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Sustainability of rain-fed agriculture in semiarid regions is being threatened by climate variability and change. Weather and climate information (WCI) can be used to reduce the effects of this threat on agricultural production. WCI may be available, but is it readily accessible and communicated/disseminated efficiently to intended end users? Are stakeholders able to interpret the information to correctly inform decision-making? To answer these questions, in view of intermediate stakeholders (service providers to farmers), a study was carried out in two districts of the Midlands Province of Zimbabwe to identify the type and sources of WCI received by these stakeholders as well as constraints and opportunities to access, interpretation, and use of WCI. The study sample was drawn from the Midlands Provincial Drought Relief Committee, a link between the sources of WCI and the smallholder farmers. A questionnaire pretested for clarity and checked for internal consistency of themes using the standardized Cronbach’s alpha was used to collect data. Descriptive statistics were generated using SPSS (version 20.0). Findings were that WCI was sometimes not readily available or was received late. Approximately 36% of the intermediate stakeholders (service providers) passed on WCI to farmers in its original form, from the main source the Meteorological Services Department. It was also unfortunate to discover that 36% of the respondents had challenges interpreting WCI. Impediments to the use of WCI by farmers included scientific information not aligning with indigenous information, which is better understood by farmers, and lack of trust in WCI. It is imperative to improve access to WCI and to train stakeholders on interpretation and dissemination of WCI.

The rapid population, economic and standard of living growth with the global climate changes is increasing the per capita demand on water. This increase in water demand is resulting in less available fresh water supply for agriculture. To sustain irrigated agriculture, better water management is necessary at all levels. Water supply in the Middle East and North Africa region (MENA) is unequally distributed in space and time. This region has among the lowest per capita water supply in the world. On the other hand, the intensive extraction and use of water without proper planning and provisions for the protection of their water resource has led to serious water pollution. Agriculture consumes 70–80% of water in this region. This leads to a fundamental problem for water-short countries that should manage between their renewable water resources and their capacity for food production. Water-short countries do import food commodities, which has imbedded water called \\“virtual water”. The aim of this paper is to present a model with the general objective to maximize water productivity (monitory units per cubic meter of water). The mathematical model resulted in a maximum water productivity of 6.92 $/m3 with eight crops out of 43 crops grown on site. The remaining 35 crops induced a saving 3,408 m3/ha, which equals the virtual water. Three sets of scenarios were tested. First a decrease in available water from 100% to 50% showed a decrease in the objective function value from 6.92 to 4.727 $/m3, second a decrease in on farm crop prices by 10, 20 and 40% caused decreases in the objective function value by 4.8%, 9.66% and 20.29% respectively, while an increase in prices increased the objective function value and third an imposition of certain crops in the project area decreased water productivity.

The provision of resilience and adaptation to climate change to smallholder irrigation communities is a critical component in implementing common pool resource management. Institutions in many smallholder irrigation schemes in developing countries are diverse and have potential to contribute to building climate resilience and improving livelihoods of smallholder irrigator. Human behaviour, institutional capacity and culture play important roles in shaping adaptive capacity of communities to climate change. Although much is known about how these contribute to this adaptive capacity, research focusing on their interaction is limited. In order to close this the gap, this study seeks to explore how socio-demographic, governance and institutional factors influence adaptive capacity in Exchange, Insukamini and Ruchanyu irrigation schemes. Questionnaire-based interviews, group discussions and key informant interviews were used for data collection. Adaptive capacity calculated using the livelihood vulnerability model was used as the dependent variable for this study. Ordinary least square regression was used to assess socio-demographic, institutional and governance factors influencing adaptive capacity in the smallholder irrigation scheme. The study reveals that adaptive capacity is influenced by age, gender, education, land tenure security, irrigation committee satisfaction, cooperatives, and interaction of factors. The link between age and gender were negatively moderated by awareness of irrigation policies, access to credit and land tenure security. Assessing factors influencing adaptive capacity help to improve the livelihoods of scheme farmers in the face of climate change.

