Ground Monitoring

Vegetation Monitoring

ACP’s ground monitoring is done for both vegetation and herbivores. The surveys are conducted every 4 to 6 weeks.

Herb-layer biomass, greenness and grazing intensity

The monthly ground monitoring of the vegetation is conducted both in the plots shown in the basin area (Figure 2) and in the group ranches image on (Figure 3).

The monitoring that started in 1975 is conducted in each plot, where vegetation cover is measured using the point intercept method (5) . For each frame, ten pins are dropped through a slanting pin frame at an angle of 67°, and each plant hit recorded on a predesigned capture form, onto a digital tablet using open data kit (ODK).

The data is the then transmitted via a cloud network and downloaded onto the ACP’s integrated database (Figure 5) for storage and subsequent analysis. Plant cover is estimated as a percentage of total hits over the total number of pins(6). Grass height is recorded in centimeters. Percentage grazing pressure is estimated from the proportion of grazed and non-grazed hits (Table 1).

Sampling is done in collaboration with the Kenya Wildlife Service (KWS) in Amboseli. No endangered plant species are involved. The plots in (Figure 2) were drawn from an initial sample of 101 randomized plots at the start of the monitoring (See supplementary section).

Species composition

Species composition of all plants that include bush and tree cover sampling that began in 1977 is done once or more a year during the rains, using the point intercept and exclusion quadrant sampling methods(8). See supplementary section for more details.

Plot Level Herbivore Monitoring

Counts over a 500m radius are made of all animal species from the center of the plots in the basin and surrounding group ranches.

This exercise is done simultaneously with the vegetation sampling hence providing a basis for comparing herbivore and plant relations. The distance from the center of the plot is estimated using a range finder.

Notes on the activity of the animal such as grazing, walking or resting are also taken. Once the data is logged onto the ODK tablet, it is then transmitted from the field to the ACP database.

Additional eighty plots have been included recently for intensive herbivore counting done twice or three times a year. (See supplementary section for the list of species included in the surveys).

Herbivore Body Condition Scores

Livestock and wildlife (zebra, wildebeest and buffalo) body condition scores (BCS) are observed during the ground herbivore monitoring and recorded following the photographic scale shown below (Figure 8).

Amboseli Conservation Program has been tracking range-land conditions in the Amboseli region since 1976. The tracking measures plant biomass, greenness and grazing pressure in 20 permanent plots each month in the 700 square kilometer area in and around the Amboseli Basin used heavily by livestock and wildlife in the dry season. The methods used and the results of the long-term monitoring have been published in (Western et al., 2015)

We have now developed a simplified method of graphically presenting the range-land tracking data to provide group ranch and grazing committees an early warning system indicating the severity of pasture shortage for each year and month. The method uses grazing pressure on a scale of 0 to 100 as a measure of pasture availability. 

Zero grazing occurs after good rains and low grazing pressure. To simply the index we use an arrow to indicate the severity of pasture conditions. The arrow in the green range indicates less than a third of the pasture has been grazed down, amber up to two thirds and red severely grazed.

We will be developing and posting tracking details on livestock body condition, milk yields and market prices over the coming month to improve ACP’s range-land monitoring and projections of the seasonal outlook. 

Illustration 3 gives a preview of livestock condition and milk production adding weight to the severe outlook for the 2019 long dry season and an early warning of the need for early action to prevent heavy economic losses.(Figure 9)

Ground Monitoring

Vegetation Monitoring

ACP’s ground monitoring is done for both vegetation and herbivores. The surveys are conducted every 4 to 6 weeks.

Herb-layer biomass, greenness and grazing intensity

The monthly ground monitoring of the vegetation is conducted both in the plots shown in the basin area (Figure 2) and in the group ranches image on (Figure 3).

The monitoring that started in 1975 is conducted in each plot, where vegetation cover is measured using the point intercept method (5) . For each frame, ten pins are dropped through a slanting pin frame at an angle of 67°, and each plant hit recorded on a predesigned capture form, onto a digital tablet using open data kit (ODK).

The data is the then transmitted via a cloud network and downloaded onto the ACP’s integrated database (Figure 5) for storage and subsequent analysis. Plant cover is estimated as a percentage of total hits over the total number of pins(6). Grass height is recorded in centimeters. Percentage grazing pressure is estimated from the proportion of grazed and non-grazed hits (Table 1).

Sampling is done in collaboration with the Kenya Wildlife Service (KWS) in Amboseli. No endangered plant species are involved. The plots in (Figure 2) were drawn from an initial sample of 101 randomized plots at the start of the monitoring (See supplementary section).

