Possible interactions between environmental factors in determining species optima

Questions: 1. Indicator values, such as those of Ellenberg, for different environmental factors are seen as independent. We tested for the presence of interactions between environmental factors ( soil moisture and reaction) to see if this assumption is simplistic. 2. How close are Ellenberg indicator values (IVs) related to the observed optima of species response curves in an area peripheral to those where they have been previously employed and 3. Can the inclusion of bryophytes add to the utility of IVs?

Location: South Uist, Outer Hebrides, Scotland, UK.

Methods: Two grids (ca. 2000 m x 2000 m) were sampled at 50-m intervals across the transition from machair to upland communities covering an orthogonal gradient of both soil pH ( reaction) and soil moisture content. Percentage cover data for vascular plants, bryophytes and lichens were recorded, along with pH and moisture content of the underlying sand/soil/peat. Reaction optima, derived from species response curves calculated using HOF models, were compared between wet and dry sites, and moisture optima between acidic and basic samples. Optima for the whole data set were compared to Ellenberg IVs to assess their performance in this area, with and without the inclusion of bryophytes.

Results: A number of species showed substantially different pH optima at high and low soil moisture contents (18% of those tested) and different soil moisture optima at high and low pH (49%). For a number of species the IVs were poor predictors of their actual distribution across the sampled area. Bryophytes were poor at explaining local variation in the environmental factors and also their inclusion with vascular plants negatively affected the strength of relationships.

Conclusions: A substantial number of species showed an interaction between soil moisture and reaction in determining their optima on the two respective gradients. It should be borne in mind that IVs such as Ellenberg's may not be independent of one another.

Influence of the experimental design of gene expression studies on the inference of gene regulatory networks: environmental factors

The inference of gene regulatory networks gained within recent years a considerable interest in the biology and biomedical community. The purpose of this paper is to investigate the influence that environmental conditions can exhibit on the inference performance of network inference algorithms. Specifically, we study five network inference methods, Aracne, BC3NET, CLR, C3NET and MRNET, and compare the results for three different conditions: (I) observational gene expression data: normal environmental condition, (II) interventional gene expression data: growth in rich media, (III) interventional gene expression data: normal environmental condition interrupted by a positive spike-in stimulation. Overall, we find that different statistical inference methods lead to comparable, but condition-specific results. Further, our results suggest that non-steady-state data enhance the inferability of regulatory networks.

Plant community assembly at small scales: spatial versus environmental factors in a central European grassland

Dispersal limitation and environmental conditions are crucial drivers of plant species distribution and establishment. As these factors operate at different spatial scales, we asked: Do the environmental factors known to determine community assembly at broad scales operate at fine scales (few meters)? How much do these factors account for community variation at fine scales? In which way do biotic and abiotic interactions drive changes in species composition? We surveyed the plant community within a dry grassland along a very steep gradient of soil characteristics like pH and nutrients. We used a spatially explicit sampling design, based on three replicated macroplots of 15x15, 12x12 and 12x12 meters in extent. Soil samples were taken to quantify several soil properties (carbon, nitrogen, plant available phosphorus, pH, water content and dehydrogenase activity as a proxy for overall microbial activity). We performed variance partitioning to assess the effect of these variables on plant composition and statistically controlled for spatial autocorrelation via eigenvector mapping. We also applied null model analysis to test for non-random patterns in species co-occurrence using randomization schemes that account for patterns expected under species interactions. At a fine spatial scale, environmental factors explained 18% of variation when controlling for spatial autocorrelation in the distribution of plant species, whereas purely spatial processes accounted for 14% variation. Null model analysis showed that species spatially segregated in a non-random way and these spatial patterns could be due to a combination of environmental filtering and biotic interactions. Our grassland study suggests that environmental factors found to be directly relevant in broad scale studies are present also at small scales, but are supplemented by spatial processes and more direct interactions like competition.

