Probabilistic skill in ensemble seasonal forecasts

Simulation models are widely employed to make probability forecasts of future conditions on seasonal to annual lead times. Added value in such forecasts is reflected in the information they add, either to purely empirical statistical models or to simpler simulation models. An evaluation of seasonal probability forecasts from the Development of a European Multimodel Ensemble system for seasonal to inTERannual prediction (DEMETER) and ENSEMBLES multi-model ensemble experiments is presented. Two particular regions are considered: Nino3.4 in the Pacific and the Main Development Region in the Atlantic; these regions were chosen before any spatial distribution of skill was examined. The ENSEMBLES models are found to have skill against the climatological distribution on seasonal time-scales. For models in ENSEMBLES that have a clearly defined predecessor model in DEMETER, the improvement from DEMETER to ENSEMBLES is discussed. Due to the long lead times of the forecasts and the evolution of observation technology, the forecast-outcome archive for seasonal forecast evaluation is small; arguably, evaluation data for seasonal forecasting will always be precious. Issues of information contamination from in-sample evaluation are discussed and impacts (both positive and negative) of variations in cross-validation protocol are demonstrated. Other difficulties due to the small forecast-outcome archive are identified. The claim that the multi-model ensemble provides a ‘better’ probability forecast than the best single model is examined and challenged. Significant forecast information beyond the climatological distribution is also demonstrated in a persistence probability forecast. The ENSEMBLES probability forecasts add significantly more information to empirical probability forecasts on seasonal time-scales than on decadal scales. Current operational forecasts might be enhanced by melding information from both simulation models and empirical models. Simulation models based on physical principles are sometimes expected, in principle, to outperform empirical models; direct comparison of their forecast skill provides information on progress toward that goal.

Effect of seasonal variation on some physical properties and heat stability of milk subjected to ultra-high temperature and in-container sterilisation

Heat stability was evaluated in bulk raw milk, collected throughout the year and subjected to ultra-high temperature (UHT) or in-container sterilisation, with and without added calcium chloride (2 mM), disodium hydrogen phosphate (DSHP, 10 mM) and trisodium citrate (TSC, 10 mM). More sediment was observed following in-container sterilisation (0.24%) compared with UHT (0.19%). Adding CaCl2 made the milk more unstable to UHT than to in-container sterilisation, while adding DSHP and TSC made the milk more unstable during in-container sterilisation than to UHT processing, although TSC addition increased the sediment formed by UHT processing. Better heat stability was observed in autumn and winter than in spring and summer following UHT. However, following in-container sterilisation, samples with added stabilising salts showed significantly improved heat stability in autumn, whereas with added CaCl2, the best heat stability was observed in spring. No correlation was found between urea and heat stability. DSHP and TSC made the milk more unstable during in-container sterilisation than to UHT processing, although TSC addition increased the sediment formed by UHT processing. Better heat stability was observed in autumn and winter than in spring and summer following UHT. However, following in-container sterilisation, samples with added stabilising salts showed significantly improved heat stability in autumn, whereas with added CaCl2, the best heat stability was observed in spring. No correlation was found between urea and heat stability.

Evaluation of modern and mid-Holocene seasonal precipitation of the Mediterranean and northern Africa in the CMIP5 simulations

We analyse the spatial expression of seasonal climates of the Mediterranean and northern Africa in pre-industrial (piControl) and mid-Holocene (midHolocene, 6 yr BP) simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Modern observations show four distinct precipitation regimes characterized by differences in the seasonal distribution and total amount of precipitation: an equatorial band characterized by a double peak in rainfall, the monsoon zone characterized by summer rainfall, the desert characterized by low seasonality and total precipitation, and the Mediterranean zone characterized by summer drought. Most models correctly simulate the position of the Mediterranean and the equatorial climates in the piControl simulations, but overestimate the extent of monsoon influence and underestimate the extent of desert. However, most models fail to reproduce the amount of precipitation in each zone. Model biases in the simulated magnitude of precipitation are unrelated to whether the models reproduce the correct spatial patterns of each regime. In the midHolocene, the models simulate a reduction in winter rainfall in the equatorial zone, and a northward expansion of the monsoon with a significant increase in summer and autumn rainfall. Precipitation is slightly increased in the desert, mainly in summer and autumn, with northward expansion of the monsoon. Changes in the Mediterranean are small, although there is an increase in spring precipitation consistent with palaeo-observations of increased growing-season rainfall. Comparison with reconstructions shows most models underestimate the mid-Holocene changes in annual precipitation, except in the equatorial zone. Biases in the piControl have only a limited influence on midHolocene anomalies in ocean–atmosphere models; carbon-cycle models show no relationship between piControl bias and midHolocene anomalies. Biases in the prediction of the midHolocene monsoon expansion are unrelated to how well the models simulate changes in Mediterranean climate.