Here we introduce the LakeATLAS dataset, which provides a broad range of hydro-environmental characteristics for more than 1.4 million lakes and reservoirs globally with an area of at least 10 ha. LakeATLAS forms part of the larger HydroATLAS data repository and expands the existing datasets of sub-basin and river reach descriptors by adding equivalent information for lakes and reservoirs in a compatible structure. Matching its HydroATLAS counterparts, version 1.0 of LakeATLAS contains data for 56 variables, partitioned into 281 individual attributes and organized in six categories: hydrology; physiography; climate; land cover & use; soils & geology; and anthropogenic influences. LakeATLAS derives these attributes by processing and reformatting original data from well-established global digital maps at 15 arc-second (~500 m) grid cell resolution and assigns the information spatially to each lake by aggregating it within the lake, in a 3-km vicinity buffer around the lake, and/or within the entire upstream drainage area of the lake. The standardized format of LakeATLAS ensures versatile applicability in hydro-ecological assessments from regional to global scales.

Soils are increasingly recognized as major contributors to ecosystem services such as food production and climate regulation (1, 2), and demand for up-to-date and relevant soil information is soaring. But communicating such information among diverse audiences remains challenging because of inconsistent use of technical jargon, and outdated, imprecise methods. Also, spatial resolutions of soil maps for most parts of the world are too low to help with practical land management. While other earth sciences (e.g., climatology, geology) have become more quantitative and have taken advantage of the digital revolution, conventional soil mapping delineates space mostly according to qualitative criteria and renders maps using a series of polygons, which limits resolution. These maps do not adequately express the complexity of soils across a landscape in an easily understandable way

Rising levels of atmospheric CO2 concentration (Ca) and simultaneous climate change profoundly affect plant physiological performance while challenging our ability to estimate vegetation–atmosphere fluxes. To predict rates of water and carbon exchange between vegetation and the atmosphere, we require a formulation for stomatal conductance (gs) that captures the multidimensional response of stomata to changing environmental conditions. The unified stomatal optimization (USO) theory provides a formulation for gs with the ability to predict the response of gs to novel environmental conditions such as elevated Ca (eCa), warmer temperatures and/or changing water availability. We tested for the effect of eCa and seasonally varying climate on stomatal behaviour, as defined by the USO theory, during the first year of free-air CO2 enrichment in a native eucalypt woodland (the EucFACE experiment). We hypothesized that under eCa, gs would decrease and photosynthesis (Anet) would increase, but fundamental stomatal behaviour described in the USO model would remain unchanged. We also predicted that the USO slope parameter g1 would increase with temperature and water availability. Over 20 months, we performed quarterly gas exchange campaigns encompassing a wide range of temperatures and water availabilities. We measured gs, Anet and leaf water potential (Ψ) at mid-morning, midday and pre-dawn (Ψ only) under ambient and eCa and prevailing climatic conditions, at the tree tops (20 m height). We found that eCa induced a 20% reduction in stomatal conductance under non-limiting water availability, enhanced mid-morning Anet by 24% in three out of five measurement campaigns and had no significant effect on Ψ. The parameter g1 was conserved under eCa, weakly increased with temperature and did not respond to increasing water availability. Our results suggest that under eCa and variable rainfall, mature eucalypt trees exhibit a conservative water-use strategy, but this strategy may be modified by growth temperature. We show that the USO theory successfully predicts coupling of carbon uptake and water loss in future atmospheric conditions in a native woodland and thus could be incorporated into ecosystem-scale and global vegetation models.

