Modelling future range shift gaps in a biodiversity hotspot : a case study of critically endangered plants in Madagascar

The synergy between climate and land use land cover change is expected to influence species distribution at local and regional scales in tropical regions. However, robust quantification of species responses and species-specific dispersal rates is lacking for most of Sub-Saharan Africa. This project aims to model range-shift gaps for 84 endangered or critically endangered plant species due to environmental change in Madagascar. To achieve this deforestation and forest degradation rates were quantified from Landsat imagery using sub-pixel analysis in two intervals (i.e, 1994-2002 and 2002-2014). Next, intensity analysis was used to determine processes of LULCC at eco-regional scale, while morphological spatial pattern analysis was applied for the determination of protected areas connectivity. Furthermore, species distribution models were constructed using hierarchical Bayesian modelling approach that included corridor connectivity and uncertainties in the derived predictions of species distribution under current and future scenarios. Finally, six spatial indices that quantified vulnerabilities, species range-shifts and displacement were derived from these predictions. The results showed differentiation in rates of deforestation and forest degradation across eco-regions. On average plant species' range were predicted to shift by approximately 300 km under future scenarios with and without connectivity. Corridor connectivity will facilitate more species upward displacements under low emission scenarios compared to high emission scenarios. Eastern humid forest were identified as 'range shift hotspots' and will be characterised by substantial species' range contractions in future scenarios. Biodiveristy in the region will experience novel threats from climate and land use cover change. Conservationist need to adapt on-going intervention programmes to prepare for the potential risks of species extinctions due to environmental change through the integration of spatial conservation planning concepts in policy formulation

Feeding efficiency gains can increase the greenhouse gas mitigation potential of the Tanzanian dairy sector.

We use an attributional life cycle assessment (LCA) and simulation modelling to assess the effect of improved feeding practices and increased yields of feed crops on milk productivity and GHG emissions from the dairy sector of Tanzania’s southern highlands region. We calculated direct non-CO2 emissions from dairy production and the CO2 emissions resulting from the demand for croplands and grasslands using a land footprint indicator. Baseline GHG emissions intensities ranged between 19.8 and 27.8 and 5.8–5.9 kg CO2eq kg−1 fat and protein corrected milk for the Traditional (local cattle) and Modern (improved cattle) sectors. Land use change contributed 45.8–65.8% of the total carbon footprint of dairy. Better feeding increased milk yields by up to 60.1% and reduced emissions intensities by up to 52.4 and 38.0% for the Traditional and Modern sectors, respectively. Avoided land use change was the predominant cause of reductions in GHG emissions under all the scenarios. Reducing yield gaps of concentrate feed crops lowered emissions further by 11.4–34.9% despite increasing N2O and CO2 emissions from soils management and input use. This study demonstrates that feed intensification has potential to increase LUC emissions from dairy production, but that fertilizer-dependent yield gains can offset this increase in emissions through avoided emissions from land use change

Assessment of variability of peat physicochemical properties, subsidence and their interactions within Selangor forests

Tropical peat swamp forests are carbon-rich ecosystems both above- and belowground, which play a major role in the climate balance of the earth. The majority of the world's tropical peat forest cover is located in Southeast Asia and is increasingly threatened by anthropogenic disturbances. Despite their importance for biodiversity conservation and climatic balance of the earth, pristine peatlands are almost extinct in many parts of Southeast Asia. Peninsular Malaysia is one such region, where there are no undisturbed peatlands left in the west coast. We studied the largest peat forest area in the west coast of Malaysia, located in the state of Selangor. We evaluated variability of peat subsidence (for 1 year), peat physicochemical properties and macronutrient contents between forest regions and between different depths (not for subsidence) covering the top 50 cm, and the complex interactions between them. We found that there was significant peat subsidence in all the studied regions, however, there was no significant difference in subsidence between different forest regions. Physicochemical properties such as peat moisture, pH and carbon (C) content and all macronutrient contents except phosphorus (P), either varied between regions, or showed significant interactions between region and depth in Selangor peat forests. All the measured peat physicochemical properties varied with depth. Among macronutrients, only nitrogen (N), P and calcium (Ca) showed significant change with depth, while there were no changes with depth for sulphur (S), potassium (K) and magnesium (Mg) contents. These changes in each peat physicochemical property and macronutrient contents correlated with changes in other peat physicochemical properties and nutrient contents; however, there is a need for controlled experiments to further understand these significant interactions. The findings show continued carbon loss in secondary peat swamp forests through subsidence, indicating the long-term impact of selective logging and associated historical drainage. The significant variability of peat physicochemical properties and macronutrient contents with region and depth, also show the need for intensive sampling to characterise large secondary peat swamp forests

Embedding stakeholders’ priorities into the low-emission development of the East African dairy sector

