Acquiring, managing and applying knowledge for environmental conservation

We are experiencing an explosion of knowledge with relevance to conserving biodiversity and protecting the environment necessary to sustain life on earth. Many science disciplines are involved in generating this ne, knowledge and real progress can be made when scientists collaborate across disciplines to generate both macro- and micro-environmental knowledge and then communicate and interact with specialists in sociology, economics and public policy. An important requirement is that the often complex scientific concepts and their voluminous supporting data are managed in such ways as to make them accessible across the many specializations involved. Horticultural science has much to contribute to the knowledge base for environmental conservation. While it seems that production horticulture has been slow to embrace knowledge and concepts that would reduce the heavy reliance on agricultural chemicals, the use of peat as a growing medium, and lead to more sustainable use of water and other resources, environmental horticulture is providing valuable opportunities to rescue or protect endangered species, educate the public about plants and plant science, and demonstrate environmental stewardship and sustainable production practices. Likewise, social horticulture is drawing, attention to the many contributions of horticultural foods and parks and gardens to human health and welfare. Overall, horticulture has a vital role to play in integrating, knowledge from other scientific, social, economic and political disciplines.

Predicting how many animals will be where: how to build, calibrate and evaluate individual-based models

Individual-based models (IBMs) can simulate the actions of individual animals as they interact with one another and the landscape in which they live. When used in spatially-explicit landscapes IBMs can show how populations change over time in response to management actions. For instance, IBMs are being used to design strategies of conservation and of the exploitation of fisheries, and for assessing the effects on populations of major construction projects and of novel agricultural chemicals. In such real world contexts, it becomes especially important to build IBMs in a principled fashion, and to approach calibration and evaluation systematically. We argue that insights from physiological and behavioural ecology offer a recipe for building realistic models, and that Approximate Bayesian Computation (ABC) is a promising technique for the calibration and evaluation of IBMs. IBMs are constructed primarily from knowledge about individuals. In ecological applications the relevant knowledge is found in physiological and behavioural ecology, and we approach these from an evolutionary perspective by taking into account how physiological and behavioural processes contribute to life histories, and how those life histories evolve. Evolutionary life history theory shows that, other things being equal, organisms should grow to sexual maturity as fast as possible, and then reproduce as fast as possible, while minimising per capita death rate. Physiological and behavioural ecology are largely built on these principles together with the laws of conservation of matter and energy. To complete construction of an IBM information is also needed on the effects of competitors, conspecifics and food scarcity; the maximum rates of ingestion, growth and reproduction, and life-history parameters. Using this knowledge about physiological and behavioural processes provides a principled way to build IBMs, but model parameters vary between species and are often difficult to measure. A common solution is to manually compare model outputs with observations from real landscapes and so to obtain parameters which produce acceptable fits of model to data. However, this procedure can be convoluted and lead to over-calibrated and thus inflexible models. Many formal statistical techniques are unsuitable for use with IBMs, but we argue that ABC offers a potential way forward. It can be used to calibrate and compare complex stochastic models and to assess the uncertainty in their predictions. We describe methods used to implement ABC in an accessible way and illustrate them with examples and discussion of recent studies. Although much progress has been made, theoretical issues remain, and some of these are outlined and discussed.

Behavioural responses of the seven-spot ladybird Coccinella septempunctata to plant headspace chemicals collected from four crop Brassicas and Arabidopsis thaliana, infested with Myzus persicae

1 Insects using olfactory stimuli to forage for prey/hosts are proposed to encounter a ‘reliability–detectability problem’, where the usability of a stimulus depends on its reliability as an indicator of herbivore presence and its detectability. 2 We investigated this theory using the responses of female seven-spot ladybirds Coccinella septempunctata (Coleoptera: Coccinellidae) to plant headspace chemicals collected from the peach-potato aphid Myzus persicae and four commercially available Brassica cultivars; Brassica rapa L. cultivar ‘turnip purple top’, Brassica juncea L. cultivar ‘red giant mustard’, Brassica napus L. cultivar ‘Apex’, Brassica napus L. cultivar ‘Courage’ and Arabidopsis thaliana. For each cultivar/species, responses to plants that were undamaged, previously infested by M. persicae and infested with M. persicae, were investigated using dual-choice Petri dish bioassays and circular arenas. 3 There was no evidence that ladybirds responded to headspace chemicals from aphids alone. Ladybirds significantly preferred headspace chemicals from B. napus cv. Apex that were undamaged compared with those from plants infested with aphids. For the other four species/cultivars, there was a consistent trend of the predators being recorded more often in the half of the Petri dish containing plant headspace chemicals from previously damaged and infested plants compared with those from undamaged ones. Furthermore, the mean distance ladybirds walked to reach aphid-infested A. thaliana was significantly shorter than to reach undamaged plants. These results suggest that aphid-induced plant chemicals could act as an arrestment or possibly an attractant stimulus to C. septempunctata. However, it is also possible that C. septempunctata could have been responding to aphid products, such as honeydew, transferred to the previously damaged and infested plants. 4 The results provide evidence to support the ‘reliability–detectability’ theory and suggest that the effectiveness of C. septempunctata as a natural enemy of aphids may be strongly affected by which species and cultivar of Brassica are being grown.