Improving climate change detection through optimal seasonal averaging: the case of the North Atlantic jet and European precipitation

The detection of anthropogenic climate change can be improved by recognising the seasonality in the climate change response. This is demonstrated for the North Atlantic jet (zonal wind at 850 hPa, U850) and European precipitation responses projected by the CMIP5 climate models. The U850 future response is characterised by a marked seasonality: an eastward extension of the North Atlantic jet into Europe in November-April, and a poleward shift in May-October. Under the RCP8.5 scenario, the multi-model mean response in U850 in these two extended seasonal means emerges by 2035-2040 for the lower--latitude features and by 2050-2070 for the higher--latitude features, relative to the 1960-1990 climate. This is 5-15 years earlier than when evaluated in the traditional meteorological seasons (December--February, June--August), and it results from an increase in the signal to noise ratio associated with the spatial coherence of the response within the extended seasons. The annual mean response lacks important information on the seasonality of the response without improving the signal to noise ratio. The same two extended seasons are demonstrated to capture the seasonality of the European precipitation response to climate change and to anticipate its emergence by 10-20 years. Furthermore, some of the regional responses, such as the Mediterranean precipitation decline and the U850 response in North Africa in the extended winter, are projected to emerge by 2020-2025, according to the models with a strong response. Therefore, observations might soon be useful to test aspects of the atmospheric circulation response predicted by some of the CMIP5 models.

Population ecology of the Asian house rat (Rattus tanezumi) in complex lowland agroecosystems in the Philippines

Context. Rattus tanezumi (the Asian house rat) is the principal rodent pest of rice and coconut crops in the Philippines. Little is known about the population and breeding ecology of R. tanezumi in complex agroecosystems; thus, current methods of rodent control may be inappropriate or poorly implemented. Aims. To investigate the habitat use, population dynamics and breeding biology of R. tanezumi in complex lowland agroecosystems of the Sierra Madre Biodiversity Corridor, Luzon, and to develop ecologically based rodent management (EBRM) strategies that will target specific habitats at specific times to improve cost-efficiency and minimise non-target risks. Methods. An 18-month trapping study was conducted in rice monoculture, rice adjacent to coconut, coconut groves, coconut-based agroforest and forest habitats. Trapped animals were measured, marked and assessed for breeding condition. Key results. Five species of rodent were captured across all habitats with R. tanezumi the major pest species in both the rice and coconut crops. The stage of the rice crop was a major factor influencing the habitat use and breeding biology of R. tanezumi. In rice fields, R. tanezumi abundance was highest during the tillering to ripening stages of the rice crop and lowest during the seedling stage, whereas in coconut groves abundance was highest from the seedling to tillering stage of nearby rice crops. Peaks in breeding activity occurred from the booting stage of the rice crop until just after harvest, but >10% of females were in breeding condition at each month of the year. Conclusions. In contrast with the practices applied by rice farmers in the study region, the most effective time for lethal management based on the breeding ecology of R. tanezumi is likely to be during the early stages of the rice crop, before the booting stage. Farmers generally apply control actions as individuals. We recommend coordinated community action. Continuous breeding throughout the year may necessitate two community campaigns per rice cropping season. To limit population growth, the most effective time to reduce nesting habitat is from the booting stage until harvest. Implications. By adopting EBRM strategies, we expect a reduction in costs associated with rodent control, as well as improved yield and reduced risk to non-target species.

The impact of date palm fruits and their component polyphenols, on gut microbial ecology, bacterial metabolites and colon cancer cell proliferation

