The influence of land use on stream biofilm nutrient limitation across eight North American ecoregions

2009 ◽  
Vol 66 (7) ◽  
pp. 1081-1094 ◽  
Author(s):  
Laura T. Johnson ◽  
Jennifer L. Tank ◽  
Walter K. Dodds
Keyword(s):  
Land Use ◽  
Nutrient Limitation ◽  
Nutrient Enrichment ◽  
Inorganic Nitrogen ◽  
Gross Primary Production ◽  
Urban Land Use ◽  
P Availability ◽  
Chl A ◽  
Land Use Types ◽  
Inorganic And Organic

Nutrient diffusing substrata were used to determine the influence of inorganic nitrogen (N) and phosphorus (P) availability on community respiration (CR), gross primary production (GPP), and chlorophyll a (chl a) on inorganic and organic substrata. We incubated substrata in nine streams each in a total of eight ecoregions (n = 72 streams) located in a range of native vegetation, agriculture, and urban land-use types. On organic substrata, CR was nutrient-limited in 94% of reference streams but showed significant nutrient limitation in only 60% and 65% of agricultural and urban streams, respectively. The relative magnitude of nutrient limitation for CR on organic substrata decreased with increasing percent modified land use in the basin (agriculture + urban). On inorganic and organic substrata, GPP and chl a were rarely nutrient-limited across all ecoregions and land-use types, although the magnitude of nutrient limitation increased with increasing light availability. The effect of human land use on nutrient limitation of biofilm CR, GPP, and chl a was influenced by ecoregion, yet heterotrophic biofilms were consistently most sensitive to nutrient enrichment across ecoregions. Both heterotrophic and autotrophic biofilm constituents should be considered to fully understand stream ecosystem responses to nutrient enrichment.

scholarly journals Patterns in nutrient limitation and chlorophyll a along an anthropogenic eutrophication gradient in French Mediterranean coastal lagoons

2010 ◽  
Vol 67 (4) ◽  
pp. 743-753 ◽  
Author(s):  
Philippe Souchu ◽  
Béatrice Bec ◽  
Val H. Smith ◽  
Thierry Laugier ◽  
Annie Fiandrino ◽  
...  
Keyword(s):  
Nutrient Limitation ◽  
Chlorophyll A ◽  
Nutrient Enrichment ◽  
Coastal Waters ◽  
Coastal Lagoons ◽  
Inorganic Nitrogen ◽  
Nutrient Concentrations ◽  
Chl A ◽  
Mediterranean Lagoons ◽  
Ecosystem Comparison

A cross-ecosystem comparison of data obtained from 20 French Mediterranean lagoons with contrasting eutrophication status provided the basis for investigating the variables that best predict chlorophyll a (Chl a) concentrations and nutrient limitation of phytoplankton biomass along a strong nutrient enrichment gradient. Summer concentrations of dissolved inorganic nitrogen (DIN) and phosphorus (DIP) comprised only a small fraction of total nitrogen (TN) and total phosphorus (TP). On the basis of inorganic nutrient concentrations, the most oligotrophic lagoons appeared to be phosphorus-limited, with a tendency towards the development of nitrogen limitation as eutrophication increased, as evidenced by decreasing DIN:DIP ratios. A weak but significantly positive relationship was found between dissolved silicate (DSi) and Chl a, reflecting DSi accumulation in the water column along the trophic state gradient and implying a progressive shift away from potential Si limitation of phytoplankton growth. Observed concentrations of Chl a were far better explained by TN and TP than by DIN and DIP concentrations, suggesting that a total nutrient based approach is likely to be the most appropriate for managing eutrophication in Mediterranean lagoons and other coastal waters. These results give credence to the idea that marine and freshwater environments respond in a similar fashion to nutrient enrichment.

THE IMPACT OF DIFFERENT URBAN LAND USE TYPES ON AIR POLLUTION IN THE MEGACITY OF SÃO PAULO

2020 ◽  
Vol 7 (1) ◽  
pp. 91
Author(s):  
Júlio Barboza Chiquetto ◽  
Maria Elisa Siqueira Silva ◽  
Rita Yuri Ynoue ◽  
Flávia Noronha Dutra Ribieiro ◽  
Débora Souza Alvim ◽  
...  
Keyword(s):  
Land Use ◽  
Air Pollution ◽  
Urban Land ◽  
Sao Paulo ◽  
Urban Land Use ◽  
São Paulo ◽  
Land Use Types ◽  
The Impact

