The role of the West African Monsoon in the tropical to mid-latitudes climate

The interaction between atmosphere–land–ocean–biosphere systems plays a prominent role on the atmospheric dynamics and on the convective rainfall distribution over the West Africa monsoon area during the boreal summer. In particular, the initialization of convective systems in the Sub – Sahelian region has been directly linked to soil moisture heterogeneities identified as the major triggering, development and propagation of convective systems. The present study aims at investigating African monsoon large scale convective dynamics and rainfall diurnal cycle through an exploration of the hypothesis behind the mechanisms of a monsoon phenomenon as an emergence of a collective dynamics of many propagating convective systems. Such hypothesis is based on the existence of an internal self – regulation mechanism among the various components. To achieve these results a multiple analysis was performed based on remote sensed rainfall dataset, and global and regional modelling data for a period of 5 seasons: 2004 - 2008. Satellite rainfall data and convective occurrence variability were studied for assessing typical spatio – temporal signatures and characteristics with an emphasis to the diurnal cycle footprint. A global model and regional model simulation datasets, specifically developed for this analysis and based on Regional Atmospheric Modelling System – RAMS, have been analysed. Results from numerical model datasets highlight the evidence of a synchronization between the destabilization of the convective boundary layer and rainfall occurrence due to the solar radiation forcing through the latent heat release. This supports the conclusion that the studied interacting systems are associated with a process of mutual adjustment of rhythms. Furthermore, this rainfall internal coherence was studied in relation to the West African Heat Low pressure system, which has a prominent role in the large scale summer variability over the Mediterranean area since it is acting as one of dynamic link between sub tropical and midlatitudes variability.

Spatial and temporal variation in population genetic structure of wild Nile tilapia (Oreochromis niloticus) across Africa

Background: Reconstructing the evolutionary history of a species is challenging. It often depends not only on the past biogeographic and climatic events but also the contemporary and ecological factors, such as current connectivity and habitat heterogeneity. In fact, these factors might interact with each other and shape the current species distribution. However, to what extent the current population genetic structure reflects the past and the contemporary factors is largely unknown. Here we investigated spatio-temporal genetic structures of Nile tilapia (Oreochromis niloticus) populations, across their natural distribution in Africa. While its large biogeographic distribution can cause genetic differentiation at the paleo-biogeographic scales, its restricted dispersal capacity might induce a strong genetic structure at micro-geographic scales. Results: Using nine microsatellite loci and 350 samples from ten natural populations, we found the highest genetic differentiation among the three ichthyofaunal provinces and regions (Ethiopian, Nilotic and Sudano-Sahelian) (R(ST) = 0.38 - 0.69). This result suggests the predominant effect of paleo-geographic events at macro-geographic scale. In addition, intermediate divergences were found between rivers and lakes within the regions, presumably reflecting relatively recent interruptions of gene flow between hydrographic basins (R(ST) = 0.24 - 0.32). The lowest differentiations were observed among connected populations within a basin (R(ST) = 0.015 in the Volta basin). Comparison of temporal sample series revealed subtle changes in the gene pools in a few generations (F = 0 - 0.053). The estimated effective population sizes were 23 - 143 and the estimated migration rate was moderate (m similar to 0.094 - 0.097) in the Volta populations. Conclusions: This study revealed clear hierarchical patterns of the population genetic structuring of O. niloticus in Africa. The effects of paleo-geographic and climatic events were predominant at macro-geographic scale, and the significant effect of geographic connectivity was detected at micro-geographic scale. The estimated effective population size, the moderate level of dispersal and the rapid temporal change in genetic composition might reflect a potential effect of life history strategy on population dynamics. This hypothesis deserves further investigation. The dynamic pattern revealed at micro-geographic and temporal scales appears important from a genetic resource management as well as from a biodiversity conservation point of view.

