scholarly journals Modelling vegetation structure-based bird habitat resources in Australian temperate woodlands, using multi-sensors

2013 ◽  
Vol 46 (1) ◽  
pp. 641-674 ◽  
Author(s):  
Peter S. Lee ◽  
Brendan G. Mackey ◽  
Sandra L. Berry
Keyword(s):  
Vegetation Structure ◽  
Temperate Woodlands ◽  
Bird Habitat

scholarly journals Development of a Bird Habitat Resource Classification Scheme Based on Vegetation Structure Analysis

2018 ◽  
Vol 115 (12) ◽  
pp. 2307
Author(s):  
Peter S. Lee ◽  
Brendan G. Mackey
Keyword(s):  
Structure Analysis ◽  
Vegetation Structure ◽  
Classification Scheme ◽  
Resource Classification ◽  
Bird Habitat

Remotely sensed indicators of habitat heterogeneity: Use of synthetic aperture radar in mapping vegetation structure and bird habitat

1997 ◽  
Vol 60 (3) ◽  
pp. 217-227 ◽  
Author(s):  
Marc L. Imhoff ◽  
Thomas D. Sisk ◽  
Anthony Milne ◽  
Garth Morgan ◽  
Tony Orr
Keyword(s):  
Synthetic Aperture Radar ◽  
Vegetation Structure ◽  
Habitat Heterogeneity ◽  
Remotely Sensed ◽  
Synthetic Aperture ◽  
Bird Habitat ◽  
Aperture Radar

Analisis Keragaman Tanaman Sebagai Jasa Lingkungan Pada Lanskap Agroforestri di Daerah Aliran Sungai Krueng Aceh

2019 ◽  
Vol 4 (2) ◽  
Author(s):  
Zulkifli Aiyub Kadir ◽  
Bahagia Bahagia
Keyword(s):  
Water Conservation ◽  
Vegetation Structure ◽  
Swot Analysis ◽  
Diversity Index ◽  
Middle Stream ◽  
Land Management System ◽  
Study Sites ◽  
Aleurites Moluccana ◽  
Lansium Domesticum ◽  
Agroforestry Practices

<p>Humans have utilized landscape for  produces a diverse character of the wider area of the watershed. Agroforestry is a land management system in addressing the problems that arise due to changes in land use of soil and water conservation. The aim of the study was to analyze plant diversity in agroforestry practices that have services in the Krueng watershed landscape in Aceh watershed. Develop strategies in the Krueng Aceh DAS agroforestry service. This research was conducted in the upper, middle and downstream of the Krueng Aceh watershed, with a rapid method of Agro-Biodiversity Appraisal and SWOT. The results showed that the composition of the vegetation structure found in the study sites tended to vary with the diversity index of agroforestry that was currently in the upstream and middle of the Krueng Aceh watershed. Based on SWOT analysis, internal scores are 2.45 and external scores are 3.21. Agroforestry practices in the upper stream of Krueng Aceh watershed were dominated by <em>Aleurites moluccana</em>, <em>Areca cathecu</em>, and  <em>Averrhoa bilimbi</em> L  species with the highest INP in the upper stream of Krueng Aceh watershed. Vegetation at the middle stream of Krueng Aceh watershed dominated by <em>Areca cathecu,</em> <em>Lansium domesticum</em> and Musa<em> paradisiaca</em>.  </p>

The Vegetation Structure of Evergreen Coniferous Forests of Daehuksan Island in the Dadohaehaesang National Park

2018 ◽  
Vol 30 (1) ◽  
pp. 173-193 ◽  
Author(s):  
Yeongjun Cho ◽  
Hasong Kim ◽  
Hyeonho Myeong ◽  
Jungwon Park ◽  
Janggeun Oh
Keyword(s):  
Vegetation Structure ◽  
National Park ◽  
Coniferous Forests

Vegetation structure and environmental gradients in the Sallum area, Egypt

2005 ◽  
Vol 31 (1) ◽  
pp. 15-32 ◽  
Author(s):  
Fawzy M. Salama ◽  
Monier Abd El-Ghani ◽  
Salah El Naggar ◽  
Khadija A. Baayo
Keyword(s):  
Vegetation Structure ◽  
Environmental Gradients

Are reptile responses to fire shaped by forest type and vegetation structure? Insights from the Mediterranean basin

2019 ◽  
Vol 437 ◽  
pp. 340-347 ◽  
Author(s):  
Brahim Chergui ◽  
Soumia Fahd ◽  
Xavier Santos
Keyword(s):  
Vegetation Structure ◽  
Mediterranean Basin ◽  
Forest Type ◽  
The Mediterranean ◽  
The Mediterranean Basin

scholarly journals Effects of habitat edges on vegetation structure and the vulnerable golden-brown mouse lemur (Microcebus ravelobensis) in northwestern Madagascar