The fruit of the date palm (Phoenix dactylifera L.) is a rich source of dietary fibre and polyphenols. We have investigated gut bacterial changes induced by the whole date fruit extract (digested date extract; DDE) and its polyphenol-rich extract (date polyphenol extract; DPE) using faecal, pH-controlled, mixed batch cultures mimicking the distal part of the human large intestine, and utilising an array of microbial group-specific 16S rRNA oligonucleotide probes. Fluorescence microscopic enumeration indicated that there was a significant increase in the growth of bifidobacteria in response to both treatments, whilst whole dates also increased bacteroides at 24 h and the total bacterial counts at later fermentation time points when compared with DPE alone. Bacterial metabolism of whole date fruit led to the production of SCFA, with acetate significantly increasing following bacterial incubation with DDE. In addition, the production of flavonoid aglycones (myricetin, luteolin, quercetin and apigenin) and the anthocyanidin petunidin in less than 1 h was also observed. Lastly, the potential of DDE, DPE and metabolites to inhibit Caco-2 cell growth was investigated, indicating that both were capable of potentially acting as antiproliferative agents in vitro, following a 48 h exposure. This potential to inhibit growth was reduced following fermentation. Together these data suggest that consumption of date fruits may enhance colon health by increasing beneficial bacterial growth and inhibiting the proliferation of colon cancer cells. This is an early suggestion that date intake by humans may aid in the maintenance of bowel health and even the reduction of colorectal cancer development.

Mercury and methylmercury bioaccumulation by polychaete worms is governed by both feeding ecology and mercury bioavailability in coastal mudflats

Polychaete worms are abundant in many mudflats but their importance to coastal food web Hg biomagnification is not known. We sampled sediments and polychaete worms from mudflats in the Bay of Fundy to investigate the bioaccumulation of mercury (Hg) and methylmercury (MeHg) in the coastal invertebrate food web. Hg concentrations in the sediments were low (<20 μg kg−1). Labile Hg (methanol/KOH sediment extraction) in surface sediments (0–1 cm) was positively correlated with Hg bioaccumulation by surface sediment-ingesting polychaetes but, surprisingly, there was a negative correlation between δ15N (i.e. trophic level) and THg bioaccumulation factors in polychaete worms. Worms feeding on deeper sediments contained the greatest MeHg concentrations (69.6 μg kg−1). Polychaetes are an important vector for Hg biomagnification to the coastal avian food web. This research demonstrates that feeding depth and method of feeding are more important than trophic position or sediment Hg concentrations for predicting Hg bioaccumulation.

Social and ecological drivers of success in agri-environment schemes: the roles of farmers and environmental context

1. Agri-environment schemes remain a controversial approach to reversing biodiversity losses, partly because the drivers of variation in outcomes are poorly understood. In particular, there is a lack of studies that consider both social and ecological factors. 2. We analysed variation across 48 farms in the quality and biodiversity outcomes of agri-environmental habitats designed to provide pollen and nectar for bumblebees and butterflies or winter seed for birds. We used interviews and ecological surveys to gather data on farmer experience and understanding of agri-environment schemes, and local and landscape environmental factors. 3. Multimodel inference indicated social factors had a strong impact on outcomes and that farmer experiential learning was a key process. The quality of the created habitat was affected positively by the farmer’s previous experience in environmental management. The farmer’s confidence in their ability to carry out the required management was negatively related to the provision of floral resources. Farmers with more wildlife-friendly motivations tended to produce more floral resources, but fewer seed resources. 4. Bird, bumblebee and butterfly biodiversity responses were strongly affected by the quantity of seed or floral resources. Shelter enhanced biodiversity directly, increased floral resources and decreased seed yield. Seasonal weather patterns had large effects on both measures. Surprisingly, larger species pools and amounts of semi-natural habitat in the surrounding landscape had negative effects on biodiversity, which may indicate use by fauna of alternative foraging resources. 5. Synthesis and application. This is the first study to show a direct role of farmer social variables on the success of agri-environment schemes in supporting farmland biodiversity. It suggests that farmers are not simply implementing agri-environment options, but are learning and improving outcomes by doing so. Better engagement with farmers and working with farmers who have a history of environmental management may therefore enhance success. The importance of a number of environmental factors may explain why agri-environment outcomes are variable, and suggests some – such as the weather – cannot be controlled. Others, such as shelter, could be incorporated into agri-environment prescriptions. The role of landscape factors remains complex and currently eludes simple conclusions about large-scale targeting of schemes.

Molecular and phenotypic characterization of the alternative seasonal growth habit and flowering time in barley (Hordeum vulgare ssp. vulgare L.)

