Blog List

Wednesday, 7 December 2016

Long-term influences on nitrogen dynamics and pH in an acidic sandy soil after single and multi-year applications of alkaline treated biosolids

Published Date
1 October 2015, Vol.208:111, doi:10.1016/j.agee.2015.04.010

Author 
  • G.W. Price a,,
  • T. Astatkie a
  • J.D. Gillis b
  • K. Liu c
  • aDepartment of Engineering, Faculty of Agriculture, Dalhousie University, Truro, Nova Scotia B2N 5E3, Canada
  • bDepartment of Bioresource Engineering, McGill University, Faculty of Agricultural and Environmental Sciences, Macdonald-Stewart Building MS1-027, 21111 Lakeshore Road, Sainte-Anne-de-Bellevue, Quebec H9X 3V9, Canada
  • cDepartment of Soil Science, Faculty of Agricultural and Food Sciences, University of Manitoba, Winnipeg, Manitoba R3T 2N2, Canada

Highlights
  • Raising soil pH depends on annual applications of alkaline treated biosolids.
  • One-time use of biosolids at high rates moderately alters long term soil pH.
  • Nitrogen mineralization of biosolids were greatest at the two highest rates.
  • Annual applications of biosolids increased long term soil nitrogen concentrations.
Abstract

We present results of a four year field study examining the changes in seasonal soil mineral nitrogen (SMN) and soil pH from the application of an alkaline treated biosolid (ATB) in an acidic sandy loam soil. Results of two management practices, annual ATB applications and a single application, and different rates of ATB (0, 7, 14, 28 and 42 Mg ha−1) were also compared over the four year study period. Corn (Zea mays L.) was used as the test crop throughout the study. Soil pH was effectively modified in all treatments receiving ATB rates, compared to the control, under both management practices but best results were achieved under annual ATB application. Soil cation exchange capacity was increased under annual ATB applications, by 3× at the highest ATB. Compared to the control, soil nitrogen and pH displayed significant changes under frequent additions with increasing rates of ATB. Our results indicate that a single application at the highest ATB rate had a residual effect on soil pH but little impact on subsequent SMN dynamics. Average soil mineral nitrogen (SMN) concentrations in the single application management ranged from 8.3 to 9.3 mg kg−1in the final three years of the study but ranged from 8.5 to 12.1 mg kg−1 under the annual application management. In contrast, annual applications of ATB at rates ≥14 Mg ha−1 increased seasonal SMN by 15–42% and soil pH by 1–1.5 pH units. Seasonal SMN dynamics under different ATB rates and management practices were also examined using a soil nitrogen ratio (SNR) and as an area under the seasonal SMN curve.

Abbreviations

  • ATB, alkaline treated biosolids
  • AUC, area under the curve
  • N, nitrogen
  • SNR, soil nitrogen ratio
  • SMN, soil mineral nitrogen

  • Keywords

  • Soil fertility
  • Municipal biosolids
  • Soil mineral nitrogen
  • Soil nitrogen ratio (SNR)
  • Area under the curve

  •  Table 1
    Table 1.
    Fig. 1.
     Table 2
    Table 2.
    Fig. 2.
     Table 3
    Table 3.
     Table 4
    Table 4.
    Fig. 3.
    Fig. 4.
    Fig. 5.
     Table 5
    Table 5.
    Fig. 6.
     Table 6
    Table 6.
     Table 7
    Table 7.
    Fig. 7.
    Fig. 8.
    • ⁎ 
      Corresponding author. Tel.: +1 902 896 2461.


    For further details log on website :
    http://www.sciencedirect.com/science/article/pii/S0167880915001425

    TREE BIOMASS

    Published Date
    1982, Pages 5565doi:10.1016/B978-0-12-652780-3.50012-9

    Author 

    A.A. Moslemi

    First page preview

    Copyright © 1982 ACADEMIC PRESS, INC. Published by Elsevier Inc. All rights reserved.

    For further details log on website :
    http://www.sciencedirect.com/science/article/pii/B9780126527803500129

    WOOD FOR FUEL

    Published Date
    1982, Pages 5153, doi:10.1016/B978-0-12-652780-3.50011-7

    Author 

    James S. Bethel

    First page preview



    For further details log on website :
    http://www.sciencedirect.com/science/article/pii/B9780126527803500117

    THE POTENTIAL COSTS OF GROWING AND HARVESTING WOOD FOR ENERGY IN AUSTRALIA AND NEW ZEALAND

    Published Date
    1982, Pages 3949, doi:10.1016/B978-0-12-652780-3.50010-5

  • Author 

  • W.H.M. Rawlins
  • C.M. Kerruish

  • G.P. Horgan

    First page preview

    Copyright © 1982 ACADEMIC PRESS, INC. Published by Elsevier Inc. All rights reserved.

