Tree characteristics and vegetation structure in the interior of Arabuko-Sokoke Forest and adjacent farmlands in Gede, Kilifi County, Kenya

Latest version published by National Museums of Kenya on Nov 21, 2018 National Museums of Kenya

We present data on tree characteristics and vegetation structure in the interior of Arabuko-Sokoke Forest (ASF) and human-modified habitats (farmlands) on the eastern part of this coastal forest in Gede, Kilifi County Kenya. A total of 210 Point-Centered Quarter (PCQ) points were used to sample vegetation in each habitat type. Each PCQ point was ≥ 30 m distant from each other, and in each quarter of the PCQ point we recorded the following data: the nearest tree species of at least 20 cm Diameter at Breast Height (DBH), its crown diameter and distant of the tree from the centre of PCQ point. At the centre of each PCQ we also recorded percentage understory vegetation density and canopy cover. Results show that the interior of ASF was dominated by indigenous trees (Brachystegia spiciformis (30%), followed by Cynometra webberi (29%) and Manilkara sansibarensis (18); while in the farmland it was dominated by exotic fruit trees (coconut (Cocos nucifera (54%), followed by mango (Mangifera indica (31%) and cashew nut (Anacardium occidentale (11%). The mean distance between trees (>20cm in DBH) in the farmlands (9.5M) was smaller than in the forest interior (10.95M). The % understory vegetation density of forest interior (38.2 ±1.5) was higher than that of the farmlands (5.8 ± 1.3). The % canopy cover of the forest (42.8±1.4) was more closed than that of the farmlands (29.3 ±1.9). This information provides a baseline information on the vegetation structure of the two main habitat types, and can be used to monitor habitat structure trends in the long run.

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How to cite

Researchers should cite this work as follows:

Musila S, Syingi R, Gichuki N, Castro-Arellano I (2018): Tree characteristics and vegetation structure in the interior of Arabuko-Sokoke Forest and adjacent farmlands in Gede, Kilifi County, Kenya. v1.2. National Museums of Kenya. Dataset/Occurrence. http://ipt.museums.or.ke/ipt/resource?r=vegetation2016&v=1.2

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The publisher and rights holder of this work is National Museums of Kenya. This work is licensed under a Creative Commons Attribution Non Commercial (CC-BY-NC) 4.0 License.

GBIF Registration

This resource has been registered with GBIF, and assigned the following GBIF UUID: 10a90c7d-6459-45b3-a0f2-a507a54bbc9f.  National Museums of Kenya publishes this resource, and is itself registered in GBIF as a data publisher endorsed by GBIF Kenya.

Keywords

Observation; Vegetation; Structure; Brachystegia; Cynometra; farmlands; Arabuko Sokoke Forest; Gede; Occurrence

Contacts

Who created the resource:

Simon Musila
Head of Section - Mammalogy
National Museums of Kenya, Zoology Department Museum Hill Road 40658 Nairobi Nairobi KE
http://www.museums.or.ke
Robert Syingi
Research Intern
National Museums of Kenya Museum Hill Road 40658 - 00100 Nairobi Nairobi KE
Nathan Gichuki
Professor
University of Nairobi, School of Biological Sciences Chiromo Nairobi Nairobi KE
Ivan Castro-Arellano
Associate Professor
Texas State University-San Marcos 7866-4684 San Marcos Texas US

Who can answer questions about the resource:

Simon Musila
Head of Section - Mammalogy
National Museums of Kenya Museum Hill Road 40658 Nairobi Nairobi KE

Who filled in the metadata:

Simon Musila
Head of Section - Mammalogy
National Museums of Kenya Museum Hill Road 40658 Nairobi Nairobi KE

Who else was associated with the resource:

Processor
Esther Mwangi
Research Scientist
National Museums of Kenya Museum Hill Road 40658 Nairobi Nairobi KE
http://www.museums.or.ke
Publisher
Lawrence Monda
ICT Manager
National Museums of Kenya Museum Hill Road 40658 Nairobi Nairobi KE
http://www.museums.or.ke

Geographic Coverage

The interior of Arabuko-Sokoke Forest (ASF) and adjacent farmlands around Gede (especially Mtsangoni, Mida, Arabuko, Gede, Watamu and Msabaha villages), Kenya

Bounding Coordinates South West [-3.504, 39.79], North East [-3.197, 40.018]

