to discern processes affecting remnant forest patches. Biophysical and socio-ecological indicators were selected from a published dataset via expert consultation, and nine archetypes were developed by applying a cluster analysis. Evaluating the results in relation to ecoregions and landscape features using high resolution imagery, we identify common underlying social-ecological change pressures and characteristics. The most common archetype (2) is characterized by being close to protected areas and having a low average annual precipitation and cluster along the northern fringe of the study area. The second most common archetype (5) is characterized by lying in highly disturbed landscapes, having undergone biomass losses, and widely distributed throughout central and western Nigeria. Patches of archetype 8 found predominantly in mangrove and swamp forests, exhibit positive above-ground biomass changes and greening trends; we propose that these vegetation changes could benefit conservation measures and carbon sequestration programs. In contrast, archetype 10 patches show both forest and biomass losses and gains and are often encompass fragmented forests in urban/arable landscapes. Identifying such common patterns of anthropogenic and ecological change provides a means of prioritizing regionalized strategies for their conservation and sustainable use

A Remote Sensing-Based Inventory of West Africa Tropical Forest Patches: A Basis for Enhancing Their Conservation and Sustainable Use

The rate of tropical deforestation is increasing globally, and the fragmentation of remaining forests is particularly high in arable landscapes of West Africa. As such, there is an urgent need to map and monitor these remnant forest patches/fragments and so identify their multiple benefits and values. Indeed, recognizing their existence will help ensure their continued provision of ecosystem services while facilitating their conservation and sustainable use. The aim of this study is therefore to inventory and characterise the current extent and change of remnant forest patches of West Africa, using multi-source remote sensing products, time-series analyses, and ancillary datasets. Specifically, we collate and analyse descriptive and change metrics to provide estimates of fragment size, age, biophysical conditions, and relation to social-ecological change drivers, which together provide novel insights into forest fragment change dynamics for over four decades. We map forests patches outside protected areas with a tree cover ≥30%, a tree height of ≥5 m, an area ≥1 km2 and ≤10 km2. Appended to each patch are descriptive and change dynamics attributes. We find that most fragments are small, secondary forest patches and these cumulatively underwent the most forest loss. However, on average, larger patches experience more loss than smaller ones, suggesting that small patches persist in the landscape. Primary forest patches are scarce and underwent fewer losses, as they may be less accessible. In 1975 most patches were mapped as secondary, degraded forests, savanna, woodland, and mangrove, and relatively few comprised cropland, settlements, and agriculture, suggesting that new forest patches rarely emerged from arable land over the past 45 years (1975–2020), but rather are remnants of previously forested landscapes. Greening is widespread in larger secondary fragments possibly due to regrowth from land abandonment and migration to urban areas. Forest loss and gain are greater across fragments lying in more modified landscapes of secondary forests, while forest loss increases with distance to roads. Finally, larger forest patches harbour a denser tree cover and higher trees as they may be less impacted by human pressures. The number and extent of West African forest patches are expected to further decline, with a concurrent heightening of forest fragmentation and accompanying edge effects. Lacking any conservation status, and subject to increasing extractive demands, their protection and sustainable use is imperative

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Vegetation Trends, Drought Severity and Land Use-Land Cover Change during the Growing Season in Semi-Arid Contexts

Drought severity and impact assessments are necessary to effectively monitor droughts in semi-arid contexts. However, little is known about the influence land use-land cover (LULC) has—in terms of the differences in annual sizes and configurations—on drought effects. Coupling remote sensing and Geographic Information System techniques, drought evolution was assessed and mapped. During the growing season, drought severity and the effects on LULC were examined and whether these differed between areas of land change and persistence. This study used areas of economic importance to Botswana as case studies. Vegetation Condition Index, derived from Normalised Difference Vegetation Index time series for the growing seasons (2000–2018 in comparison to 2020–2021), was used to assess droughts for 17 constituencies (Botswana’s fourth administrative level) in the Central District of Botswana. Further analyses by LULC types and land change highlighted the vulnerability of both human and natural systems to drought. Identified drought periods in the time series correspond to declared drought years by the Botswana government. Drought severity (extreme, severe, moderate and mild) and the percentage of land areas affected varied in both space and time. The growing seasons of 2002–2003, 2003–2004 and 2015–2016 were the most drought-stricken in the entire time series, coinciding with the El Niño southern oscillation (ENSO). The lower-than-normal vegetation productivity during these growing seasons was evident from the analysis. With the above-normal vegetation productivity in the ongoing season (2020–2021), the results suggest the reversal of the negative vegetation trends observed in the preceding growing seasons. However, the extent of this reversal cannot be confidently ascertained with the season still ongoing. Relating drought severity and intensities to LULC and change in selected drought years revealed that most lands affected by extreme and severe drought (in descending order) were in tree-covered areas (forests and woodlands), grassland/rangelands and croplands. These LULC types were the most affected as extreme drought intersected vegetation productivity decline. The most impacted constituencies according to drought severity and the number of drought events were Mahalapye west (eight), Mahalapye east (seven) and Boteti west (seven). Other constituencies experienced between six and two drought events of varying durations throughout the time series. Since not all constituencies were affected similarly during declared droughts, studies such as this contribute to devising appropriate context-specific responses aimed at minimising drought impacts on social-ecological systems. The methodology utilised can apply to other drylands where climatic and socioeconomic contexts are similar to those of Botswana