    For further details log on website :
    http://www.sciencedirect.com/science/article/pii/B9780126527803500105

    HARVESTING WOOD FOR ENERGY IN NORTH AMERICA

    Published Date
    1982, Pages 2538, doi:10.1016/B978-0-12-652780-3.50009-9

    Author 

    León Jorge Castaños M.

    Roger A. Arola

    First page preview



    For further details log on website :
    http://www.sciencedirect.com/science/article/pii/B9780126527803500099

    TREE HARVESTING CHANGES IN SWEDEN DUE TO WHOLE TREE UTILIZATION

    Published Date
    1982, Pages 1924, doi:10.1016/B978-0-12-652780-3.50008-7

    Author 
    Bengt-Olof Danielsson

    First page preview



    For further details log on website :
    http://www.sciencedirect.com/science/article/pii/B9780126527803500087

    THE PRODUCTION OF WOOD FOR ENERGY

    Published Date
    1982, Pages 517, doi:10.1016/B978-0-12-652780-3.50007-5

    Author 

    L. Zsuffa

    First page preview



    For further details log on website :
    http://www.sciencedirect.com/science/article/pii/B9780126527803500075

    WOOD AS A WORLD-WIDE FUEL SOURCE

    Published Date
    1982, Pages 14, doi:10.1016/B978-0-12-652780-3.50006-3

    Author 

    Pentti Hakkila

    First page preview



    For further details log on website :
    http://www.sciencedirect.com/science/article/pii/B9780126527803500063

    Patterns of plant diversity in seven temperate forest types of Western Himalaya, India

    Published Date
    1 September 2016, Vol.9(3):280292, doi:10.1016/j.japb.2016.03.018
    Open Access, Creative Commons license, Funding information

    Original article

    Author

  • Javid Ahmad Dar
  • Somaiah Sundarapandian ,,


  • Department of Ecology and Environmental Sciences, School of Life Sciences, Pondicherry University, Puducherry, India

    Received 6 July 2015. Revised 4 March 2016. Accepted 29 March 2016. Available online 8 April 2016.

    Abstract

    Plant biodiversity patterns were analyzed in seven temperate forest types [Populus deltoides (PD), Juglans regiaCedrus deodaraPinus wallichiana, mixed coniferous, Abies pindrow (AP) and Betula utilis (BU)] of Kashmir Himalaya. A total of 177 plant species (158 genera, 66 families) were recorded. Most of the species are herbs (82.5%), while shrubs account for 9.6% and trees represent 7.9%. Species richness ranged from 24 (PD) to 96 (AP). Shannon, Simpson, and Fisher α indices varied: 0.17–1.06, 0.46–1.22, and 2.01–2.82 for trees; 0.36–0.94, 0.43–0.75, and 0.08–0.35 for shrubs; and 0.35–1.41, 0.27–0.95, and 5.61–39.98 for herbs, respectively. A total of five species were endemic. The total stems and basal area of trees were 35,794 stems (stand mean 330 stems/ha) and 481.1 m2 (stand mean 40.2 m2/ha), respectively. The mean density and basal area ranged from 103 stems/ha (BU) to 1,201 stems/ha (PD), and from 19.4 m2/ha (BU) to 51.9 m2/ha (AP), respectively. Tree density decreased with increase in diameter class. A positive relationship was obtained between elevation and species richness and between elevation and evenness (R2 = 0.37 and 0.19, respectively). Tree and shrub communities were homogenous in nature across the seven forest types, while herbs showed heterogeneous distribution pattern.

    Keywords

  • broad-leaved forests
  • coniferous forests
  • elevational gradient
  • phytodiversity

