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Alternate bars migrate downstream during floods due to coupled erosion and deposition on both sides of alluvial river channels. During low discharge periods, vegetation can grow on the tops of these bars, reducing migration rates and increasing bar wavelengths and bar heights. We explore two specific effects of above-ground vegetation on flow and transport. First, above-ground roots and groundcover can reduce bedload transport rates due to near-bed roughness, an effect not explored in most previous studies. Second, vegetation bodies (i.e. the above-ground trunk, stem, branches, and leaves) generate hydraulic drag. We model vegetation influences on alternate bar evolution using previously proposed equations which consider both vegetation body and above-ground root effects. We investigated three scenarios: vegetation body effects only, above-ground root effects only, and the full vegetation system (i.e., body and above-ground roots together). We find that vegetation body and root effects both reduce the bar migration rate and increase the bar wavelength. Reduced flow velocities over the bars due to vegetation body effects tend to enhance velocities and localized erosion on the opposite side of the channel, which in turn increases relative bar heights. Bar morphology and migration rate are most sensitive to vegetation growth rates at lower flood discharges where bar-top vegetation persists from year to year and older vegetation has stronger impacts on flow and transport. Higher peak floods tend to remove and reset vegetation growth, resulting in little sensitivity to growth rate.

Vegetation-covered water bodies (VCW) are a vital component of wetlands, and their distribution information is crucial for studying the dynamic interactions between vegetation and water. However, due to vegetation obstruction, optical remote sensing has limitations in extracting such water bodies, as it typically identifies only open water areas effectively. In contrast, microwave remote sensing, with its vegetation-penetrating capability and specular reflection characteristics, provides a more comprehensive identification of wetland water bodies. Previous studies have shown that the additional water body areas (SW) identified by SAR but not by optical sensors are often accompanied by significant vegetation cover. However, a systematic assessment of SW’s potential in mapping VCW is still lacking. This study uses the Caohai Wetland in Guizhou, China, as an example, leveraging Sentinel-2A and RadarSat-2 imagery from adjacent periods and multiple water body extraction methods to extract SW and explore its performance in mapping VCW during the dry season. Results show that during the initial stage of vegetation senescence (7 January 2019), the use of SW achieved high accuracy in mapping VCW, with overall accuracy, kappa coefficient, and F1 score reaching 84.2%, 68.4%, and 85.3%, respectively. However, as vegetation senescence deepened (12 January 2020), these metrics dropped to 76.2%, 60.7%, and 87%, respectively, indicating a significant decline in accuracy. During the vegetation regrowth stage (7 April 2020), the overall accuracy, kappa coefficient, and F1 score were 71.1%, 57.2%, and 70.9%, respectively. As vegetation continued to grow (21 April 2019), these metrics improved to 79.4%, 67.2%, and 86.6%. In summary, SW extracted from high-resolution optical and SAR imagery can preliminarily map VCW during the dry season. Furthermore, its identification accuracy improves significantly with increasing vegetation density. This study provides a novel perspective for wetland water body monitoring and the study of vegetation-water interactions.

An organismic concept of land plants is outlined, which is based on a synthesis of plant morphology and plant anatomy. The entire plant, the living unity, is conceived as the organism being subdivided into cells, which cannot be interpreted as organisms themselves in the sense of elementary organisms. The evolution of land plant tissue systems is discussed in the introductive chapter. To test the proposed concept, some frondose plants were selected from liverworts (Pellia epiphylla, Metzgeria furcata, Pallavicinia lyallii) and comparable fern gametophytes (Dryopteris filix mas, Vittaria lineata, Stenochlaena tenuifolia) and studied with respect to their organization and the principles of development. They all have an archetypic, two-dimensional, open construction, which is described as the \"repens-type\" of plant construction. Primary form growth occurs in the marginal blastozone, which controls cell wall integration. One of the most significant processes of form generation is blastozone fractionation. The tissues leaving the blastozone differentiate during extension growth and maturation of the vegetation body. While the plant grows continuously in the blastozone, it decays steadily in the necrozone. The implications of the two-dimensional repens-type are discussed. It appears as a perfect plant construction, fit to start plant evolution on the land surface. Growing upwards into the atmosphere, the repens-type is obscured. But is reappears in all groups of higher land plants. This demonstrates the existence of evolutionary cycles in plants. It is argued that mutation and selection do not suffice to understand cyclical evolutionary patterns. The influence of organismic construction seems to predetermine evolution because of the limited options to change an appropriately functioning construction. Via construction analysis evolutionary options can be detected and thus, evolution becomes predictable to some extent. Instead of being object of mutation and selection, living organisms should be conceived as subjects in evolution (Weingarten 1993).