A poluição do ar é influenciada por fatores naturais e antropogênicos. Quatro pontos de monitoramento (veicular, comercial, residencial e background urbano (BGU))da poluição do ar em São Paulo foram avaliados durante 16 anos, revelando diferenças significativas devidoao uso do solo em todas as escalas temporais. Na escala diurna, as concentrações de poluentes primários são duas vezes mais altas nos pontos veicular e residencial do que no ponto BGU, onde a concentração de ozonio (O3) é 50% mais alta. Na escala sazonal, as concentrações de monóxido de carbono(CO) variaram em 80% devido ao uso do solo, e 55% pela sazonalidade.As variações sazonais ede uso do solo exercem impactos similares nas concentrações de O3 e monóxido de nitrogênio (NO). Para o material particulado grosso (MP10) e o dióxido de nitrogênio(NO2), as variações sazonais são mais intensas do que as por uso do solo. Na série temporal de 16 anos, o ponto BGU apresentou correlações mais fortes e significativas entre a média mensal de ondas longas (ROL) e o O3 (0,48) e o MP10 (0,37), comparadas ao ponto veicular (0,33 e 0,22, respectivamente). Estes resultados confirmam que o uso do solo urbano tem um papel significativo na concentração de poluentes em todas as escalas de análise, embora a sua influência se torne menos pronunciada em escalas maiores, conforme a qualidade do ar transita de um sistema antropogênico para um sistema natural. Isto poderá auxiliar decisões sobre políticas públicas em megacidades envolvendo a modificação do uso do solo.

scholarly journals Micropollutants in Urban Stormwater Runoff of Different Land Uses

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1312
Author(s):  
Daniel Wicke ◽  
Andreas Matzinger ◽  
Hauke Sonnenberg ◽  
Nicolas Caradot ◽  
Rabea-Luisa Schubert ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Land Use ◽  
Surface Waters ◽  
Flame Retardants ◽  
Stormwater Runoff ◽  
Monitoring Program ◽  
Quality Standards ◽  
Urban Land Use ◽  
Organic Micropollutants ◽  
Land Use Types

The main aim of this study was a survey of micropollutants in stormwater runoff of Berlin (Germany) and its dependence on land-use types. In a one-year monitoring program, event mean concentrations were measured for a set of 106 parameters, including 85 organic micropollutants (e.g., flame retardants, phthalates, pesticides/biocides, polycyclic aromatic hydrocarbons (PAH)), heavy metals and standard parameters. Monitoring points were selected in five catchments of different urban land-use types, and at one urban river. We detected 77 of the 106 parameters at least once in stormwater runoff of the investigated catchment types. On average, stormwater runoff contained a mix of 24 µg L−1 organic micropollutants and 1.3 mg L−1 heavy metals. For organic micropollutants, concentrations were highest in all catchments for the plasticizer diisodecyl phthalate. Concentrations of all but five parameters showed significant differences among the five land-use types. While major roads were the dominant source of traffic-related substances such as PAH, each of the other land-use types showed the highest concentrations for some substances (e.g., flame retardants in commercial area, pesticides in catchment dominated by one family homes). Comparison with environmental quality standards (EQS) for surface waters shows that 13 micropollutants in stormwater runoff and 8 micropollutants in the receiving river exceeded German quality standards for receiving surface waters during storm events, highlighting the relevance of stormwater inputs for urban surface waters.

scholarly journals A Novel Query Strategy-Based Rank Batch-Mode Active Learning Method for High-Resolution Remote Sensing Image Classification

2021 ◽  
Vol 13 (11) ◽  
pp. 2234
Author(s):  
Xin Luo ◽  
Huaqiang Du ◽  
Guomo Zhou ◽  
Xuejian Li ◽  
Fangjie Mao ◽  
...  
Keyword(s):  
Land Use ◽  
Active Learning ◽  
Euclidean Distance ◽  
Urban Land Use ◽  
Misclassification Rate ◽  
Training Set ◽  
Batch Mode ◽  
Land Use Types ◽  
Information Divergence ◽  
Uncertainty Score

