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Rapid local adaptation frequently occurs during the spread of invading species. It remains unclear, however, how consistent, and therefore potentially predictable, such patterns of local adaptation are. One approach to this question is to measure patterns of local differentiation in functional traits and plasticity levels in invasive species in multiple regions. Finding consistent patterns of local differentiation in replicate regions suggests that these patterns are adaptive. Further, this outcome indicates that the invading species likely responds predictably to selection along environmental gradients, even though standing genetic variation is likely to have been reduced during introduction. We studied local differentiation in the invasive annual plant Erodium cicutarium in two invaded regions, California and Chile. We collected seeds from across strong gradients in precipitation and temperature in Mediterranean-climate parts of the two regions (10 populations per region). We grew seeds from maternal families from these populations through two generations and exposed the second generation to contrasting levels of water and nutrient availability. We measured growth, flowering time and leaf functional traits across these treatments to obtain trait means and plasticity measures. We found strong differentiation among populations in all traits. Plants from drier environments flowered earlier, were less plastic in flowering time and reached greater size in all treatments. Correlations among traits within regions suggested a coordinated evolutionary response along environmental gradients associated with growing season length. There was little divergence in traits and trait intercorrelations between regions, but strongly parallel divergence in traits within regions. Similar, statistically consistent patterns of local trait differentiation across two regions suggest that local adaptation to environmental gradients has aided the spread of this invasive species, and that the formation of ecotypes in newly invaded environments has been relatively consistent and predictable.
The propagation of a seismic rupture on a fault introduces spatial variations in the seismic wave field surrounding the fault. This directivity effect results in larger shaking amplitudes in the rupture propagation direction. Its seismic radiation pattern also causes amplitude variations between the strike-normal and strike-parallel components of horizontal ground motion. We investigated the landslide response to these effects during the 2016 Kumamoto earthquake (M-w 7.1) in central Kyushu (Japan). Although the distribution of some 1500 earthquake-triggered landslides as a function of rupture distance is consistent with the observed Arias intensity, the landslides were more concentrated to the northeast of the southwest-northeast striking rupture. We examined several landslide susceptibility factors: hillslope inclination, the median amplification factor (MAF) of ground shaking, lithology, land cover, and topographic wetness. None of these factors sufficiently explains the landslide distribution or orientation (aspect), although the landslide head scarps have an elevated hillslope inclination and MAF. We propose a new physics-based ground-motion model (GMM) that accounts for the seismic rupture effects, and we demonstrate that the low-frequency seismic radiation pattern is consistent with the overall landslide distribution. Its spatial pattern is influenced by the rupture directivity effect, whereas landslide aspect is influenced by amplitude variations between the fault-normal and fault-parallel motion at frequencies < 2 Hz. This azimuth dependence implies that comparable landslide concentrations can occur at different distances from the rupture. This quantitative link between the prevalent landslide aspect and the low-frequency seismic radiation pattern can improve coseismic landslide hazard assessment.
We show that near-real-time seismic monitoring of fluid injection allowed control of induced earthquakes during the stimulation of a 6.1-km-deep geothermal well near Helsinki, Finland. A total of 18,160 m(3) of fresh water was pumped into crystalline rocks over 49 days in June to July 2018. Seismic monitoring was performed with a 24-station borehole seismometer network. Using near-real-time information on induced-earthquake rates, locations, magnitudes, and evolution of seismic and hydraulic energy, pumping was either stopped or varied-in the latter case, between well-head pressures of 60 and 90 MPa and flow rates of 400 and 800 liters/min. This procedure avoided the nucleation of a project-stopping magnitude M-W 2.0 induced earthquake, a limit set by local authorities. Our results suggest a possible physics-based approach to controlling stimulation-induced seismicity in geothermal projects.
The novel space-borne Global Navigation Satellite System Reflectometry (GNSS-R) technique has recently shown promise in monitoring the ocean state and surface wind speed with high spatial coverage and unprecedented sampling rate. The L-band signals of GNSS are structurally able to provide a higher quality of observations from areas covered by dense clouds and under intense precipitation, compared to those signals at higher frequencies from conventional ocean scatterometers. As a result, studying the inner core of cyclones and improvement of severe weather forecasting and cyclone tracking have turned into the main objectives of GNSS-R satellite missions such as Cyclone Global Navigation Satellite System (CYGNSS). Nevertheless, the rain attenuation impact on GNSS-R wind speed products is not yet well documented. Evaluating the rain attenuation effects on this technique is significant since a small change in the GNSS-R can potentially cause a considerable bias in the resultant wind products at intense wind speeds. Based on both empirical evidence and theory, wind speed is inversely proportional to derived bistatic radar cross section with a natural logarithmic relation, which introduces high condition numbers (similar to ill-posed conditions) at the inversions to high wind speeds. This paper presents an evaluation of the rain signal attenuation impact on the bistatic radar cross section and the derived wind speed. This study is conducted simulating GNSS-R delay-Doppler maps at different rain rates and reflection geometries, considering that an empirical data analysis at extreme wind intensities and rain rates is impossible due to the insufficient number of observations from these severe conditions. Finally, the study demonstrates that at a wind speed of 30 m/s and incidence angle of 30 degrees, rain at rates of 10, 15, and 20 mm/h might cause overestimation as large as approximate to 0.65 m/s (2%), 1.00 m/s (3%), and 1.3 m/s (4%), respectively, which are still smaller than the CYGNSS required uncertainty threshold. The simulations are conducted in a pessimistic condition (severe continuous rainfall below the freezing height and over the entire glistening zone) and the bias is expected to be smaller in size in real environments.