The assessment of drought hazards is important due to their socio-economic impacts on water resources, agriculture, and ecosystems. In this study, the effects of drought on changing water area and canopy of the Lake Urmia watershed in the northwest of Iran have been monitored and evaluated. For this purpose, the Standardized Precipitation Index (SPI) was calculated in short and medium periods (1-month and 3-month) to determine the dry-spell periods in the Lake Urmia basin. In reviewing this analysis, the annual average has been examined and evaluated. Furthermore, Moderate Resolution Imaging Spectroradiometer (MODIS) and remote sensing data were used to calculate the Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the Normalized Difference Water Index (NDWI), and the Temperature–Vegetation–Dryness Index (TVDI) to identify the area of water body, water level, and vegetation changes during 20 years (2000–2020). The Pearson correlation coefficient was also employed to explore the relationship between the drought and the remote sensing-derived indices. According to the results of drought analysis, 2000, 2002, 2004, 2006, 2008, 2010, 2012, 2014, 2016, 2018, and 2020 had experienced dry spells in the Lake Urmia basin. The NDWI changes also showed that the maximum area of the Lake Urmia happened in 2000, and its minimum was recorded in 2014. The variation of NDVI values showed that the highest values of vegetation cover were estimated to be 2,850 km2 in.2000, and its lowest value was 1,300 km2 in.2014. The maximum EVI and TDVI were calculated in 2000, while their minimum was observed in 2012 and 2014. Also, the correlation analysis showed that the SPI had the highest correlation with NDVI. Meanwhile, 1-month SPI had a higher correlation than the 3-month SPI with NDVI and EVI. As a concluding remark, NDVI and NDWI were more suitable indices to monitor the changes in vegetation and drought-related water area. The results can be used to make sound decisions regarding the rapid assessment of remote sensing-derived data and water-related indices.

Data needed for macroecological analyses are difficult to compile and often hidden away in supplementary material under non-standardized formats. Phylogenies, range data, and trait data often use conflicting taxonomies and require ad hoc decisions to synonymize species or fill in large amounts of missing data. Furthermore, most available data sets ignore the large impact that humans have had on species ranges and diversity. Ignoring these impacts can lead to drastic differences in diversity patterns and estimates of the strength of biological rules. To help overcome these issues, we assembled PHYLACINE, The Phylogenetic Atlas of Mammal Macroecology. This taxonomically integrated platform contains phylogenies, range maps, trait data, and threat status for all 5,831 known mammal species that lived since the last interglacial (∼130,000 years ago until present). PHYLACINE is ready to use directly, as all taxonomy and metadata are consistent across the different types of data, and files are provided in easy-to-use formats. The atlas includes both maps of current species ranges and present natural ranges, which represent estimates of where species would live without anthropogenic pressures. Trait data include body mass and coarse measures of life habit and diet. Data gaps have been minimized through extensive literature searches and clearly labelled imputation of missing values. The PHYLACINE database will be archived here as well as hosted online so that users may easily contribute updates and corrections to continually improve the data. This database will be useful to any researcher who wishes to investigate large-scale ecological patterns. Previous versions of the database have already provided valuable information and have, for instance, shown that megafauna extinctions caused substantial changes in vegetation structure and nutrient transfer patterns across the globe.

