Data from ILAM surveys conducted by ARCOS in Mukura landscape for year 2016

Faustin Gashakamba1, Faustin Gashakamba2

1 Albertine Rift Conservation Society, KIG 14 Ave, 1735 Kigali, Rwanda, Kigali, Rwanda; 2 

Corresponding author(s): Faustin Gashakamba (fgashakamba@arcosnetwork.org), Faustin Gashakamba (gashakamba@gmail.com)

Received {date}; Revised {date}; Accepted {date}; Published {date}

Citation: Combination of authors, year of data paper publication (in parentheses), Title, Journal Name, Volume, Issue number (in parentheses), and doi of the data paper.

Resource Citation

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

Abstract

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"

Keywords: Samplingevent

Project details

Project title: The Albertine Rift Biodiversity Data Mobilization Project
Personnel: Dr Sam Kanyamibwa, Jean Paul Kubwimana
Funding: Rwanda's Green Fund (FONERWA)
Biodiversity Information for Development (BID)
Study area descriptions/descriptor: 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.

Data published through GBIF: http://arbims.arcosnetwork.org/ipt/resource?r=arcos_ilam_mukura-2016

Spatial coverage

General spatial 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.
Coordinates: 2°14'6''S and 1°51'3.6''S Latitude; 29°24'57.6''E and 29°42'46.8''E Longitude 

Temporal coverage: March 9, 2016 - March 11, 2016

Datasets

Dataset description
Object name: Darwin Core Archive Data from ILAM surveys conducted by ARCOS in Mukura landscape for year 2016
Character encoding: UTF-8
Format name: Darwin Core Archive format
Format version: 1.0
Distribution: http://arbims.arcosnetwork.org/ipt/archive.do?r=arcos_ilam_mukura-2016
Publication date of data: 2021-09-28
Language: English
Licences of use: Public Domain (CC0 1.0)

Metadata language: English
Date of metadata creation: 2018-04-24
Hierarchy level: Dataset