Contextualizing local-scale point sample data using global-scale spatial datasets: Lessons learnt from the analysis of large-scale land acquisitions

This paper examines how the geospatial accuracy of samples and sample size influence conclusions from geospatial analyses. It does so using the example of a study investigating the global phenomenon of large-scale land acquisitions and the socio-ecological characteristics of the areas they target. First, we analysed land deal datasets of varying geospatial accuracy and varying sizes and compared the results in terms of land cover, population density, and two indicators for agricultural potential: yield gap and availability of uncultivated land that is suitable for rainfed agriculture. We found that an increase in geospatial accuracy led to a substantial and greater change in conclusions about the land cover types targeted than an increase in sample size, suggesting that using a sample of higher geospatial accuracy does more to improve results than using a larger sample. The same finding emerged for population density, yield gap, and the availability of uncultivated land suitable for rainfed agriculture. Furthermore, the statistical median proved to be more consistent than the mean when comparing the descriptive statistics for datasets of different geospatial accuracy. Second, we analysed effects of geospatial accuracy on estimations regarding the potential for advancing agricultural development in target contexts. Our results show that the target contexts of the majority of land deals in our sample whose geolocation is known with a high level of accuracy contain smaller amounts of suitable, but uncultivated land than regional- and national-scale averages suggest. Consequently, the more target contexts vary within a country, the more detailed the spatial scale of analysis has to be in order to draw meaningful conclusions about the phenomena under investigation. We therefore advise against using national-scale statistics to approximate or characterize phenomena that have a local-scale impact, particularly if key indicators vary widely within a country.

Phenology for tropoclimatological surveys and large-scale mapping

Biotic and abiotic phenological observations can be collected from continental to local spatial scale. Plant phenological observations may only be recorded wherever there is vegetation. Fog, snow and ice are available as phenological para-meters wherever they appear. The singularity of phenological observations is the possibility of spatial intensification to a microclimatic scale where the equipment of meteorological measurements is too expensive for intensive campaigning. The omnipresence of region-specific phenological parameters allows monitoring for a spatially much more detailed assessment of climate change than with weather data. We demonstrate this concept with phenological observations with the use of a special network in the Canton of Berne, Switzerland, with up to 600 observations sites (more than 1 to 10 km² of the inhabited area). Classic cartography, gridding, the integration into a Geographic Information System GIS and large-scale analysis are the steps to a detailed knowledge of topoclimatic conditions of a mountainous area. Examples of urban phenology provide other types of spatially detailed applications. Large potential in phenological mapping in future analyses lies in combining traditionally observed species-specific phenology with remotely sensed and modelled phenology that provide strong spatial information. This is a long history from cartographic intuition to algorithm-based representations of phenology.

The geography of large-scale land acquisitions: Analysing socio-ecological patterns of target contexts in the global South

This paper analyses local geographical contexts targeted by transnational large-scale land acquisitions (>200 ha per deal) in order to understand how emerging patterns of socio-ecological characteristics can be related to processes of large-scale foreign investment in land. Using a sample of 139 land deals georeferenced with high spatial accuracy, we first analyse their target contexts in terms of land cover, population density, accessibility, and indicators for agricultural potential. Three distinct patterns emerge from the analysis: densely populated and easily accessible croplands (35% of land deals); remote forestlands with lower population densities (34% of land deals); and moderately populated and moderately accessible shrub- or grasslands (26% of land deals). These patterns are consistent with processes described in the relevant case study literature, and they each involve distinct types of stakeholders and associated competition over land. We then repeat the often-cited analysis that postulates a link between land investments and target countries with abundant so-called “idle” or “marginal” lands as measured by yield gap and available suitable but uncultivated land; our methods differ from the earlier approach, however, in that we examine local context (10-km radius) rather than countries as a whole. The results show that earlier findings are disputable in terms of concepts, methods, and contents. Further, we reflect on methodologies for exploring linkages between socioecological patterns and land investment processes. Improving and enhancing large datasets of georeferenced land deals is an important next step; at the same time, careful choice of the spatial scale of analysis is crucial for ensuring compatibility between the spatial accuracy of land deal locations and the resolution of available geospatial data layers. Finally, we argue that new approaches and methods must be developed to empirically link socio-ecological patterns in target contexts to key determinants of land investment processes. This would help to improve the validity and the reach of our findings as an input for evidence-informed policy debates.

