Advanced mapping of environmental data: Geostatistics, Machine Learning and Bayesian Maximum Entropy

This book combines geostatistics and global mapping systems to present an up-to-the-minute study of environmental data. Featuring numerous case studies, the reference covers model dependent (geostatistics) and data driven (machine learning algorithms) analysis techniques such as risk mapping, conditional stochastic simulations, descriptions of spatial uncertainty and variability, artificial neural networks (ANN) for spatial data, Bayesian maximum entropy (BME), and more.

A framework for assessing the scale of influence of environmental factors on ecological patterns

The distribution of living organisms, habitats and ecosystems is primarily driven by abiotic environmental factors that are spatially structured. Assessing the spatial structure of environmental factors, e.g., through spatial autocorrelation analyses (SAC), can thus help us understand their scale of influence on the distribution of organisms, habitats, and ecosystems. Yet SAC analyses of environmental factors are still rarely performed in biogeographic studies. Here, we describe a novel framework that combines SAC and statistical clustering to identify scales of spatial patterning of environmental factors, which can then be interpreted as the scales at which those factors influence the geographic distribution of biological and ecological features. We illustrate this new framework with datasets at different spatial or thematic resolutions. This framework is conceptually and statistically robust, providing a valuable approach to tackle a wide range of issues in ecological and environmental research and particularly when building predictors for ecological models. The new framework can significantly promote fundamental research on all spatially-structured ecological patterns. It can also foster research and application in such fields as global change ecology, conservation planning, and landscape management.

Long term global evaluation of a national AIDS prevention strategy: the case of Switzerland.

OBJECTIVES: The Swiss Aids prevention strategy has been subject to a continuous process of evaluation for the past 12 years. This paper describes the conceptual approach, methodology, results obtained and contribution to policy-making of that evaluation.¦DESIGN: The evaluation is on-going, global with respect to all components of the strategy, and utilization-focused. Each successive phase of the evaluation has included 10-20 studies centred either on aspects of process, of outcome or of environmental context. Findings are synthesized at the end of each phase. METHODS: Both quantitative and qualitative methods are used. Studies generally have one of three functions within the overall evaluation: assessment of trends through surveys or other types of repeated studies; evaluation of specific areas through a series of studies from different viewpoints; in-depth investigation or rapid assessment through one-off studies. Various methods of triangulation are used to validate findings. RESULTS: The evaluation has allowed for: the observation of behavioural change in different populations; the availability of scientific data in controversial fields such as drug-use policy; an understanding of the diversity of public appropriation of prevention messages. Recommendations are regularly formulated and have been used by policy-makers and field workers for strategy development. CONCLUSIONS: The global approach adopted corresponds well to the evaluation requirements of an integrated long-term prevention strategy. Cost is low relative to the extent of information provided. Such an evaluation cannot however address the question of causal relationship between the strategy and observed changes. The evaluation has contributed to the development of a culture of evaluation in Swiss AIDS prevention more generally.

The influence of environmental spatial structure on the life history traits and diversity of species in a metacommunity

Several models have been proposed to understand how so many species can coexist in ecosystems. Despite evidence showing that natural habitats are often patchy and fragmented, these models rarely take into account environmental spatial structure. In this study we investigated the influence of spatial structure in habitat and disturbance regime upon species' traits and species' coexistence in a metacommunity. We used a population-based model to simulate competing species in spatially explicit landscapes. The species traits we focused on were dispersal ability, competitiveness, reproductive investment and survival rate. Communities were characterized by their species richness and by the four life-history traits averaged over all the surviving species. Our results show that spatial structure and disturbance have a strong influence on the equilibrium life-history traits within a metacommunity. In the absence of disturbance, spatially structured landscapes favour species investing more in reproduction, but less in dispersal and survival. However, this influence is strongly dependent on the disturbance rate, pointing to an important interaction between spatial structure and disturbance. This interaction also plays a role in species coexistence. While spatial structure tends to reduce diversity in the absence of disturbance, the tendency is reversed when disturbance occurs. In conclusion, the spatial structure of communities is an important determinant of their diversity and characteristic traits. These traits are likely to influence important ecological properties such as resistance to invasion or response to climate change, which in turn will determine the fate of ecosystems facing the current global ecological crisis.

