The page lists 38 deliverables related to the research project "AfricanBioServices".
title and desprition | type | last update |
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Quantitative modelling of land useMuch data is already available on human population density, settlements, wildlife and livestock densities, rainfall, primary biomass production, agricultural practices and land use from WP1. AfricanBioServices will also have access to collected microeconomic and cultural data from household surveys. Groups of experts in economic development, conservation, forestry, and agriculture have described the various competing land uses. The land cover/use will be updated by ILRI, DRSRS, NTNU and TAWIRI will map land cover of the Greater Serengeti Mara Ecosystem in 2015. The land cover/use will be updated by using the newly launched Landsat 8. Maps for 1975, 1995 and 2015 will be derived from the interpretation of satellite images to describe the development of the land cover from 1975 to 2015. Existing data on human population density, settlements, wildlife and livestock densities, rainfall, primary biomass production, agricultural practices, microeconomic and cultural data from household surveys are used to evaluate the most important drivers and related factors with land cover changes. A Bayesian belief network for land cover changes and projection will be developed based on consultation with stakeholders and the relative importance of land-use activities and other external factors. Part of the data gathering will be by developing and playing a board game with stakeholders on different levels simulating development of local communities. NTNU, NINA, in collaboration with UCPH will parameterize the results of different competing land-use scenarios on future land cover, welfare and ecosystem integrity. Scenarios of land use change between 2015 and 2030 will be developed based on forecasts of population growths and management strategies. We furthermore discuss with stakeholders the drivers and affinities for developing local communities in the direction of “Downward spiralâ€, “Green Havenâ€, “Globalisation†and “Local Sustainable Communitiesâ€. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
Building databaseValidated data will be brought together in a centralized database (NTNU will coordinate the work) which is user friendly and can be accessed by the scientific community, conservationists, and general public. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Open Research Data Pilot | 2020-04-09 |
Carnivore, vulture and other raptor densities surveyed by call-in stationsTo assess the effect of different land-use types and management regimes on carnivore and vulture populations, call-in station surveys will be conducted in selected parts of Serengeti National Park, Ngorongoro Conservation Area, and Loliondo Game Controlled Area (NTNU, NINA). The survey will replicate the census methodology conducted by Maddox (2003), such that information between the two time periods is comparable, and can be linked to data on potential drivers of change during the two periods. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
Maps on biophysical and socioeconomic characteristicsThe deliverable constitutes a selection of GSME management relevant maps based on spatial data collated by WP1 and generated by UCPH form the data in Deliverable 5.1. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
EVALUATION OF WELFARE IMPLICATIONS OF ECOSYSTEM SERVICE AND MANAGEMENT CHANGEThe deliverable constitutes a report describing household welfare implications of future scenarios of change (task 5.1). Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
Data Management Plan FinalWork: AfricanBioServices\' Data Management Plan (DMP) is a document that will describe the data management life cycle for all data sets that will be collected, processed or generated by AfricanBioServices .It will outline how research data will be handled during AfricanBioServices, and even after the project is completed, describing what data will be collected, processed or generated and following what methodology and standards, whether and how this data will be shared and/or made open, and how it will be curated and preserved. The DMP will not be a fixed document; it evolves and gains more precision and substance during the lifespan of the project. The first version of the DMP is expected to be delivered within the first 6 months of the project by NTNU in collaboration with TAWIRI. This DMP deliverable will be in compliance with the template provided by the Commission. More elaborated versions of the DMP will be delivered at later at M 18, M36 and M48. New versions of the DMP will be created whenever important changes to the project occur due to inclusion of new data sets, changes in consortium policies or external factors. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Open Research Data Pilot | 2020-04-09 |
LITERATURE REVIEW AND POLICY ANALYSIS IDENTIFYING PERFORMANCE PROBLEMS OF TANZANIA\'S WILDLIFE MANAGEMENT AREAS AND THEIR CAUSESThe deliverable constitutes a working paper report (under task 5.2) applying a literature review to identify problems in the implementation and functioning of Wildlife Management Areas (WMAs) in Tanzania and a policy analysis to trace the legal origin and cause of these problems. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
