Quantifying uncertainty in the simulation of crop-climate processes

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (λ, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966–1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of λ near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

Quantification of physical and biological uncertainty in the simulation of the yield of a tropical crop using present-day and doubled CO2 climates

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (lambda, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966-1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of lambda near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

Climate vs. soil factors in local adaptation of two common plant species

Evolutionary theory suggests that divergent natural selection in heterogeneous environments can result in locally adapted plant genotypes. To understand local adaptation it is important to study the ecological factors responsible for divergent selection. At a continental scale, variation in climate can be important while at a local scale soil properties could also play a role. We designed an experiment aimed to disentangle the role of climate and ( abiotic and biotic) soil properties in local adaptation of two common plant species. A grass (Holcus lanatus) and a legume ( Lotus corniculatus), as well as their local soils, were reciprocally transplanted between three sites across an Atlantic-Continental gradient in Europe and grown in common gardens in either their home soil or foreign soils. Growth and reproductive traits were measured over two growing seasons. In both species, we found significant environmental and genetic effects on most of the growth and reproductive traits and a significant interaction between the two environmental effects of soil and climate. The grass species showed significant home site advantage in most of the fitness components, which indicated adaptation to climate. We found no indication that the grass was adapted to local soil conditions. The legume showed a significant home soil advantage for number of fruits only and thus a weak indication of adaptation to soil and no adaptation to climate. Our results show that the importance of climate and soil factors as drivers of local adaptation is species-dependent. This could be related to differences in interactions between plant species and soil biota.

EU Policies on Bioenergy and their Potential Clash with the WTO

The paper outlines EU policy on bioenergy, including biofuels, in the context of its policy initiatives to promote renewable energy to combat greenhouse gas emissions and climate change. The EU's Member States are responsible for implementing EU policy: thus, the UK's Renewables Obligation on electricity suppliers and its Renewable Transport Fuel Obligation and road-fuel tax rebates are examined. It is unlikely that EU policy is in conflict with the WTO Agreement on Agriculture or that on Subsidies and Countervailing Measures, but its provisions on environmental sustainability criteria could be problematic.

Introduction: perspectives for economically important wild species and neglected crops in the Mediterranean

The Mediterranean region is one of the major centres of origin and diversification of cultivated plants and many crop wild relatives are found there. In addition, many native species are still widely harvested from the wild for food, medicine and other uses and some of these have potential for development as alternative crop especially in marginal zones. While there have been several recent initiatives that address the cataloguing and conservation of these species, such as the Network on Identification, Conservation and Use of Wild Plants in the Mediterranean Region (MEDUSA and the Bioversity International (IPGRI) studies on Underutilized Mediterranean Species (VMS), no comprehensive assessment has yet been made and little work undertaken on their agricultural potential. It has been confidently predicted that consequences of global change in the Mediterranean region - population movements and migrations, changes in disturbance regimes, and climate change - will be serious. One the one hand, this will affect the survival prospects of many of these underutilized species and on the other hand it will enhance their importance as the source of potential new crop germplasm. The conservation and availability of genetic diversity of both crops and underutilized species is essential if we are to be able to meet the increasing demand for food and other crops that will be adapted to the new ecoclimatic envelopes that will develop in the region as a consequence of global change. The rapid rate of climatic and other change that is expected adds urgency to the task of assessing, conserving and sustainably using this rich diversity of wild species of economic value in the region but new strategies will be need to be developed to achieve this. The Mediterranean region has the potential of becoming a major source of new crop development in the coming decades.

Accessing biodiversity resources in computational environments from workflow applications

In the Biodiversity World (BDW) project we have created a flexible and extensible Web Services-based Grid environment for biodiversity researchers to solve problems in biodiversity and analyse biodiversity patterns. In this environment, heterogeneous and globally distributed biodiversity-related resources such as data sets and analytical tools are made available to be accessed and assembled by users into workflows to perform complex scientific experiments. One such experiment is bioclimatic modelling of the geographical distribution of individual species using climate variables in order to predict past and future climate-related changes in species distribution. Data sources and analytical tools required for such analysis of species distribution are widely dispersed, available on heterogeneous platforms, present data in different formats and lack interoperability. The BDW system brings all these disparate units together so that the user can combine tools with little thought as to their availability, data formats and interoperability. The current Web Servicesbased Grid environment enables execution of the BDW workflow tasks in remote nodes but with a limited scope. The next step in the evolution of the BDW architecture is to enable workflow tasks to utilise computational resources available within and outside the BDW domain. We describe the present BDW architecture and its transition to a new framework which provides a distributed computational environment for mapping and executing workflows in addition to bringing together heterogeneous resources and analytical tools.