Slopes of Avian Species-Area Relationships, Human Population Density, and Environmental Factors

There is increasing interest in how humans influence spatial patterns in biodiversity. One of the most frequently noted and marked of these patterns is the increase in species richness with area, the species-area relationship (SAR). SARs are used for a number of conservation purposes, including predicting extinction rates, setting conservation targets, and identifying biodiversity hotspots. Such applications can be improved by a detailed understanding of the factors promoting spatial variation in the slope of SARs, which is currently the subject of a vigorous debate. Moreover, very few studies have considered the anthropogenic influences on the slopes of SARs; this is particularly surprising given that in much of the world areas with high human population density are typically those with a high number of species, which generates conservation conflicts. Here we determine correlates of spatial variation in the slopes of species-area relationships, using the British avifauna as a case study. Whilst we focus on human population density, a widely used index of human activities, we also take into account (1) the rate of increase in habitat heterogeneity with increasing area, which is frequently proposed to drive SARs, (2) environmental energy availability, which may influence SARs by affecting species occupancy patterns, and (3) species richness. We consider environmental variables measured at both local (10 km x 10 km) and regional (290 km x 290 km) spatial grains, but find that the former consistently provides a better fit to the data. In our case study, the effect of species richness on the slope SARs appears to be scale dependent, being negative at local scales but positive at regional scales. In univariate tests, the slope of the SAR correlates negatively with human population density and environmental energy availability, and positively with the rate of increase in habitat heterogeneity. We conducted two sets of multiple regression analyses, with and without species richness as a predictor. When species richness is included it exerts a dominant effect, but when it is excluded temperature has the dominant effect on the slope of the SAR, and the effects of other predictors are marginal.

Combining environmental and medical datasets to explore potential associations between environmental factors and health: Policy implications for human health risk assessments

This review paper discusses the use of Tellus and Tellus Border soil and stream geochemistry data to investigate the relationship between medical data and naturally occurring background levels of potentially toxic elements (PTEs) such as heavy metals in soils and water. The research hypothesis is that long-term low level oral exposure of PTEs via soil and water may result in cumulative exposures that may act as risk factors for progressive diseases including cancer and chronic kidney disease. A number of public policy implications for regional human health risk assessments, public health policy and education are also explored alongside the argument for better integration of multiple data sets to enhance ongoing medical and social research. This work presents a partnership between the School of Geography, Archaeology and Palaeoecology, Northern Ireland Cancer Registry, Queen’s University Belfast, and the nephrology (kidney medicine) research group.

Nuclear cataract shows significant familial aggregation in an older population after adjustment for possible shared environmental factors.

PURPOSE: To quantify the association between siblings in age-related nuclear cataract, after adjusting for known environmental and personal risk factors. METHODS: All participants (probands) in the Salisbury Eye Evaluation (SEE) project and their locally resident siblings underwent digital slit lamp photography and were administered a questionnaire to assess risk factors for cataract including: age, gender, lifetime sun exposure, smoking and diabetes history, and use of alcohol and medications such as estrogens and steroids. In addition, blood pressure, body mass index, and serum antioxidants were measured in all participants. Lens photographs were graded by trained observers masked to the subjects' identity, using the Wilmer Cataract Grading System. The odds ratio for siblings for affectedness with nuclear cataract and the sibling correlation of nuclear cataract grade, after adjusting for covariates, were estimated with generalized estimating equations. RESULTS: Among 307 probands (mean age, 77.6 +/- 4.5 years) and 434 full siblings (mean age, 72.4 +/- 7.4 years), the average sibship size was 2.7 per family. After adjustment for covariates, the probability of development of nuclear cataract was significantly increased (odds ratio [OR] = 2.07, 95% confidence interval [CI], 1.30-3.30) among individuals with a sibling with nuclear cataract (nuclear grade > or = 3.0). The final fitted model indicated a magnitude of heritability for nuclear cataract of 35.6% (95% CI: 21.0%-50.3%) after adjustment for the covariates. CONCLUSIONS: Findings in this study are consistent with a genetic effect for age-related nuclear cataract, a common and clinically significant form of lens opacity.

Cortical, but not posterior subcapsular, cataract shows significant familial aggregation in an older population after adjustment for possible shared environmental factors.

PURPOSE:

To quantify the risk for age-related cortical cataract and posterior subcapsular cataract (PSC) associated with having an affected sibling after adjusting for known environmental and personal risk factors.

DESIGN:

Sibling cohort study.

PARTICIPANTS:

Participants in the ongoing Salisbury Eye Evaluation (SEE) study (n = 321; mean age, 78.1+/-4.2 years) and their locally resident siblings (n = 453; mean age, 72.6+/-7.4 years) were recruited at the time of Rounds 3 and 4 of the SEE study. INTERVENTION/TESTING METHODS: Retroillumination photographs of the lens were graded for the presence of cortical cataract and PSC with the Wilmer grading system. The residual correlation between siblings' cataract grades was estimated after adjustment for a number of factors (age; gender; race; lifetime exposure to ultraviolet-B light; cigarette, alcohol, estrogen, and steroid use; serum antioxidants; history of diabetes; blood pressure; and body mass index) suspected to be associated with the presence of cataract.

