scholarly journals Natural and Human-Transformed Vegetation and Landscape Reflected by Modern Pollen Data in the Boreonemoral Zone of Northeastern Europe

Forests ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1166
Author(s):  
Normunds Stivrins ◽  
Agrita Briede ◽  
Dace Steinberga ◽  
Nauris Jasiunas ◽  
Jurijs Jeskins ◽  
...  
Keyword(s):  
Land Use ◽  
Surface Sediment ◽  
Vegetation Type ◽  
Accumulation Rate ◽  
Pearson Correlation ◽  
Forest Biomass ◽  
Principal Component ◽  
Vegetation Composition ◽  
Landscape Characteristics ◽  
Modern Pollen

Modern pollen composition obtained from waterbody surface sediment represents surrounding vegetation and landscape features. A lack of detailed information on modern pollen from Latvia potentially limits the strength of various pollen-based reconstructions (vegetation composition, climate, landscape, human impact) for this territory. The aim of this study is to compare how modern pollen from natural and human-made waterbodies reflects the actual vegetation composition and landscape characteristics. Modern pollen analyses from surface sediment samples of 36 waterbodies from Latvia alongside oceanic-continental, lowland-upland, urban-rural and forested-agricultural gradients have been studied. In addition, we considered the dominant Quaternary sediment, soil type and land use around the studied waterbodies in buffer zones with widths of one and four km. The information on climate for the last 30 years from the closest meteorological station for each study site was obtained. Data were analyzed using Pearson correlation and principal component analysis. Results show that relative pollen values from surface sediment of waterbodies reflect dominant vegetation type and land use. Modern forest biomass had a positive correlation with pollen accumulation rate, indicating the potential use of pollen-based forest biomass reconstructions for the boreonemoral zone after additional research and calibration.

scholarly journals Distribution of Geochemical Fractions of Phosphorus in Surface Sediment in Daya Bay, China

2020 ◽  
Vol 17 (12) ◽  
pp. 4430
Author(s):  
Hongping Liao ◽  
Ciguang Pan ◽  
Lian Gan ◽  
Zhixin Ke ◽  
Huijuan Tang
Keyword(s):  
Surface Sediment ◽  
Pearson Correlation ◽  
Principal Component ◽  
Extraction Methods ◽  
Molar Ratio ◽  
Daya Bay ◽  
Internal Source ◽  
Spatial Distributions ◽  
Dominant Form ◽  
Geochemical Fractions

Surface sediment samples were collected from 19 sites throughout Daya Bay, China, to study the concentrations, and spatial distributions of different fractions of phosphorus through sequential extraction methods. Like many coastal and marine areas, De-P was the dominant form of P, contributing 47.5% of TP, followed by O-P, contributing 25.5% of TP. Ex-P and Fe-P contribute the lowest to TP. The concentration of sedimentary TP ranged from 290.3~525.1 µg/g, with the average of 395.3 µg/g, which was a similar range to other estuaries and coastal areas. Based on the spatial distribution, Pearson correlation and Principal component analysis, different fractions of phosphorus showed different spatial distributions due to different sources. The molar ratio of organic carbon to phosphorus (TOC/O-P) ranged from 199 to 609, with the average of 413, which was much higher than the Redfield ratio, suggesting terrestrial sources of organic matter in Daya Bay surface sediment. The average bioavailable phosphorus was 149.6 µg/g and contributed 37.8% (24.6~56.0%) of TP, indicating that the surface sediments of Day Bay act as an important internal source of P.

scholarly journals PRIORITY AREAS FOR FOREST CONSERVATION, AIMING AT THE MAINTENANCE OF WATER RESOURCES, THROUGH THE MULTICRITERIA EVALUATION1

2017 ◽  
Vol 41 (1) ◽  
Author(s):  
Victor A M Silva ◽  
Kaline de Mello ◽  
Carlos Alberto Vettorazzi ◽  
Danilo Ribeiro da Costa ◽  
Roberta Averna Valente
Keyword(s):  
Land Use ◽  
Water Resources ◽  
Land Cover ◽  
Forest Conservation ◽  
Management Practices ◽  
Pearson Correlation ◽  
Pairwise Comparison ◽  
Land Use Land Cover ◽  
Priority Areas ◽  
Landscape Characteristics