Taxonomic Coverage

Various plants taxon

Kingdom  Plantae

Temporal Coverage

Start Date / End Date 2016-11-11 / 2016-11-27

Project Data

No Description available

Title Factors influencing bat community structure and temporal activity patterns in Arabuko-Sokoke Forest and adjacent human-modified habitats, Gede-Malindi, Kenya
Identifier BID-AF2017-0274-NAC
Funding The project was funded by British Ecological Society (Ecologists in Africa (http://www.britishecologicalsociety.org/funding/ecologists-in-africa/) grant Number 4632-5670) and Sino-African Joint Research Center, CAS (SAJC201612). We appreciate the guidance provided by Simon Kajengo during vegetation surveys in Gede villages and assistance in data collection by Aaron Musyoka.
Study Area Description Point-centered Quarter (PCQ) method (Cottam and Curtis 1956; Cintrón and Schaeffer 1984) was used to sample woody vegetation in ASF and farmland where bats were studied. PCQ points were ≥ 30 m distant from each other so as to avoid sampling the same trees on two different points. In each quarter we recorded the nearest tree species of at least 20 cm Diameter at Breast Height (DBH) measured by ruler, and the distance of the tree from the centre of the PCQ point estimated by pacing (Mitchell 2007). A total of 70 PCQ points were selected each in Cynometra, Brachystegia and mixed vegetation types in ASF, as well each in mango, coconut and mixed tree plots on the farmlands. We used cover boards to assess percent understory vegetation density (Robel et al. 1970; Devos and Mosby 1971; Nudds 1977). A plywood board, painted in white-and-red checkerboard pattern (twenty five 10 ×10 cm squares) was used to assess % understory vegetation density around each PCQ point. One observer counted the number of squares that were >50% obscured by vegetation, from a board held at 1.5 m above the ground by an assistant at a distance of 5 m from the centre of PCQ point, both in the North and South compass direction. The percentage canopy cover was assessed by eye as described by Korhonen et al. (2006) and Lentini et al. (2012) bearing in mind that it may not be possible to control for bias in visual estimation, because the human eye is notoriously poor at making consistent estimations (Jennings et al. 1999). We used a toilet roll as a sighting tube to estimate the % vegetation directly above the exposed area (45 mm in diameter, 98 mm long) of the toilet roll tube (Fanshawe 1993). The sighting tube was always held vertically at each point to reduce the error in % canopy cover estimation (Jennings et al., 1999). Our data was aligned to the Darwin Core standards before publishing on Global Biodiversity Information Facility (GBIF) through the Integrated Publishing Toolkit (IPT) at National Museums of Kenya.

The personnel involved in the project:

Robert Syingi

Bibliographic Citations

  1. Cintrón G, Schaeffer NY (1984) Methods for studying mangrove structure. In: Snedaker SC, Snedaker JG (eds) The mangrove ecosystem: research methods. UNESCO, Paris, pp 91-113
  2. Cottam G, Curtis JT (1956) The use of distance measures in phytosociological sampling. Ecology 37:451-460 https://doi.org/10.2307/1930167
  3. DeVos A, Mosby HS (1971) Habitat analysis and evaluation. In: Giles GR (ed) wildlife management techniques. The Wildlife Society, Washington DC, pp 142-143
  4. Fanshawe, J.H. 1993. The effects of selective logging on bird community of Arabuko-Sokoke Forest, Kenya. PhD thesis. University of Oxford. Oxford. pp. 210.
  5. Jennings SB, Brown ND, Sheil D (1999) Assessing forest canopies and understorey illumination: canopy closure, canopy cover and other measures. Forestry 72(1):59-73. https://doi.org/10.1093/forestry/72.1.59
  6. Lentini PE, Gibbons P, Fischer J, Law B, Hanspach J, Martin TG (2012) Bats in a Farming Landscape Benefit from Linear Remnants and Unimproved Pastures. PLoS ONE 7(11): e48201. doi:10.1371/journal.pone.0048201 https://doi.org/10.1371/journal.pone.0048201
  7. Korhonen L, Korhonen KT, Rautiainen M, Stenberg P (2006) Estimation of Forest Canopy Cover: a Comparison of Field Measurement Techniques. Silva Fennica 40(4):577-588
  8. Mitchell K (2007) Quantitative analysis by the point-centered quarter method. Hobart and William Smith Colleges, Geneva and New York
  9. Nudds TD (1977) Quantifying the vegetation structure of wildlife cover. Wildlife Society Bulletin 5:113-117 https://www.jstor.org/stable/3781453
  10. Robel RJ, Briggs JN, Dayton AD, Hulbert LC (1970) Relationship between visual obstruction measurements and weight of grassland. Journal of Range Management 23:295-297 DOI: 10.2307/3896225

Additional Metadata

Alternative Identifiers 10a90c7d-6459-45b3-a0f2-a507a54bbc9f
http://ipt.museums.or.ke/ipt/resource?r=vegetation2016