Species composition

Species composition of all plants that include bush and tree cover sampling that began in 1977 is done once or more a year during the rains, using the point intercept and exclusion quadrant sampling methods(8). See supplementary section for more details.

Plot Level Herbivore Monitoring

Counts over a 500m radius are made of all animal species from the center of the plots in the basin and surrounding group ranches.

This exercise is done simultaneously with the vegetation sampling hence providing a basis for comparing herbivore and plant relations. The distance from the center of the plot is estimated using a range finder.

Notes on the activity of the animal such as grazing, walking or resting are also taken. Once the data is logged onto the ODK tablet, it is then transmitted from the field to the ACP database.

Additional eighty plots have been included recently for intensive herbivore counting done twice or three times a year. (See supplementary section for the list of species included in the surveys).

Herbivore Body Condition Scores

Livestock and wildlife (zebra, wildebeest and buffalo) body condition scores (BCS) are observed during the ground herbivore monitoring and recorded following the photographic scale shown below (Figure 8).

Amboseli Conservation Program has been tracking range-land conditions in the Amboseli region since 1976. The tracking measures plant biomass, greenness and grazing pressure in 20 permanent plots each month in the 700 square kilometer area in and around the Amboseli Basin used heavily by livestock and wildlife in the dry season. The methods used and the results of the long-term monitoring have been published in (Western et al., 2015)

We have now developed a simplified method of graphically presenting the range-land tracking data to provide group ranch and grazing committees an early warning system indicating the severity of pasture shortage for each year and month. The method uses grazing pressure on a scale of 0 to 100 as a measure of pasture availability. 

Zero grazing occurs after good rains and low grazing pressure. To simply the index we use an arrow to indicate the severity of pasture conditions. The arrow in the green range indicates less than a third of the pasture has been grazed down, amber up to two thirds and red severely grazed.

We will be developing and posting tracking details on livestock body condition, milk yields and market prices over the coming month to improve ACP’s range-land monitoring and projections of the seasonal outlook. 

Illustration 3 gives a preview of livestock condition and milk production adding weight to the severe outlook for the 2019 long dry season and an early warning of the need for early action to prevent heavy economic losses.(Figure 9)

Figure 2: Major habitats amalgamated into eight habitats from 29 vegetation zones defined in the 1967 baseline and subsequent surveys. The 10m radius permanent plots monitored every 4 to 6 weeks are shown. The 20 vegetation plots were selected from a randomized set of 101 original plots. (4)
Figure 3: Ground vegetation monitoring in selected group ranches. The plots where monitoring is done within the ranches are also shown.
Figure 5: Percentage cover showing number of hits, misses and total number of pins captured. For instance, percentage cover here is calculated as: (Number of Hits)/(Total number of pins) × 100, which gives, 5/9 × 100=55.6. The grass height is recorded in cm.
Table 1: Calculations and estimates of vegetation variables collected in the permanent plots in the basin and the surrounding group ranches.
Figure 8: Counting of all herbivore species (including livestock) seen over the 500m radius from the centre of the plots scattered across the Amboseli ecosystem .
Figure 9 : Livestock body condition scores and milk yield in the Amboseli ecosystem

Dr. David Western

Founder & Chairman

Amboseli Ecosystem Monitoring

info@amboselimonitoring.org

Nairobi, Kenya

Dr. David Western, known as Jonah, began research into savannas ecosystems at Amboseli in 1967, looking at the interactions of humans and wildlife.

His work, unbroken since then, has served as a barometer of changes in the savannas and test of conservation solutions based on the continued coexistence of people and wildlife.

Jonah is currently chairman of the African Conservation Centre, Nairobi. He directed Wildlife Conservation Society programs internationally, established Kenya’s Wildlife Planning Unit, chaired the World Conservation Union’s African Elephant and Rhino Specialist Group, and was founding president of The International Ecotourism Society, chairman of the Wildlife Clubs of Kenya, director of Kenya Wildlife Service, and founder of the African Conservation Centre in Nairobi.

He is an adjunct professor in Biology at the University of California, San Diego.

Western’s publications include;
Conservation for the Twenty-first Century (OUP, 1989), Natural Connections: Perspectives in Community-based Conservation (Island Press, 1994) and In the Dust of Kilimanjaro (Shearwater, 2001).

He is presently conducting a study on climate change in the Kenya-Tanzania borderlands in collaboration with University of California San Diego, University of York, Missouri Botanical Gardens, and African Conservation Centre.