Holocene land-cover reconstructions for studies on land cover-climate feedbacks

The major objectives of this paper are: (1) to review the pros and cons of the scenarios of past anthropogenic land cover change (ALCC) developed during the last ten years, (2) to discuss issues related to pollen-based reconstruction of the past land-cover and introduce a new method, REVEALS (Regional Estimates of VEgetation Abundance from Large Sites), to infer long-term records of past land-cover from pollen data, (3) to present a new project (LANDCLIM: LAND cover – CLIMate interactions in NW Europe during the Holocene) currently underway, and show preliminary results of REVEALS reconstructions of the regional land-cover in the Czech Republic for five selected time windows of the Holocene, and (4) to discuss the implications and future directions in climate and vegetation/land-cover modeling, and in the assessment of the effects of human-induced changes in land-cover on the regional climate through altered feedbacks. The existing ALCC scenarios show large discrepancies between them, and few cover time periods older than AD 800. When these scenarios are used to assess the impact of human land-use on climate, contrasting results are obtained. It emphasizes the need for methods such as the REVEALS model-based land-cover reconstructions. They might help to fine-tune descriptions of past land-cover and lead to a better understanding of how long-term changes in ALCC might have influenced climate. The REVEALS model is demonstrated to provide better estimates of the regional vegetation/land-cover changes than the traditional use of pollen percentages. This will achieve a robust assessment of land cover at regional- to continental-spatial scale throughout the Holocene. We present maps of REVEALS estimates for the percentage cover of 10 plant functional types (PFTs) at 200 BP and 6000 BP, and of the two open-land PFTs "grassland" and "agricultural land" at five time-windows from 6000 BP to recent time. The LANDCLIM results are expected to provide crucial data to reassess ALCC estimates for a better understanding of the land suface-atmosphere interactions.

Repeated and predictable patterns of ecotypic differentiation during a biological invasion: lake-stream divergence in parapatric Swiss stickleback

The relative importance of ecological selection and geographical isolation in promoting and constraining genetic and phenotypic differentiation among populations is not always obvious. Interacting with divergent selection, restricted opportunity for gene flow may in some cases be as much a cause as a consequence of adaptation, with the latter being a hallmark of ecologi- cal speciation. Ecological speciation is well studied in parts of the native range of the three-spined stickleback. Here, we study this process in a recently invaded part of its range. Switzerland was colonized within the past 140 years from at least three different colonization events involving differ- ent stickleback lineages. They now occupy diverse habitats, ranging from small streams to the pelagic zone of large lakes. We use replicated systems of parapatric lake and stream populations, some of which trace their origins to different invasive lineages, to ask (i) whether phenotypic divergence occurred among populations inhabiting distinct habitats, (ii) whether trajec- tories of phenotypic divergence follow predictable parallel patterns and (iii) whether gene flow constrains divergent adaptation or vice versa. We find consistent phenotypic divergence between populations occupying distinct habitats. This involves parallel evolution in several traits with known eco- logical relevance in independent evolutionary lineages. Adaptive divergence supersedes homogenizing gene flow even at a small spatial scale. We find evidence that adaptive phenotypic divergence places constraints on gene flow over and above that imposed by geographical distance, signalling the early onset of ecological speciation.

Past forest composition, structures and processes – How paleoecology can contribute to forest conservation

The importance of long-term historical information derived from paleoecological studies has long been recognized as a fundamental aspect of effective conservation. However, there remains some uncertainty regarding the extent to which paleoecology can inform on specific issues of high conservation priority, at the scale for which conservation policy decisions often take place. Here we review to what extent the past occurrence of three fundamental aspects of forest conservation can be assessed using paleoecological data, with a focus on northern Europe. These aspects are (1) tree species composition, (2) old/large trees and coarse woody debris, and (3) natural disturbances. We begin by evaluating the types of relevant historical information available from contemporary forests, then evaluate common paleoecological techniques, namely dendrochronology, pollen, macrofossil, charcoal, and fossil insect and wood analyses. We conclude that whereas contemporary forests can be used to estimate historical, natural occurrences of several of the aspects addressed here (e.g. old/large trees), paleoecological techniques are capable of providing much greater temporal depth, as well as robust quantitative data for tree species composition and fire disturbance, qualitative insights regarding old/large trees and woody debris, but limited indications of past windstorms and insect outbreaks. We also find that studies of fossil wood and paleoentomology are perhaps the most underutilized sources of information. Not only can paleoentomology provide species specific information, but it also enables the reconstruction of former environmental conditions otherwise unavailable. Despite the potential, the majority of conservation-relevant paleoecological studies primarily focus on describing historical forest conditions in broad terms and for large spatial scales, addressing former climate, land-use, and landscape developments, often in the absence of a specific conservation context. In contrast, relatively few studies address the most pressing conservation issues in northern Europe, often requiring data on the presence or quantities of dead wood, large trees or specific tree species, at the scale of the stand or reserve. Furthermore, even fewer examples exist of detailed paleoecological data being used for conservation planning, or the setting of operative restorative baseline conditions at local scales. If ecologist and conservation biologists are going to benefit to the full extent possible from the ever-advancing techniques developed by the paleoecological sciences, further integration of these disciplines is desirable.

Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP)

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.

Pits formation from volatile outgassing on 67P/Churyumov-Gerasimenko

We investigate the thermal evolution of comet 67P/Churyumov-Gerasimenko's subsurface in the Seth_01 region, where active pits have been observed by the ESA/Rosetta mission. Our simulations show that clathrate destabilization and amorphous ice crystallization can occur at depths corresponding to those of the observed pits in a timescale shorter than 67P/Churyumov-Gerasimenko's lifetime in the comet's activity zone in the inner solar system. Sublimation of crystalline ice down to such depths is possible only in the absence of a dust mantle, which requires the presence of dust grains in the matrix small enough to be dragged out by gas from the pores. Our results are consistent with both pits formation via sinkholes or subsequent to outbursts, the dominant process depending on the status of the subsurface porosity. A sealed dust mantle would favor episodic and disruptive outgassing as a result of increasing gas pressure in the pores, while high porosity should allow the formation of large voids in the subsurface due to the continuous escape of volatiles. We finally conclude that the subsurface of 67P/Churyumov-Gerasimenko is not uniform at a spatial scale of similar to 100-200 m.

On seeing the trees and the forest: Single-signal and multisignal analysis of periictal intracranial EEG

Epileptic seizures are associated with a dysregulation of electrical brain activity on many different spatial scales. To better understand the dynamics of epileptic seizures, that is, how the seizures initiate, propagate, and terminate, it is important to consider changes of electrical brain activity on different spatial scales. Herein we set out to analyze periictal electrical brain activity on comparatively small and large spatial scales by assessing changes in single intracranial electroencephalography (EEG) signals and of averaged interdependences of pairs of EEG signals.

Comparison of climate field reconstruction techniques: Application to Europe

This paper presents a comparison of principal component (PC) regression and regularized expectation maximization (RegEM) to reconstruct European summer and winter surface air temperature over the past millennium. Reconstruction is performed within a surrogate climate using the National Center for Atmospheric Research (NCAR) Climate System Model (CSM) 1.4 and the climate model ECHO-G 4, assuming different white and red noise scenarios to define the distortion of pseudoproxy series. We show how sensitivity tests lead to valuable “a priori” information that provides a basis for improving real world proxy reconstructions. Our results emphasize the need to carefully test and evaluate reconstruction techniques with respect to the temporal resolution and the spatial scale they are applied to. Furthermore, we demonstrate that uncertainties inherent to the predictand and predictor data have to be more rigorously taken into account. The comparison of the two statistical techniques, in the specific experimental setting presented here, indicates that more skilful results are achieved with RegEM as low frequency variability is better preserved. We further detect seasonal differences in reconstruction skill for the continental scale, as e.g. the target temperature average is more adequately reconstructed for summer than for winter. For the specific predictor network given in this paper, both techniques underestimate the target temperature variations to an increasing extent as more noise is added to the signal, albeit RegEM less than with PC regression. We conclude that climate field reconstruction techniques can be improved and need to be further optimized in future applications.

Finding Homogeneity in Heterogeneity - A New Approach to Quantifying Landscape Mosaics Developed for the Lao PDR

A key challenge for land change science in general and research on swidden agriculture in particular, is linking land cover information to human–environment interactions over larger spatial areas. In Lao PDR, a country facing rapid and multi-level land change processes, this hinders informed policy- and decision-making. Crucial information on land use types and people involved is still lacking. This article proposes an alternative approach for the description of landscape mosaics. Instead of analyzing local land use combinations, we studied land cover mosaics at a meso-level of spatial scale and interpreted these in terms of human–environmental interactions. These landscape mosaics were then overlaid with population census data. Results showed that swidden agricultural landscapes, involving 17% of the population, dominate 29% of the country, while permanent agricultural landscapes involve 74% of the population in 29% of the territory. Forests still form an important component of these landscape mosaics.