Generalized anxiety disorder (GAD) is one of the most common anxiety disorders. The brain’s dysfunctional processing of interoceptive information is increasingly recognized as an important component of anxiety disorders. However, the neural mechanisms remain insufficiently understood. In the present study, patients with GAD and healthy control participants underwent an eyes-closed (EC) resting state (interoception) and eyes-open (EO) resting state (exteroception) without paying conscious attention to heartbeat. Electrocardiography (ECG) and electroencephalography (EEG) signals were recorded at the same time. The results show that in healthy controls, the heartbeat-evoked brain potential (HEP) was modulated by the conditions, with a significantly higher amplitude under EC than EO, while this was not the case in GAD patients. Further analysis revealed that the dysfunction of HEP modulation in GAD patients may be attributed to excessive interoceptive processing under EO, with a marginally higher HEP in GAD than in the healthy controls. Finally, the right prefrontal HEP amplitude during EC condition was significantly correlated with the severity of the patients’ anxiety symptoms. Our results suggest that altered cortical processing of interoceptive signals may play an important role in the pathophysiology of generalized anxiety disorder.
Increasing global demand of vegetable oils and biofuels results in significant oil palm expansion in Southeast Asia, predominately in Malaysia and Indonesia. The land conversion to oil palm plantations leads to deforestation, loss of biodiversity, and greenhouse gas emission over the past decades. Quantifying the consequences of oil palm expansion requires fine scale and frequently updated datasets of land cover dynamics. Previous studies focused on total changes for a multi-year interval without identifying the exact time of conversion, causing uncertainty in the timing of carbon emission estimates from 15 land cover change. Using Advanced Land Observing Satellite (ALOS) Phased Array Type L-band Synthetic Aperture Radar (PALSAR), ALOS-2 PALSAR-2 and Moderate Resolution Imaging Spectroradiometer (MODIS) datasets, we produced an Annual Oil Palm Area Dataset (AOPD) at 100-meter resolution in Malaysia and Indonesia from 2001 to 2016. We first mapped the oil palm extent using PALSAR/PALSAR-2 data for 2007-2010 and 2015-2016 and then applied a disturbance and recovery algorithm (BFAST) to detect land cover change time-points using MODIS data during the years without PALSAR data (2011-20 2014 and 2001-2006). The new oil palm land cover maps are assessed to have an accuracy of 86.61% in the mapping step (2007-2010 and 2015-2016). During the intervening years when MODIS data are used, 75.74% of the change detected time matched the timing of actual conversion using Google Earth and Landsat images. The AOPD dataset revealed spatiotemporal oil palm dynamics every year and shows that plantations expanded from 2.59 to 6.39 M ha and from 3.00 to 12.66 M ha in Malaysia and Indonesia, respectively (i.e., a net increase of 146.60% and 322.46%) between 2001 and 2016. The increasing 25 trends from our dataset are consistent with those from the national inventories, but slightly greater because of inclusion of smallholder oil palm plantations in our dataset. We highlight the capability of combining multiple resolution radar and optical satellite datasets in annual plantation mapping at large extent using image classification and statistical boundary-based change detection to achieve long time-series. The consistent characterization of oil palm dynamics can be further used in downstream applications. The annual oil palm plantation maps from 2001 to 2016 at 100 m resolution is published in the Tagged Image 30File Format with georeferencing information (GeoTIFF) at https://doi.org/10.5281/zenodo.3467071 .
Significant efforts have been invested to restore mangrove forests worldwide through reforestation and afforestation. However, blue carbon benefit has not been compared between these two silvicultural pathways at the global scale. Here, we integrated results from direct field measurements of over 370 restoration sites around the world to show that mangrove reforestation (reestablishing mangroves where they previously colonized) had a greater carbon storage potential per hectare than afforestation (establishing mangroves where not previously mangrove). Greater carbon accumulation was mainly attributed to favorable intertidal positioning, higher nitrogen availability, and lower salinity at most reforestation sites. Reforestation of all physically feasible areas in the deforested mangrove regions of the world could promote the uptake of 671.5–688.8 Tg CO2-eq globally over a 40-year period, 60% more than afforesting the same global area on tidal flats (more marginal sites). Along with avoiding conflicts of habitat conversion, mangrove reforestation should be given priority when designing nature-based solutions for mitigating global climate change.
Abstract. Land use change (LUC) is a fundamental anthropogenic disturbance in the global carbon cycle. Here we present model developments in a global dynamic vegetation model ORCHIDEE-MICT for more realistic representation of LUC processes. First, we included gross land use change (primarily shifting cultivation) and forest wood harvest in addition to net land use change. Second, we included sub-grid even-aged land cohorts to represent secondary forests, and to keep track of the age of agricultural lands since LUC, which are associated with variable soil carbon stocks. Combination of these two features allows simulating shifting cultivation with a short rotation length involving mainly secondary forests instead of primary ones. This is in contrast with the traditional approach where a single patch is used for a given land cover type in a model grid cell and forests are thus close to primary ones. We have tested the model over Southern Africa for the period 1501–2005 forced by a historical land use change data set. Including gross land use change and wood harvest has increased LUC emissions in both simulations with (Sage) and without (Sageless) sub-grid secondary forests, but larger increase is found in Sageless (by a factor of 2) than Sage (by a factor of 1.5). Emissions from bi-directional land turnover alone are 35 % lower in Sage than Sageless, mainly because the secondary forests cleared for agricultural land have a lower aboveground biomass than primary ones. We argue that, without representing sub-grid land cohort demography, the additional emissions from land turnover/gross land use change are overestimated. In addition, our developments provide possibilities to account for continental or global forest demographic change resulting from past anthropogenic and natural disturbances.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.