Hasil untuk "Physical geography"

S. Sontag

I want to describe not what it’s really like to emigrate to the kingdom of the ill and to live there, but the punitive or sentimental fantasies concocted about that situation; not real geography but stereotypes of national character. My subject is not physical illness itself but the uses of illness as a figure or metaphor. My point is that illness is not a metaphor, and that the most truthful way of regarding illness—and the healthiest way of being ill—is one most purified of, most resistant to, metaphoric thinking. Yet it is hardly possible to take up one’s residence in the kingdom of the ill unprejudiced by the lurid metaphors with which it has been landscaped. It is toward an elucidation of those metaphors, and a liberation from them, that I dedicate this inquiry.

W. Zelinsky

D. Quah

M. Small, Laura Adler

Recent years have seen a resurgence of interest in the relation between networks and spatial context. This review examines critically a selection of the literature on how physical space affects the formation of social ties. Different aspects of this question have been a feature in network analysis, neighborhood research, geography, organizational science, architecture and design, and urban planning. Focusing primarily on work at the meso- and microlevels of analysis, we pay special attention to studies examining spatial processes in neighborhood and organizational contexts. We argue that spatial context plays a role in the formation of social ties through at least three mechanisms, spatial propinquity, spatial composition, and spatial configuration; that fully capturing the role of spatial context will require multiple disciplinary perspectives and both qualitative and quantitative research; and that both methodological and conceptual questions central to the role of space in networks remain to be answered. We conclude by identifying major challenges in this work and proposing areas for future research.

H. Brammer

Abstract The physical geography of Bangladesh’s coastal area is more diverse and dynamic than is generally recognised. Failure to recognise this has led to serious misconceptions about the potential impacts of a rising sea-level on Bangladesh with global warming. This situation has been aggravated by accounts giving incorrect information on current rates of coastal erosion and land subsidence. This paper describes physical conditions within individual physiographic regions in Bangladesh’s coastal area based on ground-surveyed information, and it reviews possible area-specific mitigation measures to counter predicted rates of sea-level rise in the 21st century. Two important conclusions are drawn: the adoption of appropriate measures based on knowledge of the physical geography of potentially-affected areas could significantly reduce the currently-predicted displacement of many millions of people; and the impacts of a slowly-rising sea-level are currently much less than those generated by rapidly increasing population pressure on Bangladesh’s available land and water resources and by exposure to existing environmental hazards, and the latter problems need priority attention.

C. C. Correa Ayram, M. Mendoza, A. Etter et al.

Guo Chen, Hao Wang, Qing-wei Zhang et al.

Study region: The Zhifanggou watershed of the Loess Plateau, China. Study focus: Using rainfall simulation experiments coupled with high-throughput sequencing and fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), we revealed the linkages between DOM molecular characteristics and bacterial/fungal communities in runoff from slopes colonized by three typical biocrusts (cyanobacterial, cyanobacterial-moss, and moss crusts), with bare slope as control. New hydrological insights for the region: Biocrust succession significantly increased DOM molecular diversity by 12–24 % compared to bare slope, while maintaining stable microbial diversity. The bacterial communities in runoff were dominated by Proteobacteria and Actinobacteriota (61–79 %), while Ascomycota (60–94 %) prevailed fungal communities. The DOM molecular composition in runoff was closely associated with bacterial and fungal communities and the biocrusts characteristics within runoff plots. The compositional differences of all compound classes or elemental combinations in runoff generally decreased with biocrust succession. Besides, the positive Spearman correlation between bacteria and DOM in runoff predominantly distributed in higher O/C and lower H/C molecular families, while vice versa for the fungi. Meanwhile, bipartite network analysis further demonstrated that both positive and negative interactions were closely associated to molecular characteristics. When the H/C or O/C ratios of DOM molecules were more similar, their correlations with microbial taxa showed greater similarity. Overall, our findings offer insights into DOM-microbe co-transport mechanisms at soil-aquatic interfaces of semiarid ecosystems.

Roland Baumhauer

B. Tiffney, S. Manchester

Khokan Kumer Sarker, Mohammed Mainuddin, Richard W. Bell et al.

