998 resultados para interspecific relationships


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Namibia has high levels of invertebrate endemism, but biodiversity research has been geographically and taxonomically limited. In South African savannah, species richness of ground-foraging ant assemblages is regulated by dominant ant species, but this pattern has not been tested in other arid environments. In this study, we provide a description of ant diversity at baits in three different Namibian habitats (savannah, saltpan and desert), and we test the relationship between ant dominance and richness for ground-foraging and arboreal species. Forty-two ant species were collected in this study, with species richness being highest in the saltpan, followed by savannah and then desert. Ant assemblages were most similar between the savannah and desert, due to shared arboreal species. Similarity between savannah and saltpan ant assemblages was due to an overlap in ground-foraging species. Ground ants were more diverse than arboreal ants, and several species were observed at baits for both strata, although the degree of overlap varied with habitat type. The dominance-richness relationship varied depending on habitat and sampling strata. We found a unimodal relationship in the saltpan, but not in the savannah. For ground ants the relationship was logarithmic, with increasing abundance of dominants leading to decreasing overall species richness. However, no trend was observed for the arboreal ant assemblage. In the desert, low ant abundance meant that we were unable to assign species dominance, possibly due to reduced foraging activity caused by high temperatures. The lack of a consistent dominance-richness trend across assemblages may be the result of varying degrees of environmental stress or competition. Our study is a preliminary description of diversity and dominance in Namibia, and we hope it stimulates further research on ant assemblages in arid regions of Africa.

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The total reactive phosphorus (TRP) and nitrate concentrations of the River Enborne, southern England, were monitored at hourly interval between January 2010 and December 2011. The relationships between these high-frequency nutrient concentration signals and flow were used to infer changes in nutrient source and dynamics through the annual cycle and each individual storm event, by studying hysteresis patterns. TRP concentrations exhibited strong dilution patterns with increasing flow, and predominantly clockwise hysteresis through storm events. Despite the Enborne catchment being relatively rural for southern England, TRP inputs were dominated by constant, non-rain-related inputs from sewage treatment works (STW) for the majority of the year, producing the highest phosphorus concentrations through the spring–summer growing season. At higher river flows, the majority of the TRP load was derived from within-channel remobilisation of phosphorus from the bed sediment, much of which was also derived from STW inputs. Therefore, future phosphorus mitigation measures should focus on STW improvements. Agricultural diffuse TRP inputs were only evident during storms in the May of each year, probably relating to manure application to land. The nitrate concentration–flow relationship produced a series of dilution curves, indicating major inputs from groundwater and to a lesser extent STW. Significant diffuse agricultural inputs with anticlockwise hysteresis trajectories were observed during the first major storms of the winter period. The simultaneous investigation of high-frequency time series data, concentration–flow relationships and hysteresis behaviour through multiple storms for both phosphorus and nitrate offers a simple and innovative approach for providing new insights into nutrient sources and dynamics.

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Global controls on month-by-month fractional burnt area (2000–2005) were investigated by fitting a generalised linear model (GLM) to Global Fire Emissions Database (GFED) data, with 11 predictor variables representing vegetation, climate, land use and potential ignition sources. Burnt area is shown to increase with annual net primary production (NPP), number of dry days, maximum temperature, grazing-land area, grass/shrub cover and diurnal temperature range, and to decrease with soil moisture, cropland area and population density. Lightning showed an apparent (weak) negative influence, but this disappeared when pure seasonal-cycle effects were taken into account. The model predicts observed geographic and seasonal patterns, as well as the emergent relationships seen when burnt area is plotted against each variable separately. Unimodal relationships with mean annual temperature and precipitation, population density and gross domestic product (GDP) are reproduced too, and are thus shown to be secondary consequences of correlations between different controls (e.g. high NPP with high precipitation; low NPP with low population density and GDP). These findings have major implications for the design of global fire models, as several assumptions in current models – most notably, the widely assumed dependence of fire frequency on ignition rates – are evidently incorrect.

