scholarly journals Temporal effects of cutting intensity on Diptera assemblages in eastern Borneo rainforest Indonesia

2020 ◽  
Vol 21 (3) ◽  
Author(s):  
Ahmad - Budiaman ◽  
Noor Farikhah Haneda ◽  
Indahwati ◽  
Dini Febrian ◽  
Laela Nur Rahmah
Keyword(s):  
Species Richness ◽  
Forest Canopy ◽  
Tropical Rainforest ◽  
Canopy Cover ◽  
Malaise Trap ◽  
Selective Cutting ◽  
Temporal Effects ◽  
Cutting Intensity ◽  
Single Predictor ◽  
Planting System

Abstract. Budiaman A, Haneda NF, Indahwati, Febrian D, Rahmah LN . 2020. Temporal effects of cutting intensity on Diptera assemblages in eastern Borneo rainforest Indonesia. Biodiversitas 21: 1074-1081. Studies on the effects of varying cutting intensity on the abundance and species richness of Diptera in tropical rainforest are limited, particularly in Southeast Asia region. The aim of the study was to assess the temporal effect of cutting intensity on Diptera community in tropical rainforest in the eastern Borneo rainforest, Indonesia, which was logged using the Indonesian Selective Cutting and Planting system. The field study was carried out in 2016. Responses of Diptera to the Indonesian Selective Cutting and Planting systems in the eastern Borneo rainforest, Indonesia were examined. We compared the abundance and morphospecies composition of Diptera before cutting and after cutting at three different treatments: low cutting intensity, medium cutting intensity and high cutting intensity. Diptera was collected using a malaise trap. Selective cutting of tropical rainforest altered biodiversity of Diptera. The abundance and morphospecies composition of Diptera were greater after cutting than before cutting at all cutting intensities. Our study showed that cutting intensity did not significantly affect the abundance and morphospecies composition of Diptera. Results of the study clearly indicated that the percentage of forest canopy cover could be a single predictor for abundance and morphospecies composition of Diptera in the natural rainforest of eastern Borneo, Indonesia.

scholarly journals Changes in Long-Term Light Properties of a Mixed Conifer—Broadleaf Forest in Southwestern Europe

Forests ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1485
Author(s):  
Ignacio Ruiz de la Cuesta ◽  
Juan A. Blanco ◽  
J. Bosco Imbert ◽  
Javier Peralta ◽  
Javier Rodríguez-Pérez
Keyword(s):  
Species Richness ◽  
Forest Canopy ◽  
Mixed Forest ◽  
Canopy Cover ◽  
Anthropogenic Factors ◽  
Canopy Openness ◽  
Area Index ◽  
Sampling Points ◽  
The Relationship

Natural and anthropogenic factors affect forest structure worldwide, primarily affecting forest canopy and its light properties. However, not only stand-replacing events modify canopy structure, but disturbances of lower intensity can also have important ecological implications. To study such effects, we analyzed long-term changes in light properties of a conifer–broadleaf mixed forest in the Southwestern Pyrenees, placed in the fringe between the Mediterranean and Eurosiberian biogeographical regions. At this site, a thinning trial with different intensities (0%, 20%, and 30–40% basal area removed) took place in 1999 and 2009, windstorms affected some plots in 2009 and droughts were recurrent during the sampling period (2003, 2005, 2011). We monitored light properties during 14 years (2005–2019) with hemispherical photographs. We applied partial autocorrelation functions to determine if changes between years could be attributed to internal canopy changes or to external disturbances. In addition, we mapped the broadleaf canopy in 2003, 2008, and 2016 to calculate broadleaf canopy cover and richness at the sampling points with different buffer areas of increasing surface. We applied generalized linear mixed models to evaluate the effects of light variables on canopy richness and cover. We found that light variables had the most important changes during the period 2008 to 2010, reacting to the changes caused that year by the combined effects of wind and forest management. In addition, we found that an area of 4.0 m radius around the sampling points was the best to explain the relationship between light properties and species richness, whereas a radius of 1.0 m was enough to estimate the relationship between light and canopy cover. In addition, light-related variables such as diffuse light and leaf area index were related to species richness, whereas structural variables such as canopy openness were related to canopy cover. In summary, our study demonstrates that non stand-replacing disturbances such as windstorms, thinning, or droughts can have an important role in modifying structural and light-related canopy properties, which in turn may influence natural processes of stand development and ecological succession.