SYNTHESIS OF STUDIES OF POLICY OUTCOMESThe deliverable constitutes a report synthesising the insights of several independent studies carried out under AfricanBioServices (task 5.2). These include evaluating experience with selected environmental management policies, the role of different institutions in environmental management, the role of resource degradation as a driver of conflicts all providing information and recommendations for improved policy development. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
How wildlife affects fire frequencyThe migrating wildebeest and zebra in the region consume about 6,900 tonnes of grass per day. It may be too simple however to see this as only competition for livestock. Increased residency time of wildebeest on village lands may dampen the effects of climate change by removing biomass and reducing fire frequency. This may in turn promote a greater diversity of vegetation and improve the resilience of village lands to external perturbations as intense fires and droughts. RUG, TAWIRI and UG will investigate if (a) GPS collared wildebeest are attracted to areas of new growth following recent fires (MODIS imagery), and (b) if areas frequented by wildebeest burn less often (due to removal of biomass), with consequences for woodland cover and grazing opportunities. Building from Task 2.2 ILRI, UG and RUG will compare vegetation diversity over 3 years in 20 Whitaker plots located in village grazing lands that are shared with the migration with 20 plots that are not shared with the migration, across regional soil and rainfall gradients. ILRI, UG and RUG will record the fire return interval in each area, changes in vegetation structure as well as placing camera traps to quantify the amount of grazing by livestock versus migrants. Thus ILRI, UG and RUG will be able to determine links between fires, wildebeest and vegetation resilience that enhance the sustainability of village lands and enhance the benefits that people derive from the ecosystems in terms of improved grazing, provision of fire wood, and wild harvests (such as honey, medicinal plants and herbs). Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
Ecotourism benefit sharing strategiesUG will map and classify land-use types around the Greater Serengeti-Mara Ecosystem, including survey data on the key economic indicators for individual tourism operators. Wild dogs will be used as model species to elucidate the values, trade-offs and options for balancing wildlife-based tourism with depredation on livestock. NTNU, TAWIRI and NINA will conduct an analysis of predation risk of livestock by wild dogs into encounter and kill rates by relating resource selection of wild dogs (subtask 2.2.1) and livestock densities (Task 4.5) with kill sites of livestock (Hebblewhite et al. 2005). The distribution of individual tourist operations will be overlapped with (de)predation risk maps to assess strategies for sustainable ecotourism initiatives. Wildebeest and zebra will be used by UG as model species to investigate the conditions in which migratory species may provide ecotourism revenues. Pilot data shows that cortisol, progesterone, and nitrogen15 isotopes vary over the tail-hair length and provide reliable metrics of stress, reproduction, and starvation cycles. Every 18 months TAWIRI will recapture the GPS collared animals (subtask 2.2.1) and collect hair samples. By combining the time-sequence of hair samples with GPS data UG, NTNU and NINA will be able to determine if the behaviour of the animal is due to stress (high cortisol). These two exemplars enable UG, NINA, NTNU and TAWIRI to determine if wildlife are responding to particular management strategies besides their natural biological requirements, and its consequences and options for improved revenues from ecotourism on village lands and other management areas. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
Biodiversity in areas of different land useBy comparing the abundance and diversity over multiple sites covering the region, NTNU, NINA, SUA and UDSM will identify indicators of healthy and natural ecosystems compared to those that are exploited by humans. Microbe diversity (fungi and bacteria) will be investigated by identifying eDNA in soil samples (NTNU, UDSM)) (Acosta-Martinez et al. 2008). eDNA in water samples will be analysed to assess the diversity of amphibians, reptiles and fish (NTNU, UDSM,) (Thomsen et al. 2012). Birds and mammals will be recorded by NTNU, NINA and UDSM using road transects and rodents using traps. Data on local knowledge and utilization of birds and mammals will be collected in villages surrounding Serengeti National Park by presenting questionnaires to villagers (NTNU, SUA). Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
Fieldwork with partnersCollection and integration of existing data is not only important in the identification of gaps in existing information and knowledge but also avoids repetition and duplication during execution of the proposed study. In general the available data (animal, livestock and human population censuses, biodiversity, vegetation and soil maps, aerial photos, etc.), are scattered in different institutions and national archives in the form of paper reports, excel sheets, GIS, and in graphical presentations. This makes it difficult to access the data, preventing them from being used to assist in interpretation on the status of biodiversity and livelihoods In addition to existing data, gaps will be filled by collecting new data for the four other science WPs (WP2-5). WP1 will help to provide baseline data for WPs 2-5 which will then be used to establish patterns and trends in the social, economic and ecological components in the Greater Serengeti-Mara Ecosystem and use it for advising on the best options in mitigating the impact of drivers of change on biodiversity for enhanced ecosystem services. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