  • Western Himalaya


  • Introduction
    The Himalayas are one of the youngest and richest ecosystems on earth with a variety of species and forest types due to the varying altitude, topographic, and climatic conditions (Mani 1978). The Himalayas cover about 12.84% of the total geographical area of India (Negi 2009). Himalayan forests are considered to be among the world’s most depleted forests (Schickhoff 1995). Himalaya is recognized as one of the hotspots of biodiversity and harbors nearly 8,000 species of flowering plants, of which 25.3% are endemic (Singh and Hajra 1996). In the past 3 decades, there has been 23% loss of forest cover in western Himalayas (Anonymous 2005). Himalayas are complex and dynamic ecosystems that provide different ecosystem services (Khan et al 2012).
    Species composition, community structure, and function are the most important ecological attributes of forest ecosystems, which show variations in response to environmental, as well as anthropogenic variables (Gairola et al., 2008Shaheen et al., 2012 and Bisht and Bhat, 2013). A complex of factors viz. vegetation type, slope, aspect, edaphic factors, and altitude (Sharma et al., 2009Sharma et al., 2010a and Gairola et al., 2011a) determines the community composition, structure, and distribution pattern of diversity in mountain vegetation (Kessler, 2001 and Schmidt et al., 2006). One important factor in mountain ecosystems is elevation (McVicar and Korner 2012), which has a strong influence on the structure of the vegetation in most mountains in the world (Zhang et al 2006). Changes in species diversity along elevational gradient have been the subject of numerous studies (Lomolino, 2001 and Fetene et al., 2006), most of them found a hump shaped distribution, showing peak species diversity near the middle of the gradient (Austrheim, 2002 and Zhang and Ru, 2010). The plant community structure and distribution pattern of Himalayan forests are poorly understood (Peer et al 2007). Western Himalaya not only supports huge floristic diversity (Sharma et al 2010b), but also stores large carbon stocks (Sharma et al., 2010bDar and Sundarapandian, 2015a and Dar and Sundarapandian, 2015b).
    Kashmir Himalaya is located in the extreme northwest of the Himalayan biodiversity hotspot, and harbors a rich floristic diversity of immense scientific interest and supports about 12% of the country’s total angiosperm flora and 3% of its endemics, while the region represents only 0.4% of the total geographical area of India (Dar et al 2012). North-western Himalaya represents a unique bio-region owing primarily to its varied topography and habitat heterogeneity along a wide elevational range.
    Several workers have also presented quantitative phytosociological work from different areas of Kashmir (Blatter, 1928–1929Dar and Kachroo, 1982Singh and Kachroo, 1983Ara et al., 1995Dar et al., 1995Dar et al., 2002 and Khuroo et al., 2004). However, there is a paucity of quantitative information on different forest types of temperate forests of Kashmir Himalaya. Hence the present study aimed to assess the variation in vegetation structure and floristic diversity of seven major forest types of temperate forests of Kashmir Himalaya, India, which are expected to provide current status and baseline data that can be used for biodiversity conservation and effective management of these fragile ecosystems.

    Materials and methods

    Study area

    The present study was carried out in two forest divisions (Anantnag and Lidder) in seven temperate forest types of northwestern Himalaya, along an elevational gradient of 1,550–3,250 m of Anantnag District, Jammu and Kashmir, India (Figure 1 and Table 1). The district constitutes the south-central part of Jammu and Kashmir State and is situated between 33° 22ʹ and 34° 27ʹ N latitudes, and 74° 30ʹ and 75° 35ʹ E longitudes. The district is surrounded by Pirpanjal range in the south and southeast and Zanskar range in the north and northeast and the elevational gradient of the area ranges from 1,500 m to 5,420 m. The highest peak in the area is Kolahoi (5,420 m). The type of vegetation varies along the elevational gradient. The lower valley harbors broad-leaved vegetation up to an altitude of 2,000 m. Coniferous natural forests occur between 2,000 and 2,800 m, beyond which there is high altitude broad-leaved Betula utilis forest mixed with Abies pindrow up to 3,250 m. Above 3,250 m elevation, the area is covered by alpine grassland vegetation. The soil types found in the region are of four orders: entisols, inceptisols, alfisols, and mollisols (Anonymous 1991). The climate of the area is sub-humid temperate and is influenced by monsoon conditions. The year is divisible into four distinct seasons: spring (March–May); summer (June–August); autumn (September–November); and winter (December–February). This temperate region receives moderate to high snowfall from December to February. Annual precipitation from 2000 to 2012 in this area ranged from 844 mm to 1,213 mm and the mean monthly temperatures range from –8.3°C to 26°C (Figure 2). July is the warmest month of the year, with temperatures rising to an average of 29.5°C; January is the coldest month, with temperature dropping to –8.3°C.
    Figure 1. Location of the plots of seven temperate forest types of Kashmir Himalaya, India: AP = Abies pindrow; BU = Betula utilis; CD = Cedrus deodara; JR = Juglans regia; MC = mixed coniferous; PD = Populus deltoides; PW = Pinus wallichiana.
    Table 1. Study site characteristics of seven temperate forest types of Kashmir Himalaya, India.
    Forest typeLatitude (o)Longitude (o)Altitude (m)Number of plots
    Populus deltoides(PD)75.08–75.2033.72–33.781,550–1,80015
    Juglans regia (JR)75.25–75.3533.75–33.891,800–2,00013
    Cedrus deodara(CD)75.31–75.4033.73–33.992,050–2,30014
    Pinus wallichiana(PW)75.27–75.3533.93–34.032,000–2,30020
    Mixed coniferous (MC)75.19–75.4733.60–34.072,200–2,40012
    Abies pindrow (AP)75.28–75.4733.59–34.102,300–2,80022
    Betula utilis (BU)75.36–75.5033.59–33.992,800–3,25015
    Figure 2. Mean monthly maximum and minimum temperature and precipitation pattern of 12 years of data (2002–2013) in the study area (Data from MeT Department, Srinagar, India which is nearest to the study area): Max. = maximum; Min. = minimum; temp = temperature.

