Data from ILAM surveys conducted by ARCOS in Mukura landscape for year 2016
Latest version published by Albertine Rift Conservation Society (ARCOS) on Sep 28, 2021
In the effort to promote informed policy and decision making and planning at different levels of the government, ARCOS conducts regular surveys in key landscapes in Rwanda. These studies follow a framework termed Integrated Landscape Assessment and Monitoring (ILAM) where biodiversity, ecosystem services and socio-economic aspects are looked at using indicators classified through the OECD's Pressure-State-Response model. This dataset therefore contains data generated through an ILAM study that was conducted by ARCOS in Mukura landscape (Rutsiro District) in the upstream part of Akagera river. The survey was conducted with funding support from the Rwanda’s Fund for Environment and Climate Change (FONERWA)under a project a project entitled "Using Water_Energy_Food Security Nexus to Promote Climate Resilient Decisions and Model Actions in selected Landscapes along Akagera Basin"
Data Records
The data in this sampling event resource has been published as a Darwin Core Archive (DwC-A), which is a standardized format for sharing biodiversity data as a set of one or more data tables. The core data table contains 30 records. 1 extension data tables also exist. An extension record supplies extra information about a core record. The number of records in each extension data table is illustrated below.
- Event (core)
- Occurrence
This IPT archives the data and thus serves as the data repository. The data and resource metadata are available for download in the downloads section. The versions table lists other versions of the resource that have been made publicly available and allows tracking changes made to the resource over time.
Downloads
Download the latest version of this resource data as a Darwin Core Archive (DwC-A) or the resource metadata as EML or RTF:
| Data as a DwC-A file | download 30 records in English (11 KB) - Update frequency: as needed |
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| Metadata as an EML file | download in English (17 KB) |
| Metadata as an RTF file | download in English (16 KB) |
Versions
The table below shows only published versions of the resource that are publicly accessible.
How to cite
Researchers should cite this work as follows:
Gashakamba F (2018): Data from ILAM surveys conducted by ARCOS in Mukura landscape for year 2016. v1.0. Albertine Rift Conservation Society (ARCOS). Dataset/Samplingevent. http://arbmis.arcosnetwork.org/ipt/resource?r=arcos_ilam_mukura-2016&v=1.0
Rights
Researchers should respect the following rights statement:
The publisher and rights holder of this work is Albertine Rift Conservation Society (ARCOS). To the extent possible under law, the publisher has waived all rights to these data and has dedicated them to the Public Domain (CC0 1.0). Users may copy, modify, distribute and use the work, including for commercial purposes, without restriction.
GBIF Registration
This resource has been registered with GBIF, and assigned the following GBIF UUID: e2ad3813-19df-4440-b757-e2f861770ae5. Albertine Rift Conservation Society (ARCOS) publishes this resource, and is itself registered in GBIF as a data publisher endorsed by Albertine Rift Conservation Society.
Keywords
Samplingevent
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Geographic Coverage
Mukura forest is part of the Gishwati-Mukura national park, a series of patches of mountain forest perched on the steep hills that constitute the Congo-Nile divide. The forest is know for its high degree of endemism both in its fauna and flora taxa and is an important source of good and services that are crucial to livelihoods of surrounding communities.
| Bounding Coordinates | South West [-2.235, 29.416], North East [-1.851, 29.713] |
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Temporal Coverage
| Start Date / End Date | 2016-03-09 / 2016-03-11 |
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Project Data
This dataset has been published with support from a GBIF-mediated initiative called BID (Diodiversity Information for Development). This data itself was collected in the framework of a project implemented by ARCOS with the goal to provide evidence-based policy guidance and promote local actions that foster climate resilience and participatory sustainable development along the Akagera Basin
| Title | The Albertine Rift Biodiversity Data Mobilization Project |
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| Identifier | BID-AF2015-0115-REG |
| Funding | Rwanda's Green Fund (FONERWA) Biodiversity Information for Development (BID) |
| Study Area Description | Mukura landscape corresponds to Mukura forest catchment that covers parts of Rutsiro and Ngororero districts in Western Rwanda. Due to administrative and budgetary constraints, the project only focused on the parts of the landscape located in Rutsiro district. Mukura landscape features many tourism attractions including the shores of Lake Kivu, with several Islands, tea and coffee plantations, and Gishwati and Mukura natural forests where a habitat corridor has been planned to be established between the two forests. The landscape comprises of two major sub-basins that make part of Akagera basin namely Satinsyi and Secoko sub-basins; that cover an area of 50,193 ha. Rutsiro side of the landscape comprises Musogoro and Muregeya sub-basin that makes part of Kivu basin and covers a total area of 23,518 ha. Apart from Mukura natural forest, much of Mukura landscape consists of agro-ecosystems characterized by subsistence agriculture of various crops coupled with extensive cattle farming systems near Mukura forest. |
| Design Description | Four transects of 2 km long each were used, three to cover the variation in habitat types of the forest: one in the interior control zone and two in the edges, and one to cover the agroecosystems outside Mukura natural forest. Transects were approximately designed following existing trails and footpaths. In general, reconnaissance walks were made; where possible footpaths were used to ease access, and enable more sites to be visited. For the agroecosystems and other open habitats, a line transect was followed instead (Owiunji at al. 2005). 1 Bird survey Transects were long enough to cover the variation of habitat types and land uses, for example forest, agriculture and waterbodies. The team used point counts along the transect in the already existing work trails (David Hill at al. 2005). 