Disseminate to general publicAfricanBioServices plan to be publishing high quality scientific papers aimed at high impact journals (e.g. Ecology, Conservation Biology, Journal of Applied Ecology, Journal of Animal Ecology, PLOS one, Trends in Ecology and Evolution); 1) on the website, 2) through own series of AfricanBioServices Technical Papers (as a numbered series). The consortium will develop an internal review process which would be used to maintain a high standard of the scientific papers aimed for high impact journals. NTNU will design a style and Technical Paper layout to be used by all consortium members. This will become a landmark series, reporting data, new protocols and processes, and the more technical details of the project not amenable for journal publication. In addition, publications and attendance to international conferences, providing unique interaction with the scientific community, is also planned. There will be occasions to share our expertise in this specific field with other leading European researchers, research managers, and potential users who are active in the ecosystem services sciences sectors. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
Models of choice of livelihood strategiesThe deliverable constitutes a working paper report containing an outcome of task 5.3 applying field economic experiments to evaluate household demand for selected environmental goods and options for reducing this demand. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
List of scientific presentationsThe dissemination to the academic, private and governmental sectors outside the project for transfer and utilization of AfricanBioServices obtained knowledge and technology. List of scientific presentations produced Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
Dissemination and exploitation plan finalThe final version of the PEDR. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
Modelled wildlife and livestock populationUnderstanding responses of livestock and wildlife populations to climate and land use changes and human population growth is crucial to planning effective management and conservation, and sustainable ecosystem services. UHOH will relate wildlife and livestock population trends and distribution to existing climate, NDVI, land use and human population data using statistical models. Reliable estimates of projected future population sizes and the associated demographic and sampling uncertainties are important for quantifying expected changes in wildlife and livestock population sizes and population responses to changes in climate, land use and anthropogenic activities. UHOH will use existing climate, land use and human population growth data to build a hidden process model for predicting future population sizes and predicted rainfall scenarios to explore likely future population performances. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
Impact of land-use on nutrient availabilityNutrient cycling will be measured via transplantation experiments and using small-scale manipulative exclosures in locations varying in precipitation across the region; inside protected areas compared to pastures outside the park (NTNU, SUA). For the transplant experiment, whole grass turfs will be moved to other regimes of land use or precipitation and compared to each other and to non-moved vegetation. Also the nutrient contents of the soils will be compared. The small-scale manipulative exclosures will make it possible to harvest and analyse nutrient contents in leaves in the different land use types during different periods of the year. In this way NTNU, SUA and UDSM will determine how land-use influences nutrient contents in soils and the temporal variation in grass nutrient levels during the year and dependent on different grazing regime or region. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
Models on spatial patterns in welfare dependence on ecosystem servicesThe deliverable constitutes a report presenting an analysis of the determinants of reliance on selected ecosystem services in the GSME based on the household questionnaire survey data contained in the database constituting deliverable 5.1. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
Impact of wildlife movements on sicknessDisease transmission between wildlife and livestock is often controlled by fencing, which may negatively affect ecosystem services by disconnecting fundamental processes. Recent advances in epidemiological surveillance in the Serengeti allows us to investigate alternative disease control strategies that will enhance the sustainability of mixed wildlife-livestock systems and optimize ecosystem services (Ferguson et al. 2013). UG, ILRI and TAWIRI will investigate ecosystem-oriented control strategies of FMD in a threefold approach. UG, ILRI and TAWIRI will use focused group discussions and key informant interviews with livestock keepers to understand the economic, environmental, social and political drivers in livestock management strategies. The second component will quantify the probability of transmission between livestock and wildlife by deploying GPS loggers on cattle to monitor their movement in relation to that of wildebeest in different land-use areas. Third, UG, ILRI and TAWIRI will extend the existing surveillance and sample banks of FMD in livestock to include opportunistic sampling of wildlife (from routine immobilization) with particular emphasis on the populations of migrating wildebeest that routinely encounter livestock. Finally these datasets will be combined to develop an epidemiological model of FMD transmission that can be used to identify potential barriers and test different vaccination strategies, such as reactive point vaccinations versus pro-active buffer area vaccinations or sporadic versus continual vaccinations. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
