Thermokarst is a land surface lowered and disrupted by melting ground ice. Thermokarst is a major driver of landscape change in the Arctic, but has been considered to be a minor process in Antarctica. Here, we use ground-based and airborne LiDAR coupled with timelapse imaging and meteorological data to show that 1) thermokarst formation has accelerated in Garwood Valley, Antarctica; 2) the rate of thermokarst erosion is presently ~ 10 times the average Holocene rate; and 3) the increased rate of thermokarst formation is driven most strongly by increasing insolation and sediment/albedo feedbacks. This suggests that sediment enhancement of insolation-driven melting may act similarly to expected increases in Antarctic air temperature (presently occurring along the Antarctic Peninsula), and may serve as a leading indicator of imminent landscape change in Antarctica that will generate thermokarst landforms similar to those in Arctic periglacial terrains.
Concentrations of particulate emissions from a quarry located in hilly terrain were calculated by two common atmospheric dispersion models, AERMOD and CALPUFF. Evaluation of these models for emissions from quarries/open pit mines that are located in complex topography is missing from the literature. Due to severe uncertainties in the input parameters, numerous scenarios were simulated and model sensitivity was studied. Model results were compared among themselves, and to measured total suspended particulate (TSP). For a wide range of meteorological and topographical conditions studied, AERMOD predictions were in a better agreement with the measurements than those obtained by CALPUFF. The use of AERMOD’s “Open pit” tool seems unnecessary when accurate digital topographic data are available. Onsite meteorological data are shown to be crucial for reliable dispersion calculations in complex terrain.
Pluto’s surface is surprisingly young and geologically active. One of its youngest terrains is the near-equatorial region informally named Sputnik Planum, which is a topographic basin filled by nitrogen (N2) ice mixed with minor amounts of CH4 and CO ices. Nearly the entire surface of the region is divided into irregular polygons about 20-30 kilometres in diameter, whose centres rise tens of metres above their sides. The edges of this region exhibit bulk flow features without polygons. Both thermal contraction and convection have been proposed to explain this terrain, but polygons formed from thermal contraction (analogous to ice-wedges or mud-crack networks) of N2 are inconsistent with the observations on Pluto of non-brittle deformation within the N2-ice sheet. Here we report a parameterized convection model to compute the Rayleigh number of the N2 ice and show that it is vigorously convecting, making Rayleigh-Bénard convection the most likely explanation for these polygons. The diameter of Sputnik Planum’s polygons and the dimensions of the ‘floating mountains’ (the hills of of water ice along the edges of the polygons) suggest that its N2 ice is about ten kilometres thick. The estimated convection velocity of 1.5 centimetres a year indicates a surface age of only around a million years.
In this communication we introduce marmap, a package designed for downloading, plotting and manipulating bathymetric and topographic data in R. marmap can query the ETOPO1 bathymetry and topography database hosted by the NOAA, use simple latitude-longitude-depth data in ascii format, and take advantage of the advanced plotting tools available in R to build publication-quality bathymetric maps. Functions to query data (bathymetry, sampling information…) are available interactively by clicking on marmap maps. Bathymetric and topographic data can also be used to calculate projected surface areas within specified depth/altitude intervals, and constrain the calculation of realistic shortest path distances. Such information can be used in molecular ecology, for example, to evaluate genetic isolation by distance in a spatially-explicit framework.
Sinking particulate organic matter (POM, phytodetritus) is the principal limiting resource for deep-sea life. However, little is known about spatial variation in POM supply to the abyssal seafloor, which is frequently assumed to be homogenous. In reality, the abyss has a highly complex landscape with millions of hills and mountains. Here, we show a significant increase in seabed POM % cover (by ~1.05 times), and a large significant increase in megafauna biomass (by ~2.5 times), on abyssal hill terrain in comparison to the surrounding plain. These differences are substantially greater than predicted by current models linking water depth to POM supply or benthic biomass. Our observed variations in POM % cover (phytodetritus), megafauna biomass, sediment total organic carbon and total nitrogen, sedimentology, and benthic boundary layer turbidity, all appear to be consistent with topographically enhanced current speeds driving these enhancements. The effects are detectable with bathymetric elevations of only 10 s of metres above the surrounding plain. These results imply considerable unquantified heterogeneity in global ecology.
