From Statistical Data to Spatial Knowledge - informing decision making in Vietnam

Vietnam has developed rapidly over the past 15 years. However, progress was not uniformly distributed across the country. Availability, adequate visualization and analysis of spatially explicit data on socio-economic and environmental aspects can support both research and policy towards sustainable development. Applying appropriate mapping techniques allows gleaning important information from tabular socio-economic data. Spatial analysis of socio-economic phenomena can yield insights into locally-specifi c patterns and processes that cannot be generated by non-spatial applications. This paper presents techniques and applications that develop and analyze spatially highly disaggregated socioeconomic datasets. A number of examples show how such information can support informed decisionmaking and research in Vietnam.

Spatial isolation and genetic differentiation in naturally fragmented plant populations of the Swiss Alps

Aims The effect Of anthropogenic landscape fragmentation on the genetic diversity and adaptive potential of plant populations is a major issue in conservation biology. However, little is known about the partitioning of genetic diversity in alpine species, which occur in naturally fragmented habitats. Here, we, investigate molecular patterns of three alpine plants (Epilobium fleischeri, Geum reptans and Campanula thyrsoides) across Switzerland and ask whether Spatial isolation has led to high levels of populations differentiation, increasing over distance, and a decrease of within-population variability. We further hypothesize that file contrasting potential for long-distance dispersal (LDD) of Seed in these Species will considerably influence and explain diversity partitioning. Methods For each study species, we Sampled 20-23 individuals from each of 20-32 populations across entire Switzerland. We applied Random Amplified Polymorphic Dimorphism markers to assess genetic diversity within (Nei's expected heterozygosity, H-e; percentage of polymorphic hands, P-P) and among (analysis of molecular variance, Phi(st)) populations and correlated population size and altitude with within-populalion diversity. Spatial patterns of genetic relatedness were investigated using Mantel tests and standardized major axis regression as well as unweighted pair group method with arithmetic mean cluster analyses and Monmonier's algorithm. To avoid known biases, We standardized the numbers of populations, individuals and markers using multiple random reductions. We modelled LDD with a high alpine wind data set using the terminal velocity and height of seed release as key parameters. Additionally, we assessed a number of important life-history traits and factors that potentially influence genetic diversity partitioning (e.g. breeding system, longevity and population size). Important findings For all three species, We found a significant isolation-by-distance relationship but only a moderately high differentiation among populations (Phi(st): 22.7, 48 and 16.8%, for E. fleischeri, G. reptans and C. thyrsoides, respectively). Within-population diversity (H-c: 0.19-0.21, P-p: 62-75%) was not reduced in comparison to known results from lowland species and even small populations with < 50 reproductive individuals contained high levels of genetic diversity. We further found no indication that a high long-distance seed dispersal potential enhances genetic connectivity among populations. Gene flow seems to have a strong stochastic component causing large dissimilarity between population pairs irrespective of the spatial distance. Our results suggest that other life-history traits, especially the breeding System, may play an important role in genetic diversity partitioning. We conclude that spatial isolation in the alpine environment has a strong influence on population relatedness but that a number of factors can considerably influence the strength of this relationship.

Statistical analysis of multichannel scalp field data

High density spatial and temporal sampling of EEG data enhances the quality of results of electrophysiological experiments. Because EEG sources typically produce widespread electric fields (see Chapter 3) and operate at frequencies well below the sampling rate, increasing the number of electrodes and time samples will not necessarily increase the number of observed processes, but mainly increase the accuracy of the representation of these processes. This is namely the case when inverse solutions are computed. As a consequence, increasing the sampling in space and time increases the redundancy of the data (in space, because electrodes are correlated due to volume conduction, and time, because neighboring time points are correlated), while the degrees of freedom of the data change only little. This has to be taken into account when statistical inferences are to be made from the data. However, in many ERP studies, the intrinsic correlation structure of the data has been disregarded. Often, some electrodes or groups of electrodes are a priori selected as the analysis entity and considered as repeated (within subject) measures that are analyzed using standard univariate statistics. The increased spatial resolution obtained with more electrodes is thus poorly represented by the resulting statistics. In addition, the assumptions made (e.g. in terms of what constitutes a repeated measure) are not supported by what we know about the properties of EEG data. From the point of view of physics (see Chapter 3), the natural “atomic” analysis entity of EEG and ERP data is the scalp electric field

Changes in species composition in alpine snowbeds with climate change inferred from small-scale spatial patterns