    Field methods

    Phytosociological analysis was carried out from March 2011 to October 2013. Seven forest types between 1,550 m and 3,250 m elevation were selected and named on the basis of their dominant tree species: Populus deltoides (PD); Juglans regia (JR); Cedrus deodara (CD); Pinus wallichiana (PW); mixed coniferous (MC); A. pindrow(AP); and B. utilis (BU). A total of 111 nested plots of 50 m × 50 m size were laid at random in the seven forest types (Table 1Figure 1) and each plot was further subdivided into 25 quadrats of 10 m × 10 m to collect the quantitative data on the tree layer. In the same plots, 525 quadrats of 5 m × 5 m (75 in each forest type) and the same number of 1 m × 1 m quadrats were laid to study shrub and herbaceous layer respectively. All individuals ≥ 10 cm girth at breast height were considered as trees and enumerated. The collected specimens and photographs were identified at the Centre for Taxonomy, Department of Botany, University of Kashmir, Srinagar, India.

    Data analysis

    Species diversity indices such as Shannon, Simpson, Fisher’s α and Evenness were calculated using the Past 3.1 program (version 3.1; Øyvind Hammer, Natural History Museum, University of Oslo). Importance value index (IVI) was sum of the values of relative frequency, relative density, and relative basal area (Curtis and McIntosh 1950). The abundance to frequency (A/F) ratio for different species was determined by following Whitford (1949) and Gairola et al (2011a). The ratio indicates regular (< 0.025), random (0.025–0.050), and contagious (> 0.050) distribution pattern. Species heterogeneity was calculated by following Whittaker (1972). Regression analysis was used to study the relationship between elevation and species richness, and diversity indices. Regression analysis was used to study the relationship of elevation with species richness and evenness.

    Results

    Species richness and diversity

    A total of 177 species (14 trees, 17 shrubs and 146 herbs including grasses) from 158 genera belonging to 66 families were recorded (Table 2), of which 82.5% of the species belonged to the herbaceous community, while shrubs accounted for 9.6%, and trees for 7.9%. Species richness varied among the forest types, ranging from 24 species in PD forest to 96 species in AP forest with an average of 73 species per forest type for conifers and 33 species for broad-leaved forest types, with an overall mean of 58 species. Thirty-one species (18%) were common to all the forest types, while 75 species (42%) are uncommon; occurring at only one site not in others and 25 species (14%) were found in more than two forest types.
    Table 2. Phytosociological and diversity attributes of seven temperate forest types [Populus deltoides (PD), Juglans regia (JR), Cedrus deodara (CD), Pinus wallichiana (PW), mixed coniferous (MC), Abies pindrow (AP), and Betula utilis (BU)] of Kashmir Himalaya, India.
    ParameterPDJRCDPWMCAPBUTotal
    No. of plots15131420122215111
    Species richness24315877629660177
    Genera24315675598858158
    Families1622304030403266
    Tree species richness464733214
    Shrub species richness9579317
    Herb species richness20254565528455146
    Shannon index
    Tree0.560.600.550.181.060.410.170.50
    Shrub1.220.530.730.760.460.74
    Herb2.682.542.182.492.012.822.832.50
    Simpson index
    Tree0.720.730.750.940.360.790.920.74
    Shrub0.430.750.660.680.750.65
    Herb0.080.140.250.200.350.200.110.19
    Fisher α
    Tree0.521.140.711.410.500.500.350.73
    Shrub0.950.450.700.870.270.64
    Herb5.616.8313.6223.1420.8039.9825.4319.34
    Evenness
    Tree0.330.320.400.170.960.470.600.46
    Shrub0.320.250.200.150.520.28
    Herb0.420.160.090.090.060.070.140.14
    Species heterogeneity
    Trees0.340.550.460.210.80.40.29
    Shrubs000.70.320.370.320.48
    Herbs0.90.80.790.810.630.770.87
    Total tree density18,0082,8562,7313,9782,3534,3241,54435,794
    Tree density
    (stems/ha)
    1,201220195199196197103322
    Total tree basal area
    (m2)
    541.7500.2610.7897.2560.51,141.0290.84,542.1
    Tree basal area
    (m2/ha)
    36.138.543.644.946.751.919.440.92
    Shrub density
    (No./ha)
    12,39232,61615,28026,24017,88820,883
    Herb density
    (No./m2)
    192259357361233287196279
    Maximum tree dbh (cm)51.994.6103.8150.4129.3119.193.9106.14
    Mean tree dbh (cm)16.944.751.352.353.255.445.845.65
    dbh = diameter at breast height.
    The average number of species per stand in seven forests ranged from 20 to 36 (Table 2). Shannon’s index ranged from 0.17 (BU) to 1.06 (MC), from 0.46 (BU) to 1.22 (CD) and from 2.01 (MC) to 2.83 (BU) for trees, shrubs, and herbs, respectively. The highest Simpson index values were observed in PW (0.94), PW/BU (0.75), and MC (0.35) for trees, shrubs, and herbs, respectively, and lowest values were in MC (0.36), CD (0.43), and PD (0.08). The highest values of Fisher’s α were observed in PW (1.41), CD (0.95), and AP (39.98) for trees, shrubs, and herbs, respectively, and lowest values were in BU (0.35), PW (0.45), and PD (5.61). Species evenness index values ranged from 0.17 to 0.96 for trees, from 0.15 to 0.52 for shrubs, and from 0.06 to 0.42 for herbs and were highest in MC (0.96), BU (0.52), and PD (0.42) for trees, shrubs, and herbs, respectively. Species richness varied greatly across the forest types and was 2–7, 3–9, and 20–84 for trees, shrubs, and herbs, respectively.