RESULTS:

The average sibship size was 2.7 per family. Multivariate analysis revealed the magnitude of heritability (h(2)) for cortical cataract to be 24% (95% CI, 6%-42%), whereas that for PSC was not statistically significant (h(2) 4%; 95% CI, 0%-11%) after adjustment for the covariates. The model revealed that increasing age, female gender, a history of diabetes, and black race increased the odds of cortical cataract, whereas higher levels of provitamin A were protective. A history of diabetes and steroid use increased the odds for PSC.

CONCLUSIONS:

This study is consistent with a significant genetic effect for age-related cortical cataract but not PSC.

The `Chicken and Egg' of Subjective and Social Factors in Desistance from Crime

It is now widely acknowledged that progression from persistent offending to desistance from crime is the outcome of a complex interaction between subjective/ agency factors and social/environmental factors. A methodological challenge for desistance researchers is to unravel the differential impacts of these internal and external factors and the sequence in which they come into play. Towards this, the present investigation draws on a prospective study of 130 male property offenders, interviewed in the 1990s (the Oxford Recidivism Study), and followed up 10 years later. The analysis supports a `subjective—social model' in which subjective states measured before release have a direct effect on recidivism as well as indirect effects through their impact on social circumstances experienced after release from prison.

Are richness patterns of common and rare species equally well explained by environmental variables?

We investigated relationships between richness patterns of rare and common grassland species and environmental factors, focussing on comparing the degree to which the richness patterns of rare and common species are determined by simple environmental variables. Using data collected in the Machair grassland of the Outer Hebrides of Scotland, we fitted spatial regression models using a suite of grazing, soil physicochemical and microtopographic covariates, to nested sub-assemblages of vascular and non-vascular species ranked according to rarity. As expected, we found that common species drive richness patterns, but rare vascular species had significantly stronger affinity for high richness areas. After correcting for the prevalence of individual species distributions, we found differences between common and rare species in 1) the amount of variation explained: richness patterns of common species were better summarised by simple environmental variables, 2) the associations of environmental variables with richness showed systematic trends between common and rare species with coefficient sign reversal for several factors, and 3) richness associations with rare environments: richness patterns of rare vascular species significantly matched rare environments but those of non-vascular species did not. Richness patterns of rare species, at least in this system, may be intrinsically less predictable than those of common species.

Bird diversity and environmental gradients in Britain:a test of the species-energy hypothesis

1. We tested the species diversity-energy hypothesis using the British bird fauna. This predicts that temperature patterns should match diversity patterns. We also tested the hypothesis that the mechanism operates directly through effects of temperature on thermoregulatory loads; this further predicts that seasonal changes in temperature cause matching changes in patterns of diversity, and that species' body mass is influential.

2. We defined four assemblages using migration status (residents or visitors) and season (summer or winter distribution). Records of species' presence/absence in a total of 2362, 10 x 10-km, quadrats covering most of Britain were used, together with a wide selection of habitat, topographic and seasonal climatic data.

3. We fitted a logistic regression model to each species' distribution using the environmental data. We then combined these individual species models mathematically to form a diversity model. Analysis of this composite model revealed that summer temperature was the factor most strongly associated with diversity.

4. Although the species-energy hypothesis was supported, the direct mechanism, predicting an important role for body mass and matching seasonal patterns of change between diversity and temperature, was not supported.

5. However, summer temperature is the best overall explanation for bird diversity patterns in Britain. It is a better predictor of winter diversity than winter temperature. Winter diversity is predicted more precisely from environmental factors than summer diversity.

6. Climate change is likely to influence the diversity of different areas to different extents; for resident species, low diversity areas may respond more strongly as climate change progresses. For winter visitors, higher diversity areas may respond more strongly, while summer visitors are approximately neutral.

Neovascular age-related macular degeneration risk based on CFH, LOC387715/HTRA1, and smoking

Age-related macular degeneration (AMD) is the major cause of blindness in the elderly. Those with the neovascular end-stage of disease have irreversible loss of central vision. AMD is a complex disorder in which genetic and environmental factors play a role. Polymorphisms in the complement factor H (CFH) gene, LOC387715, and the HTRA1 promoter are strongly associated with AMD. Smoking also contributes to the etiology. We aimed to provide a model of disease risk based on these factors.