Contributions of labile and resistant organic materials to the immobilization of inorganic soil N when used in the restoration of abandoned agricultural fields

We have examined the contributions sucrose and sawdust make to the net immobilization of inorganic soil N and assimilation of both C and N into microbial biomass when they are used as part of a restoration plan to promote the establishment of indigenous vegetation on abandoned agricultural fields on the Central Hungarian Plain. Both amendments led to net N immobilization. Sucrose addition also led to mobilization of N from the soil organic N pool and its immobilization into microbial biomass, whereas sawdust addition apparently immobilized soil N into a non-biomass compartment or a biomass component that was not detected by the conventional biomass N assay (CHCl3 fumigation and extraction). This suggests that the N was either cycled through the biomass, but not immobilized within it, or that it was immobilized in a protected biomass fraction different to the fraction into which N was immobilized in response to sucrose addition.

Microbial and biochemical soil quality indicators and their potential for differentiating areas under contrasting agricultural management regimes

The aim of this study was to examine interrelationships between functional biochemical and microbial indicators of soil quality, and their suitability to differentiate areas under contrasting agricultural management regimes. The study included five 0.8 ha areas on a sandy-loam soil which had received contrasting fertility and cropping regimes over a 5 year period. These were organically managed vegetable, vegetable -cereal and arable rotations, an organically managed grass clover ley, and a conventional cereal rotation. The organic areas had been converted from conventional cereal production 5 years prior to the start of the study. All of the biochemical analyses, including light fraction organic matter (LFOM) C and N, labile organic N (LON), dissolved organic N and water-soluble carbohydrates showed significant differences between the areas, although the nature of the relationships between the areas varied between the different parameters, and were not related to differences in total soil organic matter content. The clearest differences were seen in LFOM C and N and LON, which were higher in the organic arable area relative to the other areas. In the case of the biological parameters, there were differences between the areas for biomass-N, ATP, chitin content, and the ratios of ATP: biomass and basal respiration: biomass. For these parameters, the precise relationships between the areas varied. However, relative to the conventionally managed area, areas under organic management generally had lower biomass-N and higher ATP contents. Arbuscular mycorrhizal fungus colonization potential was extremely low in the conventional area relative to the organic areas. Further, metabolic diversity and microbial community level physiological profiles, determined by analysis of microbial community metabolism using Biolog GN plates and the activities of eight key nutrient cycling enzymes, grouped the organic areas together, but separated them from the conventional area. We conclude that microbial parameters are more effective and consistent indicators of management induced changes to soil quality than biochemical parameters, and that a variety of biochemical and microbial analyses should be used when considering the impact of management on soil quality. (C) 2004 Elsevier Ltd. All rights reserved.

A semi-quantitative approach to deriving a model structure for the uptake of organic chemicals by vegetation

An expert elicitation exercise was undertaken to determine those components and processes that are most important for modeling plant uptake of organic chemicals. The state of our knowledge of these processes was also assessed. This semi-quantitative analysis allowed the construction of an idealized model with seven compartments; soil bulk, soil water, roots, stem, leaves, fruit, and air. Three main areas were identified further research: 1) the uptake of organic chemicals by fruit; 2) the internal transfer of organic chemicals between plant structures (e.g., stem and leaves); and 3) the transfer via the soil-air-plant pathway. Until new data becomes available to quantify these processes, it is proposed that an equilibrium partitioning approach is used between plant components other than fruit or that models consist of both an edible and inedible compartment.

Plant uptake of non-ionic organic chemicals

Plant uptake of organic chemicals is an important process when considering the risks associated with land contamination, the role of vegetation in the global cycling of persistent organic pollutants, and the potential for industrial discharges to contaminate the food chain. There have been some significant advances in our understanding of the processes of plant uptake of organic chemicals in recent years; most notably there is now a better understanding of the air to plant transfer pathway, which may be significant for a number of industrial chemicals. This review identifies the key processes involved in the plant uptake of organic chemicals including those for which there is currently little information, e.g., plant lipid content and plant metabolism. One of the principal findings is that although a number of predictive models exist using established relationships, these require further validation if they are to be considered sufficiently robust for the purposes of contaminated land risk assessment or for prediction of the global cycling of persistent organic pollutants. Finally, a number of processes are identified which should be the focus of future research

Identifying management zones in agricultural fields using spatially constrained classification of soil and ancillary data