    Species area curves

    The species area curves of understory vegetation for all the seven forest types reached an asymptote within 1,775 m2 area (Figure 3). PD and JR forests reached an asymptote on 625 m2 and 850 m2, whereas AP forest type reached an asymptote on 1,775 m2.
    Figure 3. Species area curves for seven temperate forest types of Kashmir Himalaya, India: AP = Abies pindrow; BU = Betula utilis; CD = Cedrus deodara; JR = Juglans regia; MC = mixed coniferous; PD = Populus deltoides; PW = Pinus wallichiana.

    Density and stand basal area

    There were 35,794 individuals of trees and the mean stand density in seven forest types ranged from 103 trees/ha in the BU forest to 1,201 trees/ha in the PD forest (Table 2). The total basal area was 4,542.1 m2 and the mean stand basal area ranged from 19.4 m2/ha to 51.9 m2/ha in BU and AP forests, respectively. The highest shrub density (32,616 individuals/ha) and basal area (2.9 m2/ha) was observed in PW forest, whereas the least density (12,392 individuals/ha) and basal area (0.96 m2/ha) was in CD and MC forests, respectively. In PD and JR forests, no shrub species was found. In case of herbaceous community, the highest density (361 individuals/m2) and basal area (13.07 cm2/m2) were observed in PW and AP forests, respectively, while the least density (192 individuals/m2) and basal area (4.45 cm2/m2) were found in PD and BU forests, respectively.

    Population density

    The population density of the enumerated 14 tree species varied considerably across the seven forest types. In PD forest type, P. deltoides was the most abundant species (94%, 1125 stems) in terms of density and IVI (Table 3). Similarly, J. regia (82%, 181 stems), C. deodara (88%, 172 stems), P. wallichiana (97%, 193 stems), A. pindrow(90%, 178 stems), and B. utilis (95%, 98 stems) were dominant species in JR, CD, PW, AP, and BU forest types, respectively. In MC forest, A. pindrow (33.41%, 65 stems), P. wallichiana (21.89%, 43 stems), and Pinus wallichiana (44.7%, 88 stems) were dominant.
    Table 3. Importance value index (IVI) of seven temperate forest types [Populus deltoides (PD), Juglans regia (JR), Cedrus deodara (CD), Pinus wallichiana (PW), Mixed coniferous (MC), Abies pindrow (AP) and Betula utilis (BU)] of Kashmir Himalaya, India.
    SpeciesMean IVI