Flume experiments were conducted to comprehend the impact of different patterns of an emergent vegetation patch on the flow field and the scour process in natural rivers. Velocity measurements, flow visualization, and scour tests were undertaken around different vegetation patch patterns, which were simulated inspired by the expansion process of a typical instream vegetation. The patch expansion process was idealized with an initially circular patch of rigid emergent stems becoming elongated due to positive and negative feedbacks. The expansion of the vegetation patch was considered to occur in three stages, in which the density of the patch from the previous stage was increased while the patch was also elongated by connecting at its downstream side with another sparser vegetation patch. These stages were replicated succesively by increasing the density and elongating the patch. In this way, two processes (i.e., elongation and decrease in permeability), which usually have hydrodynamically opposite effects on flow fields, were simulated at the same obstruction. Despite generally elongated obstacles being streamlined bodies, the morphometric analysis obtained by laser scanner revealed that streamlined elongation of permeable patches amplifies global scour and enhances localization of the local scour hole. This situation implies that as the patch expands, in the wake region, the steady‐wake region becomes shorter, turbulence diminishes, lateral shear stress enhances, and deposition cannot occur far from the patch. Consequently, as the patch expands, the hydrodynamic consequences may restrict further patch expansion after a certain length/density. Plain Language Summary What effect does enlarging a single patch have on the local flow field and scour pattern? This research question was examined experimentally. Despite the fact that streamlined patches are hydrodynamically favorable formations, morphometric scour measurements show that the streamlined extension of permeable patches increases global scour and promotes local scour hole localization. As the patch develops, the steady‐wake zone of low velocity and suppressed turbulence that favors sediment entrapment decreases restricting its expansion. Key Points Experiments were conducted to see the impact of different patterns of an emergent vegetation patch on flow field and scour in rivers Streamlined bodies are hydrodynamically favorable bodies. Yet, tests showed that the elongation of patches increases scour and localization The steady‐wake zone becomes shorter as the patch elongated, hence restricting the patch's expansion

With rising air temperature and precipitation, water and sediment fluxes in the Source Region of the Yangtze River (SRYR) have increased since 2000s. Nonetheless, the response of braided river morphology to climate‐driven water and sediment flux change is still unknown. Water bodies of 9 large braided rivers from 1990 to 2020 were extracted based on Google Earth Engine platform, and impacts of climate change on morphological indices and morphodynamic processes were quantified. A new segmentation method is presented to more precisely extract braided river water body when the branch width is less than an image pixel size. The warming and wetting trend led to vegetation cover increase. With the increase of water flux, the water area of each braided reach has increased in both flood and non‐flood season. The 3–5 years mean annual erosion and accretion intensity (newly proposed in this study) of the channel shows three different trends of increasing, weakening, and unchanged over time. These three trends can be classified into three patterns in response to climate‐change driven water and sediment flux change in the SRYR as follows: sediment increase constrained pattern (weakening or unchanged), sediment increase dominated pattern (increasing), and water increase dominated pattern (increasing or unchanged). In summary, the braided rivers in the SRYR showing consistent increasing of water area, general expansion of active channel, and increasing of erosion and accretion intensity for some of the rivers, with the climate‐driven increasing water and sediment flux. Key Points A new method of braided water body extraction improves accuracy of recognition The warming and wetting trend has led to the more durative inundation of braided rivers since 2000s and consistent expansion of the channel Mean annual channel erosion and accretion intensity differently responds to the increase of water and sediment flux in nine braided rivers

