The use of agricultural, open and forest habitats by juvenile Mauritius Kestrels Falco punctatus

Knowledge of tropical raptor habitat use is limited and yet a thorough understanding is vital when trying to conserve endangered species. We used a well studied, reintroduced population of the vulnerable Mauritius Kestrel Falco punctatus to investigate habitat preferences in a modified landscape. We constructed a high resolution digital habitat map and radiotracked 13 juvenile Kestrels to quantify habitat preferences. We distinguished seven habitat types in our study area and tracked Kestrels from 71 to 130 days old during which they dispersed from their natal territory and settled within a home-range after reaching independence. Mean home-range size was 0.95 km(2) characterized by a bimodal pattern of intensity around the natal site and post-independence home-range. Compositional analysis showed that home-ranges were located non-randomly with respect to habitat but there was no evidence to suggest differential use of habitats within home-ranges. Native and semi-invaded forest and grassland were consistently preferred, whereas agriculture was used significantly less than other habitats. No difference was found between the available length of edge dividing native forest and grassland within a home-range when compared to that available within a 2.35-km buffer around their nest-site, based on the maximum distance a juvenile was found to disperse. Repeating the analysis in three dimensions gave very similar results. Our results suggest that Mauritius Kestrels are not obligate forest dwellers as was once thought but can also exploit open habitats such as grassland. Kestrels may be using isolated mature trees within grassland as vantage points for hunting in the same way as they use the natural stratified forest structure. We suggest that the avoidance of agriculture is partly due to a lack of such vantage points. The conservation importance of forest degradation and agricultural encroachment is highlighted and comparisons with the habitat preferences of other tropical falcons are discussed.

Abstracts of communications: Proceedings of the thirty-nineth meeting of the Agricultural Research Modellers' Group

This group, which is concerned with the applications of mathematics to agricultural science, was formed in 1970 and has since met at approximately yearly intervals in London for one-day meetings. The thirty-ninth meeting of the group, chaired by Professor N. Crout of the University of Nottingham, was held in the Kohn Centre at the Royal Society, 6 Carlton House Terrace, London on Friday, 30 March 2007 when the following papers were read.

Curbing agricultural exceptionalism: The EU's response to external challenge

From 1948 to 1994, the agricultural sector was afforded special treatment in the GATT. We analyse the extent to which this agricultural exceptionalism was curbed as a result of the GATT Uruguay Round Agreement on Agriculture, discuss why it was curbed and finally explore the implication of this for EU policy making. We argue that, in particular, two major changes in GATT institutions brought about restrictions on agricultural exceptionalism. First, the Uruguay Round was a 'single undertaking' in which progress on other dossiers was contingent upon an outcome on agriculture. The EU had keenly supported this new decision rule in the GATT. Within the EU this led to the MacSharry reforms of the Common Agricultural Policy (CAP) in 1992, paving the way for a trade agreement on agriculture within the GATT. Second, under the new quasi-judicial dispute settlement procedure, countries are expected to bring their policies into conformity with WTO rules or face retaliatory trade sanctions. This has brought about a greater willingness on the part of the EU to submit its farm policy to WTO disciplines.

Ideational change in the WTO and its impacts on EU agricultural policy institutions and the CAP

This paper argues that the Uruguay Round Agreement on Agriculture (URAA) introduced the market liberal paradigm as the ideational underpinning of the new farm trade regime. Though the immediate consequences in terms of limitations on agricultural support and protection were very modest, the Agreement did impact on the way in which domestic farm policy evolves. It forced EU agricultural policy makers to consider the agricultural negotiations when reforming the Common Agricultural Policy (CAP). The new paradigm in global farm trade resulted in a process of institutional layering in which concerns raised in the World Trade Organization (WTO) were gradually incorporated in EU agricultural institutions. This has resulted in gradual reform of the CAP in which policy instruments have been changed in order to make the CAP more WTO compatible. The underlying paradigm, the state-assisted paradigm, has been sustained though it has been rephrased by introducing the concept of multifunctionality.

The visibility of agricultural subsidies and market illusions in the Common Agricultural Policy: Some evidence from farmers' views in Germany, Portugal and the United Kingdom

This article demonstrates that the design and nature of agricultural support schemes has an influence on farmers' perception of their level of dependence on agricultural support. While direct aid payments inform farmers about the extent to which they are subsidised, indirect support mechanisms veil the level of subsidisation, and therefore they are not fully aware of the extent to which they are supported. To test this hypothesis, we applied data from a survey of 4,500 farmers in three countries: the United Kingdom, Germany and Portugal. It is demonstrated that indirect support, such as that provided through artificially high consumer prices, gives an illusion of free and competitive markets among farmers. This 'visibility' hypothesis is evaluated against an alternative hypothesis that assumes farmers have complete, or at least a fairly comprehensive level of, information on agricultural support schemes. Our findings show that this alternative hypothesis can be ruled out.

Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.