    PDJRCDPWMCAPBU
    Trees
    Abies pindrow(Royle ex D. Don) Royle11.235.04100.12264.6712.11
    Acer caesium Wall. ex Brandis0.39
    Aesculus indica(Wall. ex Camb.) Hook.f.0.26
    Betula utilis D. Don287.89
    Cedrus deodara(Roxb. ex Lamb.) G. Don.258.880.31
    Juglans regia L.254.54
    Robinia pseudoacacia L.2.260.69
    Morus alba L.1.33
    Picea smithiana(Wall.) Boiss12.953.3067.1930.94
    Pinus wallichianaA. B. Jackson16.93290.44132.694.38
    Populus deltoidesMarsh.252.8324.89
    Salix alba L.16.616.05
    Taxus wallichianaZucc0.26
    Ulmus villosaBrandis ex Gamble28.3012.49
    Shrubs
    Astragalus zanskarensis L.5.91
    Berberis lyciumRoyle184.8430.8639.8122.22
    Desmodium elegans DC.1.11
    Euonymus hamiltonianus Wall. in Roxb.3.883.30
    Indigofera heterantha Wall. ex Brandis4.84
    Indigofera linifolia(Linn.f.) Retz.4.441.85
    Juniperus semiglobosa Regel3.34
    Lespedeza elegansCamb.3.20
    Lonicera japonicaThunb.4.004.836.6810.19
    Parrotiopsis jacquemontiana(Dcne.) Rehder46.492.25
    Plectranthus rugosus Wall.1.05
    Rhododendron anthopogon D. Don255.88
    Rosa macrophyllaLindl.2.861.09
    Rosa webbianaWall. ex Royle6.16
    Rubus ellipticusSmith.2.671.716.04
    Sida cordata(Burm.f.) Borss-Waalk.10.21
    Viburnum grandiflorum Wall. ex DC.43.41257.75240.09246.2340.78
    Herbs
    Achillea millefoliumL.0.920.370.361.12
    Aconitum laeveRoyle0.55
    Actaea spicata L.8.25
    Adiantum venustum D. Don1.390.391.152.89
    Agrimonia eupatoria L.0.160.47
    Ainsliaea apteraDC.0.210.230.50
    Ajuga bracteosaWall ex. Benth2.020.740.490.400.34
    Alchemilla mollis(Buser) Rothm.0.68
    Allium consanguineumKunth2.74
    Anagallis arvensisL.2.47
    Anaphalis royleanaDC.0.76
    Androsace rotundifolia Hardw.0.331.21
    Androsace sempervivoidesJacq. ex Duby0.502.27
    Anemone tetrasepala Royle0.80
    Anthemis cotula L.5.205.570.310.55
    Aquilegia fragransBenth.0.98
    Aquilegia moorcroftiana Wall. ex Royle0.47
    Arenaria orbiculataRoyle ex Edgew. & Hook.f.0.84
    Arisaema jacquemontii Blume0.66
    Artemisia absinthium L.0.570.363.13
    Artemisia laciniataWilld.0.410.360.301.99
    Atropa acuminataRoyle ex Lindl.2.06
    Bellis perennis L.0.170.34
    Bergenia ciliata(Haw.) Sternb.0.320.120.79
    Bothriochloa ischaemum (L.) Keng2.072.90
    Bupleurum himalayense Klutz0.32
    Caltha alba Jacq. ex Camb.3.28
    Cannabis sativa L.10.299.66
    Cardamine impatiens L.1.592.421.110.71
    Carduus edelbergiiRech. f.1.091.420.24
    Carpesium cernuum L.0.54
    Centaurea ibericaTrev. ex Spreng.0.66
    Cephalanthera longifolia (L.) Fritsch0.53
    Cerastium cerastoides (L.) Britt.7.350.420.711.47
    Chamaerhodiola asiatica (D. Don) Nakai1.94
    Chenopodium album L.0.160.34
    Cichorium intybusL.1.00
    Circaea alpina L. var. himalaica C. B. Clarke0.440.72
    Cirsium falconeriPetrak0.220.661.570.47
    Clematis buchananiana DC.0.60
    Clinopodium vulgare L.27.3118.244.409.8711.514.57
    Commelina benghalensis L.2.191.32
    Conium maculatumL.0.24
    Conyza canadensis(L.) Cronquist40.588.320.810.72
    Corydalis diphyllaWall.0.340.74
    Cucubalus bacciferL.0.500.83
    Cynodon dactylon(L.) Pers.16.455.3340.78
    Cynoglossum glochidiatum Wall. ex Benth.0.160.47
    Cypripedium cordigerum D. Don0.94
    Dactylis glomerataL.32.3352.513.705.0212.29
    Delphinium cashmerianumRoyle0.180.47
    Digitalis lutea L.0.300.240.89
    Dioscorea deltoidea Wall. ex Kunth0.200.12
    Diplazium esculentum (Retz.) Sw.0.770.720.852.774.78
    Elsholtzia densaBenth.1.480.88
    Elsholtzia eriostachya Benth.3.840.46
    Epilobium laxumRoyle0.590.34
    Epimedium elatumMorr. & Decne.0.43
    Epipactis helleborine (L.) Crantz.0.89
    Epipactis royleanaLindl.0.491.040.70
    Erigeron bonariensis L.0.62
    Erodium cicutarium(L.) L'Hér.0.34
    Erodium laciniatum(Cay.) Willd.0.16
    Filipendula vestita(Wall. ex G. Don) Maxim.2.76
    Fragaria nubicola(Lindl. ex Hook.f.) Lacaita25.534.0728.9832.1619.9819.760.94
    Galinsoga parviflora Cav.16.410.31
    Galium aparine L.1.190.800.860.3341.86
    Galium asperuloidesEdgew.0.39
    Geranium pratenseL.1.314.609.683.203.443.90
    Geum urbanum L.1.02
    Gnaphalium indicum L.0.41
    Heracleum candicans Wall. ex DC.0.41
    Heracleum hirsutum Edgew.0.371.13
    Hypericum perforatum L.1.260.500.69
    Impatiens brachycentra Kar. & Kir.12.801.202.787.23
    Indigofera linifolia(L.f.) Retz0.40