Abstract Replacing the original land cover by other land uses, especially when it is associated with inadequate management practices, can cause changes in runoff and rainwater infiltration. This can result in above normal levels of soil erosion and sediment-carrying to the rivers and streams. The original land cover conservation in the watersheds is, therefore, essential for the maintenance of its water resources. In this context, the main objective of this study was to prioritize areas for forest conservation in two watersheds, aiming at maintaining the water availability, in terms of quantity and quality, for the public supply. The watersheds were selected considering their regional importance and because they are similar in terms of land use / land cover. The study was developed in the Multicriteria Evaluation (MCE) context, which permits the integration of different landscape characteristics (i.e. factors), in order to obtain a solution for the decision-making process. The following criteria were selected by considering the expert's opinions: slope, flow accumulation, aspect, and land use / land cover. Their relative importance (i.e. factor weight) was defined through the Pairwise Comparison Method. The criteria maps units were normalized by a common scale and then aggregated through an MCE method named Weighted Linear Combination (WLC). Pearson correlation was used to evaluate the criteria contribution on the final map. The watershed 1 was classified in approximately 14% of its area as very high priority; 27% as high; 19% as medium; 21% as low; and 18% as very low. The watershed 2 obtained, respectively, 17%; 29%; 17%; 21%; e 17%. We conclude that the WLC method supports the definition of priority areas for forest conservation in the watersheds, in order to have an appropriate design of actions for forest conservation.

scholarly journals Lake surface-sediment pollen dataset for the alpine meadow vegetation type from the eastern Tibetan Plateau and its potential in past climate reconstructions

2021 ◽  
Author(s):  
Xianyong Cao ◽  
Fang Tian ◽  
Kai Li ◽  
Jian Ni ◽  
Xiaoshan Yu ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Surface Sediment ◽  
Alpine Meadow ◽  
Vegetation Type ◽  
Weighted Averaging ◽  
Climatic Data ◽  
The Tibetan Plateau ◽  
Eastern Tibetan Plateau ◽  
Lake Surface ◽  
Modern Pollen

Abstract. A modern pollen dataset with an even distribution of sites is essential for pollen-based past vegetation and climate estimations. As there were geographical gaps in previous datasets covering the central and eastern Tibetan Plateau, lake surface-sediment samples (n=117) were collected from the alpine meadow region on the Tibetan Plateau between elevations of 3720 and 5170 m a.s.l. Pollen identification and counting were based on standard approaches, and modern climate data were interpolated from a robust modern meteorological dataset. A series of numerical analyses revealed that precipitation is the main climatic determinant of pollen spatial distribution; Cyperaceae, Ranunculaceae, Rosaceae, and Salix indicate wet climatic conditions, while Poaceae, Artemisia, and Chenopodiaceae represent drought. Model performance of both weighted-averaging partial least squares (WA-PLS) and the random forest (RF) algorithm suggest that this modern pollen dataset has good predictive power in estimating the past precipitation for pollen spectra from the eastern Tibetan Plateau. In addition, a comprehensive modern pollen dataset can be established by combining our modern pollen dataset with previous datasets, which will be essential for the reconstruction of vegetation and climatic signals for fossil pollen sprecta on the Tibetan Plateau. Pollen datasets including both pollen counts and percentages for each sample together with their site location and climatic data are available at the National Tibetan Plateau Data Center (TPDC; DOI: 10.11888/Paleoenv.tpdc.271191).

scholarly journals Lake surface sediment pollen dataset for the alpine meadow vegetation type from the eastern Tibetan Plateau and its potential in past climate reconstructions

2021 ◽  
Vol 13 (7) ◽  
pp. 3525-3537
Author(s):  
Xianyong Cao ◽  
Fang Tian ◽  
Kai Li ◽  
Jian Ni ◽  
Xiaoshan Yu ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Surface Sediment ◽  
Alpine Meadow ◽  
Vegetation Type ◽  
Weighted Averaging ◽  
Climatic Data ◽  
The Tibetan Plateau ◽  
Eastern Tibetan Plateau ◽  
Lake Surface ◽  
Modern Pollen

