Causal relationships vs. emergent patterns in the global controls of fire frequency

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.

Observed relationships between maize yield and climate in Sri Lanka

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.

Relationships between Oak powdery mildew incidence and severity and commensal fungi

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.

Relationships Among Murine CD11chigh Dendritic Cell Subsets as Revealed by Baseline Gene Expression Patterns

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.

A new governance perspective on port–hinterland relationships: the Port Hinterland Impact (PHI) matrix

We develop a new governance perspective on port–hinterland linkages and related port impacts. Many stakeholders in a port’s hinterland now demand tangible economic benefits from port activities, as a precondition for supporting port expansion and infrastructural investments. We use a governance lens to assess this farsighted contracting challenge. We find that most contemporary economic impact assessments of port investment projects pay scant attention to the contractual relationship challenges in port-hinterland relationships. In contrast, we focus explicitly on the spatial distribution of such impacts and the related contractual relationship issues facing port authorities or port users and their stakeholders in the port hinterland. We introduce a new concept, the Port Hinterland Impact (PHI) matrix, which focuses explicitly on the spatial distribution of port impacts and related contractual relationship challenges. The PHI matrix offers insight into port impacts using two dimensions: logistics dedicatedness, as an expression of Williamsonian asset specificity in the sphere of logistics contractual relationships, and geographic reach, with a longer reach typically reflecting the need for more complex contacting to overcome ‘distance’ challenges with external stakeholders. We use the PHI matrix in our empirical, governance-based analysis of contractual relationships between the port authorities in Antwerp and Zeebrugge, and their respective stakeholders.