Mechanisms matter: predicting the ecological impacts of global change

The ability of mechanistic models to reliably extrapolate to novel conditions could position them as the gold standard in understanding the impacts of global change, but exactly how mechanistic models can be used most effectively remains to be determined. In this issue, Desforges et al. present a mechanistic physiological model to understand the drivers of muskox population dynamics. We took this as an opportunity to discuss the potential for, and challenges of, using mechanistic models to predict ecological responses to environmental change

Application of TAMSAT-ALERT soil moisture forecasts for planting date decision support in Africa

Deciding when to plant is critical for smallholders in Africa. If they plant too early, farmers risk seedling death if the rains are not established; if they plant too late, there will not be enough rain to sustain the crop through critical development periods. In this study, we present a new decision support tool (DST) that accounts for the trade-off in the risks of early and late planting through advisories based on both short- and long-range forecasts of crop water availability. Unlike most existing operational systems, which are based solely on rainfall, the DST presented here uses ensemble forecasts of soil moisture to estimate the optimal planting date at a local scale. Evaluations using >30,000 observations of planting date and yield in Kenya, Rwanda, Uganda, Zambia and Malawi demonstrate that that planting at the optimal time would increase yield by 7–10% overall, and up to 20% for late planting farmers. The DST has been piloted by One Acre Fund for the 2019–2020, 2020–2021, and 2021–2022 seasons and there is strong demand for the service to be extended further. We conclude from the evaluations and pilots that the planting date DST has the potential to strengthen farmer decision making and hence their resilience to climate variability and change

Individual-based modelling of elephant population dynamics using remote sensing to estimate food availability

Strategies for the conservation and management of many wild species requires an improved understanding of how population dynamics respond to changes in environmental conditions, including key drivers such as food availability. The development of mechanistic predictive models, in which the underlying processes of a system are modelled, enables a robust understanding of these demographic responses to dynamic environmental conditions. We present an individual-based energy budget model for a mega-herbivore, the African elephant (Loxodonta africana), which relates remotely measured changes in food availability to vital demographic rates of birth and mortality. Elephants require large spaces over which to roam in search of seasonal food, and thus are vulnerable to environmental changes which limit space use or alter food availability. The model is constructed using principles of physiological ecology; uncertain parameter values are calibrated using approximate Bayesian computation. The resulting model fits observed population dynamics data well. The model has critical value in being able to project elephant population size under future environmental conditions and is applicable to other mammalian herbivores with appropriate parameterisation

Human‐driven habitat conversion is a more immediate threat to Amboseli elephants than climate change

Global ecosystem change presents a major challenge to biodiversity conservation, which must identify and prioritize the most critical threats to species persistence given limited available funding. Mechanistic models enable robust predictions under future conditions and can consider multiple stressors in combination. Here we use an individual‐based model (IBM) to predict elephant population size in Amboseli, southern Kenya, under environmental scenarios incorporating climate change and anthropogenic habitat loss. The IBM uses projected food availability as a key driver of elephant population dynamics and relates variation in food availability to changes in vital demographic rates through an energy budget. Habitat loss, rather than climate change, represents the most significant threat to the persistence of the Amboseli elephant population in the 21st century and highlights the importance of collaborations and agreements that preserve space for Amboseli elephants to ensure the population remains resilient to environmental stochasticity

Towards drought impact-based forecasting in a multi-hazard context

The lives and livelihoods of people around the world are increasingly threatened by climate-related risks as climate change increases the frequency and severity of high-impact weather. In turn, the risk of multiple hazards occurring simultaneously grows and compound impacts become more likely. The World Meteorological Organization (WMO) proposed the use of multi-hazard impact-based forecasting (IbF) to better anticipate and reduce the impacts of concurrent hazards, but as yet, there are few operational examples in the humanitarian sector. Drought is particularly susceptible to multi-hazard influences. However, challenges encountered in the development of drought IbF systems – including poor understanding of compound impacts and specific hazard-focused mandates – raise important questions for the feasibility of multi-hazard IbF as envisioned by the WMO. With these challenges in mind, we propose an interim approach in which real-time assessment of dynamic vulnerability provides a context for drought-based IbF. The incorporation of dynamic vulnerability indicators account for the local effects of non-drought hazards, whilst the use of a drought-based system facilitates effective intervention. The proposed approach will improve our understanding of compound events, enhance adoption of IbF in the humanitarian sector, and better mitigate the impacts of concurrent hazards