Barley can be classified into three major agronomic types, based on its seasonal growth habit (SGH): spring, winter and alternative. Winter varieties require exposure to vernalization to promote subsequent flowering and are autumn-sown. Spring varieties proceed to flowering in the absence of vernalization and are sown in the spring. The ‘alternative’ (also known as ‘facultative’) SGH is only loosely defined and can be sown in autumn or spring. Here, we investigate the molecular genetic basis of alternative barley. Analysis of the major barley vernalization (VRN-H1, VRN-H2) and photoperiod (PPD-H1, PPD-H2) response genes in a collection of 386 varieties found alternative SGH to be characterized by specific allelic combinations. Spring varieties possessed spring loci at one or both of the vernalization response loci, combined with long-day non-responsive ppd-H1 alleles and wild-type alleles at the short-day photoperiod response locus, PPD-H2. Winter varieties possessed winter alleles at both vernalization loci, in combination with the mutant ppd-H2 allele conferring delayed flowering under short-day photoperiods. In contrast, all alternative varieties investigated possessed a single spring allele (either at VRN-H1 or at VRN-H2) combined with mutant ppd-H2 alleles. This allelic combination is found only in alternative types and is diagnostic for alternative SGH in the collection studied. Analysis of flowering time under controlled environment found alternative varieties flowered later than spring control lines, with the difference most pronounced under short-day photoperiods. This work provides genetic characterization of the alternative SGH phenotype, allowing precise manipulation of SGH and flowering time within breeding programmes, and provides the molecular tools for classification of all three SGH categories within national variety registration processes.

Improved seasonal prediction of the hot summer of 2003 over Europe through better representation of uncertainty in the land surface

Methods to explicitly represent uncertainties in weather and climate models have been developed and refined over the past decade, and have reduced biases and improved forecast skill when implemented in the atmospheric component of models. These methods have not yet been applied to the land surface component of models. Since the land surface is strongly coupled to the atmospheric state at certain times and in certain places (such as the European summer of 2003), improvements in the representation of land surface uncertainty may potentially lead to improvements in atmospheric forecasts for such events. Here we analyse seasonal retrospective forecasts for 1981–2012 performed with the European Centre for Medium-Range Weather Forecasts’ (ECMWF) coupled ensemble forecast model. We consider two methods of incorporating uncertainty into the land surface model (H-TESSEL): stochastic perturbation of tendencies, and static perturbation of key soil parameters. We find that the perturbed parameter approach considerably improves the forecast of extreme air temperature for summer 2003, through better representation of negative soil moisture anomalies and upward sensible heat flux. Averaged across all the reforecasts the perturbed parameter experiment shows relatively little impact on the mean bias, suggesting perturbations of at least this magnitude can be applied to the land surface without any degradation of model climate. There is also little impact on skill averaged across all reforecasts and some evidence of overdispersion for soil moisture. The stochastic tendency experiments show a large overdispersion for the soil temperature fields, indicating that the perturbation here is too strong. There is also some indication that the forecast of the 2003 warm event is improved for the stochastic experiments, however the improvement is not as large as observed for the perturbed parameter experiment.

Aspects of designing and evaluating seasonal-to-interannual Arctic sea-ice prediction systems

Using lessons from idealised predictability experiments, we discuss some issues and perspectives on the design of operational seasonal to inter-annual Arctic sea-ice prediction systems. We first review the opportunities to use a hierarchy of different types of experiment to learn about the predictability of Arctic climate. We also examine key issues for ensemble system design, such as: measuring skill, the role of ensemble size and generation of ensemble members. When assessing the potential skill of a set of prediction experiments, using more than one metric is essential as different choices can significantly alter conclusions about the presence or lack of skill. We find that increasing both the number of hindcasts and ensemble size is important for reliably assessing the correlation and expected error in forecasts. For other metrics, such as dispersion, increasing ensemble size is most important. Probabilistic measures of skill can also provide useful information about the reliability of forecasts. In addition, various methods for generating the different ensemble members are tested. The range of techniques can produce surprisingly different ensemble spread characteristics. The lessons learnt should help inform the design of future operational prediction systems.

Rooting theories of plant community ecology in microbial interactions

Predominant frameworks for understanding plant ecology have an aboveground bias that neglects soil micro-organisms. This is inconsistent with recent work illustrating the importance of soil microbes in terrestrial ecology. Microbial effects have been incorporated into plant community dynamics using ideas of niche modification and plant–soil community feedbacks. Here, we expand and integrate qualitative conceptual models of plant niche and feedback to explore implications of microbial interactions for understanding plant community ecology. At the same time we review the empirical evidence for these processes. We also consider common mycorrhizal networks, and propose that these are best interpreted within the feedback framework. Finally, we apply our integrated model of niche and feedback to understanding plant coexistence, monodominance and invasion ecology.