The vegetation structure and condition of contracting lowland habitat for Leadbeater's possum (Gymnobelideus leadbeateri)

A combination of fires and logging mean that more than 80% of the montane ash forests inhabited by Leadbeater’s possum (Gymnobelideus leadbeateri) in the Victorian Central Highlands consist of ecologically young stands possessing few trees with hollows. As a consequence, there have been predictions of a substantial decline in Leadbeater’s possum populations over the next 40 years. If this is to be averted, or reduced in extent, then an immediate means of increasing den site availability for the species is required. The results of a recent investigation into nest-box use by the species in lowland swamp forest demonstrate that high rates of occupancy can be achieved by targeting established colonies at sites where the vegetation structure is suitable for box installation. This suggests that nest boxes can be an effective means of increasing den-site availability for the possum, and therefore have considerable potential to contribute to the species’ conservation in the short term. Such measures should be applied in conjunction with altered forestry practises that better provide for the retention and future provision of mature hollow-bearing trees.

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

Jurnal Serambi Engineering ◽

10.32672/jse.v4i2.1468 ◽

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

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 Aleurites moluccana, Areca cathecu, and Averrhoa bilimbi 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 Areca cathecu, Lansium domesticum and Musa paradisiaca.

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

The Journal of Korean Island ◽

10.26840/jki.30.1.173 ◽

2018 ◽

Vol 30 (1) ◽

pp. 173-193 ◽

Cited By ~ 2

Author(s):

Yeongjun Cho ◽

Hasong Kim ◽

Hyeonho Myeong ◽

Jungwon Park ◽

Janggeun Oh

Keyword(s):

Vegetation Structure ◽

National Park ◽

Coniferous Forests

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Vegetation structure and composition in the Shoshone Mountains and Toiyabe, Toquima, and Monitor ranges, Nevada (2nd Edition)

Forest Service Research Data Archive ◽

10.2737/rds-2013-0007-2 ◽

2015 ◽

Cited By ~ 5

Author(s):

Erica Fleishman

Keyword(s):

Vegetation Structure

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Vegetation structure and environmental gradients in the Sallum area, Egypt

Ecologia mediterranea ◽

10.3406/ecmed.2005.1476 ◽

2005 ◽

Vol 31 (1) ◽

pp. 15-32 ◽

Cited By ~ 3

Author(s):

Fawzy M. Salama ◽

Monier Abd El-Ghani ◽

Salah El Naggar ◽

Khadija A. Baayo

Keyword(s):

Vegetation Structure ◽

Environmental Gradients

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

Forest Ecology and Management ◽

10.1016/j.foreco.2019.01.046 ◽

2019 ◽

Vol 437 ◽

pp. 340-347 ◽

Cited By ~ 5

Author(s):

Brahim Chergui ◽

Soumia Fahd ◽

Xavier Santos

Keyword(s):

Vegetation Structure ◽

Mediterranean Basin ◽

Forest Type ◽

The Mediterranean ◽

The Mediterranean Basin

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

BMC Ecology ◽

10.1186/s12898-020-00337-z ◽

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.

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

Environmental Sciences Europe ◽

10.1186/s12302-019-0260-7 ◽

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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Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas

Remote Sensing ◽

10.3390/rs13030507 ◽

2021 ◽

Vol 13 (3) ◽

pp. 507

Author(s):

Tasiyiwa Priscilla Muumbe ◽

Jussi Baade ◽

Jenia Singh ◽

Christiane Schmullius ◽

Christian Thau

Keyword(s):

Remote Sensing ◽

Vegetation Structure ◽

Laser Scanning ◽

Spatial Scales ◽

Terrestrial Laser Scanning ◽

Point Clouds ◽

Parameter Extraction ◽

Airborne Lidar ◽

Special Focus ◽

Vegetation Parameter

Savannas are heterogeneous ecosystems, composed of varied spatial combinations and proportions of woody and herbaceous vegetation. Most field-based inventory and remote sensing methods fail to account for the lower stratum vegetation (i.e., shrubs and grasses), and are thus underrepresenting the carbon storage potential of savanna ecosystems. For detailed analyses at the local scale, Terrestrial Laser Scanning (TLS) has proven to be a promising remote sensing technology over the past decade. Accordingly, several review articles already exist on the use of TLS for characterizing 3D vegetation structure. However, a gap exists on the spatial concentrations of TLS studies according to biome for accurate vegetation structure estimation. A comprehensive review was conducted through a meta-analysis of 113 relevant research articles using 18 attributes. The review covered a range of aspects, including the global distribution of TLS studies, parameters retrieved from TLS point clouds and retrieval methods. The review also examined the relationship between the TLS retrieval method and the overall accuracy in parameter extraction. To date, TLS has mainly been used to characterize vegetation in temperate, boreal/taiga and tropical forests, with only little emphasis on savannas. TLS studies in the savanna focused on the extraction of very few vegetation parameters (e.g., DBH and height) and did not consider the shrub contribution to the overall Above Ground Biomass (AGB). Future work should therefore focus on developing new and adjusting existing algorithms for vegetation parameter extraction in the savanna biome, improving predictive AGB models through 3D reconstructions of savanna trees and shrubs as well as quantifying AGB change through the application of multi-temporal TLS. The integration of data from various sources and platforms e.g., TLS with airborne LiDAR is recommended for improved vegetation parameter extraction (including AGB) at larger spatial scales. The review highlights the huge potential of TLS for accurate savanna vegetation extraction by discussing TLS opportunities, challenges and potential future research in the savanna biome.

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