Dr. David Western

Founder & Chairman

Dr. David Western, known as Jonah, began research into savannas ecosystems at Amboseli in 1967, looking at the interactions of humans and wildlife.

His work, unbroken since then, has served as a barometer of changes in the savannas and test of conservation solutions based on the continued coexistence of people and wildlife.

Jonah is currently chairman of the African Conservation Centre, Nairobi. He directed Wildlife Conservation Society programs internationally, established Kenya’s Wildlife Planning Unit, chaired the World Conservation Union’s African Elephant and Rhino Specialist Group, and was founding president of The International Ecotourism Society, chairman of the Wildlife Clubs of Kenya, director of Kenya Wildlife Service, and founder of the African Conservation Centre in Nairobi.

He is an adjunct professor in Biology at the University of California, San Diego.

Western’s publications include;
Conservation for the Twenty-first Century (OUP, 1989), Natural Connections: Perspectives in Community-based Conservation (Island Press, 1994) and In the Dust of Kilimanjaro (Shearwater, 2001).

He is presently conducting a study on climate change in the Kenya-Tanzania borderlands in collaboration with University of California San Diego, University of York, Missouri Botanical Gardens, and African Conservation Centre.

Dr. Victor N. Mose

Deputy Director & Head of Bio-statistical Services

Amboseli Ecosystem Monitoring

info@amboselimonitoring.org

Nairobi, Kenya

Dr. Victor N. Mose is the Deputy Director and Head of Biostatistical Services.  He  was awarded a PhD  in Biomathematics by the University of Pierre and Marie Curie (UPMC), Paris VI, France in 2013.

He has a Masters in bio-statistics from the University of Nairobi, Kenya and a Bachelors degree in Mathematics from the same University.

He also holds a financial mathematics qualification from the Institute of Actuaries, London, UK.

Victor is experienced in ecological modeling, bio-informatics, and geographical information systems (GIS). 

His research interests include Population dynamics, migration modelling, Bayesian spatial analysis, ecosystem services and economics modelling, together with biodiversity mapping.

Victor’s publications include; 
Mose, V.N., Nguyen-Huu, T., Auger, P., Western, D. 2012. Modelling herbivore population dynamics in the Amboseli National Park, Kenya: Application of spatial aggregation of variables to derive a master model. Ecological Complexity, 10, 42-51.

Dr. Victor N. Mose

Deputy Director & Head of Bio-statistical Services

Dr. Victor N. Mose is the Deputy Director and Head of Biostatistical Services.  He  was awarded a PhD  in Biomathematics by the University of Pierre and Marie Curie (UPMC), Paris VI, France in 2013.

He has a Masters in bio-statistics from the University of Nairobi, Kenya and a Bachelors degree in Mathematics from the same University.

He also holds a financial mathematics qualification from the Institute of Actuaries, London, UK.

Victor is experienced in ecological modeling, bio-informatics, and geographical information systems (GIS). 

His research interests include Population dynamics, migration modelling, Bayesian spatial analysis, ecosystem services and economics modelling, together with biodiversity mapping.

Victor’s publications include; 
Mose, V.N., Nguyen-Huu, T., Auger, P., Western, D. 2012. Modelling herbivore population dynamics in the Amboseli National Park, Kenya: Application of spatial aggregation of variables to derive a master model. Ecological Complexity, 10, 42-51.

Mr. David Maitumo

Field Officer/ Data Collector

Amboseli Ecosystem Monitoring

info@amboselimonitoring.org

Nairobi, Kenya

David has been working in Amboseli as the ACP field officer since 1977. As a member of the local Maasai community in the Amboseli area, David brings a unique perspective to the program.

His rich understanding of the interaction of people, livestock, and wildlife, and the challenges facing conservation in human landscapes, enriches his key roles in the design of field experiments and long term data collection and monitoring.

Mr. David Maitumo

Field Officer/ Data Collector

David has been working in Amboseli as the ACP field officer since 1977. As a member of the local Maasai community in the Amboseli area, David brings a unique perspective to the program.

His rich understanding of the interaction of people, livestock, and wildlife, and the challenges facing conservation in human landscapes, enriches his key roles in the design of field experiments and long term data collection and monitoring.

Ms. Winfridah Kemunto

Database Administrator

Amboseli Ecosystem Monitoring

info@amboselimonitoring.org

Nairobi, Kenya

Winfridah  is the  Amboseli Conservation Program’s database Administrator. She has a certificate from Pitman Training Institute and vast experience in working with big data that involve database management,  basic analysis, digital library, data mining and  data visualization.