    Lactuca dissectaD. Don0.200.17
    Lamium album L.0.711.35
    Lancea tibetica HK. F. & T.0.57
    Lapsana communisL.0.25
    Lavatera cashmerianaCamb.0.55
    Leontopodium himalayanum DC.1.16
    Lindelofia angustifolia(Schrenk) Brand.0.71
    Lychnis coronaria(L.) Desr.0.38
    Malva neglectaWall.70.98
    Marrubium vulgareL.0.31
    Mentha longifolia(L.) Huds.1.160.870.50
    Myosotis alpestrisF.W. Schmidt0.49
    Myosotis arvensis(L.) Hill.4.562.620.360.440.98
    Myosoton aquaticum (L.) Moench.10.4719.681.540.331.655.04
    Myriactis wallichiiLess.1.822.783.116.252.194.120.87
    Nepeta erecta(Royle ex Benth.) Benth.0.47
    Nepeta nervosaRoyle ex Benth.0.290.55
    Oenothera roseaSoland.0.47
    Oplismenus compositus (L.) P. Beauv.3.040.441.59
    Orobanche albaStephan ex Willd.0.17
    Oxalis acetosella L.31.236.2410.2922.5411.599.5318.04
    Oxyria digyna (L.) Hill0.43
    Paeonia emodiWall. ex Hk. f.1.41
    Pedicularis pectinata Wall. ex Benth.2.26
    Persicaria nepalensis (Meisn.) H. Gross0.00
    Phlomis bracteosaRoyle ex Benth.5.33
    Phytolacca latbenia(Moq) Hans Walter0.992.115.823.924.21
    Plantago erosaWall.0.171.010.55
    Plantago himalaicaPilger0.68
    Plantago lanceolataL.0.73
    Plantago major L.14.3315.302.571.940.893.120.34
    Pleurospermum candollei (DC.) C.B. Clarke in Hook. f.4.78
    Poa annua L.5.621.321.56
    Poa bulbosa L.87.74
    Poa stewartianaBor5.535.683.052.20
    Podophyllum hexandrum Royle1.101.151.301.27
    Polemonium caeruleum L.1.18
    Polygonatum verticillatum (L.) All.3.06
    Polygonum affineD. Don1.93
    Polygonum amplexicaule D. Don3.223.392.3531.04
    Potentilla atrosanguinea G. Lodd. ex D. Don.8.641.4118.10
    Potentilla bifloraWilld. ex Schlecht.0.29
    Primula macrophylla D. Don0.13
    Prunella vulgaris L.29.864.996.863.002.995.01
    Pteracanthus alatus(Wall. ex Nees) Bremek.0.15
    Pyrola rotundifoliaL.0.18
    Ranunculus hirtellus Royle0.430.670.441.010.39
    Ranunculus laetusWall. ex Royle1.08
    Ribes orientaleDesf.25.36
    Rorippa islandica(Oeder) Borbás1.46
    Rumex nepalensisSpreng4.277.643.507.82
    Sambucus nigra L.1.253.946.655.395.36
    Sedum ewersiiLedeb.0.380.50
    Silene vulgaris(Moench) Garcke0.180.380.330.44
    Solanum nigrum L.3.826.430.16
    Stellaria media (L.) Cry.0.310.43
    Stipa sibirica (L.) Lam.138.33123.31172.75128.486.53
    Swertia ciliata (D. Don ex G. Don) B. L. Burtt0.91
    Taraxacum officinale G.H. Weber ex Wiggers.8.627.293.002.612.903.95
    Thymus linearisBenth.0.471.26
    Trifolium repens L.3.693.310.311.243.27
    Trillium govanianumWall. ex Royle0.310.40
    Tussilago farfara L.0.240.97
    Juncus inflexus L.1.19
    Urtica dioica L.10.786.930.220.191.061.99
    Valeriana jatamansiJones ex Roxb.0.531.45
    Verbascum thapsus L.8.164.391.330.551.981.20
    Veronica bilobaschreb. ex L.1.7220.68
    Vincetoxicum hirundinaria Medik.0.18
    Viola canescensWall. ex Roxb.13.7819.1717.73
    Viburnum grandiflorum was the most abundant shrub species in terms of both density and IVI in coniferous forests [PW (94%, 32,616 individuals), MC (92%, 15,280 individuals), and AP (94%, 26,240 individuals)], except CD forest where Berberis lyceum (68%, 8,448 individuals) was the most abundant species. However, in BU forest, Rhododendron anthopogon (86%, 17,888 individuals) was the dominant species.
    Stipa sibirica was the dominant species in the herbaceous community in coniferous forests [CD (50.5%, 180.1 individuals/m2), PW (55%, 198.4 individuals/m2), MC (76.7%, 178.5 individuals/m2), and AP (61.7%, 177.1 individuals/m2)], while in low-elevation broad-leaved forests (PD/JR), Dactylis glomerata (33.9%, 65.22 individuals/m2) and Poa bulbosa (45.7%, 118.4 individuals/m2) were dominant species in terms of density, whereas Conyza canadensis was dominant in PD forest in terms of IVI. However, in BU forest type Malva neglecta (41.7%, 81.64 individuals/m2) was the abundant species.
    A total of five species belonging to five families were found to be endemic to Himalaya: Anaphalis royleanaDelphinium cashmerianumGeum urbanumLespedeza elegans; and Sedum ewersii. Among them, four are herbs and one is a shrub. Acer caesium (vulnerable), Cypripedium cordigerum (rare), Dioscorea deltoidea (vulnerable), J. regia (near threatened), and Taxus wallichiana(endangered) are recognized as threatened species by the International Union for Conservation of Nature.