During eruptive activity of andesitic stratovolcanoes, the extrusion of lava domes, their collapse and intermittent explosions are common volcanic hazards. Many lava domes grow in a preferred direction, in turn affecting the direction of lava flows and pyroclastic density currents. Access to active lava domes is difficult and hazardous, so detailed data characterizing lava dome growth are typically limited, keeping the processes controlling the directionality of extrusions unclear. Here we combine TerraSAR-X satellite radar observations with high-resolution airborne photogrammetry to assess morphological changes, and perform finite element modeling to investigate the impact of loading stress on shallow magma ascent directions associated with lava dome extrusion and crater formation at Volcan de Colima, Mexico. The TerraSAR-X data, acquired in similar to 1-m resolution spotlight mode, enable us to derive a chronology of the eruptive processes from intensity-based time-lapse observations of the general crater and dome evolution. The satellite images are complemented by close-range airborne photos, processed by the Structure-from-Motion workflow. This allows the derivation of high-resolution digital elevation models, providing insight into detailed loading and unloading features. During the observation period from Jan-2013 to Feb-2016, we identify a dominantly W-directed dome growth and lava flow production until Jan-2015. In Feb-2015, following the removal of the active summit dome, the surface crater widened and elongated along a NE-SW axis. Later in May-2015, a new dome grew toward the SW of the crater while a separate vent developed in the NE of the crater, reflecting a change in the direction of magma ascent and possible conduit bifurcation. Finite element models show a significant stress change in agreement with the observed magma ascent direction changes in response to the changing surface loads, both for loading (dome growth) and unloading (crater forming excavation) cases. These results allow insight into shallow dome growth dynamics and the migration of magma ascent in response to changing volcano summit morphology. They further highlight the importance of detailed volcano summit morphology surveillance, as changes in direction or location of dome extrusion may have major implications regarding the directions of potential volcanic hazards, such as pyroclastic density currents generated by dome collapse.
Sediment Transit Time and Floodplain Storage Dynamics in Alluvial Rivers Revealed by Meteoric 10Be
(2020)
Quantifying the time scales of sediment transport and storage through river systems is fundamental for understanding weathering processes, biogeochemical cycling, and improving watershed management, but measuring sediment transit time is challenging. Here we provide the first systematic test of measuring cosmogenic meteoric Beryllium-10 (10Bem) in the sediment load of a large alluvial river to quantify sediment transit times. We take advantage of a natural experiment in the Rio Bermejo, a lowland alluvial river traversing the east Andean foreland basin in northern Argentina. This river has no tributaries along its trunk channel for nearly 1,300 km downstream from the mountain front. We sampled suspended sediment depth profiles along the channel and measured the concentrations of 10Bem in the chemically extracted grain coatings. We calculated depth-integrated 10Bem concentrations using sediment flux data and found that 10Bem concentrations increase 230% from upstream to downstream, indicating a mean total sediment transit time of 8.4 ± 2.2 kyr. Bulk sediment budget-based estimates of channel belt and fan storage times suggest that the 10Bem tracer records mixing of old and young sediment reservoirs. On a reach scale, 10Bem transit times are shorter where the channel is braided and superelevated above the floodplain, and longer where the channel is incised and meandering, suggesting that transit time is controlled by channel morphodynamics. This is the first systematic application of 10Bem as a sediment transit time tracer and highlights the method's potential for inferring sediment routing and storage dynamics in large river systems.
Sustainable development goals (SDGs) have set the 2030 agenda to transform our world by tackling multiple challenges humankind is facing to ensure well-being, economic prosperity, and environmental protection. In contrast to conventional development agendas focusing on a restricted set of dimensions, the SDGs provide a holistic and multidimensional view on development. Hence, interactions among the SDGs may cause diverging results. To analyze the SDG interactions we systematize the identification of synergies and trade-offs using official SDG indicator data for 227 countries. A significant positive correlation between a pair of SDG indicators is classified as a synergy while a significant negative correlation is classified as a trade-off. We rank synergies and trade-offs between SDGs pairs on global and country scales in order to identify the most frequent SDG interactions. For a given SDG, positive correlations between indicator pairs were found to outweigh the negative ones in most countries. Among SDGs the positive and negative correlations between indicator pairs allowed for the identification of particular global patterns. SDG 1 (No poverty) has synergetic relationship with most of the other goals, whereas SDG 12 (Responsible consumption and production) is the goal most commonly associated with trade-offs. The attainment of the SDG agenda will greatly depend on whether the identified synergies among the goals can be leveraged. In addition, the highlighted trade-offs, which constitute obstacles in achieving the SDGs, need to be negotiated and made structurally nonobstructive by deeper changes in the current strategies.