Debris-flow activity in abandoned channels of the Manival torrent reconstructed with LiDAR and tree-ring data

Hydrogeomorphic processes are a major threat in many parts of the Alps, where they periodically damage infrastructure, disrupt transportation corridors or even cause loss of life. Nonetheless, past torrential activity and the analysis of areas affected during particular events remain often imprecise. It was therefore the purpose of this study to reconstruct spatio-temporal patterns of past debris-flow activity in abandoned channels on the forested cone of the Manival torrent (Massif de la Chartreuse, French Prealps). A Light Detecting and Ranging (LiDAR) generated Digital Elevation Model (DEM) was used to identify five abandoned channels and related depositional forms (lobes, lateral levees) in the proximal alluvial fan of the torrent. A total of 156 Scots pine trees (Pinus sylvestris L.) with clear signs of debris flow events was analyzed and growth disturbances (GD) assessed, such as callus tissue, the onset of compression wood or abrupt growth suppression. In total, 375 GD were identified in the tree-ring samples, pointing to 13 debris-flow events for the period 1931–2008. While debris flows appear to be very common at Manival, they have only rarely propagated outside the main channel over the past 80 years. Furthermore, analysis of the spatial distribution of disturbed trees contributed to the identification of four patterns of debris-flow routing and led to the determination of three preferential breakout locations. Finally, the results of this study demonstrate that the temporal distribution of debris flows did not exhibit significant variations since the beginning of the 20th century.

Interleukin-6 is an efficacious marker of axonal transport disruption during experimental glaucoma and stimulates neuritogenesis in cultured retinal ganglion cells

It is increasingly recognised that chronically activated glia contribute to the pathology of various neurodegenerative diseases, including glaucoma. One means by which this can occur is through the release of neurotoxic, proinflammatory factors. In the current study, we therefore investigated the spatio-temporal patterns of expression of three such cytokines, IL-1β, TNFα and IL-6, in a validated rat model of experimental glaucoma. First, only weak evidence was found for increased expression of IL-1β and TNFα following induction of ocular hypertension. Second, and much more striking, was that robust evidence was uncovered showing IL-6 to be synthesised by injured retinal ganglion cells following elevation of intraocular pressure and transported in an orthograde fashion along the nerve, accumulating at sites of axonal disruption in the optic nerve head. Verification that IL-6 represents a novel marker of disrupted axonal transport in this model was obtained by performing double labelling immunofluorescence with recognised markers of fast axonal transport. The stimulus for IL-6 synthesis and axonal transport during experimental glaucoma arose from axonal injury rather than ocular hypertension, as the response was identical after optic nerve crush and bilateral occlusion of the carotid arteries, each of which is independent of elevated intraocular pressure. Moreover, the response of IL-6 was not a generalised feature of the gp130 family of cytokines, as it was not mimicked by another family member, ciliary neurotrophic factor. Finally, further study suggested that IL-6 may be an early part of the endogenous regenerative response as the cytokine colocalised with growth-associated membrane phosphoprotein-43 in some putative regenerating axons, and potently stimulated neuritogenesis in retinal ganglion cells in culture, an effect that was additive to that of ciliary neurotrophic factor. These data comprise clear evidence that IL-6 is actively involved in the attempt of injured retinal ganglion cells to regenerate their axons.

Limitations of Remotely-sensed Aerosol as a Spatial Proxy for Fine Particulate Matter

Recent research highlights the promise of remotely-sensed aerosol optical depth (AOD) as a proxy for ground-level PM2.5. Particular interest lies in the information on spatial heterogeneity potentially provided by AOD, with important application to estimating and monitoring pollution exposure for public health purposes. Given the temporal and spatio-temporal correlations reported between AOD and PM2.5 , it is tempting to interpret the spatial patterns in AOD as reflecting patterns in PM2.5 . Here we find only limited spatial associations of AOD from three satellite retrievals with PM2.5 over the eastern U.S. at the daily and yearly levels in 2004. We then use statistical modeling to show that the patterns in monthly average AOD poorly reflect patterns in PM2.5 because of systematic, spatially-correlated error in AOD as a proxy for PM2.5 . Furthermore, when we include AOD as a predictor of monthly PM2.5 in a statistical prediction model, AOD provides little additional information to improve predictions of PM2.5 when included in a model that already accounts for land use, emission sources, meteorology and regional variability. These results suggest caution in using spatial variation in AOD to stand in for spatial variation in ground-level PM2.5 in epidemiological analyses and indicate that when PM2.5 monitoring is available, careful statistical modeling outperforms the use of AOD.