    Size class distribution

    Tree density decreased with increasing diameter class (Figure 4). In total, the highest density of 21.7% was contributed by 10.1–20 cm diameter class and lowest density of 0.3% was contributed by > 100.1 cm diameter class in all forest types. Tree density in the lower diameter class (3.1–10 cm) was greater in PD (27.1%), compared to all other forest types, while the higher diameter (≥ 100 cm) was greater in AP (1.8%) and MC (0.7%) forests. Among all the forest types, the first five diameter classes (3.1–60 cm) contributed 86.3% of the density whereas the other five diameter classes (> 60.1 cm) contributed 13.7% of the density.
    Figure 4. Size class distribution of tree density and basal area (m2) in seven temperate forest types of Kashmir Himalaya, India: AP = Abies pindrow; BU = Betula utilis; CD = Cedrus deodara; JR = Juglans regia; MC = mixed coniferous; PD = Populus deltoides; PW = Pinus wallichiana.

    Family composition

    The number of species in a family varied from 1 to 22 (Table 4). Of the total 66 families, 31.81% (21) families were represented by single genus and species and 19.7% (13) families were represented by two species. Asteraceae (represented by 21 genera and 22 species, 12.4%) and Lamiaceae (represented by 10 genera and 13 species, 7.3%) were taxonomically the most speciose families. Seven families were common among all the seven forest types.
    Table 4. Contribution of families to genera (G), species richness (S), and density (D; No./ha) in seven temperate forest types [Populus deltoides (PD), Juglans regia (JR), Cedrus deodara (CD), Pinus wallichiana (PW), mixed coniferous (MC), Abies pindrow (AP), and Betula utilis (BU)] of Kashmir Himalaya, India.

    For further details log on website :
    http://www.sciencedirect.com/science/article/pii/S2287884X16300279

    Advantages and Disadvantages of Fasting for Runners

    Author BY   ANDREA CESPEDES  Food is fuel, especially for serious runners who need a lot of energy. It may seem counterintuiti...