Site-specific management requires accurate knowledge of the spatial variation in a range of soil properties within fields. This involves considerable sampling effort, which is costly. Ancillary data, such as crop yield, elevation and apparent electrical conductivity (ECa) of the soil, can provide insight into the spatial variation of some soil properties. A multivariate classification with spatial constraint imposed by the variogram was used to classify data from two arable crop fields. The yield data comprised 5 years of crop yield, and the ancillary data 3 years of yield data, elevation and ECa. Information on soil chemical and physical properties was provided by intensive surveys of the soil. Multivariate variograms computed from these data were used to constrain sites spatially within classes to increase their contiguity. The constrained classifications resulted in coherent classes, and those based on the ancillary data were similar to those from the soil properties. The ancillary data seemed to identify areas in the field where the soil is reasonably homogeneous. The results of targeted sampling showed that these classes could be used as a basis for management and to guide future sampling of the soil.

The Phosphorus Indicators Tool: a simple model of diffuse P loss from agricultural land to water

The Phosphorus Indicators Tool provides a catchment-scale estimation of diffuse phosphorus (P) loss from agricultural land to surface waters using the most appropriate indicators of P loss. The Tool provides a framework that may be applied across the UK to estimate P loss, which is sensitive not only to land use and management but also to environmental factors such as climate, soil type and topography. The model complexity incorporated in the P Indicators Tool has been adapted to the level of detail in the available data and the need to reflect the impact of changes in agriculture. Currently, the Tool runs on an annual timestep and at a 1 km(2) grid scale. We demonstrate that the P Indicators Tool works in principle and that its modular structure provides a means of accounting for P loss from one layer to the next, and ultimately to receiving waters. Trial runs of the Tool suggest that modelled P delivery to water approximates measured water quality records. The transparency of the structure of the P Indicators Tool means that identification of poorly performing coefficients is possible, and further refinements of the Tool can be made to ensure it is better calibrated and subsequently validated against empirical data, as it becomes available.

Towards a nutrient export risk matrix approach to managing agricultural pollution at source

A generic Nutrient Export Risk Matrix (NERM) approach is presented. This provides advice to farmers and policy makers on good practice for reducing nutrient loss and is intended to persuade them to implement such measures. Combined with a range of nutrient transport modelling tools and field experiments, NERMs can play an important role in reducing nutrient export from agricultural land. The Phosphorus Export Risk Matrix (PERM) is presented as an example NERM. The PERM integrates hydrological understanding of runoff with a number of agronomic and policy factors into a clear problem-solving framework. This allows farmers and policy makers to visualise strategies for reducing phosphorus loss through proactive land management. The risk Of Pollution is assessed by a series of informed questions relating to farming intensity and practice. This information is combined with the concept of runoff management to point towards simple, practical remedial strategies which do not compromise farmers' ability to obtain sound economic returns from their crop and livestock.

The role of uncomposted materials, composts, manures, and compost extracts in reducing pest and disease incidence and severity in sustainable temperate agricultural and horticultural crop production - A review

This review evaluates evidence of the impact of uncomposted plant residues, composts, manures, and liquid preparations made from composts (compost extracts and teas) on pest and disease incidence and severity in agricultural and horticultural crop production. Most reports on pest control using such organic amendments relate to tropical or and climates. The majority of recent work on the use of organic amendments for prevention and control of diseases relates to container-produced plants, particularly ornamentals. However, there is growing interest in the potential for using composts to prevent and control diseases in temperate agricultural and horticultural field crops and information concerning their use and effectiveness is slowly increasing. The impact of uncomposted plant residues, composts, manures, and compost extracts/teas on pests and diseases is discussed in relation to sustainable temperate field and protected cropping systems. The factors affecting efficacy or such organic amendments in preventing and controlling pests and disease are examined and the mechanisms through which control is achieved are described.

An inventory of heavy metals inputs to agricultural soils in England and Wales

An inventory of heavy metal inputs (Zn, Cu, Ni, Pb, Cd, Cr, As and Hg) to agricultural soils in England and Wales in 2000 is presented, accounting for major sources including atmospheric deposition, sewage sludge, livestock manures, inorganic fertilisers and lime, agrochemicals, irrigation water, industrial by-product 'wastes' and composts. Across the whole agricultural land area, atmospheric deposition was the main source of most metals, ranging from 25 to 85% of total inputs. Livestock manures and sewage sludge were also important sources, responsible for an estimated 37-40 and 8-17% of total Zn and Cu inputs, respectively. However, at the individual field scale sewage sludge, livestock manures and industrial wastes could be the major source of many metals where these materials are applied. This work will assist in developing strategies for reducing heavy metal inputs to agricultural land and effectively targeting policies to protect soils from long-term heavy metal accumulation. (C) 2003 Elsevier Science B.V. All rights reserved.