Her interests include spatial data mining and presentation.  Before Joining ACP, she worked  as a data clerk at South Rift Land Owners Association (SORALO).

Ms. Winfridah Kemunto

Database Administrator

Winfridah  is the  Amboseli Conservation Program’s database Administrator. She has a certificate from Pitman Training Institute and vast experience in working with big data that involve database management,  basic analysis, digital library, data mining and  data visualization.

Her interests include spatial data mining and presentation.  Before Joining ACP, she worked  as a data clerk at South Rift Land Owners Association (SORALO).

Mr. Sakimba Kimiti

Assistant Researcher

Amboseli Ecosystem Monitoring

info@amboselimonitoring.org

Nairobi, Kenya

Sakimba is currently pursuing a PhD at the University of Lyon 2 in France. He previously worked as an Assistant Researcher for the Amboseli Conservation Program.

He holds a Bachelor of Science (Wildlife Management and Conservation) degree from the University of Nairobi and  a Master of Science degree in Range Management from the same University.

Prior to joining the ACP, he worked as an Ecological Assistant at South Rift Land Owners Association. At ACP, he is involved in projects dealing with the Dynamics of Predation on Spatial -temporal Basis and in Human Ecology.

His other interests include: GIS, remote sensing, satellite imagery, ecological monitoring, land use change and ecosystem vulnerability.

Mr. Sakimba Kimiti

Assistant Researcher

Sakimba is currently pursuing a PhD at the University of Lyon 2 in France. He previously worked as an Assistant Researcher for the Amboseli Conservation Program.

He holds a Bachelor of Science (Wildlife Management and Conservation) degree from the University of Nairobi and  a Master of Science degree in Range Management from the same University.

Prior to joining the ACP, he worked as an Ecological Assistant at South Rift Land Owners Association. At ACP, he is involved in projects dealing with the Dynamics of Predation on Spatial -temporal Basis and in Human Ecology.

His other interests include: GIS, remote sensing, satellite imagery, ecological monitoring, land use change and ecosystem vulnerability.

Ms. Immaculate Ombongi

Data Analyst

Amboseli Ecosystem Monitoring

info@amboselimonitoring.org

Nairobi, Kenya

Immaculate is a data analyst at ACP. She has a Bachelors’ degree in Financial Economics from Mount Kenya University.

She is experienced in  spatial  data analysis and modeling of  livestock markets in Kenya.  Her interests include GIS, remote sensing, satellite imagery processing and analysis.

Immaculate as well, supports the analysis  team  that is working on the Rangeland restoration, a program of the African Conservation Centre, also known as the JUSTDIGGIT project.

Ms. Immaculate Ombongi

Data Analyst

Immaculate is a data analyst at ACP. She has a Bachelors’ degree in Financial Economics from Mount Kenya University.

She is experienced in  spatial  data analysis and modeling of  livestock markets in Kenya.  Her interests include GIS, remote sensing, satellite imagery processing and analysis.

Immaculate as well, supports the analysis  team  that is working on the Rangeland restoration, a program of the African Conservation Centre, also known as the JUSTDIGGIT project.

Figure 1: Amboseli National Park is surrounded by Maasai group ranches. ACP has conducted aerial surveys of the 8,500 square kilometers eastern Kajiado region since 1973 using a 5 x 5 kilometer-square grids to count and map wildlife and livestock. The brown box (migration area) defines the Amboseli ecosystem—the seasonal range of the migratory wildlife populations using Amboseli National Park and permanent swamps in the dry season. Ground vegetation monitoring is done at basin area surrounding the Park and in selected group ranches (Olgulului, Kimana, Eselenkei and Mbirikani).
Figure 12:Illustration of how the monthly total count of keystone species is conducted within the Amboseli basin area that includes that protected Amboseli National Park. The counts are done on a one-by-one km grid system.

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Figure 15: A screenshot of Google Earth showing human settlement locations in the Amboseli basin area. The red placemarks show occupied settlements while the yellow ones represent the unoccupied
Table 4: Some satellites and their Spatio-temporal resolution
Figure 16: Detected bomas identified by the use of Machine Learning in the Amboseli basin area.
Figure 17: A recent sample of the Sentinel 2 image obtained for processing of the vegetation zones of the Amboseli basin area. The swamp habitat is reasonably distinguished by color red.
Figure 18: Historical changes in the Amboseli basin vegetation from aerial photography mapping that are currently being updated using satellite imagery.

Credit : Mark Manongdo