Dissemination and exploitation plan version 1This deliverable will match specific outputs with expected impacts and identify processes or dissemination pathways that will need to be for those outputs to achieve the intended impacts. Examples of these impacts include change in knowledge within the target communities, revision of the existing policies based on the information generated by the project or enactment of new ones, integration of the knowledge developed in training curricular in schools and colleges, etc. The plan will be developed in consultation with all the work package leaders who would be expected to take the lead role in identifying outputs that are likely to generate impacts and making suggestions on strategies to use to achieve the set targets. To a large extent, the exploitation plan uses most of the information given in the dissemination plan (D6.5) although it will specifically identify ways in which outputs from the project would be used to achieve impacts, not only in the local communities but also in other areas where the project outputs would be relevant. The deliverable will be developed by ILRI with inputs from NTNU. The delivery deadline is 31st November 2018. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
Household reliance on illegal huntingIllegal bushmeat provides a critical source of dietary protein for many people (Damania et al. 2014) with ca. 98,000 wildebeest hunted annually (Rentsch & Packer 2014). Offtake levels are often in excess of 10% of the population and are biologically unsustainable. A comprehensive overview of the general trends of this provisioning service is missing, in particular how rainfall, soil fertility, distance to protected area, law enforcement intensity and land use strategy (agriculture vs. pastoralism) determine whether people partake in illegal hunting or opt for other livelihoods. NTNU, SUA, UDSM and TAWIRI will combine existing data on illegal hunting and agriculture from the different conservation authorities in the Greater Serengeti-Mara Ecosystem (see WP1) into a single dataset, which will be analysed in a GIS framework to develop a statistical predictive framework of illegal hunting incidents. Given that time spent hunting detracts from the time available for farming, NTNU SUA, UDSM and TAWIRI will investigate the scenarios under which people switch between these two alternate livelihoods in different regions of the ecosystem. This will be combined with the result of household surveys in which indicators for the contribution of illegal hunting to food provisioning and income are estimated. Results will highlight illegal hunting hotspots and can be used to develop alternative sustainable food security and income strategies. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
Evaluation of impact of precipitationThe transplantation experiment carried out in WP2 will be used to estimate the effects of precipitation on grassland vegetation. The transplantation of vegetation turfs from different rainfall areas into the common gardens will enable estimation of the sensitivity and rate of change of the different vegetation types to the combination of different grazing pressures and precipitation regimes. NTNU will analyse species compositional changes, using traits-based approaches and changes in productivity and nutrient cycling (UDSM) as a consequence of changes in precipitation regimes (UDSM). Furthermore, we analyse the metal levels in soils and plants in response to different precipitation regimes to provide knowledge that can help modelling the effect of climate on biodiversity and ecosystem dynamics (UDSM). Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
Impact of land use on mammalsSpecies-specific responses in movement behaviour to anthropogenic disturbance (land-use and infrastructure) will be modelled by UG, TAWIRI, NTNU and NINA for GPS collared wildebeest UG, TAWIRI), zebra (UG, TAWIRI), impala (NTNU, NINA, TAWIRI)and wild dogs (NINA, NTNU, TAWIRI) using a hierarchical spatial approach assessing effects on both distribution (resource selection functions, niche overlap) and behavioural decisions (step selection functions). Species-specific vulnerability to modified landscapes at different trophic levels may decouple trophic interactions. NTNU, TAWIRI and NINA will conduct an analysis of the predator-prey interaction by assessing how land-use and infrastructure alters the resource use of wild dogs and impala (Hebblewhite et al. 2005). UG, NINA and NTNU will investigate chronic levels of stress in the GPS collared wildebeest (UG) and impala (NTNU, NINA) (from tail hairs and faeces, respectively) to determine if human disturbance illicits a stress response in respectively migrating and resident herbivores that changes their behaviour and occupancy. In impala, observational studies by NTNU and NINA will be used to link stress levels to flight initiation distance, vigilance and habitat selection. The effects of the land use and infrastructure on the traditional routes and occupancy times of migrating herbivores will be analysed by UG using GPS collars and camera traps in village lands. These changes in turn may affect grazing pressure and nutrient cycles. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-04-09 |