Progress and challenges of demand-led co-produced sub-seasonal-to-seasonal (S2S) climate forecasts in Nigeria

This paper identifies fundamental issues which prevent the effective uptake of climate information services in Nigeria. We propose solutions which involve the extension of short-range (1 to 5 days) forecasts beyond that of medium-range (7 to 15 days) timescales through the operational use of current forecast data as well as improve collaboration and communication with forecast users. Using newly available data to provide seamless operational forecasts from short-term to sub-seasonal timescales, we examine evidence to determine if effective demand-led sub-seasonal-to-seasonal (S2S) climate forecasts can be co-produced. This evidence involves: itemization of forecast products delivered to stakeholders, with their development methodology; enumeration of inferences of forecast products and their influences on decisions taken by stakeholders; user-focused discussions of improvements on co-produced products; and the methods of evaluating the performance of the forecast products. We find that extending the production pipeline of short-range forecast timescales beyond the medium-range, such that the medium-range forecast timescales can be fed into existing tools for applying short-range forecasts, assisted in mitigating the risks of sub-seasonal climate variability on socio-economic activities in Nigeria. We also find that enhancing of collaboration and communication channels between the producers and the forecast product users helps to: enhance the development of user-tailored impact-based forecasts; increases users’ trusts in the forecasts; and, seamlessly improves forecast evaluations. In general, these measures lead to more smooth delivery and increase in uptake of climate information services in Nigeria

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

Identifying the effects of social disruption through translocation on African elephants (loxodonta africana ), with specifics on the social and ecological impacts of orphaning

Simple Summary: The translocation of elephants is a management tool developed in the 1980s during the culling operations at the Kruger National Park, South Africa, to remove “surplus” elephants from fenced properties. Elephants live in large social networks and form strong social bonds within their family units. In particular, the mother–offspring bond is crucial to the learning and development of social skills and social and environmental competence of the calves. The leadership role and experience of the matriarch appear to be an important factor in providing the necessary knowledge to optimise social and environmental skills and competence. The translocation of smaller groups of elephants results in the social disruption of these networks. This paper looks at the social and ecological aspects of such disruption and what it implies for elephants. A herd of Orphans and a translocated herd consisting of two families were observed over several years. The Orphans demonstrated marked effects of social disruption by splitting more frequently and for longer periods than the family herd and experiencing accelerated reproduction. Social disruption may therefore reduce learning opportunities with implications for elephant society as well as for conservation. Abstract: African elephants (Loxodonta africana) exhibit a long developmental period during which they acquire complex social and ecological knowledge through social networks. Central to this is that matriarchs and older individuals play an important role as repositories of information gained through experience. Anthropogenic interventions—including poaching, culling, translocation, and hunting—can disrupt elephants’ social networks, with implications for individual fitness and potential long-term population viability. Here, we draw on a unique long-running, individual-based dataset to examine the impacts of translocation on a population of elephants in South Africa, taking into consideration demographic rates, social dynamics, and ecological decision-making. Specifically, we compared two translocated groups: a group of unrelated culling Orphans and a family herd. We found that the Orphan group experienced accelerated reproductive rates when compared with the family herd. The Orphan group also fissioned more frequently and for longer periods of time, suggesting lower cohesiveness, and were less decisive in their large-scale movement decisions. These results add to the growing body of literature on the downstream impacts of social disruption for elephants. Whilst the translocation of culling Orphans is no longer practised in South Africa, we encourage careful consideration of any elephant translocation and the resulting social disruption