Ecosystem service values and land use change in the opium poppy cultivation region in Northern Part of Lao PDR

Land use change and land-cover impacts ecosystem services and functions. In this paper according to the study area’s land use characteristic and ecosystem type, the Land use category of the study area was divided into seven categories, including Forest, Grassland, Farmland, Water, Wetlands, Urban land and Barren land. The dynamic information of the forest Land use change during 10 years was calculated by the map algebra in ArcGIS 9.2. Both in 1992 and in 2002, Forest and Grassland were two largest Land use category in the study area. Forest took up 44.7% and 39.4% of the total area, and Grassland was 50.13% and 50.72% of the total area in 1992 and 2002. Finally, we valued change in ecosystem services delivered by each land use category using coefficients published by Costanza et al. [5]. Ecosystem services value of study area, the total ecosystem services value of 10.6 million hectares of this study area decreased by 11.74%. From the coefficient of sensitivity (CS) was less than unity in all case, it indicated that the total ecosystem services values was relatively inelastic and the results suggest that we have to pay attention more on land use change and finally, policy for driving forces of land use change were developed.     

A framework for predicting and visualizing the East African wildebeest migration-route patterns in variable climatic conditions using geographic information system and remote sensing

In the Serengeti–Mara ecosystem of East Africa, the migrating wildebeests (Connochaetes taurinus) response to food resource distribution and terrain complexity impacts their movement characteristics. This manifests in varying ways such as movement speed, direction, turning frequency, and moving distance. To investigate these characteristics, indices derived from vegetation quantity (normalized difference vegetation index, NDVI) and relief (slope) were used in our previous work to quantify the relationships between migration route location versus vegetation, relief complexity, and their combination. Least cost pathways determined using these indices were representative of approximate migration routes. The simulated routes were shown to be strongly influenced by vegetation during the dry season. However the impact of climatic change (rainfall) on route location was not investigated though known to influence vegetation recovery patterns. This paper specifically addresses the impact of climatic change on route location. The mean monthly rainfall data were used to classify the rainy and dry seasons in the Serengeti, the Western, and the Mara areas as normal, drier, or wetter than normal, over the 1986–1997 period. The classification is based on the mean monthly rainfall variability about the 11-year seasonal mean. Regression analysis showed strong linear relationships between rainfall and mean NDVI for each one of the three areas. The subsequent seasonal classification based on the corresponding habitat vegetation characteristics (NDVI) revealed the relative variation of vegetation with rainfall. Using the derived general categories, migration routes are then predicted for the various categories using a route attractivity index. The seasonal migration routes were shown to change depending on the relative abundance of the rainfall during the dry season. Dry season migration routes tended toward areas with better vegetation activity, i.e., those characterized by higher NDVI gradients. Our results showed that during the western trek, wetter dry seasons have the effect of delaying the herds movement northwestward. During the northern trek, wetter dry seasons have the effect of delaying the tendency to move westward. However the variation in rainfall conditions during the rainy and dry season had no significant influence on the southern trek route location. We assume that predicted routes based on average general category conditions for different years are representative of main migration route patterns for similar seasons, therefore they are well suited for approximate route prediction, if the climatic characteristics of the year are known.     

Effect of sediment type on microphytobenthos vertical distribution: Modelling the productive biomass and improving ground truth measurements