Meeting with local stakeholdersAfricanBioServices will organize two meetings with local stakeholders (as defined in section 2.2.1); one meeting in Loliondo (Tanzania) and one in Narok (Kenya). A public AfricanBioServices symposium/workshop to present results from the research on ecosystem services and its potential applications will be organized in year 3 of the project. AfricanBioServices will use existing established dissemination channels, services and networks including seven Universities, which will assure broad exposure of the project in the educational and scientific community. ILRI and TAWIRI will be responsible for the day-to-day communication with the local stakeholders in Kenya and Tanzania. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-03-24 |
Ecosystem resilience across landscapeCombining and synthesizing existing data with novel field data and with remote sensing, RUG will parameterize different ecosystem configuration models, to capture the key differences in the organization of ecosystems along gradients of rainfall, soil fertility and temperature (with elevation as a proxy). Novel ecosystem configuration models will be used to assess differences among ecosystems in resilience in response to climatic extremes and land use change (forest clearing). These models capture the alternative flows that energy and nutrients can take between different compartments in ecosystems, with the option for different stable configurations, and regime shifts that change the ecosystem from one state to another. This will be done for the three main landscape zones of the river basins in the area (Fig. 1): the upland catchment areas, the midslope protected areas with migrant wildlife, and the lowland agricultural areas outside the protected areas. For each landscape zone, the dependence of ecosystem resilience (measured by the diversity of flora in relation to grazing pressure and fires) on key environmental drivers (rainfall, soil fertility, temperature) will be evaluated. This task takes a landscape-level perspective across the study area (Fig. 1) integrating specific mechanistic studies on the interplay of wildlife, livestock, water and fire. This sets the stage for the following tasks by paying special attention to the key spatial connections between landscape zones as well as how ecosystem service strategies may perturb or enhance ecosystem resilience. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-03-24 |
Public symposium/workshopPublic symposium/workshop Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-03-24 |
Impact of land use on productivity and nutrient cyclingProductivity will be measured in small-scale manipulative exclosures established by NTNU, SUA, and UDSM in locations varying in precipitation across the region; inside protected areas compared to pastures outside the park. NTNU, SUA, UG and UDSM will estimate the impacts of wildlife (fenced compared to unfenced inside the park) and livestock (fenced plots compared to unfenced plots outside the national park) and climate (variable rainfall regimes) on aboveground and belowground plant productivity. Complimenting this study, aboveground and belowground plant litter will be decomposed to contrast effects of land-use and rainfall on litter recycling. DNA metabarcoding of faecal samples will be used to assess the diet of goats and impala both inside and outside the park to identify key food plants (Pegard et al. 2009). Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-03-24 |
ANALYSIS OF CHOICE OF LIVELIHOOD STRATEGIES IN RESPONSE TO ROAD DEVELOPMENTThe deliverable constitutes a working paper report (under task 5.3) applying a choice experiment to evaluate household preferences for livelihoods activity changes in response to reduced travel time to markets as a consequence of road development. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-03-24 |
Data base on household incomeThe deliverable constitutes a database containing the result of a household questionnaire survey in the GSME (task 5.1) aiming to quantify household reliance on selected tangible ecosystem services accompanied by a report describing the variables included in the database. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-03-24 |
Assessment of cyclicity of weatherBivariate cycles, such as in rainfall and temperature, can have widely different impacts on vegetation and animals than independent cycles in both components. UHOH will use existing climate data to build models to test for evidence of and quantify bivariate seasonal oscillations in weather components in the Greater Serengeti-Mara Ecosystem. Testing for presence and significance of bivariate cycles and quantifying quasi-periodic bivariate annual and seasonal rainfall, temperature and NDVI oscillations will be based on squared coherence and bivariate structural equation models (Diggle 1990; Harvey 1990). Climate change and land use change may also lead to progressive shifts in seasonal weather characteristics. UHOH will use existing climate data to build models for establishing if seasonality in rainfall, temperature and NDVI is progressively changing (evolving) over time in the Greater Serengeti-Mara Ecosystem.using complex demodulation analysis and structural time-series models. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-03-24 |