The intensification of cropping systems in the salt-affected coastal zones of the Ganges Delta can boost food security in the region. The scarcity of fresh water, coupled with varying degrees of soil and water salinity are however limiting factors for the expansion of irrigated cropping in that area. In this study, we assessed the potential of growing sunflowers using combinations of low and medium saline water for irrigation. The experiments were conducted at two locations with six irrigation treatments in 2016–2017 and 2017–2018. The treatments were: T1—two irrigations at early vegetative (25–30 days after sowing; DAS) and flowering stages (60–65 DAS) with low salinity water (LSW, electric conductivity, EC_w < 2 dS m⁻¹); T2—two irrigations, one at the vegetative stage with LSW and one at the flowering stage with medium salinity water (MSW, 2 < EC_w < 5dS m⁻¹); T3—two irrigations, one at the vegetative stage with LSW and one at seed development stage (75–80 DAS) with MSW; T4—three irrigations at the vegetative, flowering and seed development stages with LSW; T5—three irrigations, at vegetative stage with LSW, and flowering and seed development stages with MSW; and T6—three irrigations, two at the vegetative and flowering stages with LSW and one at the seed development stage with MSW. Irrigation with LSW at early growth stages and MSW at later growth stages did not significantly (<i>p</i> < 0.05) affect the yield compared to the LSW irrigation at early and later growth stages. Crop water productivity and irrigation water productivity of sunflowers (<i>p</i> < 0.001) increased substantially with the decreasing amount of irrigation water with an average of 1.18 kg m⁻³ and 2.22 kg m⁻³ in 2017 and 0.92 kg m⁻³ and 1.29 kg m⁻³ in 2018, respectively. Grain yield was significantly correlated with root zone solute potential. The flowering and seed development stages of sunflowers in February–March were sensitive to both low and medium saline water irrigation for seed yield. Overall, the results show that irrigation with LSW (EC_w < 2dS m⁻¹) at early growth stages and MSW (2 < EC_w < 5dS m⁻¹) at later growth stages could be an option for dry-season sunflowers in the coastal zones of the Ganges Delta which would allow double cropping in this area.

Nosiseko Mashiyi, Lerato Shikwambana, Mahlatse Kganyago

Methane (CH4) is the second most abundant anthropogenic greenhouse gas after carbon dioxide (CO2), accounting for about 20% of global emissions. CH4 anthropogenic emission sources include landfills, oil and natural gas systems, agricultural activities, coal mining, stationary and mobile combustion, wastewater treatment and certain industrial processes. In this work, we examine the spatio-temporal dynamics of CH4 and its relationship to climatic and vegetation parameters in the Northern Cape province in South Africa. Various datasets from the TROPOspheric Monitoring Instrument, Moderate Resolution Imaging Spectroradiometer, Atmospheric Infrared Sounder and the Global Precipitation Climatology Project were used. The results show an increasing trend of CH4 concentration throughout the entire province. The greatest increase in CH4 concentration is observed in the western parts of the province during June–July–August (JJA) season. CH4 concentration shows negligible correlation with most climatic parameters, i.e. Temperature (Temp), Precipitation (Precip) and NDVI for both seasons. The Temp–NDVI relationship shows high correlation values of [Formula: see text]= –0.71 and [Formula: see text] = 0.82 for the DJF and JJA seasons, respectively. Seasonality plays a critical role in the relationships of the CH4 to climatic and vegetation parameters. This study shows that we are in a crisis, and robust mitigation strategies are needed to combat this.

Alexandre Barboni, Alexandre Stegner, Franck Dumas et al.

Abstract Seasonal evolution of both surface signature and subsurface structure of a Mediterranean mesoscale anticyclones is assessed using the Coastal and Regional Ocean Community high‐resolution numerical model with realistic background stratification and fluxes. In good agreement with remote‐sensing and in‐situ observations, our numerical simulations capture the seasonal cycle of the anomalies induced by the anticyclone, both in the sea surface temperature (SST) and in the mixed layer depth (MLD). The eddy signature on the SST shifts from warm‐core in winter to cold‐core in summer, while the MLD deepens significantly in the core of the anticyclone in late winter. Our sensitivity analysis shows that the eddy SST anomaly can be accurately reproduced only if the vertical resolution is high enough (∼4 m in near surface) and if the atmospheric forcing contains high‐frequency. In summer with this configuration, the vertical mixing parameterized by the k − ϵ closure scheme is three times higher inside the eddy than outside the eddy, and leads to an anticyclonic cold core SST anomaly. This differential mixing is explained by near‐inertial waves, triggered by the high‐frequency atmospheric forcing. Near‐inertial waves propagate more energy inside the eddy because of the lower effective Coriolis parameter in the anticyclone core. On the other hand, eddy MLD anomaly appears more sensitive to horizontal resolution, and requires SST retroaction on air‐sea fluxes. These results detail the need of high frequency forcing, high vertical and horizontal resolutions to accurately reproduce the evolution of a mesoscale eddy.