An informative training set is necessary for ensuring the robust performance of the classification of very-high-resolution remote sensing (VHRRS) images, but labeling work is often difficult, expensive, and time-consuming. This makes active learning (AL) an important part of an image analysis framework. AL aims to efficiently build a representative and efficient library of training samples that are most informative for the underlying classification task, thereby minimizing the cost of obtaining labeled data. Based on ranked batch-mode active learning (RBMAL), this paper proposes a novel combined query strategy of spectral information divergence lowest confidence uncertainty sampling (SIDLC), called RBSIDLC. The base classifier of random forest (RF) is initialized by using a small initial training set, and each unlabeled sample is analyzed to obtain the classification uncertainty score. A spectral information divergence (SID) function is then used to calculate the similarity score, and according to the final score, the unlabeled samples are ranked in descending lists. The most “valuable” samples are selected according to ranked lists and then labeled by the analyst/expert (also called the oracle). Finally, these samples are added to the training set, and the RF is retrained for the next iteration. The whole procedure is iteratively implemented until a stopping criterion is met. The results indicate that RBSIDLC achieves high-precision extraction of urban land use information based on VHRRS; the accuracy of extraction for each land-use type is greater than 90%, and the overall accuracy (OA) is greater than 96%. After the SID replaces the Euclidean distance in the RBMAL algorithm, the RBSIDLC method greatly reduces the misclassification rate among different land types. Therefore, the similarity function based on SID performs better than that based on the Euclidean distance. In addition, the OA of RF classification is greater than 90%, suggesting that it is feasible to use RF to estimate the uncertainty score. Compared with the three single query strategies of other AL methods, sample labeling with the SIDLC combined query strategy yields a lower cost and higher quality, thus effectively reducing the misclassification rate of different land use types. For example, compared with the Batch_Based_Entropy (BBE) algorithm, RBSIDLC improves the precision of barren land extraction by 37% and that of vegetation by 14%. The 25 characteristics of different land use types screened by RF cross-validation (RFCV) combined with the permutation method exhibit an excellent separation degree, and the results provide the basis for VHRRS information extraction in urban land use settings based on RBSIDLC.

Urban land use types contribute to grassland conservation: The example of Berlin

2013 ◽  
Vol 12 (3) ◽  
pp. 263-272 ◽  
Author(s):  
Leonie K. Fischer ◽  
Moritz von der Lippe ◽  
Ingo Kowarik
Keyword(s):  
Land Use ◽  
Urban Land ◽  
Urban Land Use ◽  
Grassland Conservation ◽  
Land Use Types

scholarly journals Inferring Urban Land Use from Multi-Source Urban Mobility Data Using Latent Multi-View Subspace Clustering

2021 ◽  
Vol 10 (5) ◽  
pp. 274
Author(s):  
Qiliang Liu ◽  
Weihua Huan ◽  
Min Deng ◽  
Xiaolin Zheng ◽  
Haotao Yuan
Keyword(s):  
Land Use ◽  
Subspace Clustering ◽  
Urban Land ◽  
Urban Land Use ◽  
Single Type ◽  
Underlying Structure ◽  
Urban Mobility ◽  
Trajectory Data ◽  
Mobility Data ◽  
Land Use Types

In the era of big data, vast urban mobility data introduce new opportunities to infer urban land use from the perspective of social function. Most existing works only derive land use information from a single type of urban mobility dataset, which is typically biased and results in difficulty obtaining a comprehensive view of urban land use. It remains challenging to fuse high-dimensional and noisy multi-source urban mobility data to infer urban land use. This study aimed to infer urban land use from multi-source urban mobility data using latent multi-view subspace clustering. The variation in the number of origin/destination points over time was initially used to characterize land use types. Then, a latent multi-view representation was applied to construct the common underlying structure shared by multi-source urban mobility data and effectively deal with noise. Finally, based on the latent multi-view representation, the subspace clustering method was used to infer the land use types. Experiments on taxi trajectory data and bus smart card data in Beijing reveal that, compared with the method using a single type of urban mobility dataset and the weighted fusion method, the approach presented in this study obtains the highest detection rate of land use. The urban land use inferred in this study provides calibration and reference for urban planning.

scholarly journals Spatial-Temporal Analysis of Human Dynamics on Urban Land Use Patterns Using Social Media Data by Gender

2018 ◽  
Vol 7 (9) ◽  
pp. 358 ◽  
Author(s):  
Chengcheng Lei ◽  
An Zhang ◽  
Qingwen Qi ◽  
Huimin Su ◽  
Jianghao Wang
Keyword(s):  
Land Use ◽  
Urban Land Use ◽  
Moran’S I ◽  
Land Use Patterns ◽  
Moran's I ◽  
Residential Land ◽  
Human Dynamics ◽  
Use Patterns ◽  
Land Use Types ◽  
Olympic Village

The relationship between urban human dynamics and land use types has always been an important issue in the study of urban problems in China. This paper used location data from Sina Location Microblog (commonly known as Weibo) users to study the human dynamics of the spatial-temporal characteristics of gender differences in Beijing’s Olympic Village in June 2014. We applied mathematical statistics and Local Moran’s I to analyze the spatial-temporal distribution of Sina Microblog users in 100 m × 100 m grids and land use patterns. The female users outnumbered male users, and the sex ratio ( S R varied under different land use types at different times. Female users outnumbered male users regarding residential land and public green land, but male users outnumbered female users regarding workplace, especially on weekends, as the S R on weekends ( S R was 120.5) was greater than that on weekdays ( S R was 118.8). After a Local Moran’s I analysis, we found that High–High grids are primarily distributed across education and scientific research land and residential land; these grids and their surrounding grids have more female users than male users. Low–Low grids are mainly distributed across sports centers and workplaces on weekdays; these grids and their surrounding grids have fewer female users than male users. The average number of users on Saturday was the highest value and, on weekends, the number of female and male users both increased in commercial land, but male users were more active than female users ( S R was 110).