1.1 Point counts Point counts were used to sample bird’s populations for estimating densities in local areas, determining population trends over regional areas, assessing habitat preferences and other scientific and population monitoring purposes hence, criteria for conducting point counts depend strongly on the purposes to which they will be put (Douglas, 1995). Point counts were used to assess bird species habitat preferences, species richness and abundance as well as the check list of bird species in the landscape. Other recorded data included habitat types and threats rated on 4 categories ranking system. No attempt was made to estimate bird density because of time constraint. The unlimited distance Circular-plot surveyed were established at an interval of 200 m along the preexisting reconnaissance trails (Douglas,1995). Each point in this work was visited twice a day (from 7:30 to 11:30 am and from 14 to 17 pm). At each point, the team waited for 2 minutes to let the birds settle down and then recorded all bird seen or heard for a period of 10 minutes. Dominant habitat types at the points were classified into various categories such as primary or secondary forest, agricultural land and wetland. GPS waypoints were taken for each point to help easier monitoring for the next years. 1.2 Opportunistic sampling Opportunistic observations were also used to maximize the number of species encountered in each transect and in the landscape. All bird species seen or heard at different times of the day outside of point counts transects were recorded and used to update the species list for the surveyed sectors (Owiunji at al. 2005). The analysis focused on classifying bird species encountered along the transects into ecological categories, summaries of individuals in each habitat category to determine major groups that dominate different habitats. Shannon Wiener diversity index, and evenness were calculated to compare diversity in different habitat types. To assess the conservation status of surveyed birds, their status on IUCN Red List and Albertine Rift endemics (ARE) was determined. Birds recorded were assigned the categories below to look at patterns of forest specialists. Ecological categories used in this analysis included: - RB: Resident in the country and breeding recorded confirmed - F: Forest visitor - FF: Forest Specialist-Species typical of forest interiors - NBR: Non-breeding Resident - VS: Visitor/Migrant/Wanderer - NF: Non-forest species - O: Occasional Visitor / - P: Palearctic migrant –a species not breads in Europe or Asia - PAM: Palearctic Migrant - W: Water bird specialist- Normally restricted to wetland or open water - M: Migrant - IAM: Interafrican Migrant - B: Breeding Note that the number of ecological classes is an initial measure of an ecosystem’s wise use while the proportion of classes and their relative abundance are affected by change in ecosystem structure. .2 Butterflies survey Established butterfly monitoring methods are designed for open habitats such as grasslands. Not all rare species’ habitats were easy to see across and navigate, in which case, a new approach to monitoring was necessary (David Hill at al. 2005). The most common method used for monitoring butterfly populations are capture-mark-recapture and transect counts. Capture-mark-recapture methods are the most rigorous because they allow for estimation of daily and total population sizes, recruitment, survival, and detection probabilities (Haddad at al. 2008), but the methods are resource intensive and have the potential to harm fragile butterflies in the marking process (Murphy at al. 1987). The team used the same line transects set by the ornithology team as an alternative and non-invasive method (Thomas at al. 1983) and, to maximize our time spent surveying, each site was visited twice, and the survey ‘‘point’’ (the center of the location where we were conducting our butterfly counts) was based at every 200m along that line (Erica at al. 2015) to reduce the possibility of double counting that could have direct impact on the abundance of butterfly species. At each survey point, butterfly individuals were either captured using the insect net or a high-resolution camera to make sure that butterflies at the point were detected with certainty (Thomas at al. 2010). A magnifying lens, and a hand-book were used for direct identification of individuals captured by the insect net (Erica at al.2015). The team started the survey as soon as they arrived at the survey point and recorded any butterflies flushed from the point upon approach as detected at the start of the survey period which was fixed at 10min to not allow much movements of butterflies toward the observers and hence limit the fact of overestimating the population size and species richness (Buckland at al. 1993). For more precision and accuracy, only butterflies that were distant from the observer in 2 m intervals were recorded (Thomas et al. 2010). All counts were done from 9:30 to 16:30 to reduce factors that can dramatically influence detectability like weather conditions. When it rained, the team had to revisit the transect the following day (Erica at al. 2015). Data were treated using Microsoft excel to calculate the Shannon-Weiner (H’) diversity index, the Evenness (J’) as a measure of species richness in different habitat types. Biodiversity Professional software (Lambshead at al. 1977) was used to plot the rarefaction curve for comparing the species richness in different habitat types and landscapes 3 Dragonflies and damselflies survey For this ILAM survey, multiple sample sites within different natural habitat (Mukura forest), agro-ecosystems and residential areas were sampled for dragonflies and damselflies in Mukura landscape, and Visual encounter surveys of adult odonates were carried out from the month of March to June 2016 randomly in morning 9:30 am to 12:00 and afternoon from 14pm to 16:30 pm with fine weather conditions. The counting zones were 5 m out from water’s edge on one side and 2m on either side of the transect in agroecosystem areas and the team followed the transect set by the ornithology team (smallshine at al.2010). The survey was conducted along a 2km long transect that could cover different types of habitats, and a scan was made in each surveying center for 10 minutes. All the dragonflies and damselflies observed were identified visually with the aid of a pair of close-focus binoculars or caught with an aerial net when necessary and identified using the field guide. Pictures of dragonflies and damselflies were taken using a high-resolution camera to help in subsequent identification. Subsequent captures were identified and released from the insect nets directly. Biodiversity Professional software (Lambshead at al. 1977) was used to plot the rarefaction curve to compare the species richness as important parameters for stability and functioning of an ecosystem in four sampled sites (F. Bibi and Z. Ali 2013) and we used Excel to calculate the Shannon-Weiner (H’) diversity index and the Evenness (J’), to show similarity and differences in the use of 4 sampled sites based on the composition of dragonflies and damselflies species recorded. |
The personnel involved in the project:
Additional Metadata
| Alternative Identifiers | e2ad3813-19df-4440-b757-e2f861770ae5 |
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| http://arbims.arcosnetwork.org/ipt/resource?r=arcos_ilam_mukura-2016 |