TRENDS IN PARTICULATE MATTER AND MORTALITY: AN APPROACH TO THE ASSESSMENT OF UNMEASURED CONFOUNDING

We propose a method for diagnosing confounding bias under a model which links a spatially and temporally varying exposure and health outcome. We decompose the association into orthogonal components, corresponding to distinct spatial and temporal scales of variation. If the model fully controls for confounding, the exposure effect estimates should be equal at the different temporal and spatial scales. We show that the overall exposure effect estimate is a weighted average of the scale-specific exposure effect estimates. We use this approach to estimate the association between monthly averages of fine particles (PM2.5) over the preceding 12 months and monthly mortality rates in 113 U.S. counties from 2000-2002. We decompose the association between PM2.5 and mortality into two components: 1) the association between “national trends” in PM2.5 and mortality; and 2) the association between “local trends,” defined as county-specificdeviations from national trends. This second component provides evidence as to whether counties having steeper declines in PM2.5 also have steeper declines in mortality relative to their national trends. We find that the exposure effect estimates are different at these two spatio-temporalscales, which raises concerns about confounding bias. We believe that the association between trends in PM2.5 and mortality at the national scale is more likely to be confounded than is the association between trends in PM2.5 and mortality at the local scale. If the association at the national scale is set aside, there is little evidence of an association between 12-month exposure to PM2.5 and mortality.

An analysis of the spatial and temporal patterns of highly pathogenic avian influenza occurrence in Vietnam using national surveillance data

The objectives of this study were to describe the spatio-temporal pattern of an epidemic of highly pathogenic avian influenza (HPAI) in Vietnam and to identify potential risk factors for the introduction and maintenance of infection within the poultry population. The results indicate that during the time period 2004–early 2006 a sequence of three epidemic waves occurred in Vietnam as distinct spatial and temporal clusters. The risk of outbreak occurrence increased with a greater percentage of rice paddy fields, increasing domestic water bird and chicken density. It increased with reducing distance to higher population density aggregations, and in the third epidemic wave with increasing percentage of aquaculture. The findings indicate that agri-livestock farming systems involving domestic water birds and rice production in river delta areas are important for the maintenance and spread of infection. While the government’s control measures appear to have been effective in the South and Central parts of Vietnam, it is likely that in the North of Vietnam the vaccination campaign led to transmission of infection which was subsequently brought under control.

Cortical local and long-range synchronization interplay in human absence seizure initiation

Brain activity relies on transient, fluctuating interactions between segregated neuronal populations. Synchronization within a single and between distributed neuronal clusters reflects the dynamics of these cooperative patterns. Thus absence epilepsy can be used as a model for integrated, large-scale investigation of the emergence of pathological collective dynamics in the brain. Indeed, spike-wave discharges (SWD) of an absence seizure are thought to reflect abnormal cortical hypersynchronization. In this paper, we address two questions: how and where do SWD arise in the human brain? Therefore, we explored the spatio-temporal dynamics of interactions within and between widely distributed cortical sites using magneto-encephalographic recordings of spontaneous absence seizures. We then extracted, from their time-frequency analysis, local synchronization of cortical sources and long-range synchronization linking distant sites. Our analyses revealed a reproducible sequence of 1) long-range desynchronization, 2) increased local synchronization and 3) increased long-range synchronization. Although both local and long-range synchronization displayed different spatio-temporal profiles, their cortical projection within an initiation time window overlap and reveal a multifocal fronto-central network. These observations contradict the classical view of sudden generalized synchronous activities in absence epilepsy. Furthermore, they suggest that brain states transition may rely on multi-scale processes involving both local and distant interactions.