Robust discrimination between EEG responses to categories of environmental sounds in early coma.

Humans can recognize categories of environmental sounds, including vocalizations produced by humans and animals and the sounds of man-made objects. Most neuroimaging investigations of environmental sound discrimination have studied subjects while consciously perceiving and often explicitly recognizing the stimuli. Consequently, it remains unclear to what extent auditory object processing occurs independently of task demands and consciousness. Studies in animal models have shown that environmental sound discrimination at a neural level persists even in anesthetized preparations, whereas data from anesthetized humans has thus far provided null results. Here, we studied comatose patients as a model of environmental sound discrimination capacities during unconsciousness. We included 19 comatose patients treated with therapeutic hypothermia (TH) during the first 2 days of coma, while recording nineteen-channel electroencephalography (EEG). At the level of each individual patient, we applied a decoding algorithm to quantify the differential EEG responses to human vs. animal vocalizations as well as to sounds of living vocalizations vs. man-made objects. Discrimination between vocalization types was accurate in 11 patients and discrimination between sounds from living and man-made sources in 10 patients. At the group level, the results were significant only for the comparison between vocalization types. These results lay the groundwork for disentangling truly preferential activations in response to auditory categories, and the contribution of awareness to auditory category discrimination.

Amniotic fluid insulin-like growth factor binding protein 3 concentration as early indicator of fetal growth restriction.

OBJECTIVE: Insulin-like growth factor-I (IGF-I) is an important regulator of fetal growth and its bioavailability depends on insulin-like growth factor binding proteins (IGFBPs). Genes coding for IGF-I and IGFBP3 are polymorphic. We hypothesized that either amniotic fluid protein concentration at the beginning of the second trimester or genotype of one of these two genes could be predictive of abnormal fetal growth. STUDY DESIGN: Amniotic fluid samples (14-18 weeks of pregnancy) from 123 patients with appropriate for gestational age (AGA) fetuses, 39 patients with small for gestational age (SGA) fetuses and 34 patients with large for gestational age (LGA) were analyzed. Protein concentrations were evaluated by ELISA and gene polymorphisms by PCR. RESULTS: Amniotic fluid IGFBP3 concentrations were significantly higher in SGA compared to AGA group (P=0.030), and this was even more significant when adjusted to gestational age at the time of amniocentesis and other covariates (ANCOVA analysis: P=0.009). Genotypic distribution of IGF-I variable number of tandem repeats (VNTR) polymorphism was significantly different in SGA compared to AGA group (P=0.029). 19CA/20CA genotype frequency was threefold decreased in SGA compared to AGA group and the risk of SGA occurrence of this genotype was decreased accordingly: OR=0.289, 95%CI=0.1-0.9, P=0.032. Genotype distribution of IGFBP3(A-202C) polymorphism was similar in all three groups. CONCLUSIONS: High IGFBP3 concentrations in amniotic fluid at the beginning of the second trimester are associated with increased risks of SGA while 19CA/20CA genotype at IGF-I VNTR polymorphism is associated with reduced risks of SGA. Neither IGFBP3 concentrations, nor IGF-I/IGFBP3 polymorphisms are associated with modified risks of LGA.

Detection of active oxalate-carbonate pathway ecosystems in the Amazon Basin: Global implications of a natural potential C sink