Abstract. A modern pollen dataset with an even distribution of sites is essential for pollen-based past vegetation and climate estimations. As there were geographical gaps in previous datasets covering the central and eastern Tibetan Plateau, lake surface sediment samples (n=117) were collected from the alpine meadow region on the Tibetan Plateau between elevations of 3720 and 5170 m a.s.l. Pollen identification and counting were based on standard approaches, and modern climate data were interpolated from a robust modern meteorological dataset. A series of numerical analyses revealed that precipitation is the main climatic determinant of pollen spatial distribution: Cyperaceae, Ranunculaceae, Rosaceae, and Salix indicate wet climatic conditions, while Poaceae, Artemisia, and Chenopodiaceae represent drought. Model performance of both weighted-averaging partial least squares (WA-PLS) and the random forest (RF) algorithm suggest that this modern pollen dataset has good predictive power in estimating the past precipitation from pollen spectra from the eastern Tibetan Plateau. In addition, a comprehensive modern pollen dataset can be established by combining our modern pollen dataset with previous datasets, which will be essential for the reconstruction of vegetation and climatic signals for fossil pollen spectra on the Tibetan Plateau. Pollen datasets including both pollen counts and percentages for each sample, together with their site location and climatic data, are available at the National Tibetan Plateau Data Center (TPDC; Cao et al., 2021; https://doi.org/10.11888/Paleoenv.tpdc.271191).

scholarly journals Bioprospecting of Sechium spp. varieties for the selection of characters with pharmacological activity

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
María Isabel Iñiguez-Luna ◽  
Jorge Cadena-Iñiguez ◽  
Ramón Marcos Soto-Hernández ◽  
Francisco Javier Morales-Flores ◽  
Moisés Cortes-Cruz ◽  
...  
Keyword(s):  
Cell Lines ◽  
Proliferative Activity ◽  
Meta Analysis ◽  
Pearson Correlation ◽  
Statistical Significance ◽  
Economic Value ◽  
Principal Component ◽  
Malignant Cell ◽  
Length Polymorphisms ◽  
Relevant Variables

AbstractBioprospecting identifies new sources of compounds with actual or potential economic value that come from biodiversity. An analysis was performed regarding bioprospecting purposes in ten genotypes of Sechium spp., through a meta-analysis of 20 information sources considering different variables: five morphological, 19 biochemical, anti-proliferative activity of extracts on five malignant cell lines, and 188 polymorphic bands of amplified fragment length polymorphisms, were used in order to identify the most relevant variables for the design of genetic interbreeding. Significant relationships between morphological and biochemical characters and anti-proliferative activity in cell lines were obtained, with five principal components for principal component analysis (SAS/ETS); variables were identified with a statistical significance (< 0.7 and Pearson values ≥ 0.7), with 80.81% of the accumulation of genetic variation and 110 genetic bands. Thirty-nine (39) variables were recovered using NTSYSpc software where 30 showed a Pearson correlation (> 0.5) and nine variables (< 0.05), Finally, using a cladistics analysis approach highlighted 65 genetic bands, in addition to color of the fruit, presence of thorns, bitter flavor, piriform and oblong shape, and also content of chlorophylls a and b, presence of cucurbitacins, and the IC50 effect of chayote extracts on the four cell lines.

scholarly journals Comparison of Capability of SAR and Optical Data in Mapping Forest above Ground Biomass Based on Machine Learning

2020 ◽  
Vol 5 (1) ◽  
pp. 13
Author(s):  
Negar Tavasoli ◽  
Hossein Arefi
Keyword(s):  
Machine Learning ◽  
Carbon Stock ◽  
Vegetation Indices ◽  
Forest Biomass ◽  
Principal Component ◽  
Optical Data ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Texture Characteristics ◽  
Sentinel 2

Assessment of forest above ground biomass (AGB) is critical for managing forest and understanding the role of forest as source of carbon fluxes. Recently, satellite remote sensing products offer the chance to map forest biomass and carbon stock. The present study focuses on comparing the potential use of combination of ALOSPALSAR and Sentinel-1 SAR data, with Sentinel-2 optical data to estimate above ground biomass and carbon stock using Genetic-Random forest machine learning (GA-RF) algorithm. Polarimetric decompositions, texture characteristics and backscatter coefficients of ALOSPALSAR and Sentinel-1, and vegetation indices, tasseled cap, texture parameters and principal component analysis (PCA) of Sentinel-2 based on measured AGB samples were used to estimate biomass. The overall coefficient (R2) of AGB modelling using combination of ALOSPALSAR and Sentinel-1 data, and Sentinel-2 data were respectively 0.70 and 0.62. The result showed that Combining ALOSPALSAR and Sentinel-1 data to predict AGB by using GA-RF model performed better than Sentinel-2 data.