Modeling Calcium Concentration and Biochemical Reactions

Almost all regions of the brain receive one or more neuromodulatory inputs, and disrupting these inputs produces deficits in neuronal function. Neuromodulators act through intracellular second messenger pathways to influence the electrical properties of neurons, integration of synaptic inputs, spatio-temporal firing dynamics of neuronal networks, and, ultimately, systems behavior. Second messengers pathways consist of series of bimolecular reactions, enzymatic reactions, and diffusion. Calcium is the second messenger molecule with the most effectors, and thus is highly regulated by buffers, pumps and intracellular stores. Computational modeling provides an innovative, yet practical method to evaluate the spatial extent, time course and interaction among second messenger pathways, and the interaction of second messengers with neuron electrical properties. These processes occur both in compartments where the number of molecules are large enough to describe reactions deterministically (e.g. cell body), and in compartments where the number of molecules is small enough that reactions occur stochastically (e.g. spines). – In this tutorial, I explain how to develop models of second messenger pathways and calcium dynamics. The first part of the tutorial explains the equations used to model bimolecular reactions, enzyme reactions, calcium release channels, calcium pumps and diffusion. The second part explains some of the GENESIS, Kinetikit and Chemesis objects that implement the appropriate equations. In depth explanation of calcium and second messenger models is provided by reviewing code, both in XPP, Chemesis and Kinetikit, that implements simple models of calcium dynamics and second messenger cascades.

From Broadstone to Zackenberg

Ecological networks are typically complex constructions of species and their interactions. During the last decade, the study of networks has moved from static to dynamic analyses, and has attained a deeper insight into their internal structure, heterogeneity, and temporal and spatial resolution. Here, we review, discuss and suggest research lines in the study of the spatio-temporal heterogeneity of networks and their hierarchical nature. We use case study data from two well-characterized model systems (the food web in Broadstone Stream in England and the pollination network at Zackenberg in Greenland), which are complemented with additional information from other studies. We focus upon eight topics: temporal dynamic space-for-time substitutions linkage constraints habitat borders network modularity individual-based networks invasions of networks and super networks that integrate different network types. Few studies have explicitly examined temporal change in networks, and we present examples that span from daily to decadal change: a common pattern that we see is a stable core surrounded by a group of dynamic, peripheral species, which, in pollinator networks enter the web via preferential linkage to the most generalist species. To some extent, temporal and spatial scales are interchangeable (i.e. networks exhibit ‘ergodicity’) and we explore how space-for-time substitutions can be used in the study of networks. Network structure is commonly constrained by phenological uncoupling (a temporal phenomenon), abundance, body size and population structure. Some potential links are never observed, that is they are ‘forbidden’ (fully constrained) or ‘missing’ (a sampling effect), and their absence can be just as ecologically significant as their presence. Spatial habitat borders can add heterogeneity to network structure, but their importance has rarely been studied: we explore how habitat generalization can be related to other resource dimensions. Many networks are hierarchically structured, with modules forming the basic building blocks, which can result in self-similarity. Scaling down from networks of species reveals another, finer-grained level of individual-based organization, the ecological consequences of which have yet to be fully explored. The few studies of individual-based ecological networks that are available suggest the potential for large intraspecific variance and, in the case of food webs, strong size-structuring. However, such data are still scarce and more studies are required to link individual-level and species-level networks. Invasions by alien species can be tracked by following the topological ‘career’ of the invader as it establishes itself within a network, with potentially important implications for conservation biology. Finally, by scaling up to a higher level of organization, it is possible to combine different network types (e.g. food webs and mutualistic networks) to form super networks, and this new approach has yet to be integrated into mainstream ecological research. We conclude by listing a set of research topics that we see as emerging candidates for ecological network studies in the near future.