RENEWABLE RESOURCE SCARCITY, INSTITUTIONS, AND THE SUPPORT OF VIOLENCEThe deliverable constitutes a working paper report (under task 5.2) testing hypothesis about the relationship between access to scarce or declining resources, poverty and inequality and violent conflicts. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-03-24 |
Data Management Plan version 3Work: AfricanBioServices\' Data Management Plan (DMP) is a document that will describe the data management life cycle for all data sets that will be collected, processed or generated by AfricanBioServices .It will outline how research data will be handled during AfricanBioServices, and even after the project is completed, describing what data will be collected, processed or generated and following what methodology and standards, whether and how this data will be shared and/or made open, and how it will be curated and preserved. The DMP will not be a fixed document; it evolves and gains more precision and substance during the lifespan of the project. The first version of the DMP is expected to be delivered within the first 6 months of the project by NTNU in collaboration with TAWIRI. This DMP deliverable will be in compliance with the template provided by the Commission. More elaborated versions of the DMP will be delivered at later at M 18, M36 and M48. New versions of the DMP will be created whenever important changes to the project occur due to inclusion of new data sets, changes in consortium policies or external factors. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Open Research Data Pilot | 2020-03-24 |
LAND DIVISION, DISPOSSESSION AND FENCING IN THE MAASAI MARA, KENYAThe deliverable constitutes a working paper report (under task 5.2) describing the land division, dispossession and fencing occurring in the Maasai Mara of Kenya analysed from a political ecology perspective focusing on the inclusion and exclusion of local people in wildlife conservation. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-03-24 |
Modelled trends in climate and vegetation and characteristics of extreme eventsUHOH will gather existing climate data, perform quality control, literature research and hypothesis formulation for the climate model. Then it will characterize trends, test for presence and quantify seasonality in rainfall, temperature, and NDVI. Trends and seasonality in rainfall, temperature and Normalized Difference Vegetation Index (NDVI) in the Greater Serengeti-Mara Ecosystem will be modelled using structural time-series models, semi-parametric generalized linear mixed models and spectral density analysis. UHOH will also test for spatial coherence in the established trends and seasonality in rainfall, temperature and NDVI across the Greater Serengeti-Mara Ecosystem. Evidence for regional temperature warming and progressive habitat desiccation will be assessed using semi-parametric regression analysis (Ruppert 2003) based on penalized cubic B-splines and constructed penalized cubic basis spline effects to contrast temperatures at any two given time points to test for significance of a warming trend. UHOH will use existing rainfall data, conduct appropriate quality controls, literature review and develop hypotheses for the drought and flood model. Next, it will quantify the recurrence frequency, severity, timing and multi-annual persistence of climatic extremes. UHOH will also use statistics of rarity to quantify recurrence frequency of climatic extremes, standardized percentile departure from long-term means to quantify severity, and lag-autocorrelations and number of runs of wet or dry years to quantify multi-annual persistence of droughts and floods in the time series of rainfall, temperature and NDVI in Greater Serengeti-Mara Ecosystem. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-03-24 |
Ethics requirement reportCopies of ethical approvals by the competent legal local/national Ethics Boards/Bodies/administrations must be submitted to the EASME prior to the commencement of the research. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-03-24 |
Website, Project leaflet producedNTNU will build and maintain a website and produce brochures to disseminate results from WPs 1-5 to the general public. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-03-24 |
Collection of social, economic and ecological dataBy collecting and compiling existing data from all relevant sources TAWIRI and ILRI will bring together the baseline data necessary for WPs 2-5 and identify gaps in existing information and knowledge. TAWIRI will collect baseline data from Tanzania National Parks (TANAPA), Ministry of Natural resources and Tourism (MNRT), Wildlife Division (WD), Forestry and Beekeeping Division (FBD), Ngorongoro Conservation Area Authority (NCAA), Tanzania Meteorological Authority (TMA), National Bureau of Statistics (NBS), Institute of Resource Assessment (IRA), Local Government Authorities adjacent to the Greater Serengeti-Mara Ecosystem and Tanzanian universities. ILRI NTNU and KWS will collect data from KWS, regional remote sensing and surveying institutions, universities, and government, all in Kenya as well as counties adjacent to Greater Serengeti-Mara Ecosystem. The baseline data established in Task 1.2 will be entered into centralise databases at TAWIRI and ILRI and used in WPs 2-5. NTNU will assist TAWIRI in establishing and running the databases. Programme: H2020-EU.3.5.2. - Topic(s): SC5-06-2014 |
Documents, reports | 2020-03-24 |