scholarly journals KEANEKARAGAMAN JENIS ANGGREK ALAM EPIFIT PADA BERBAGAI TUTUPAN TAJUK HUTAN DI DESA BALAI SEBUT KABUPATEN SANGGAU

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Dunatus Sudarso ◽  
Dwi Astiani ◽  
Hanna Artuti Ekamawanti
Keyword(s):  
Species Diversity ◽  
Forest Canopy ◽  
Tropical Rainforest ◽  
Canopy Cover ◽  
Survey Method ◽  
Epiphytic Orchids ◽  
Plot Sampling ◽  
Open Forest ◽  
Closed Forest ◽  
Canopy Species

Epiphytic orchids can be found living naturally in the tropical rainforest. Destruction or degradation of forest area in Balai Sebut District Sanggau Regency due to caused degradation of canopy cover. This condition may affect microclimate which than impacts at the presence of species, one of which is epiphytic orchids that grow naturally in the forest. This study used a survey method with purposive double plot sampling for 1 month (28 Mei – 21 July 2019) in the field. Observation plots were made with a size of 20 x 50 m with a total of 12 plots. The results showed that there where 32 types of epiphytic orchids with a total of 431 individuals. At closed forest canopy cover and had been accomplished (>70%) can be 16 species of orchids with 220 individuals, at forest canopy (50-70%) can be 25 species of orchids with 159 individuals, can be at open forest canopy cover (50%) there were 10 species of orchids with 52 individuals. The dominant orchids species in the three canopy cover Flikingeria bicostata with Celogne peltastes.Keywords: closed forest canopy, epiphytic orchids, medium and open forest canopy, species diversity.

scholarly journals Estimating Forest Canopy Cover by Multiscale Remote Sensing in Northeast Jiangxi, China

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 433
Author(s):  
Xiaolan Huang ◽  
Weicheng Wu ◽  
Tingting Shen ◽  
Lifeng Xie ◽  
Yaozu Qin ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Forest Canopy ◽  
Canopy Cover ◽  
Google Earth ◽  
Tree Canopy ◽  
Landsat Data ◽  
High Resolution Data ◽  
Modis Ndvi ◽  
Tree Canopy Cover

This research was focused on estimation of tree canopy cover (CC) by multiscale remote sensing in south China. The key aim is to establish the relationship between CC and woody NDVI (NDVIW) or to build a CC-NDVIW model taking northeast Jiangxi as an example. Based on field CC measurements, this research used Google Earth as a complementary source to measure CC. In total, 63 sample plots of CC were created, among which 45 were applied for modeling and the remaining 18 were employed for verification. In order to ascertain the ratio R of NDVIW to the satellite observed NDVI, a 20-year time-series MODIS NDVI dataset was utilized for decomposition to obtain the NDVIW component, and then the ratio R was calculated with the equation R = (NDVIW/NDVI) *100%, respectively, for forest (CC >60%), medium woodland (CC = 25–60%) and sparse woodland (CC 1–25%). Landsat TM and OLI images that had been orthorectified by the provider USGS were atmospherically corrected using the COST model and used to derive NDVIL. R was multiplied for the NDVIL image to extract the woody NDVI (NDVIWL) from Landsat data for each of these plots. The 45 plots of CC data were linearly fitted to the NDVIWL, and a model with CC = 103.843 NDVIW + 6.157 (R2 = 0.881) was obtained. This equation was applied to predict CC at the 18 verification plots and a good agreement was found (R2 = 0.897). This validated CC-NDVIW model was further applied to the woody NDVI of forest, medium woodland and sparse woodland derived from Landsat data for regional CC estimation. An independent group of 24 measured plots was utilized for validation of the results, and an accuracy of 83.0% was obtained. Thence, the developed model has high predictivity and is suitable for large-scale estimation of CC using high-resolution data.