A climatology of the diurnal variations of stratospheric and mesospheric ozone over Bern, Switzerland

The ground-based radiometer GROMOS, stationed in Bern (47.95° N, 7.44° E), Switzerland, has a unique dataset: it obtains ozone profiles from November 1994 to present with a time resolution of 30 min and equal quality during night- and daytime. Here, we derive a monthly climatology of the daily ozone cycle from 17 yr of GROMOS observation. We present the diurnal ozone variation of the stratosphere and mesosphere. Characterizing the diurnal cycle of stratospheric ozone is important for correct trend estimates of the ozone layer derived from satellite observations. The diurnal ozone cycle from GROMOS is compared to two models: The Whole Atmosphere Community Climate Model (WACCM) and the Hamburg Model of Neutral and Ionized Atmosphere (HAMMONIA). Aura Microwave Limb Sounder (Aura/MLS) ozone data, from night- and daytime overpasses over Bern, have also been included in the comparison. Generally, observation and models show good qualitative agreement: in the lower mesosphere, daytime ozone is for both GROMOS and models around 25% less than nighttime ozone (reference is 22:30–01:30). In the stratosphere, ozone reaches its maximum in the afternoon showing values several percent larger than the midnight value. It is important that diurnal ozone variations of this order are taken into account when merging different data sets for the derivation of long-term ozone trends in the stratosphere. Further, GROMOS and models indicate a seasonal behavior of daily ozone variations in the stratosphere with a larger afternoon maximum during daytime in summer than in winter. At 0.35 hPa, observations from GROMOS and Aura/MLS show a seasonal pattern in diurnal ozone variations with larger relative amplitudes during daytime in winter (−25 ± 5%) than in summer (−18 ± 4%) (compared to mean values around midnight). For the first time, a time series of the diurnal variations in ozone is presented: 17 yr of GROMOS data show strong interannual variations in the diurnal ozone cycle for both the stratosphere and the mesosphere. There are some indications that strong temperature tides can suppress the diurnal variation of stratospheric ozone via the anticorrelation of temperature and ozone. That means the spatio-temporal variability of solar thermal tides seems to affect the diurnal cycle of stratospheric ozone.

A climatology of the diurnal variations of stratospheric and mesospheric ozone over Bern, Switzerland

The ground-based radiometer GROMOS, stationed in Bern (47.95° N, 7.44° E), Switzerland, has a unique dataset: it obtains ozone profiles from November 1994 to present with a time resolution of 30 min and equal quality during night- and daytime. Here, we derive a monthly climatology of the daily ozone cycle from 17 yr of GROMOS observation. We present the diurnal ozone variation of the stratosphere and mesosphere. Characterizing the diurnal cycle of stratospheric ozone is important for correct trend estimates of the ozone layer derived from satellite observations. The diurnal ozone cycle from GROMOS is compared to two models: The Whole Atmosphere Community Climate Model (WACCM) and the Hamburg Model of Neutral and Ionized Atmosphere (HAMMONIA). Aura Microwave Limb Sounder (Aura/MLS) ozone data, from night- and daytime overpasses over Bern, have also been included in the comparison. Generally, observation and models show good qualitative agreement: in the lower mesosphere, daytime ozone is for both GROMOS and models around 25% less than nighttime ozone (reference is 22:30–01:30). In the stratosphere, ozone reaches its maximum in the afternoon showing values several percent larger than the midnight value. It is important that diurnal ozone variations of this order are taken into account when merging different data sets for the derivation of long-term ozone trends in the stratosphere. Further, GROMOS and models indicate a seasonal behavior of daily ozone variations in the stratosphere with a larger afternoon maximum during daytime in summer than in winter. At 0.35 hPa, observations from GROMOS and Aura/MLS show a seasonal pattern in diurnal ozone variations with larger relative amplitudes during daytime in winter (−25 ± 5%) than in summer (−18 ± 4%) (compared to mean values around midnight). For the first time, a time series of the diurnal variations in ozone is presented: 17 yr of GROMOS data show strong interannual variations in the diurnal ozone cycle for both the stratosphere and the mesosphere. There are some indications that strong temperature tides can suppress the diurnal variation of stratospheric ozone via the anticorrelation of temperature and ozone. That means the spatio-temporal variability of solar thermal tides seems to affect the diurnal cycle of stratospheric ozone.