Land use impacts are commonly quantified and compared using 2D maps, limiting the scale of their reported impacts to surface area estimates. Yet, nearly all land use involves disturbances below the land surface. Incorporating this third dimension into our estimates of land use impact is especially important when examining the impacts of mining. Mountaintop mining is the most common form of coal mining in the Central Appalachian ecoregion. Previous estimates suggest that active, reclaimed or abandoned mountaintop mines cover ~7% of Central Appalachia. While this is double the areal extent of development in the ecoregion (estimated to occupy <3% of the land area), the impacts are far more extensive than areal estimates alone can convey as the impacts of mines extend 10s to 100s of meters below the current land surface. Here, we provide the first estimates for the total volumetric and topographic disturbance associated with mining in a 11,500 km2 region of southern West Virginia. We find that the cutting of ridges and filling of valleys has lowered the median slope of mined landscapes in the region by nearly 10 degrees while increasing their average elevation by 3m as a result of expansive valley filling. We estimate that in southern West Virginia, more than 6.4km3 of bedrock has been broken apart and deposited into 1,544 headwater valley fills. We used NPDES monitoring datatsets available for 91 of these valley fills to explore whether fill characteristics could explain variation in the pH or selenium concentrations reported for streams draining these fills. We found that the volume of overburden in individual valley fills correlates with stream pH and selenium concentration, and suggest that a three-dimensional assessment of MTMVF impacts is necessary to predict both the severity and the longevity of the resulting environmental impacts.
Modelling approaches have the potential to significantly contribute to the spatial management of the deep-sea ecosystem in a cost effective manner. However, we currently have little understanding of the accuracy of such models, developed using limited data, of varying resolution. The aim of this study was to investigate the performance of predictive models constructed using non-simulated (real world) data of different resolution. Predicted distribution maps for three deep-sea habitats were constructed using MaxEnt modelling methods using high resolution multibeam bathymetric data and associated terrain derived variables as predictors. Model performance was evaluated using repeated 75/25 training/test data partitions using AUC and threshold-dependent assessment methods. The overall extent and distribution of each habitat, and the percentage contained within an existing MPA network were quantified and compared to results from low resolution GEBCO models. Predicted spatial extent for scleractinian coral reef and Syringammina fragilissima aggregations decreased with an increase in model resolution, whereas Pheronema carpenteri total suitable area increased. Distinct differences in predicted habitat distribution were observed for all three habitats. Estimates of habitat extent contained within the MPA network all increased when modelled at fine scale. High resolution models performed better than low resolution models according to threshold-dependent evaluation. We recommend the use of high resolution multibeam bathymetry data over low resolution bathymetry data for use in modelling approaches. We do not recommend the use of predictive models to produce absolute values of habitat extent, but likely areas of suitable habitat. Assessments of MPA network effectiveness based on calculations of percentage area protection (policy driven conservation targets) from low resolution models are likely to be fit for purpose.
Topographic variation underpins a myriad of patterns and processes in hydrology, climatology, geography and ecology and is key to understanding the variation of life on the planet. A fully standardized and global multivariate product of different terrain features has the potential to support many large-scale research applications, however to date, such datasets are unavailable. Here we used the digital elevation model products of global 250 m GMTED2010 and near-global 90 m SRTM4.1dev to derive a suite of topographic variables: elevation, slope, aspect, eastness, northness, roughness, terrain roughness index, topographic position index, vector ruggedness measure, profile/tangential curvature, first/second order partial derivative, and 10 geomorphological landform classes. We aggregated each variable to 1, 5, 10, 50 and 100 km spatial grains using several aggregation approaches. While a cross-correlation underlines the high similarity of many variables, a more detailed view in four mountain regions reveals local differences, as well as scale variations in the aggregated variables at different spatial grains. All newly-developed variables are available for download at Data Citation 1 and for download and visualization at http://www.earthenv.org/topography.
Recent studies have proposed that the bathymetric fabric of the seafloor formed at mid-ocean ridges records rapid (23,000 to 100,000 years) fluctuations in ridge magma supply caused by sealevel changes that modulate melt production in the underlying mantle. Using quantitative models of faulting and magma emplacement, we demonstrate that, in fact, seafloor-shaping processes act as a low-pass filter on variations in magma supply, strongly damping fluctuations shorter than about 100,000 years. We show that the systematic decrease in dominant seafloor wavelengths with increasing spreading rate is best explained by a model of fault growth and abandonment under a steady magma input. This provides a robust framework for deciphering the footprint of mantle melting in the fabric of abyssal hills, the most common topographic feature on Earth.
The Anthropocene is a geological epoch marked by major human influences on processes in the atmosphere, biosphere, hydrosphere and geosphere. One of the most dramatic features of the Anthropocene is the massive alteration of the Earth’s vegetation, including forests. Here we investigate the role of topography in shaping human impacts on tree cover from local to global scales. We show that human impacts have resulted in a global tendency for tree cover to be constrained to sloped terrain and losses to be concentrated on flat terrain. This effect increases in strength with increasing human pressure and is most pronounced in countries with rapidly growing economies, limited human population stress and highly effective governments. These patterns likely reflect the relative inaccessibility of sloped topography and have important implications for conservation and modelling of future tree cover.