scholarly journals Towards Understanding Variability in Droughts in Response to Extreme Climate Conditions over the Different Agro-Ecological Zones of Pakistan

2021 ◽  
Vol 13 (12) ◽  
pp. 6910
Author(s):  
Adil Dilawar ◽  
Baozhang Chen ◽  
Arfan Arshad ◽  
Lifeng Guo ◽  
Muhammad Irfan Ehsan ◽  
...  
Keyword(s):  
Pearson Correlation ◽  
Principal Component ◽  
Mitigation Strategies ◽  
Precipitation Extremes ◽  
Climate Mitigation ◽  
Mean Annual Temperature ◽  
Climate Extreme ◽  
Ecological Zones ◽  
The Mean ◽  
Agro Ecological Zones

Here, we provided a comprehensive analysis of long-term drought and climate extreme patterns in the agro ecological zones (AEZs) of Pakistan during 1980–2019. Drought trends were investigated using the standardized precipitation evapotranspiration index (SPEI) at various timescales (SPEI-1, SPEI-3, SPEI-6, and SPEI-12). The results showed that droughts (seasonal and annual) were more persistent and severe in the southern, southwestern, southeastern, and central parts of the region. Drought exacerbated with slopes of −0.02, −0.07, −0.08, −0.01, and −0.02 per year. Drought prevailed in all AEZs in the spring season. The majority of AEZs in Pakistan’s southern, middle, and southwestern regions had experienced substantial warming. The mean annual temperature minimum (Tmin) increased faster than the mean annual temperature maximum (Tmax) in all zones. Precipitation decreased in the southern, northern, central, and southwestern parts of the region. Principal component analysis (PCA) revealed a robust increase in temperature extremes with a variance of 76% and a decrease in precipitation extremes with a variance of 91% in the region. Temperature and precipitation extremes indices had a strong Pearson correlation with drought events. Higher temperatures resulted in extreme drought (dry conditions), while higher precipitation levels resulted in wetting conditions (no drought) in different AEZs. In most AEZs, drought occurrences were more responsive to precipitation. The current findings are helpful for climate mitigation strategies and specific zonal efforts are needed to alleviate the environmental and societal impacts of drought.

scholarly journals Ecological Risk Assessment and Contamination History of Heavy Metals in the Sediments of Chagan Lake, Northeast China

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 894
Author(s):  
Panfeng Liu ◽  
Chaojie Zheng ◽  
Meilan Wen ◽  
Xianrong Luo ◽  
Zhiqiang Wu ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Principal Component Analysis ◽  
Ecological Risk ◽  
Surface Sediment ◽  
Northeast China ◽  
Principal Component ◽  
Potential Ecological Risk ◽  
210Pb Dating ◽  
History Of ◽  
Chagan Lake

The study deals with the spatio-temporal distribution of heavy metals in the sediments of Chagan lake, Northeast China. The pollution history of heavy metals is studied simultaneously through the 210Pb dating method by analyzing the characteristic of As, Hg, Cd, Cr, Ni, Cu, Pb, and Zn concentration-depth profiles. The potential ecological risk index (RI) and geo-accumulation index (Igeo) were used to evaluate the contamination degree. Principal component analysis (PCA), based on the logarithmic transformation and isometric log-ratio (ilr) transformed data, was applied with the aim of identifying the sources of heavy metals. The element concentrations show that the heavy metals are enriched in the surface sediment and sediment core with a varying degree, which is higher in the surficial residue. The results of Igeo indicate that the Cd and Hg in the surface sediment have reached a slightly contaminated level while other elements, uncontaminated. The results of RI show that the study area can be classified as an area with moderate ecological risk in which Cd and Hg mostly contribute to the overall risk. For the sediment core, the 210Pb dating results accurately reflect the sedimentary history over 153 years. From two evaluation indices (RI and Igeo) calculated by element concentration, there is no contamination, and the potential ecological risk is low during this period. The comparative study between raw and ilr transformed data shows that the closure effect of the raw data can be eliminated by ilr transformation. After that, the components obtained by robust principal component analysis (RPCA) are more representative than those obtained by PCA, both based on ilr transformed dataset, after eliminating the influence of outliers. Based on ilr transformed data with RPCA, three primary sources could be inferred: Cr, Ni, As, Zn, and Cu are mainly derived from natural sources; the main source of Cd and Hg are associated with agricultural activities and energy development; as for Pb, it originated from traffic and coal-burning activities, which is consistent with the fact that the development of tourism, fishery, and agriculture industries has led to the continuous increasing levels of anthropogenic Pb in Chagan Lake. The summarized results and conclusions will undoubtedly enhance the governmental awareness of heavy metal pollution and facilitate appropriate pollution control measures in Chagan Lake.