Evaluating the fitness of organisms is an essential step towards understanding their responses to environmental change. Connections between energy expenditure and fitness have been postulated for nearly a century. However, testing this premise among wild animals is constrained by difficulties in measuring energy expenditure while simultaneously monitoring conventional fitness metrics such as survival and reproductive output. We addressed this issue by exploring the functional links between field metabolic rate (FMR), body condition, sex, age and reproductive performance in a wild population. We deployed 3D accelerometers on 115 Adélie penguins Pygoscelis adeliae during four breeding seasons at one of the largest colonies of this species, Cape Crozier, on Ross Island, Antarctica. The demography of this population has been studied for the past 18 years. From accelerometry recordings, collected for birds of known age and breeding history, we determined the vector of the dynamic body acceleration (VeDBA) and used it as a proxy for FMR. This allowed us to demonstrate relationships among FMR, a breeding quality index (BQI) and body condition. Notably, we found a significant quadratic relationship between mean VeDBA during foraging and BQI for experienced breeders, and individuals in better body condition showed lower rates of energy expenditure. We conclude that using FMR as a fitness component complementary to more conventional fitness metrics will yield greater understanding of evolutionary and conservation physiology. A plain language summary is available for this article. Plain Language Summary

Speciation through homoploid hybridization (HHS) is considered extremely rare in animals. This is mainly because the establishment of reproductive isolation as a product of hybridization is uncommon. Additionally, many traits are underpinned by polygeny and/or incomplete dominance, where the hybrid phenotype is an additive blend of parental characteristics. Phenotypically intermediate hybrids are usually at a fitness disadvantage compared with parental species and tend to vanish through backcrossing with parental population(s). It is therefore unknown whether the additive nature of hybrid traits in itself could lead successfully to HHS. Using a multi-marker genetic data set and a meta-analysis of diet and morphology, we investigated a potential case of HHS in the prions (Pachyptila spp.), seabirds distinguished by their bills, prey choice, and timing of breeding. Using approximate Bayesian computation, we show that the medium-billed Salvin’s prion (Pachyptila salvini) could be a hybrid between the narrow-billed Antarctic prion (Pachyptila desolata) and broad-billed prion (Pachyptila vittata). Remarkably, P. salvini’s intermediate bill width has given it a feeding advantage with respect to the other Pachyptila species, allowing it to consume a broader range of prey, potentially increasing its fitness. Available metadata showed that P. salvini is also intermediate in breeding phenology and, with no overlap in breeding times, it is effectively reproductively isolated from either parental species through allochrony. These results provide evidence for a case of HHS in nature, and show for the first time that additivity of divergent parental traits alone can lead directly to increased hybrid fitness and reproductive isolation.

Open access funding provided by CSIRO Library Services. N/A.

Every year, millions of birds migrate between breeding and nonbreeding habitat, but the relative numbers of animals moving between sites are difficult to observe directly. Here we propose FlywayNet, a discrete network model based on observed count data, to determine the most likely migration links between regions using statistical modelling and efficient inference tools. Our approach advances on previous studies by accounting for noisy observations and flexible stopover durations by modelling using interacting hidden semi-Markov Models. In FlywayNet, individual birds sojourn in stopover nodes for a period of time before moving to other nodes with an unknown probability that we aim to estimate. Exact estimation using existing approaches is not possible, so we designed customised versions of the Monte Carlo expectation-maximisation and approximate Bayesian computation algorithms for our model. We compare the efficiency and quality of estimation of these approaches on synthetic data and an applied case study. Our algorithms performed well on benchmark problems, with low absolute error and strong correlation between estimated and known parameters. On a case study using citizen science count data of the Far Eastern Curlew (Numenius madagascariensis), an endangered shorebird from the East Asian-Australasian Flyway, the ABC and MCEM algorithms generated contrasting recommendations due to a difference in optimisation criteria and noise in the data. For ABC, we recovered key features of population-level movements predicted by experts despite the challenges of noisy unstructured data. Understanding connectivity places local conservation efforts and threat mitigation in the global context, yet it has proven difficult to rigorously quantify connectivity at the population level. Our approach provides a flexible framework to infer the structure of migratory networks in birds and other organisms.