A. Birkinshaw, M. Sutter, M. Nussbaum et al.

ABSTRACT: As the call for an international standard for milk from grassland-based production systems continues to grow, so too do the monitoring and evaluation policies surrounding this topic. Individual stipulations by countries and milk producers to market their milk under their own grass-fed labels include a compulsory number of grazing days per year (ranging from 120 d for certain labels to 180 d for others), a specified amount of herbage in the diet, or a prescribed dietary proportion of grassland-based forages (GBF) fed and produced on-farm. As these multifarious policy and label requirements are laborious and costly to monitor on-farm, fast economical proxies would be advantageous to verify the proportion of GBF consumed by the cows in the final product. With this in mind, we employed readily available mid-infrared spectral data (n = 1,132 spectra) from routine milk controls to develop binary classification models for 4 main feed groups from a primarily forage-based diet: total GBF (≥50% [n = 955], ≥75% [n = 599], ≥85% [n = 356]), pasture (≥20% [n = 451], ≥50% [n = 284], ≥70% [n = 152]), fresh herbage (pasture + fresh herbage indoor feeding; ≥20% [n = 517], ≥50% [n = 325], ≥70% [n = 182]), and whole plant corn (fresh + conserved; ≥10% [n = 646], ≥30% [n = 187]), with the latter as a negative control. We compared 4 machine learning methods to assess which statistical model performs best at discriminating these classes. Three of these models have not yet been tested for herd-level dietary proportion classification, and all 4 follow completely different approaches: least absolute shrinkage and selection operator (LASSO), partial least squares discriminant analysis (PLS-DA), random forest (RF), and support vector machines (SVM). Seasonality has been a missing element from previous dietary herbage proportion classification models. As grazing and fresh herbage indoor feeding are highly dependent on the season, we developed an indicator to incorporate seasonality in a consistent, unbiased manner into our models. We also tested 3 sets of covariates. The first set included only mid-infrared spectra derived data, the second included mid-infrared spectra derived data plus seasonality indices and the third included mid-infrared spectra derived data, seasonality indices and additional herd specific information (DIM, breed, and parity). Of the 4 machine learning algorithms tested for the binary classification of GBF proportion at herd level, LASSO and PLS-DA performed best according to evaluation metrics; however, the RF and SVM models were not far behind the best performing model evaluation metrics in each feed category. Our best performing model, the LASSO model containing seasonality indices and herd specific information, classified total GBF ≥50% with an accuracy of 78.6%, precision of 85.1%, sensitivity of 90.6%, specificity of 14.1%, and F1 score (harmonic mean of precision and sensitivity) of 87.7%; this was very similar to the PLS-DA model. Our results suggest that in general, LASSO and PLS-DA machine learning algorithms perform better for dietary GBF classification than RF or SVM algorithms.

Caleb Renner, Nathan Conroy, Evan Thaler et al.

Rainfall frequency and intensity are expected to increase in the Arctic, with potential detrimental impacts on permafrost, leading to enhanced thawing and carbon release to the atmosphere. However, there have been very few studies on the effect of discrete rain events on permafrost in the Arctic and sub-Arctic. Conducting controlled rainfall experiments within permafrost landscapes can provide an improved understanding of the effect of changing intensity, duration, and timing of rain events on permafrost tundra ecosystems. Here, we describe the design and implementation of the Next-Generation Ecosystem Experiment Arctic Rainfall Simulator (NARS), a variable intensity (4–82 mm/h) rainfall simulator that can be used to study the effects of rainfall on permafrost stability. The NARS design includes a 3D-printed 4 cm H-flume and uses an eTape resistivity sensor that was calibrated (R2 = 0.9–0.96) to measure discharge from the system. NARS is designed to be lightweight, simple to construct, and can be easily deployed in remote locations. As a field validation of updated rainfall simulator design and modernized controls, NARS was tested on the Seward Peninsula, AK. Because of its portability, versatility in deployment, dimensions, and rainfall intensity, NARS represents a methodological innovation for researching the impacts of rainfall on permafrost environments. HIGHLIGHTS Rainfall is expected to increase in the Arctic over the next century.; The effects of rainfall on permafrost stability are poorly understood.; We developed a variable intensity rainfall simulator for use in remote areas.; The new rainfall simulator is lightweight and modernizes simulator controls.; The simulator can be used to study rain effects on permafrost.;

Zixuan Wang, Yang Xiao, Taotao Zhang et al.