Intertidal flats are frequently colonised by microphytobenthos (MPB) assemblages that form transient biofilms at the sediment surface which are responsible for large fractions of estuarine primary production. The large spatio-temporal variability in MPB biomass distribution in concert with the fact that tidal flats can cover many km² makes the use of remote sensing particularly useful in assessing MPB distribution. Water content, sediment type and MPB vertical migration are variables that affect the relationship between ground truth measurements and remote sensing of benthic chlorophyll. The effect of chlorophyll depth distribution (top 2 mm) on the relationship between benthic chlorophyll and several remote sensing indices (NDVI, PI, R562/R647, derivative indices and PAM fluorescence) was investigated over a 2 year sampling period at 6 sites (Tagus estuary, Portugal). Additionally, the effect of the dark adaptation time required to measure the minimum fluorescence parameter (F₀) was also tested. Sediment type strongly affected MPB depth distribution with muddy sites showing a strong negative exponential decay in chlorophyll with distance from the surface while sandy sites had a homogenous distribution over the same scale (2 mm). Chlorophyll content (mass per unit mass, μg g^− 1) in the top 2 mm was better correlated with remote sensing indices than concentration (mass per unit volume, mg m^− 3), both for NDVI (0.72 vs. 0.45) and for PAM fluorescence (0.70 vs. 0.55). Separating the data by transect increased the correlation values in all situations. A fitted model of chlorophyll depth distribution showed that the effect of asymmetrical chlorophyll depth distribution was stronger on the correlations between chlorophyll concentration and NDVI than on chlorophyll content and NDVI (0.46-2 mm vs. 0.74-125 μm, muddy site) the same was valid for fluorescence (0.66-2 mm vs. 0.92-125 μm, muddy site). Dark adapting the samples for more than 5 min did not result in any significant difference in the relationship between F₀ and chlorophyll a. The residuals from the regression of chlorophyll content on NDVI were positively correlated (0.7) with the mass per unit of mass of sediment < 63 μm and negatively (− 0.6) with chlorophyll concentration, this indicates that if no correction is performed to account for chlorophyll depth distribution both units will be strongly affected by the mass of < 63 μm particles. The results demonstrate that although expressing chlorophyll a as concentration is generally a better option for ground truth measurements care should be taken to account for chlorophyll depth distribution since strong asymmetries within the sampling depth can introduce large errors.     

Seasonal changes in chlorophyll distributions in Amazon floodplain lakes derived from MODIS images

To assess seasonal changes in phytoplanktonic chlorophyll distributions in Amazon floodplain lakes, a linear mixing model was applied to Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data acquired at four river stages: rising (April), high (June), decreasing (September), and low (November). The study area is located in a floodplain reach from Parintins (Amazonas) to near Almeirim (Pará). A three-end-member mixing model designed to uncouple three fractions [high suspended inorganic matter (ip), low inorganic suspended matter (w), and high chlorophyll a (Chl)] was tested in Lake Curuaí (1.5°S 55.43°W) based on field sampling done almost concurrently with satellite overpasses. During high water, phytoplankton patches are confined to lakes closer to terra firme under the influence of clear water inflow, whereas during the low and decreasing water stages, the patches are more evenly distributed over the floodplain.     

Evidence for Megalake Chad, north-central Africa, during the late Quaternary from satellite data

The existence of a very large Lake Chad during the late Quaternary, Megalake Chad, has long been questioned. A Megalake Chad would present strong evidence for climatic fluctuations of great magnitude during the Holocene in tropical Africa. In this paper we used satellite data from Landsat and Modis sensors to collect and analyse new information on landforms in a 2 000 000 km² region of the Lake Chad Basin. We detected 2300 km of remains marking the ancient shoreline of Megalake Chad. The satellite data also indicated many Saharan rivers and relict deltas leading to the long paleoshoreline. Large dunefield flattenings were observed and interpreted as the result of wave-cut erosion by the paleolake. Similarities were noticed between the landforms observed along the paleoshoreline of Megalake Chad and that of the former Aral Sea. This finding has significant consequences for reconstructing paleohydrology and paleoenvironments through the Lake Chad basin, and continental climate change.     

On the dynamics of dengue epidemics from large-scale information

A model for the spatial and temporal dynamics of dengue fever is proposed in this article. The vector population dynamics is derived from a diffusion equation that is based on environmental parameters at the scale of a remote-sensing image. Vectors and hosts populations are then classically divided into compartments corresponding to their respective disease status. The transmission processes between hosts and vectors are described by a set of differential equations. The link between the vector population diffusion model and the compartmental model enables one to describe both the spatial and temporal dynamics of the disease. Simulations in artificial and actual landscapes show the advantage of using remotely sensed and complementary meteorological data for modelling in a realistic way the geographic spread of a vector-borne disease such as dengue fever.     

Developing a denoising filter for electron microscopy and tomography data in the cloud

The low radiation conditions and the predominantly phase-object image formation of cryo-electron microscopy (cryo-EM) result in extremely high noise levels and low contrast in the recorded micrographs. The process of single particle or tomographic 3D reconstruction does not completely eliminate this noise and is even capable of introducing new sources of noise during alignment or when correcting for instrument parameters. The recently developed Digital Paths Supervised Variance (DPSV) denoising filter uses local variance information to control regional noise in a robust and adaptive manner. The performance of the DPSV filter was evaluated in this review qualitatively and quantitatively using simulated and experimental data from cryo-EM and tomography in two and three dimensions. We also assessed the benefit of filtering experimental reconstructions for visualization purposes and for enhancing the accuracy of feature detection. The DPSV filter eliminates high-frequency noise artifacts (density gaps), which would normally preclude the accurate segmentation of tomography reconstructions or the detection of alpha-helices in single-particle reconstructions. This collaborative software development project was carried out entirely by virtual interactions among the authors using publicly available development and file sharing tools.     