Alpine snowbeds are characterised by a very short growing season. However, the length of the snow-free period is increasingly prolonged due to climate change, so that snowbeds become susceptible to invasions from neighbouring alpine meadow communities. We hypothesised that spatial distribution of species generated by plant interactions may indicate whether snowbed species will coexist with or will be out-competed by invading alpine species – spatial aggregation or segregation will point to coexistence or competitive exclusion, respectively. We tested this hypothesis in snowbeds of the Swiss Alps using the variance ratio statistics. We focused on the relationships between dominant snowbed species, subordinate snowbed species, and potentially invading alpine grassland species. Subordinate snowbed species were generally spatially aggregated with each other, but were segregated from alpine grassland species. Competition between alpine grassland and subordinate snowbed species may have caused this segregation. Segregation between these species groups increased with earlier snowmelt, suggesting an increasing importance of competition with climate change. Further, a dominant snowbed species (Alchemilla pentaphyllea) was spatially aggregated with subordinate snowbed species, while two other dominants (Gnaphalium supinum and Salix herbacea) showed aggregated patterns with alpine grassland species. These dominant species are known to show distinct microhabitat preferences suggesting the existence of hidden microhabitats with different susceptibility to invaders. These results allow us to suggest that alpine snowbed areas are likely to be reduced as a consequence of climate change and that invading species from nearby alpine grasslands could outcompete subordinate snowbed species. On the other hand, microhabitats dominated by Gnaphalium or Salix seem to be particularly prone to invasions by non-snowbed species.

Spatial variability of recent sedimentation in Lake Ohrid (Albania/Macedonia)

Abstract. Lake Ohrid is likely of Pliocene age and thus commonly referred to as the oldest existing lake in Europe. In this study spatial variability of recent sediment composition is assessed using >50 basin wide distributed surface sediment samples. Analysis of biogeochemical bulk parameters, selected metals, pigment concentrations as well as grain size distributions revealed a significant spatial heterogeneity in surface sediment composition. It implies that sedimentation in Lake Ohrid is controlled by an interaction of multiple natural and anthropogenic factors and processes. Major factors controlling surface sediment composition are related to differences in geological catchment characteristics, anthropogenic land use, and a counterclockwise rotating surface water current. In some instances processes controlling sediment composition also seem to impact distribution patterns of biodiversity, which suggests a common interaction of processes responsible for both patterns.

Analysis of polygonal cracking patterns in chloride-bearing terrains on Mars: Indicators of ancient playa settings

The ancient southern highlands on Mars (~3.5 Gyr old) contain > 600 regions that display spectral evidence in the infrared for the presence of chloride-bearing materials. Many of these locations were previously reported to display polygonal cracking patterns. We studied more than 80 of the chloride-bearing terrains using high-resolution (0.25-0.5 m/pixel) images, as well as near-infrared spectral data, to characterize the surface textures and the associated cracking patterns and mineralogies. Our study indicates that ~75% of the studied locations display polygonal cracks that resemble desiccation cracks, while some resemble salt expansion/thrust polygons. Furthermore, we detect, spectrally, the presence of smectites in association with ~30% of the studied fractured terrains. We note that smectites are a special class of swelling clay minerals that can induce formation of large desiccation cracks. As such, we suggest that the cracking patterns are indicative of the presence of smectite phyllosilicates even in the absence of spectral confirmation. Our results suggest that many chloride-bearing terrains have a lacustrine origin and a geologic setting similar to playas on Earth. Such locations would have contained ephemeral lakes that may have undergone repeated cycles of desiccation and recharging by a near-surface fluctuating water table in order to account for the salt-phyllosilicates associations. These results have notable implications for the ancient hydrology of Mars. We propose that the morphologies and sizes of the polygonal cracks can be used as paleoenvironmental, as well as lithological, indicators that could be helpful in planning future missions.

Landscape mosaics maps as a basis for spatial assessment and negotiation of ecosystem services and their trade-offs at the meso-scale: Examples from Laos, Madagascar and China

