Context.
Hydrodynamical simulations of planet-disk interactions suggest that planets may be responsible for a number of the substructures frequently observed in disks in both scattered light and dust ...thermal emission. Despite the ubiquity of these features, direct evidence of planets embedded in disks and of the specific interaction features like spiral arms within planetary gaps are still rare.
Aims.
In this study we discuss recent observational results in the context of hydrodynamical simulations in order to infer the properties of a putative embedded planet in the cavity of a transition disk.
Methods.
We imaged the transition disk SR 21 in
H
-band in scattered light with SPHERE/IRDIS and in thermal dust emission with ALMA band 3 (3 mm) observations at a spatial resolution of 0.1″. We combine these datasets with existing Band 9 (430
μ
m) and Band 7 (870
μ
m) ALMA continuum data.
Results.
The Band 3 continuum data reveals a large cavity and a bright ring peaking at 53 au strongly suggestive of dust trapping. The ring shows a pronounced azimuthal asymmetry, with a bright region in the northwest that we interpret as a dust overdensity. A similarly asymmetric ring is revealed at the same location in polarized scattered light, in addition to a set of bright spirals inside the millimeter cavity and a fainter spiral bridging the gap to the outer ring. These features are consistent with a number of previous hydrodynamical models of planet-disk interactions, and suggest the presence of a ∼1
M
Jup
planet at 44 au and PA = 11 deg. This makes SR21 the first disk showing spiral arms inside the millimeter cavity, and the first disk for which the location of a putative planet can be precisely inferred.
Conclusions.
The main features of SR 21 in both scattered light and thermal emission are consistent with hydrodynamical predictions of planet-disk interactions. With the location of a possible planet being well constrained by observations, it is an ideal candidate for follow-up observations to search for direct evidence of a planetary companion still embedded in its disk.
To understand forest dynamics under today’s changing environmental conditions, it is important to analyze the state of forests at large scales. Forest inventories are not available for all regions, ...so it is important to use other additional methods, e.g., remote sensing observations. Increasingly, remotely sensed data based on optical instruments and airborne LIDAR are becoming widely available for forests. There is great potential in analyzing these measurements and gaining an understanding of forest states. In this work, we combine the new-generation radiative transfer model mScope with the individual-based forest model FORMIND to generate reflectance spectra for forests. Combining the two models allows us to account for species diversity at different height layers in the forest. We compare the generated reflectances for forest stands in Finland, in the region of North Karelia, with Sentinel-2 measurements. We investigate which level of forest representation gives the best results and explore the influence of different calculation methods of mean leaf parameters. For the majority of the forest stands, we generated good reflectances with all levels of forest representation compared to the measured reflectance. Good correlations were also found for the vegetation indices (especially NDVI with R2=0.62). This work provides a forward modeling approach for relating forest reflectance to forest characteristics. With this tool, it is possible to analyze a large set of forest stands with corresponding reflectances. This opens up the possibility to understand how reflectance is related to succession and different forest conditions.
We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles ...to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation-Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2-33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9-112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of −14 to −19 Pg C °C−1 on a 100 year time scale. For CH4 emissions, our approach assumes a fixed saturated area and that increases in CH4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10-18%. The simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming.
Deriving gross & net primary productivity (GPP & NPP) and carbon turnover time of forests from remote sensing remains challenging. This study presents a novel approach to estimate forest productivity ...by combining radar remote sensing measurements, machine learning and an individual-based forest model. In this study, we analyse the role of different spatial resolutions on predictions in the context of the Radar BIOMASS mission (by ESA). In our analysis, we use the forest gap model FORMIND in combination with a boosted regression tree (BRT) to explore how spatial biomass distributions can be used to predict GPP, NPP and carbon turnover time (
) at different resolutions. We simulate different spatial biomass resolutions (4 ha, 1 ha and 0.04 ha) in combination with different vertical resolutions (20, 10 and 2 m). Additionally, we analysed the robustness of this approach and applied it to disturbed and mature forests. Disturbed forests have a strong influence on the predictions which leads to high correlations (
> 0.8) at the spatial scale of 4 ha and 1 ha. Increased vertical resolution leads generally to better predictions for productivity (GPP & NPP). Increasing spatial resolution leads to better predictions for mature forests and lower correlations for disturbed forests. Our results emphasize the value of the forthcoming BIOMASS satellite mission and highlight the potential of deriving estimates for forest productivity from information on forest structure. If applied to more and larger areas, the approach might ultimately contribute to a better understanding of forest ecosystems.
Understanding the processes that shape forest functioning, structure, and diversity remains challenging, although data on forest systems are being collected at a rapid pace and across scales. Forest ...models have a long history in bridging data with ecological knowledge and can simulate forest dynamics over spatio‐temporal scales unreachable by most empirical investigations.