Integrating spatial data and shorebird nesting locations to predict the potential future impact of global warming on coastal habitats: A case study on Farasan Islands,Saudi Arabia

One of the expected effects of the global warming is changing coastal habitats by accelerating the rate of sea level rise. Coastal habitats support large number of marine and wetland species including shorebirds (plovers, sandpipers and allies). In this study, we investigate how coastal habitats may be impacted by sea level rise in the Farasan Islands, Kingdom of Saudi Arabia. We use Kentish plover Charadrius alexandrinus – a common coastal breeding shorebird – as an ecological model species to predict the influence of sea level rise. We found that any rise of sea level is likely to inundate 11% of Kentish plover nests. In addition, 5% of the coastal areas of Farasan Islands, which support 26% of Kentish plover nests, will be flooded, if sea level rises by one metre. Our results are constrained by the availability of data on both elevation and bird populations. Therefore, we recommend follow-up studies to model the impacts of sea level rise using different elevation scenarios, and the establishment of a monitoring programme for breeding shorebirds and seabirds in Farasan Islands to assess the impact of climate change on their populations.     

The potential of the satellite derived green chlorophyll index for estimating midday light use efficiency in maize, coniferous forest and grassland

Light use efficiency (LUE) is an important variable in carbon cycle and climate change research. We present an investigation of remotely estimating midday LUE using the green chlorophyll index (CI_green) derived from the cloud-free Moderate Resolution Imaging Spectroradiometer (MODIS) images in maize, coniferous forest and grassland. Similar temporal patterns are observed in both canopy chlorophyll content and midday LUE which indicates that the chlorophyll content in the maize canopy servers as a proxy of midday LUE (R² = 0.736, p < 0.001). Therefore, the CI_green, tested as a good indicator of canopy chlorophyll content (R² = 0.840, p < 0.001), has been demonstrated to be a reliable candidate in providing reasonable estimates of midday LUE with determination coefficient R² equals to 0.820 and a root mean square error (RMSE) of 0.002 mol CO₂ per mol incident photosynthetic photon flux density (PPFD). Further validation of the prediction model derived from the maize site demonstrates that the CI_green has potential to be applied in the coniferous forest and grassland ecosystems with RMSE of 0.005 and 0.004 mol CO₂ mol⁻¹ PPFD, respectively. A comparison analysis between different vegetation types is included and these results could be helpful in the development of future LUE and terrestrial models.     

Remote monitoring and follow-up of cardiovascular implantable electronic devices in the Netherlands : An expert consensus report of the Netherlands Society of Cardiology

Remote monitoring of cardiac implanted electronic devices (CIED: pacemaker, cardiac resynchronisation therapy device and implantable cardioverter defibrillator) has been developed for technical control and follow-up using transtelephonic data transmission. In addition, automatic or patient-triggered alerts are sent to the cardiologist or allied professional who can respond if necessary with various interventions. The advantage of remote monitoring appears obvious in impending CIED failures and suspected symptoms but is less likely in routine follow-up of CIED. For this follow-up the indications, quality of care, cost-effectiveneness and patient satisfaction have to be determined before remote CIED monitoring can be applied in daily practice. Nevertheless remote CIED monitoring is expanding rapidly in the Netherlands without professional agreements about methodology, responsibilities of all the parties involved and that of the device patient, and reimbursement. The purpose of this consensus document on remote CIED monitoring and follow-up is to lay the base for a nationwide, uniform implementation in the Netherlands. This report describes the technical communication, current indications, benefits and limitations of remote CIED monitoring and follow-up, the role of the patient and device manufacturer, and costs and reimbursement. The view of cardiology experts and of other disciplines in conjunction with literature was incorporated in a preliminary series of recommendations. In addition, an overview of the questions related to remote CIED monitoring that need to be answered is given. This consensus document can be used for future guidelines for the Dutch profession.