Forest canopy cover analysis using UAS lidar

2017 ◽  
Author(s):  
Qingwang Liu ◽  
Shiming Li ◽  
Kailong Hu ◽  
Yong Pang ◽  
Zengyuan Li
Keyword(s):  
Forest Canopy ◽  
Canopy Cover

The accuracy of large-area forest canopy cover estimation using Landsat in boreal region

2016 ◽  
Vol 53 ◽  
pp. 118-127 ◽  
Author(s):  
Hadi ◽  
Lauri Korhonen ◽  
Aarne Hovi ◽  
Petri Rönnholm ◽  
Miina Rautiainen
Keyword(s):  
Forest Canopy ◽  
Canopy Cover ◽  
Large Area ◽  
Boreal Region

scholarly journals Estimation of forest canopy cover: a comparison of field measurement techniques

Silva Fennica ◽  
2006 ◽  
Vol 40 (4) ◽  
Author(s):  
Lauri Korhonen ◽  
Kari Korhonen ◽  
Miina Rautiainen ◽  
Pauline Stenberg
Keyword(s):  
Field Measurement ◽  
Forest Canopy ◽  
Measurement Techniques ◽  
Canopy Cover

scholarly journals Effects of Malaise trap spacing on species richness and composition of terrestrial arthropod bulk samples

2020 ◽  
Author(s):  
D Steinke ◽  
TWA Braukmann ◽  
L Manerus ◽  
A Woodhouse ◽  
V Elbrecht
Keyword(s):  
Species Richness ◽  
Field Experiments ◽  
Collection Efficiency ◽  
Malaise Trap ◽  
Number Of Factors ◽  
Large Numbers ◽  
Set Up ◽  
Taxonomic Groups ◽  
A Site ◽  
Malaise Traps

AbstractThe Malaise trap has gained popularity for assessing diverse terrestrial arthropod communities because it collects large samples with modest effort. A number of factors that influence collection efficiency, placement being one of them. For instance, when designing larger biotic surveys using arrays of Malaise traps we need to know the optimal distance between individual traps that maximises observable species richness and community composition. We examined the influence of spacing between Malaise traps by metabarcoding samples from two field experiments at a site in Waterloo, Ontario, Canada. For one experiment, we used two trap pairs deployed at weekly increasing distance (3m increments from 3 to 27 m). The second experiment involved a total of 10 traps set up in a row at 3m distance intervals for three consecutive weeks.Results show that community similarity of samples decreases over distance between traps. The amount of species shared between trap pairs shows drops considerably at about 15m trap-to-trap distance. This change can be observed across all major taxonomic groups and for two different habitat types (grassland and forest). Large numbers of OTUs found only once within samples cause rather large dissimilarity between distance pairs even at close proximity. This could be caused by a large number of transient species from adjacent habitat which arrive at the trap through passive transport, as well as capture of rare taxa, which end up in different traps by chance.

scholarly journals Detecting Long-Term Urban Forest Cover Change and Impacts of Natural Disasters Using High-Resolution Aerial Images and LiDAR Data

2020 ◽  
Vol 12 (11) ◽  
pp. 1820
Author(s):  
Raoul Blackman ◽  
Fei Yuan
Keyword(s):  
Remote Sensing ◽  
Ecosystem Services ◽  
Forest Canopy ◽  
High Spatial Resolution ◽  
Urban Forest ◽  
Urban Canopy ◽  
Canopy Cover ◽  
Random Point ◽  
Aerial Images ◽  
Lidar Data

Urban forests provide ecosystem services; tree canopy cover is the basic quantification of ecosystem services. Ground assessment of the urban forest is limited; with continued refinement, remote sensing can become an essential tool for analyzing the urban forest. This study addresses three research questions that are essential for urban forest management using remote sensing: (1) Can object-based image analysis (OBIA) and non-image classification methods (such as random point-based evaluation) accurately determine urban canopy coverage using high-spatial-resolution aerial images? (2) Is it possible to assess the impact of natural disturbances in addition to other factors (such as urban development) on urban canopy changes in the classification map created by OBIA? (3) How can we use Light Detection and Ranging (LiDAR) data and technology to extract urban canopy metrics accurately and effectively? The urban forest canopy area and location within the City of St Peter, Minnesota (MN) boundary between 1938 and 2019 were defined using both OBIA and random-point-based methods with high-spatial-resolution aerial images. Impacts of natural disasters, such as the 1998 tornado and tree diseases, on the urban canopy cover area, were examined. Finally, LiDAR data was used to determine the height, density, crown area, diameter, and volume of the urban forest canopy. Both OBIA and random-point methods gave accurate results of canopy coverages. The OBIA is relatively more time-consuming and requires specialist knowledge, whereas the random-point-based method only shows the total coverage of the classes without locational information. Canopy change caused by tornado was discernible in the canopy OBIA-based classification maps while the change due to diseases was undetectable. To accurately exact urban canopy metrics besides tree locations, dense LiDAR point cloud data collected at the leaf-on season as well as algorithms or software developed specifically for urban forest analysis using LiDAR data are needed.

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