scholarly journals Key soil parameters affecting the survival of Panax notoginseng under continuous cropping

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Wumei Xu ◽  
Fengyun Wu ◽  
Haoji Wang ◽  
Linyan Zhao ◽  
Xue Liu ◽  
...  
Keyword(s):  
Soil Ph ◽  
Pearson Correlation ◽  
Principal Component ◽  
Panax Notoginseng ◽  
Soil Parameters ◽  
Continuous Cropping ◽  
Poor Growth ◽  
Available N ◽  
The Poor ◽  
Replant Problem

AbstractNegative plant-soil feedbacks lead to the poor growth of Panax notoginseng (Sanqi), a well-known herb in Asia and has been used worldwide, under continuous cropping. However, the key soil parameters causing the replant problem are still unclear. Here we conducted a field experiment after 5-year continuous cropping. Sanqi seedlings were cultivated in 7 plots (1.5 m × 2 m), which were randomly assigned along a survival gradient. In total, 13 important soil parameters were measured to understand their relationship with Sanqi’s survival. Pearson correlation analysis showed that 6 soil parameters, including phosphatase, urease, cellulase, bacteria/fungi ratio, available N, and pH, were all correlated with Sanqi’s survival rate (P < 0.05). Principal component analysis (PCA) indicated that they explained 61% of the variances based on the first component, with soil pH being closely correlated with other parameters affecting Sanqi’s survival. The optimum pH for Sanqi growth is about 6.5, but the mean soil pH in the study area is 5.27 (4.86–5.68), therefore it is possible to ameliorate the poor growth of Sanqi by increasing soil pH. This study may also help to reduce the replant problem of other crops under continuous cropping since it is widespread in agricultural production.

scholarly journals Effects of habitat structure and land-use intensity on the genetic structure of the grasshopper species Chorthippus parallelus

2014 ◽  
Vol 1 (2) ◽  
pp. 140133 ◽  
Author(s):  
Kerstin R. Wiesner ◽  
Jan Christian Habel ◽  
Martin M. Gossner ◽  
Hugh D. Loxdale ◽  
Günter Köhler ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Land Use ◽  
Genetic Structure ◽  
Sampling Site ◽  
Land Use Intensity ◽  
Habitat Size ◽  
Grasshopper Species ◽  
Chorthippus Parallelus ◽  
Landscape Characteristics ◽  
Local Populations

Land-use intensity (LUI) is assumed to impact the genetic structure of organisms. While effects of landscape structure on the genetics of local populations have frequently been analysed, potential effects of variation in LUI on the genetic diversity of local populations have mostly been neglected. In this study, we used six polymorphic microsatellites to analyse the genetic effects of variation in land use in the highly abundant grasshopper Chorthippus parallelus . We sampled a total of 610 individuals at 22 heterogeneous grassland sites in the Hainich-Dün region of Central Germany. For each of these grassland sites we assessed habitat size, LUI (combined index of mowing, grazing and fertilization), and the proportion of grassland adjoining the sampling site and the landscape heterogeneity (the latter two factors within a 500 m buffer zone surrounding each focal site). We found only marginal genetic differentiation among all local populations and no correlation between geographical and genetic distance. Habitat size, LUI and landscape characteristics had only weak effects on most of the parameters of genetic diversity of C. parallelus ; only expected heterozygosity and the grasshopper abundances were affected by interacting effects of LUI, habitat size and landscape characteristics. The lack of any strong relationships between LUI, abundance and the genetic structure might be due to large local populations of the species in the landscape, counteracting local differentiation and potential genetic drift effects.

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