Declining survival rates in a reintroduced population of the Mauritius kestrel: evidence for non-linear density dependence and environmental stochasticity

1. We studied a reintroduced population of the formerly critically endangered Mauritius kestrel Falco punctatus Temmink from its inception in 1987 until 2002, by which time the population had attained carrying capacity for the study area. Post-1994 the population received minimal management other than the provision of nestboxes. 2. We analysed data collected on survival (1987-2002) using program MARK to explore the influence of density-dependent and independent processes on survival over the course of the population's development. 3.We found evidence for non-linear, threshold density dependence in juvenile survival rates. Juvenile survival was also strongly influenced by climate, with the temporal distribution of rainfall during the cyclone season being the most influential climatic variable. Adult survival remained constant throughout. 4. Our most parsimonious capture-mark-recapture statistical model, which was constrained by density and climate, explained 75.4% of the temporal variation exhibited in juvenile survival rates over the course of the population's development. 5. This study is an example of how data collected as part of a threatened species recovery programme can be used to explore the role and functional form of natural population regulatory processes. With the improvements in conservation management techniques and the resulting success stories, formerly threatened species offer unique opportunities to further our understanding of the fundamental principles of population ecology.

ENABLE: a wrist worn device with integrated accessible services to support old people living independently and safely at home

This RTD project, 2007-2009, is partly funded by the European Commission, in Framework Programme 6. It aims to assist elderly people for living well, independently and at case. ENABLE will provide a number of services for elderly people based on the new technology provided by mobile phones. The project is developing a Wrist unit with both integrated and external sensors, and with a radio frequency link to a mobile phone. Dedicated ENABLE software running on the wrist unit and mobile phone makes these services fully accessible for the elderly users. This paper outlines the fundamental motivation and the approach which currently is undertaken in order to collect the more detailed user needs and requirements. The general architecture and the design of the ENABLE system are outlined.

Impact of future climate changes on high pollution levels

Changes in climate variability as well as changes in extreme weather and climate events in the 20th century, especially those that took place during the last two to three decades of the 20th century, have been discussed in many recent scientific publications. Attempts to project the results of such studies in the future have been made under different assumptions. In this paper, we have chosen one of the well-known scenarios predicting changes of the climate in the world during the last 30 years of the 21st century. This scenario is used, together with several general predictions related to the future climate, to produce three climatic scenarios. The derived climatic scenarios are used to calculate predictions for future pollution levels in Denmark and in Europe by applying the Unified Danish Eulerian Model (UNI-DEM), on a space domain containing the whole of Europe.

Case studies in interannual to decadal climate predictability

The predictability of ocean and climate variables is investigated, using a perfect model-based case study approach that recognises that predictability is dependent on the initial climate state. In line with previous studies, large scale ocean variables, show predictability for several years or more; by contrast, the predictability of climate variables is generally limited to, 2 years at most. That predictability shows high sensitivity to the initial state is demonstrated by predictable climate signals, arising in different regions, variables and seasons for different initial conditions. The predictability of climate variables, in the second year is of particular interest, because this is beyond the timescale that is usually considered to be the limit, of seasonal predictability. For different initial conditions, second year predictability is found in: temperatures in southeastern, North America (winter) and western Europe (winter and summer), and precipitation in India (summer monsoon) and in the tropical, South Atlantic. Second year predictability arises either from persistence of large-scale sea surface temperature (SST) and, related ocean heat content anomalies, particularly in regions such as the North Atlantic and Southern Ocean, or from mechanisms, that involve El Nino Southern Oscillation (ENSO) dynamics.