Mapping ecosystem services (ES) and their trade-offs is a key requirement for informed decision making for land use planning and management of natural resources that aim to move towards increasing the sustainability of landscapes. The negotiations of the purposes of landscapes and the services they should provide are difficult as there is an increasing number of stakeholders active at different levels with a variety of interests present on one particular landscape.Traditionally, land cover data is at the basis for mapping and spatial monitoring of ecosystem services. In light of complex landscapes it is however questionable whether land cover per se and as a spatial base unit is suitable for monitoring and management at the meso-scale. Often the characteristics of a landscape are defined by prevalence, composition and specific spatial and temporal patterns of different land cover types. The spatial delineation of shifting cultivation agriculture represents a prominent example of a land use system with its different land use intensities that requires alternative methodologies that go beyond the common remote sensing approaches of pixel-based land cover analysis due to the spatial and temporal dynamics of rotating cultivated and fallow fields.Against this background we advocate that adopting a landscape perspective to spatial planning and decision making offers new space for negotiation and collaboration, taking into account the needs of local resource users, and of the global community. For this purpose we introduce landscape mosaicsdefined as new spatial unit describing generalized land use types. Landscape mosaics have allowed us to chart different land use systems and land use intensities and permitted us to delineate changes in these land use systems based on changes of external claims on these landscapes. The underlying idea behindthe landscape mosaics is to use land cover data typically derived from remote sensing data and to analyse and classify spatial patterns of this land cover data using a moving window approach. We developed the landscape mosaics approach in tropical, forest dominated landscapesparticularly shifting cultivation areas and present examples ofour work from northern Laos, eastern Madagascarand Yunnan Province in China.

Quantitative 3D strain analysis in analogue experiments: Integration of X-ray computed tomography and digital volume correlation techniques

The combination of scaled analogue experiments, material mechanics, X-ray computed tomography (XRCT) and Digital Volume Correlation techniques (DVC) is a powerful new tool not only to examine the 3 dimensional structure and kinematic evolution of complex deformation structures in scaled analogue experiments, but also to fully quantify their spatial strain distribution and complete strain history. Digital image correlation (DIC) is an important advance in quantitative physical modelling and helps to understand non-linear deformation processes. Optical non-intrusive (DIC) techniques enable the quantification of localised and distributed deformation in analogue experiments based either on images taken through transparent sidewalls (2D DIC) or on surface views (3D DIC). X-ray computed tomography (XRCT) analysis permits the non-destructive visualisation of the internal structure and kinematic evolution of scaled analogue experiments simulating tectonic evolution of complex geological structures. The combination of XRCT sectional image data of analogue experiments with 2D DIC only allows quantification of 2D displacement and strain components in section direction. This completely omits the potential of CT experiments for full 3D strain analysis of complex, non-cylindrical deformation structures. In this study, we apply digital volume correlation (DVC) techniques on XRCT scan data of “solid” analogue experiments to fully quantify the internal displacement and strain in 3 dimensions over time. Our first results indicate that the application of DVC techniques on XRCT volume data can successfully be used to quantify the 3D spatial and temporal strain patterns inside analogue experiments. We demonstrate the potential of combining DVC techniques and XRCT volume imaging for 3D strain analysis of a contractional experiment simulating the development of a non-cylindrical pop-up structure. Furthermore, we discuss various options for optimisation of granular materials, pattern generation, and data acquisition for increased resolution and accuracy of the strain results. Three-dimensional strain analysis of analogue models is of particular interest for geological and seismic interpretations of complex, non-cylindrical geological structures. The volume strain data enable the analysis of the large-scale and small-scale strain history of geological structures.

A meta-analysis of cambium phenology and growth: linear and non-linear patterns in conifers of the northern hemisphere

Background and Aims Ongoing global warming has been implicated in shifting phenological patterns such as the timing and duration of the growing season across a wide variety of ecosystems. Linear models are routinely used to extrapolate these observed shifts in phenology into the future and to estimate changes in associated ecosystem properties such as net primary productivity. Yet, in nature, linear relationships may be special cases. Biological processes frequently follow more complex, non-linear patterns according to limiting factors that generate shifts and discontinuities, or contain thresholds beyond which responses change abruptly. This study investigates to what extent cambium phenology is associated with xylem growth and differentiation across conifer species of the northern hemisphere. Methods Xylem cell production is compared with the periods of cambial activity and cell differentiation assessed on a weekly time scale on histological sections of cambium and wood tissue collected from the stems of nine species in Canada and Europe over 1–9 years per site from 1998 to 2011. Key Results The dynamics of xylogenesis were surprisingly homogeneous among conifer species, although dispersions from the average were obviously observed. Within the range analysed, the relationships between the phenological timings were linear, with several slopes showing values close to or not statistically different from 1. The relationships between the phenological timings and cell production were distinctly non-linear, and involved an exponential pattern. Conclusions The trees adjust their phenological timings according to linear patterns. Thus, shifts of one phenological phase are associated with synchronous and comparable shifts of the successive phases. However, small increases in the duration of xylogenesis could correspond to a substantial increase in cell production. The findings suggest that the length of the growing season and the resulting amount of growth could respond differently to changes in environmental conditions.