Disentangling shallow‐water bulk carbonate carbon isotope archives into primary and diagenetic components is a notoriously difficult task and even diagenetically screened records often provide chemostratigraphic patterns that significantly differ from global signals. This is mainly caused by the polygenetic nature of shallow‐water carbonate substrates, local carbon cycle processes causing considerable neritic–pelagic isotope gradients and the presence of hiatal surfaces resulting in extremely low carbonate preservation rates. Provided here is an in‐depth petrographic and geochemical evaluation of different carbonate phases of a mid‐Cretaceous (Barremian–Aptian) shallow‐water limestone succession (Jabal Madar section) deposited on the tropical Arabian carbonate platform in Oman. The superposition of stable isotope signatures of identified carbonate phases causes a complex and often noisy bulk carbon isotope pattern. Blocky sparite cements filling intergranular pores and bioclastic voids evidence intermediate to (arguably) deep burial diagenetic conditions during their formation, owing to different timing or differential faulting promoting the circulation of fluids from variable sources. In contrast, sparite cements filling sub‐vertical veins reveal a rock‐buffered diagenetic fluid composition with an intriguing moderate enrichment in 13C, probably due to fractionation during pressure release in the context of the Miocene exhumation of the carbonate platform under study. The presence of abundant, replacive dedolomite in mud‐supported limestone samples forced negative carbon and oxygen isotope changes that are either associated with the thermal breakdown of organic matter in the deep burial realm or the expulsion of buried meteoric water in the intermediate burial realm. Notwithstanding the documented stratigraphically variable and often facies‐related impact of different diagenetic fluids on the bulk‐rock stable isotope signature, the identification of diagenetic end‐members defined δ13C and δ18O threshold values that allowed the most reliable ‘primary’ bulk carbon isotope signatures to be extracted. Most importantly, this approach exemplifies how to place regional shallow‐water stable isotope patterns with evidence for a complex multi‐stage diagenetic history into a supraregional or even global context.
Forest structure is a crucial component in the assessment of whether a forest is likely to act as a carbon sink under changing climate. Detailed 3D structural information about the tundra–taiga ecotone of Siberia is mostly missing and still underrepresented in current research due to the remoteness and restricted accessibility. Field based, high-resolution remote sensing can provide important knowledge for the understanding of vegetation properties and dynamics. In this study, we test the applicability of consumer-grade Unmanned Aerial Vehicles (UAVs) for rapid calculation of stand metrics in treeline forests. We reconstructed high-resolution photogrammetric point clouds and derived canopy height models for 10 study sites from NE Chukotka and SW Yakutia. Subsequently, we detected individual tree tops using a variable-window size local maximum filter and applied a marker-controlled watershed segmentation for the delineation of tree crowns. With this, we successfully detected 67.1% of the validation individuals. Simple linear regressions of observed and detected metrics show a better correlation (R2) and lower relative root mean square percentage error (RMSE%) for tree heights (mean R2 = 0.77, mean RMSE% = 18.46%) than for crown diameters (mean R2 = 0.46, mean RMSE% = 24.9%). The comparison between detected and observed tree height distributions revealed that our tree detection method was unable to representatively identify trees <2 m. Our results show that plot sizes for vegetation surveys in the tundra–taiga ecotone should be adapted to the forest structure and have a radius of >15–20 m to capture homogeneous and representative forest stands. Additionally, we identify sources of omission and commission errors and give recommendations for their mitigation. In summary, the efficiency of the used method depends on the complexity of the forest’s stand structure.
We present a new algorithm for solving the common problem of flow trapped in closed depressions within digital elevation models, as encountered in many applications relying on flow routing. Unlike other approaches (e.g., the Priority-Flood depression filling algorithm), this solution is based on the explicit computation of the flow paths both within and across the depressions through the construction of a graph connecting together all adjacent drainage basins. Although this represents many operations, a linear time complexity can be reached for the whole computation, making it very efficient. Compared to the most optimized solutions proposed so far, we show that this algorithm of flow path enforcement yields the best performance when used in landscape evolution models. In addition to its efficiency, our proposed method also has the advantage of letting the user choose among different strategies of flow path enforcement within the depressions (i.e., filling vs. carving). Furthermore, the computed graph of basins is a generic structure that has the potential to be reused for solving other problems as well, such as the simulation of erosion. This sequential algorithm may be helpful for those who need to, e.g., process digital elevation models of moderate size on single computers or run batches of simulations as part of an inference study.