We describe the development that different forest modelling communities have followed to underpin the leverage that simulation models offer for advancing our understanding of forest ecosystems.
Using three widely applied but contrasting approaches – species distribution models, individual‐based forest models, and dynamic global vegetation models – as examples, we show how scientific and technical advances have led models to transgress their initial objectives and limitations. We provide an overview of recent model applications on current important ecological topics and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.
Synthesis. This overview shows that forest models, due to their complementarity and mutual enrichment, represent an invaluable toolkit to address a wide range of fundamental and applied ecological questions, hence fostering a deeper understanding of forest dynamics in the context of global change.
Forest models can help understanding the processes that shape forest functioning, structure and diversity, since they can can simulate forest dynamics over spatio‐temporal scales unreachable by most empirical investigations. Here we describe the development of three widely applied but contrasting forest mo−delling approaches — species distribution models, individual‐based models and dynamic global vegetation models. We provide an overview of recent model applications and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.
Hypothermia therapy improves survival and the neurologic outcome in animal models of traumatic brain injury. However, the effect of hypothermia therapy on the neurologic outcome and mortality among ...children who have severe traumatic brain injury is unknown.
In a multicenter, international trial, we randomly assigned children with severe traumatic brain injury to either hypothermia therapy (32.5 degrees C for 24 hours) initiated within 8 hours after injury or to normothermia (37.0 degrees C). The primary outcome was the proportion of children who had an unfavorable outcome (i.e., severe disability, persistent vegetative state, or death), as assessed on the basis of the Pediatric Cerebral Performance Category score at 6 months.
A total of 225 children were randomly assigned to the hypothermia group or the normothermia group; the mean temperatures achieved in the two groups were 33.1+/-1.2 degrees C and 36.9+/-0.5 degrees C, respectively. At 6 months, 31% of the patients in the hypothermia group, as compared with 22% of the patients in the normothermia group, had an unfavorable outcome (relative risk, 1.41; 95% confidence interval CI, 0.89 to 2.22; P=0.14). There were 23 deaths (21%) in the hypothermia group and 14 deaths (12%) in the normothermia group (relative risk, 1.40; 95% CI, 0.90 to 2.27; P=0.06). There was more hypotension (P=0.047) and more vasoactive agents were administered (P<0.001) in the hypothermia group during the rewarming period than in the normothermia group. Lengths of stay in the intensive care unit and in the hospital and other adverse events were similar in the two groups.
In children with severe traumatic brain injury, hypothermia therapy that is initiated within 8 hours after injury and continued for 24 hours does not improve the neurologic outcome and may increase mortality. (Current Controlled Trials number, ISRCTN77393684 controlled-trials.com.).
Over the last 40 years, Lake Chad, once the sixth largest lake in the world, has decreased by more than 90% in area. In this study, we use a hydrological model coupled with a lake/wetland algorithm ...to simulate the effects of lake bathymetry, human water use, and decadal climate variability on the lake’s level, surface area, and water storage. In addition to the effects of persistent droughts and increasing irrigation withdrawals on the shrinking, we find that the lake’s unique bathymetry—which allows its division into two smaller lakes—has made it more vulnerable to water loss. Unfortunately the lake’s split is favored by the 1952–2006 climatology. Failure of the lake to remerge with renewed rainfall in the 1990s following the drought years of the 1970s and 1980s is a consequence of irrigation withdrawals. Under current climate and water use, a full recovery of the lake is unlikely without an inter-basin water transfer. Breaching the barrier separating the north and south lakes would reduce the amount of supplemental water needed for recovery.
Plant functional diversity (FD) is an important component of biodiversity. Evidence shows that FD strongly determines ecosystem functioning and stability and also regulates various ecosystem services ...that underpin human well-being. Given the importance of FD, it is critical to monitor its variations in an explicit manner across space and time, a highly demanding task that cannot be resolved solely by field data. Today, high hopes are placed on satellite-based observations to complement field plot data. The promise is that multiscale monitoring of plant FD, ecosystem functioning, and their services is now possible at global scales in near real-time. However, non-trivial scale challenges remain to be overcome before plant ecology can capitalize on the latest advances in Earth Observation (EO). Here, we articulate the existing scale challenges in linking field and satellite data and further elaborated in detail how to address these challenges via the latest innovations in optical and radar sensor technologies and image analysis algorithms. Addressing these challenges not only requires novel remote sensing theories and algorithms but also urges more effective communication between remote sensing scientists and field ecologists to foster mutual understanding of the existing challenges. Only through a collaborative approach can we achieve the global plant functional diversity monitoring goal.
PDF