A growing body of evidence shows that more intensive dairy systems can be good for both nature and people. Little research considers whether such systems correspond with local priorities and preferences. Using a mixed methods approach, this study examined the effects of three intensification scenarios on milk yield and emission intensities in Kenya and Tanzania. Scenarios included (a) an incremental change to feed management; (b) adaptive change by replacing poor quality grass with nutrient-rich fodder crops; and (c) multiple change involving concurrent improvements to breeds, feeds and concentrate supplementation. These scenarios were co-constructed with diverse stakeholder groups to ensure these resonate with local preferences and priorities. Modelling these scenarios showed that milk yield could increase by 2%–15% with incremental changes to over 200% with multiple changes. Greenhouse gas emission intensities are lowest under the multiple change scenario, reducing by an estimated 44%. While raising yields, incremental change conversely raises emission intensities by 9%. Our results suggest that while future interventions that account for local priorities and preferences can enhance productivity and increase the uptake of practices, far-reaching shifts in practices are needed to reduce the climatic footprint of the dairy sector. Since top-down interventions does not align with local priorities and preferences in many situations, future low-emission development initiatives should place more emphasis on geographic and stakeholder heterogeneity when designing targeting and implementation strategies. This suggests that in low-income countries, bottom-up approaches may be more likely to improve dairy productivity and align with mitigation targets than one-size-fits-all approaches

Methods for prioritizing protected areas using individual and aggregate rankings

Despite their legal protection status, protected areas (PAs) can benefit from priority ranks when ongoing threats to their biodiversity and habitats outpace the financial resources available for their conservation. It is essential to develop methods to prioritize PAs that are not computationally demanding in order to suit stakeholders in developing countries where technical and financial resources are limited. We used expert knowledge-derived biodiversity measures to generate individual and aggregate priority ranks of 98 mostly terrestrial PAs on Madagascar. The five variables used were state of knowledge (SoK), forest loss, forest loss acceleration, PA size and relative species diversity, estimated by using standardized residuals from negative binomial models of SoK regressed onto species diversity. We compared our aggregate ranks generated using unweighted averages and principal component analysis (PCA) applied to each individual variable with those generated via Markov chain (MC) and PageRank algorithms. SoK significantly affected the measure of species diversity and highlighted areas where more research effort was needed. The unweighted- and PCA-derived ranks were strongly correlated, as were the MC and PageRank ranks. However, the former two were weakly correlated with the latter two. We recommend using these methods simultaneously in order to provide decision-makers with the flexibility to prioritize those PAs in need of additional research and conservation efforts

Sustainable development of crop-livestock farms in Africa

Crop-livestock farms across Africa are highly variable due to in agroecological and socioeconomic factors, the latter shaping the demand and supply of livestock products. Crop-livestock farms in Africa in the 20-first century are very different from most mixed farms elsewhere in the world. African crop-livestock farms are smaller in size, have fewer livestock, lower productivity and less dependency on imported feed than farms in most countries of Europe, the Americas and the intensive agricultural systems of Asia. This paper discusses the role African crop-livestock farms have in the broader socio-agricultural economy, and how these are likely to change adapting to pressures brought on by the intensification of food systems. This intensification implies increasing land productivity (more food per hectare), often leading to more livestock heads per farm, producing fertilized feeds in croplands and importing feed supplements from the market. This discussion includes (1) the links between crop yields, soil fertility and crop-livestock integration, (2) the increasing demand for livestock products and the land resources required to meet to this demand, and (3) the opportunities to integrate broader societal goals into the development of crop-livestock farms. There is ample room for development of crop-livestock farms in Africa, and keeping integration as part of the development will help prevent many of the mistakes and environmental problems related to the intensification of livestock production observed elsewhere in the world. This development can integrate biodiversity, climate change adaptation and mitigation to the current goals of increasing productivity and food security. The inclusion of broader goals could help farmers access the level of finance required to implement changes

Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017: a systematic analysis for the Global Burden of Disease Study 2017.

BACKGROUND: Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. METHODS: The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries-Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODEm), to generate cause fractions and cause-specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised

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

Assessing the quality of remaining forests on Madagascar

Separated from Africa’s mainland for tens of millions of years, Madagascar has evolved a breathtaking wealth of biodiversity, becoming home to thousands of species found nowhere else on the planet. The New Natural History of Madagascar provides the most comprehensive, up-to-date synthesis available of this island nation’s priceless biological treasures. Now fully revised and expanded, this beautifully illustrated compendium features contributions by more than 600 globally renowned experts who cover the history of scientific exploration in Madagascar, as well as the island’s geology and soils, climate, forest ecology, human ecology, marine and coastal ecosystems, plants, invertebrates, fishes, amphibians, reptiles, birds, and mammals. This invaluable two-volume reference also includes detailed discussions of conservation efforts in Madagascar that showcase several successful protected area programs that can serve as models for threatened ecosystems throughout the world