Relative importance of urban and non-urban land-use types for potential denitrification derived N2O: insights from a regional study

2018 ◽  
Vol 109 (3-4) ◽  
pp. 453-460
Author(s):  
Hui-Juan XU ◽  
Manuel DELGADO-BAQUERIZO ◽  
Fu-Xia PAN ◽  
Xin-Li AN ◽  
Brajesh K. SINGH ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Land Use ◽  
Soil Ph ◽  
Human Activities ◽  
Regional Scale ◽  
Urban Land ◽  
Urban Land Use ◽  
Relative Importance ◽  
Potential Denitrification ◽  
Land Use Types

ABSTRACTIdentifying the relative importance of urban and non-urban land-use types for potential denitrification derived N2O at a regional scale is critical for quantifying the impacts of human activities on nitrous oxide (N2O) emission under changing environments. In this study we used a regional dataset from China including 197 soil samples and six land-use types to evaluate the main predictors (land use, heavy metals, soil pH, soil moisture, substrate availability, functional and broad microbial abundances) of potential denitrification using multivariate and pathway analysis. Our results provide empirical evidence that soils on farms have the greatest potential denitrifying ability (PDA) (10.92±6.08ng N2O-N·g–1 dry soil·min–1) followed by urban soil (6.80±5.35ng N2O-N·g–1 dry soil·min–1). Our models indicate that land use (low vs. high human activity), followed by total nitrogen (TN) and heavy metals (Cu, Zn, Pb, Cd) was the most important driver of PDA. In addition, our path analysis suggests that at least part of the impacts of land use on potential denitrification were mediated via microbial abundance, soil pH and substrates including TN, dissolved organic carbon and nitrate. This study identifies the main predictors of denitrification at a regional scale which is needed to quantify the impact of human activities on ecosystem functionality under changing conditions.

scholarly journals Spatial-temporal patterns of inorganic nitrogen air concentrations and deposition in eastern China

2018 ◽  
Author(s):  
Wen Xu ◽  
Lei Liu ◽  
Miaomiao Cheng ◽  
Yuanhong Zhao ◽  
Lin Zhang ◽  
...  
Keyword(s):  
Land Use ◽  
Seasonal Variation ◽  
Dry Deposition ◽  
Inorganic Nitrogen ◽  
Eastern China ◽  
N Deposition ◽  
Organic Fertilizers ◽  
Deposition Fluxes ◽  
Significant Seasonal Variation ◽  
Land Use Types

Abstract. Five-year (2011–2015) measurements of gaseous NH3, NO2 and HNO3 and particulate NH4+ and NO3− in air and/or precipitation were conducted at twenty-seven sites in a Nationwide Nitrogen Deposition Monitoring Network (NNDMN) to better understand spatial and temporal (seasonal and annual) characteristics of reactive nitrogen (Nr) concentrations and deposition in eastern China. Our observations reveal annual average concentrations (16.4–32.6 μg N m−3), dry deposition fluxes (15.8–31.7 kg N ha−1 yr−1) and wet/bulk deposition fluxes (18.4–28.0 kg N ha−1 yr−1) based on land use were ranked as urban > rural > background sites. Annual concentrations and dry deposition fluxes of each Nr species in air were comparable at urban and background sites in northern and southern regions, but were significantly higher at northern rural sites. These results, together with good agreement between spatial distributions of NH3 and NO2 concentrations determined from ground measurements and satellite observations, demonstrate that atmospheric Nr pollution is heavier in the northern region than in the southern region. No significant inter-annual trends were found in the annual Nr dry and wet/bulk N deposition at almost all of the selected sites. A lack of significant changes in annual averages between the 2013–2015 and 2011–2012 periods for all land use types, suggests that any effects of current emission controls are not yet apparent in Nr pollution and deposition in the region. Ambient concentrations of total Nr exhibited a non-significant seasonal variation at all land use types, although significant seasonal variations were found for individual Nr species (e.g., NH3, NO2 and pNO3−) in most cases. In contrast, dry deposition of total Nr exhibited a consistent and significant seasonal variation at all land use types, with the highest fluxes in summer and the lowest in winter. Based on sensitivity tests by the GEOS-Chem model, we found that NH3 emissions from fertilizer use (including chemical and organic fertilizers) were the largest contributor (36 %) to total inorganic Nr deposition over eastern China. Our results not only improve the understanding of spatial-temporal variations of Nr concentrations and deposition in this pollution hotspot, but also provide useful information for policy-makers that mitigation of NH3 emissions should be a priority to tackle serious N deposition in eastern China.

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