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Organic Inputs (organic + input)
Selected AbstractsImportance of rhizodeposition in the coupling of plant and microbial productivityEUROPEAN JOURNAL OF SOIL SCIENCE, Issue 4 2003Eric Paterson Summary Plant roots influence the biological, chemical and physical properties of rhizosphere soil. These effects are a consequence of their growth, their activity and the exudation of organic compounds from them. In natural ecosystems, the linkages between inputs of carbon from plants and microbial activity driven by these inputs are central to our understanding of nutrient cycling in soil and the productivity of these systems. This coupling of plant and microbial productivity is also of increasing importance in agriculture, where the shift towards low-input systems increases the dependence of plant production on nutrient cycling, as opposed to fertilizers. This review considers the processes by which plants can influence the cycling of nutrients in soil, and in particular the importance of organic inputs from roots in driving microbially mediated transformations of N. This coupling of plant inputs to the functioning of the microbial community is beneficial for acquisition of N by plants, particularly in low-input systems. This occurs through stimulation of microbes that produce exoenzymes that degrade organic matter, and by promoting cycling of N immobilized in the microbial biomass via predation by protozoa. Also, plants increase the cycling of N by changes in exudation in response to nitrogen supply around roots, and in response to browsing by herbivores. Plants can release compounds in exudates that directly affect the expression of genes in microbes, and this may be an important way of controlling their function to the benefit of the plant. [source] Functional biodiversity of macroinvertebrate assemblages along major ecological gradients of boreal headwater streamsFRESHWATER BIOLOGY, Issue 9 2005JANI HEINOArticle first published online: 3 AUG 200 Summary 1. Biodiversity,environment relationships are increasingly well-understood in the context of species richness and species composition, whereas other aspects of biodiversity, including variability in functional diversity (FD), have received rather little rigorous attention. For streams, most studies to date have examined either taxonomic assemblage patterns or have experimentally addressed the importance of species richness for ecosystem functioning. 2. I examined the relationships of the functional biodiversity of stream macroinvertebrates to major environmental and spatial gradients across 111 boreal headwater streams in Finland. Functional biodiversity encompassed functional richness (FR , the number of functional groups derived from a combination of functional feeding groups and habit trait groups), FD , the number of functional groups and division of individuals among these groups, and functional evenness (FE , the division of individuals among functional groups). Furthermore, functional structure (FS) comprised the composition and abundance of functional groups at each site. 3. FR increased with increasing pH, with additional variation related to moss cover, total nitrogen, water colour and substratum particle size. FD similarly increased with increasing pH and decreased with increasing canopy cover. FE decreased with increasing canopy cover and water colour. Significant variation in FS was attributable to pH, stream width, moss cover, substratum particle size, nitrogen, water colour with the dominant pattern in FS being related to the increase of shredder-sprawlers and the decrease of scraper-swimmers in acidic conditions. 4. In regression analysis and redundancy analysis, variation in functional biodiversity was not only related to local environmental factors, but a considerable proportion of variability was also attributable to spatial patterning of environmental variables and pure spatial gradients. For FR, 23.4% was related to pure environmental effects, 15.0% to shared environmental and spatial effects and 8.0% to spatial trends. For FD, 13.8% was attributable to environmental effects, 15.2% to shared environmental and spatial effects and 5% to spatial trends. For FE, 9.0% was related to environmental variables, 12.7% to shared effects of environmental and spatial variables and 4.5% to spatial variables. For FS, 13.5% was related to environmental effects, 16.9% to shared environmental and spatial effects and 15.4% to spatial trends. 5. Given that functional biodiversity should portray variability in ecosystem functioning, one might expect to find functionally rather differing ecosystems at the opposite ends of major environmental gradients (e.g. acidity, stream size). However, the degree to which variation in the functional biodiversity of stream macroinvertebrates truly portrays variability in ecosystem functioning is difficult to judge because species traits, such as feeding roles and habit traits, are themselves strongly affected by the habitat template. 6. If functional characteristics show strong responses to natural environmental gradients, they also are likely to do so to anthropogenic environmental changes, including changes in habitat structure, organic inputs and acidifying elements. However, given the considerable degree of spatial structure in functional biodiversity, one should not expect that only the local environment and anthropogenic changes therein are responsible for this variability. Rather, the spatial context, as well as natural variability along environmental gradients, should also be explicitly considered in applied research. [source] A multi-proxy study of Holocene lake development, lake settlement and vegetation history in central Ireland,JOURNAL OF QUATERNARY SCIENCE, Issue 2 2005K. A. Selby Abstract Stratigraphical investigations, geomorphological mapping, and diatom, plant macrofossil and pollen analyses were undertaken in and around two lakes in central Ireland to establish correlations between changes in lake conditions and catchment vegetation throughout the Holocene. Similar investigations of an adjacent mire reveal early Holocene changes in lake level and area. The palaeoecological data show high correlations related to variations in lake depth and area, catchment vegetation type, organic inputs and trophic status. Catchment-scale deforestation is gradual and occurs through the Bronze and the Iron Ages, and the construction of a crannog in the early Medieval period (seventh century AD) appears to be associated with a widespread increase in deforestation and mixed agriculture in the catchment. Both pollen and plant macrofossils suggest that one of the crannogs was used for crop storage in addition to domestic and any other activities. In the early to middle Holocene similarities in the proxy-data appear to be climatically driven through changing lake levels and areal extent whereas the later Holocene record is clearly dominated by anthropogenic changes within the catchment and the construction of crannogs in the lakes. The advantages of combining multi-proxy indicators of lake hydroecology with the vegetation record are illustrated. Copyright © 2005 John Wiley & Sons, Ltd. [source] AN APPLICATION OF MULTI-CRITERIA DECISION MAKING INCORPORATING STOCHASTIC PRODUCTION FRONTIERS: A CASE STUDY OF ORGANIC COFFEE PRODUCTION IN KONA, HAWAIINATURAL RESOURCE MODELING, Issue 1 2010TADAYOSHI MASUDA Abstract In this paper, we develop a land use allocation model to search for the optimal ratio of organic (nonchemical) and conventional (chemical-use) farming acreage. The idea is to incorporate stochastic production frontiers (SPFs) to a multi-criteria decision making (MCDM) model as technological constraints. The objectives of this model are to maximize net returns, minimize chemical inputs, and optimize organic inputs given environmental and ecological concerns. The compromise solutions suggest the desirable ratio of organic and conventional farming acreage and targetable operations for each farming system to improve regional welfare. This method was applied to the Kona coffee belt, Hawaii, and the analysis determined the optimal proportion of organic and conventional Kona coffee farming fields as 0.265 to 0.735 in terms of optimizing community benefits or regional welfare. [source] | ||||||||||