BMC Ecology ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Bertrand Andriatsitohaina ◽  
Daniel Romero-Mujalli ◽  
Malcolm S. Ramsay ◽  
Frederik Kiene ◽  
Solofonirina Rasoloharijaona ◽  
...  
Keyword(s):  
Body Mass ◽  
Edge Effects ◽  
Vegetation Structure ◽  
Species Abundance ◽  
Tree Height ◽  
Logistic Function ◽  
Study Region ◽  
Large Trees ◽  
Significant Difference ◽  
Vegetation Parameters

Abstract Background Edge effects can influence species composition and community structure as a result of changes in microenvironment and edaphic variables. We investigated effects of habitat edges on vegetation structure, abundance and body mass of one vulnerable Microcebus species in northwestern Madagascar. We trapped mouse lemurs along four 1000-m transects (total of 2424 trap nights) that ran perpendicular to the forest edge. We installed 16 pairs of 20 m2 vegetation plots along each transect and measured nine vegetation parameters. To determine the responses of the vegetation and animals to an increasing distance to the edge, we tested the fit of four alternative mathematical functions (linear, power, logistic and unimodal) to the data and derived the depth of edge influence (DEI) for all parameters. Results Logistic and unimodal functions best explained edge responses of vegetation parameters, and the logistic function performed best for abundance and body mass of M. ravelobensis. The DEI varied between 50 m (no. of seedlings, no. of liana, dbh of large trees [dbh ≥ 10 cm]) and 460 m (tree height of large trees) for the vegetation parameters, whereas it was 340 m for M. ravelobensis abundance and 390 m for body mass, corresponding best to the DEI of small tree [dbh < 10 cm] density (360 m). Small trees were significantly taller and the density of seedlings was higher in the interior than in the edge habitat. However, there was no significant difference in M. ravelobensis abundance and body mass between interior and edge habitats, suggesting that M. ravelobensis did not show a strong edge response in the study region. Finally, regression analyses revealed three negative (species abundance and three vegetation parameters) and two positive relationships (body mass and two vegetation parameters), suggesting an impact of vegetation structure on M. ravelobensis which may be partly independent of edge effects. Conclusions A comparison of our results with previous findings reveals that edge effects are variable in space in a small nocturnal primate from Madagascar. Such an ecological plasticity could be extremely relevant for mitigating species responses to habitat loss and anthropogenic disturbances.

scholarly journals Correlating elements content in mosses collected in 2015 across Germany with spatially associated characteristics of sampling sites and their surroundings

2019 ◽  
Vol 31 (1) ◽  
Author(s):  
Stefan Nickel ◽  
Winfried Schröder
Keyword(s):  
Land Use ◽  
Population Density ◽  
Atmospheric Deposition ◽  
Vegetation Structure ◽  
Urban Areas ◽  
Explanatory Power ◽  
Spatial Density ◽  
Area Index ◽  
Explanatory Variables ◽  
Tree Layer

Abstract Background The aim of the study was a statistical evaluation of the statistical relevance of potentially explanatory variables (atmospheric deposition, meteorology, geology, soil, topography, sampling, vegetation structure, land-use density, population density, potential emission sources) correlated with the content of 12 heavy metals and nitrogen in mosses collected from 400 sites across Germany in 2015. Beyond correlation analysis, regression analysis was performed using two methods: random forest regression and multiple linear regression in connection with commonality analysis. Results The strongest predictor for the content of Cd, Cu, Ni, Pb, Zn and N in mosses was the sampled species. In 2015, the atmospheric deposition showed a lower predictive power compared to earlier campaigns. The mean precipitation (2013–2015) is a significant factor influencing the content of Cd, Pb and Zn in moss samples. Altitude (Cu, Hg and Ni) and slope (Cd) are the strongest topographical predictors. With regard to 14 vegetation structure measures studied, the distance to adjacent tree stands is the strongest predictor (Cd, Cu, Hg, Zn, N), followed by the tree layer height (Cd, Hg, Pb, N), the leaf area index (Cd, N, Zn), and finally the coverage of the tree layer (Ni, Cd, Hg). For forests, the spatial density in radii 100–300 km predominates as significant predictors for Cu, Hg, Ni and N. For the urban areas, there are element-specific different radii between 25 and 300 km (Cd, Cu, Ni, Pb, N) and for agricultural areas usually radii between 50 and 300 km, in which the respective land use is correlated with the element contents. The population density in the 50 and 100 km radius is a variable with high explanatory power for all elements except Hg and N. Conclusions For Europe-wide analyses, the population density and the proportion of different land-use classes up to 300 km around the moss sampling sites are recommended.

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