This paper presents a learning-based, physics-aware soil moisture (SM) retrieval algorithm for NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission. The goal of the proposed novel method is to advance CYGNSS-based SM estimations, exploiting the spatio-temporal resolution of the GNSS reflectometry (GNSS-R) signals to its highest potential within a machine learning framework. The methodology employs a fully connected Artificial Neural Network (ANN) regression model to perform SM predictions through learning the nonlinear relations of SM and other land geophysical parameters to the CYGNSS observables. In situ SM measurements from several International SM Network (ISMN) sites are used as reference labels; CYGNSS incidence angles, derived reflectivity and trailing edge slope (TES) values, as well as ancillary data, are exploited as input features for training and validation of the ANN model. In particular, the utilized ancillary data consist of normalized difference vegetation index (NDVI), vegetation water content (VWC), terrain elevation, terrain slope, and h-parameter (surface roughness). Land cover classification and inland water body masks are also used for the intermediate derivations and quality control purposes. The proposed algorithm assumes uniform SM over a 0.0833 ∘ × 0.0833 ∘ (approximately 9 km × 9 km around the equator) lat/lon grid for any CYGNSS observation that falls within this window. The proposed technique is capable of generating sub-daily and high-resolution SM predictions as it does not rely on time-series or spatial averaging of the CYGNSS observations. Once trained on the data from ISMN sites, the model is independent from other SM sources for retrieval. The estimation results obtained over unseen test data are promising: SM predictions with an unbiased root mean squared error of 0.0544 cm 3 /cm 3 and Pearson correlation coefficient of 0.9009 are reported for 2017 and 2018.

Human activity has impacted the world climate. Therefore, metropolitan areas are especially vulnerable to catastrophic weather and environmental problems. The local climate has deteriorated due to urbanization and industrialization, which has resulted in the degradation of green space, increased high concretization, soil erosion, subsidence of land, inadequate runoff, and reduced infiltration rates. This study examines the spatiotemporal changes in Land Use and Land Cover (LULC) and their impact on Land Surface Temperature (LST) and Urban Heat Islands (UHI) in Asansol Municipal Corporation (AMC). The maximum likelihood classifier method has been used to quantify the LULC and different spatial indices such as Normalized Difference Vegetation Index (NDVI), Normalized Difference Bare Soil Index (NDBSI), Normalized Difference Moisture Index (NDMI), and Particulates Matter (PM) 2.5 have applied to determine the relation with LST. The results show that the cultivation land (-42.76 km2), vegetation cover (-5.66 km2), and water body (-4.75 km2) has been decreasing continuously in the last 20 years, subsequently, the built-up area (27.65 km2), and industrial belt (6.88 km2) have been increased during the same periods due to the urbanization, industrialization, and rapid population growth. The correlation analysis shows that the NDVI, NDMI, and PM 2.5 are inversely correlated with LST, whereas NDBSI positively affects the LST. The study also shows that the bare surface, mining area, and industrial belt situated on the outskirts of the city shows comparatively higher temperatures than the core of the city in the years 2001 and 2011. Moreover, in 2021, the highest temperature has been shifted towards the city center because of high rate of concretization. Linear regression analysis shows a robust correlation (R2 > 0.40) between different spatial indices and LST for various periods. Conspicuously, built-up areas, bare surfaces, water bodies, and vegetation cover wield stimulus to the LST. The study suggests the strategic significance of adjusting urban developments and offers crucial insights into the dynamic interplay between environmental elements and urbanization.

Terrestrial ectotherms are likely to be especially sensitive to rising temperatures over coming decades. Thermal limits are used to measure climatic tolerances that potentially affect ectotherm distribution. While there is a strong relationship between the critical thermal maximum (CTmax) of insects and their latitudinal ranges, the nature of this relationship across elevation is less clear. Here we investigated the combined relationships between CTmax, elevation and ant body mass, given that CTmax can also be influenced by body mass, in the World Heritage-listed rainforests of the Australian Wet Tropics. We measured the CTmax and body mass of 20 ant species across an elevational gradient from 350 to 1000 m a.s.l. Community CTmax did not vary systematically with increasing elevation and there was no correlation between elevation and elevational ranges of species. However, body mass significantly decreased at higher elevations. Despite the negative correlation between CTmax and body mass at the community level, there was no significant difference in CTmax of different-sized ants within a species. These findings are not consistent with either the climatic variability hypothesis, Rapoport’s rule or Bergmann’s rule. Models indicated that elevation and body mass had limited influences on CTmax. Our results suggest that the distribution of most montane ants in the region is not strongly driven by thermal limitation, and climate change will likely impact ant species differently. This is likely to occur primarily through changes in rainfall via its effects on vegetation structure and therefore thermal microhabitats, rather than through direct temperature changes.