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The present study evaluated the effects of climate variability on maize (Zea mays L.) yield in Sri Lanka at different spatial scales. Biophysical data from the Department of Agriculture (DOA) in Sri Lanka for six major maize-growing districts (Ampara, Anuradhapura, Badulla, Hambantota, Moneragala, and Kurunegala) from 1990 to 2010 were analyzed. Simple linear regression models were fitted to observed climate data and detrended maize yield to identify significant correlations. The correlation between first differences of maize yield and climate (r) was further investigated at 0.50° grid scale using interpolated climate data. After 2003, significantly positive (p < 0.01) yield trends varied from 154 kg ha–1 yr–1 to 360 kg ha–1 yr–1. The correlations between maize yield and climate reported that five out of six districts were significant at 10% level. Rainfall had a consistent significant (p < 0.10) positive impact on maize yield in Anuradhapura, Hambantota, and Moneragala, where seasonal total rainfall together with high temperature (“hot-dry”) are the key limitations. Further, the seasonal mean temperature had a negative impact on maize yield in Moneragala (“hot-dry”), the only district that showed high temperatures. Badulla district (“cold-dry”) reported a significant (r = 0.38) positive correlation with mean seasonal temperature, indicating higher potential toward increasing temperatures. Each 1°C rise in seasonal mean temperature reduced maize yield by about 5% from 1990 to 2010. Overall, there was a reasonable correlation between district maize yield and seasonal climate in most of the districts within the maize belt of Sri Lanka.

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Oak (Quercus robur) powdery mildew is a common and damaging fungal disease. In a local survey at Reading, UK, oak powdery mildew was common on trees of all height classes but was most common on trees of 3-9m. A variety of other fungal species were commonly found growing in association with oak powdery mildew colonies. The abundance of such fungi was estimated through stratified sample surveys for 2.5 years. The taxa most commonly associated with oak powdery mildew were Acremonium sp., Trichoderma sp., Ampelomyces/Phoma sp. and Leptosphaerulina australis. Nearly 90% of mildew colonies were associated with L. australis, which is not generally considered as a mycoparasite or antagonist, in contrast with the other three fungi. Abundance varied between June and October surveys. Acremonium sp. abundance was greater in summer samplings whereas L. australis and Trichoderma sp. abundances were greater in autumn samplings. Ampelomyces/Phoma sp. was never observed in the absence of powdery mildew. Relationships between the mildew-associated fungi and oak powdery mildew appeared curved and differed significantly between sampling years. L. australis was positively correlated with the other three associated fungi studied when powdery mildew was also present. The variety and high population densities of the mildew associated fungi suggest that they may be important in determining the final density of oak mildew and the damage caused by it.

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The functional relationships and properties of different subtypes of dendritic cells (DC) remain largely undefined. To better characterize these cells, we used global gene analysis to determine gene expression patterns among murine CD11c(high) DC subsets. CD4(+), CD8alpha(+), and CD8alpha(-) CD4(-) (double negative (DN)) DC were purified from spleens of normal C57/BL6 mice and analyzed using Affymetrix microarrays. The CD4(+) and CD8alpha(+) DC subsets showed distinct basal expression profiles differing by >200 individual genes. These included known DC subset markers as well as previously unrecognized, differentially expressed CD Ags such as CD1d, CD5, CD22, and CD72. Flow cytometric analysis confirmed differential expression in nine of nine cases, thereby validating the microarray analysis. Interestingly, the microarray expression profiles for DN cells strongly resembled those of CD4(+) DC, differing from them by <25 genes. This suggests that CD4(+) and DN DC are closely related phylogenetically, whereas CD8alpha(+) DC represent a more distant lineage, supporting the historical distinction between CD8alpha(+) and CD8alpha(-) DC. However, staining patterns revealed that in contrast to CD4(+) DC, the DN subset is heterogeneous and comprises at least two subpopulations. Gene Ontology and literature mining analyses of genes expressed differentially among DC subsets indicated strong associations with immune response parameters as well as cell differentiation and signaling. Such associations offer clues to possible unique functions of the CD11c(high) DC subsets that to date have been difficult to define as rigid distinctions.