Matrix models for quantifying competitive intransitivity from species abundance data

In a network of competing species, a competitive intransitivity occurs when the ranking of competitive abilities does not follow a linear hierarchy (A > B > C but C > A). A variety of mathematical models suggests that intransitive networks can prevent or slow down competitive exclusion and maintain biodiversity by enhancing species coexistence. However, it has been difficult to assess empirically the relative importance of intransitive competition because a large number of pairwise species competition experiments are needed to construct a competition matrix that is used to parameterize existing models. Here we introduce a statistical framework for evaluating the contribution of intransitivity to community structure using species abundance matrices that are commonly generated from replicated sampling of species assemblages. We provide metrics and analytical methods for using abundance matrices to estimate species competition and patch transition matrices by using reverse-engineering and a colonization-competition model. These matrices provide complementary metrics to estimate the degree of intransitivity in the competition network of the sampled communities. Benchmark tests reveal that the proposed methods could successfully detect intransitive competition networks, even in the absence of direct measures of pairwise competitive strength. To illustrate the approach, we analyzed patterns of abundance and biomass of five species of necrophagous Diptera and eight species of their hymenopteran parasitoids that co-occur in beech forests in Germany. We found evidence for a strong competitive hierarchy within communities of flies and parasitoids. However, for parasitoids, there was a tendency towards increasing intransitivity in higher weight classes, which represented larger resource patches. These tests provide novel methods for empirically estimating the degree of intransitivity in competitive networks from observational datasets. They can be applied to experimental measures of pairwise species interactions, as well as to spatio-temporal samples of assemblages in homogenous environments or environmental gradients.

A 49 year hindcast of surface winds over the Iberian Peninsula

The use of hindcast climatic data is quite extended for multiple applications. However, this approach needs the support of a validation process to allow its drawbacks and, therefore, confidence levels to be assessed. In this work, the strategy relies on an hourly wind database resulting from a dynamical downscaling experiment, with a spatial resolution of 10 km, covering the Iberian Peninsula (IP), driven by the ERA40 reanalysis (1959–2001) extended by European Centre for Medium-Range Weather Forecast (ECMWF) analysis (2002–2007) and comprising two main steps. Initially, the skill of the simulation is evaluated comparing the quality-tested observational database (Lorente-Plazas et al., 2014) at local and regional scales. The results show that the model is able to portray the main features of the wind over the IP: annual cycles, wind roses, spatial and temporal variability, as well as the response to different circulation types. In addition, there is a significant added value of the simulation with respect to driving conditions, especially in regions with a complex orography. However, some problems are evident, the major drawback being the systematic overestimation of the wind speed, which is mainly attributed to a missrepresentation of frictional forces. The model skill is also lower along the Mediterranean coast and for the Pyrenees. In a second phase, the high spatio-temporal resolution of the pseudo-real wind database is used to explore the limitations of the observational database. It is shown that missing values do not affect the characterisation of the wind climate over the IP, while the length of the observational period (6 years) is sufficient for most regions, with only a few exceptions. The spatial distribution of the observational sampling schemes should be enhanced to improve the correct assessment of all IP wind regimes, particularly in some mountainous areas.

Soil and land information: How to support decision-making?

Soils are fundamental to ensuring water, energy and food security. Within the context of sus- tainable food production, it is important to share knowledge on existing and emerging tech- nologies that support land and soil monitoring. Technologies, such as remote sensing, mobile soil testing, and digital soil mapping, have the potential to identify degraded and non- /little-responsive soils, and may also provide a basis for programmes targeting the protection and rehabilitation of soils. In the absence of such information, crop production assessments are often not based on the spatio-temporal variability in soil characteristics. In addition, uncertain- ties in soil information systems are notable and build up when predictions are used for monitor- ing soil properties or biophysical modelling. Consequently, interpretations of model-based results have to be done cautiously. As such they provide a scientific, but not always manage- able, basis for farmers and/or policymakers. In general, the key incentives for stakeholders to aim for sustainable management of soils and more resilient food systems are complex at farm as well as higher levels. The same is true of drivers of soil degradation. The decision- making process aimed at sustainable soil management, be that at farm or higher level, also in- volves other goals and objectives valued by stakeholders, e.g. land governance, improved envi- ronmental quality, climate change adaptation and mitigation etc. In this dialogue session we will share ideas on recent developments in the discourse on soils, their functions and the role of soil and land information in enhancing food system resilience.