The oxalate-carbonate pathway (OCP) is a biogeochemical process, which has been described in Milicia excelsa tree ecosystems of Africa. This pathway involves biological and geological parameters at different scales: oxalate, as a by-product of photosynthesis, is oxidized by oxalotrophic bacteria leading to a local pH increase, and eventually to carbonate accumulation through time in previously acidic and carbonate-free tropical soils. Former studies have shown that this pedogenic process can potentially lead to the formation of an atmospheric carbon sink. Considering that 80% of plant species are known to produce oxalate, it is reasonable to assume that M. excelsa is not the only tree that can support OCP ecosystems. The search for similar conditions on another continent led us to South America, in an Amazon forest ecosystem (Alto Beni, Bolivia). This area was chosen because of the absence of local inherited carbonate in the bedrock, as well as its expected acidic soil conditions. Eleven tree species and associated soils were tested positive for the presence of carbonate with a more alkaline soil pH close to the tree than at a distance from it. A detailed study of Pentaplaris davidsmithii and Ceiba speciosa trees showed that oxalotrophy impacted soil pH in a similar way to at African sites (at least with 1 pH unit increasing). African and South American sites display similar characteristics regarding the mineralogical assemblage associated with the OCP, except for the absence of weddellite. The amount of carbonate accumulated is 3 to 4 times lower than the values measured in African sites related to M. excelsa ecosystems. Still, these secondary carbonates remain critical for the continental carbon cycle, as they are unexpected in the acidic context of Amazonian soils. Therefore, the present study demonstrates the existence of an active OCP in South America. The three critical components of an operating OCP are the presence of: i) local alkalinization, ii) carbonate accumulations, and iii) oxalotrophic bacteria, which were identified associated to the oxalogenic tree C. speciosa. If the question of a potential carbon sink related to oxalotrophic-oxalogenic ecosystems in the Amazon Basin is still pending, this study highlights the implication of OCP ecosystems on carbon and calcium biogeochemical coupled cycles. As previously mentioned for M. excelsa tree ecosystems in Africa, carbonate accumulations observed in the Bolivian tropical forest could be extrapolated to part or the whole Amazon Basin and might constitute an important reservoir that must be taken into account in the global carbon balance of the Tropics.

Involvement of environmental mercury and lead in the etiology of neurodegenerative diseases.

The incidence of neurodegenerative disease like Parkinson's disease and Alzheimer's disease (AD) increases dramatically with age; only a small percentage is directly related to familial forms. The etiology of the most abundant, sporadic forms is complex and multifactorial, involving both genetic and environmental factors. Several environmental pollutants have been associated with neurodegenerative disorders. The present article focuses on results obtained in experimental neurotoxicology studies that indicate a potential pathogenic role of lead and mercury in the development of neurodegenerative diseases. Both heavy metals have been shown to interfere with a multitude of intracellular targets, thereby contributing to several pathogenic processes typical of neurodegenerative disorders, including mitochondrial dysfunction, oxidative stress, deregulation of protein turnover, and brain inflammation. Exposure to heavy metals early in development can precondition the brain for developing a neurodegenerative disease later in life. Alternatively, heavy metals can exert their adverse effects through acute neurotoxicity or through slow accumulation during prolonged periods of life. The pro-oxidant effects of heavy metals can exacerbate the age-related increase in oxidative stress that is related to the decline of the antioxidant defense systems. Brain inflammatory reactions also generate oxidative stress. Chronic inflammation can contribute to the formation of the senile plaques that are typical for AD. In accord with this view, nonsteroidal anti-inflammatory drugs and antioxidants suppress early pathogenic processes leading to Alzheimer's disease, thus decreasing the risk of developing the disease. The effects of lead and mercury were also tested in aggregating brain-cell cultures of fetal rat telencephalon, a three-dimensional brain-cell culture system. The continuous application for 10 to 50 days of non-cytotoxic concentrations of heavy metals resulted in their accumulation in brain cells and the occurrence of delayed toxic effects. When applied at non-toxic concentrations, methylmercury, the most common environmental form of mercury, becomes neurotoxic under pro-oxidant conditions. Furthermore, lead and mercury induce glial cell reactivity, a hallmark of brain inflammation. Both mercury and lead increase the expression of the amyloid precursor protein; mercury also stimulates the formation of insoluble beta-amyloid, which plays a crucial role in the pathogenesis of AD and causes oxidative stress and neurotoxicity in vitro. Taken together, a considerable body of evidence suggests that the heavy metals lead and mercury contribute to the etiology of neurodegenerative diseases and emphasizes the importance of taking preventive measures in this regard.