Study Region: Poyang Lake, the largest freshwater lake in China, has been experiencing persistent shrinkage in recent years. Study Focus: The Poyang Lake Hydraulic Project (PLHP) was proposed to improve water resource and environment carrying capacity, its hydrological effects remain under investigation. This study combined a hydrodynamic model with geostatistical connectivity analysis, to quantify the influence of the PLHP on surface water connectivity in Poyang Lake. New Hydrological Insights for the Region: The PLHP enlarges inundated areas most in the recession period (September-November), accounting for 85% of the total increase throughout the operating period (September-March), and enhances the interconnection probability within these inundated regions. Statistical analysis reveals that the Connectivity Function (CF) in low connectivity conditions (CF <0.4) can be significantly increased by 0.1–0.9, primarily in areas with lower topographies. While for the saucer-shaped sub-lakes, the PLHP can rarely extend the connecting processes between the main lake and sub-lakes in low-water-level conditions below 13 m, which is the lowest threshold height of most sub-lakes. Moreover, most isolated sub-lakes have merged into the main lake when the water level is higher than 14 m, thus the PLHP is no longer effective in this condition. Therefore, the enhancement effect of the PLHP on the connectivity of sub-lakes is restricted in both high- and low-water-level years, and is most pronounced in the medium-water-level year.

João Luís Jesus Fernandes

Xiazhong Zheng, Chenfei Duan, Yun Chen et al.

Study region: Major urban areas in Henan Province of central China. Study focus: data fusion technology is also a key and difficult point in the field of flood research. Remote sensing and text data have different modalities and scales, making fusion difficult. This study proposed a remote sensing and text bimodal data fusion model based on UFCLI, and we validated the spatiotemporal distribution of floods and the calculation results of disaster losses. The results show that through the coupling analysis of remote sensing and text bimodal data, rainstorm and flood events can be fully reproduced in space and time. The proposed UFCLI effectively improves the accuracy of remote sensing single-data inversion for urban flood disaster losses. The flood loss in Henan is 121.98 billion yuan, and the accuracy improvement result is R² increased by 0.08 and MAPE decreased by 0.88. New hydrological insights for the region: In the case of sudden urban storm flooding with complex spatial and temporal evolution, the traditional hydrological-hydraulic model has many pending parameters, which makes it difficult to accurately calculate large-scale disaster losses. By establishing a theoretical model of bimodal data fusion, we effectively use the complementary spatiotemporal information using remote sensing and text to solve the differences in spatiotemporal scales existing between remote sensing and text data. The timeliness and accuracy of urban flood damage estimation have further improved. Data Availability Statement: Not applicable.

Dilfuza Egamberdieva, Hua Ma, Vyacheslav Shurigin et al.

Numerous reports confirm a positive impact of biochar amendments on soil enzyme activities, nutrient cycles, and, finally, plant growth and development. However, reports explaining the process behind such diverse observations are scarce. The aim of the present study was (1) to evaluate the effect of biochar on the growth of purslane (<i>Portulaca oleracea</i> L.) and nutrients; (2) to determine the response of rhizosphere enzyme activities linked to soil phosphorus cycling after bio-char amendment under non–saline and saline soil conditions. Furthermore, we investigate whether adding biochar to soil alters the abundance of P-cycling-related bacteria. Two rates of biochar (2% and 4%) were applied in pot experiments. Biochar addition of 2% significantly increased plant growth under non-saline and saline soil conditions by 21% and 40%, respectively. Moreover, applying biochar increased soil microbial activity as observed by fluorescein diacetate (FDA) hydrolase activity, as well as phosphomonoesterase activities, and the numbers of colony-forming units (CFU) of P-mobilizing bacteria. Soil amended with 2% biochar concentration increased total soil nitrogen (Nt), phosphorus (P), and total carbon (Ct) concentrations by 18%, 15%, and 90% under non-saline soil conditions and by 29%, 16%, and 90% in saline soil compared the control, respectively. The soil FDA hydrolytic activity and phosphatase strongly correlate with soil Ct, Nt, and P contents. The rhizosphere soil collected after biochar amendment showed a higher abundance of tricalcium phosphate-solubilizing bacteria than the control soil without biochar. Overall, this study demonstrated that 2% maize-derived biochar positively affects halophyte plant growth and thus could be considered for potential use in the reclamation of degraded saline soil.

Ramin Gobejishvili, Emil Tsereteli

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