Changes to agricultural landscapes impact the quality of land: An African continent-wide assessment in gained and displaced agricultural lands

Agricultural land area is increasing globally despite the loss of productive agricultural lands in some world regions. The knowledge about major agricultural land changes and the impacts on the quality of land in both cropland and grassland in Africa is still very limited. We conducted an African continent-wide assessment of the dynamics of agricultural landscapes (i.e., gains, losses, and net change). With pressure mounting to halt biodiversity loss and stem land degradation in agricultural areas across all world regions, promoting sustainable agriculture requires not only an understanding of agricultural land-use change but also the impacts of such changes on land quality. We identify influencing factors and model the quality of land associated with agricultural land gains and losses between 2000 and 2018. Land quality in gained and displaced croplands and grasslands was established using spatially-explicit analysis of changes in Net Primary Productivity, soil organic carbon content, crop suitability and percent yield change for five major crops of global importance grown across Africa. These are maize, rice, soybean, wheat, and alfalfa. Influencing factors in each agricultural land change area (i.e., areas of cropland and grassland gains and losses) were examined. In cropland loss and gain areas, settlement development, proximity to perennial rivers/water bodies, and access to a major road were important. For example, most land areas transitioning to cropland in Africa were associated with large distances away from major roads. The preceding finding suggests the remoteness of newly gained croplands. However, distances to a major road, waterbody, settlement, and elevation were important for explaining grassland dynamics. Land quality was better in gained croplands than in those lost, whereas gained grasslands were of lesser quality compared to areas of grassland loss. Five typologies of African countries were developed based on net yield and amount of land cultivated per crop in cropland change areas. Type 1 typifies net yield increase and cultivated land decrease, while type 2 is characterized by yield increase consequent upon cropland expansion. Net yield and land remain unchanged in type 3, while in type 4, cultivated land increased, but yield decreased for maize in 40% of African countries, and in type 5, yield and land area decreased. This study thus provides evidence about the quality of land in gained and lost agricultural areas and generalizable insights on their dynamics across Africa

Land cover change effects on land surface temperature trends in an African urbanizing dryland region

Land use-land cover (LULC) association with land surface temperature (LST) is well known. Knowledge about land change effects on LST in urbanizing African drylands is very limited. We examined LST and vegetation variations in semi-arid Gaborone (Botswana's capital) using MODIS daytime and night-time LST (DNLST), and Normalized Difference Vegetation Index (NDVI) between 2000 and 2018. Significant land transitions were identified in the land cover change map using Change Vector Analysis of Landsat-based biophysical indices of vegetation, water and bare soil. Artificial surface and tree-covered areas were net gaining categories, whereas cropland and grassland were net losing categories. Detailed profiling of DNLST trends and breakpoints was conducted in five relatively homogenous sites representing land cover/transitions. Increasing NDVI and DNLST trends found were significant. Per class, LST change at daytime and night-time are as follows: built-up areas (1.8 K, 2.2 K), Gaborone dam (5.7 K, 0.2 K), settlement expansion areas (4.6 K, 2.2 K), and rural settlement (2.0 K, 1.5 K). The cooling effect of irrigation on daytime LST was higher than night-time LST as daytime LST trend as low as −0.4 K was found in areas of irrigated croplands. Validation with synoptic station temperature data and dam water levels provides empirical evidence that MODIS gave credible DNLST estimates in this urbanizing dryland area. Our results also suggest the role of climate variability in urbanizing drylands alongside land cover change in controlling the LST. Regardless, coupling DNLST and land cover changes can provide useful information for spatial planning of drylands to create smart cities that are resilient to climate change

Assessing UN indicators of land degradation neutrality and proportion of degraded land for Botswana using remote sensing based national level metrics

Achieving land degradation neutrality (LDN) has been proposed as a way to stem the loss of land resources globally. To date, LDN operationalization at the country level has remained a challenge both from a policy and science perspective. Using an approach incorporating cloud‐based geospatial computing with machine learning, national level datasets of land cover, land productivity dynamics, and soil organic carbon stocks were developed. Using the example of Botswana, LDN and proportion of degraded land were assessed. Between 2000 and 2015, grassland lost approximately 17% of its original extent, the highest level of loss for any land category; land productivity decline was highest in artificial surface areas (11%), whereas 36% of croplands show early signs of decline. With the use of national metrics (NM), degraded areas were found to be 32.6% compared to 51.4% of the total land area when global default datasets (DD) were used. Estimates of degraded land computed with NM and DD were validated in Palapye, an agro‐pastoral region in eastern Botswana, where Composite Land Degradation Index (CLDI) field‐based data exists. Comparing land degradation (LD) in the three datasets (NM, DD, and CLDI), NM estimates were closest to the field data. The extra efforts put into developing national level data for LD assessment in this study is, thus, well‐justified. Beyond demonstrating remote sensing viability for LD assessment, the study developed procedures for generating and validating national level datasets. Using these procedures, LD monitoring will be enhanced in Botswana and elsewhere since these remote sensing datasets can be updated using freely available satellite datasets