Regenerative Grazing Experiments at Kupona Farm

KEY DETAILS

Principal Investigator
Dr. Lucy Smyth
Date
18 April 2024
Version
0.2.0
Programme
Rangelands Biodiversity Project
Study Site
Kupona
Key partners
True Range, AgWild
Contact email
lsmyth@naturalstate.org

1. PREAMBLE

Natural State’s objectives and activities are governed by a set of accepted Design Documents (DDs). These documents describe the context and purpose of all Natural State projects. Each DD documents key project details, the objective and background of the project, features of the study area, and the general methodological framework. Specific methodological details may be found in the project Standard Operating Procedures (SOP) which is available in the Related Documents section below.

1.1 DD PURPOSE

To provide a clear understanding of the purpose of each Natural State project and its contribution to Natural State’s mission of facilitating nature restoration at scale by using the latest technology and methods to revolutionise impact monitoring for carbon, biodiversity and human well-being.

1.2 DD SCOPE

This document details how this project fits within Natural State’s Impact Monitoring strategy and the principal team members overseeing the project. It explains why the project was conceived and how it will be implemented. It further directs readers to where they can find additional information relevant to the project.

2. GLOSSARY

Acoustic monitor
A passive acoustic recording device.
Biochar
A charcoal like carbon rich substance made by burning organic material through a process called pyrolysis.
Camera-trap
A remote camera with a defined automatic trigger (e.g., motion, time-lapse).
Control
: A site where management effects are not modified, providing an indication of what would have happened if the intervention(s) being studied had not been implemented.
Deployment
The defined period of continuous time a single remote sensor is active within the environment at a single, defined station as part of a survey.
EOV
Ecological Outcome Verification, a monitoring protocol used to monitor the effects of regenerative grazing by the Savory Institute.
Habitat type
Coarse, subjective classifications of the amount of woody cover in a heterogeneous savanna typically measured within a ~100m radius of the sampling location (see open grassland, open woodland, and closed woodland).
LiDAR
Light Detection and Ranging, a remote sensing method that uses laser pulses to measure distances to the Earth’s surface, providing highly detailed 3D maps.
LLBN
The Lewa-Lolldaiga-Borana-Ngare Ndare landscape (See study site description for details).
Multispectral imagery
A form of imaging which captures several spectral bands, some of which lie outside the visible spectrum.
Open grassland
Habitat patches with few or no trees, or a small clump of trees highly localized within the patch or immediate vicinity.
Open woodland
Habitat patches that are covered primarily by grass but trees or bushes are spaced somewhat regularly throughout most of the patch or immediate vicinity.
Paddock
A two dimensional site allocated a specific grazing treatment which is implemented using portable electric fencing.
Pitfall trap
A round plastic container approximately 10cm deep used to collect ground dwelling invertebrates.
Project
A concerted, data-driven effort to robustly measure variation in Biodiversity, Carbon, or Human-wellbeing in response to one or more sources of heterogeneity in a designated landscape.
Recording duration
A defined duration measured in seconds during which a device is actively recording during the recording period. The recording duration defines the duration of each individual audio file.
Recording periods
Defined periods of a 24-hour day during which the recorder operates recording cycles. The recording periods can be set in UTC or local time so it is important to make sure that recording periods are specified in the correct time zone.
S123
Survey123, a field-data collection app from ESRI which NS uses for recording all field observations and survey metadata.
Sampling design
The set of field methods employed in a survey and the manner of their use.
Sampling protocol
Explicit survey methodology that describes the design, effort, duration, configuration, and operation of a survey.
Sampling site
A distinct, discrete spatial unit defined in at least two dimensions where sampling occurs.
Soilmentor
An app used to monitor change is soil parameters in response to management regimes.
Soil bulk density
The mass of soil per unit volume, representing the compactness or density of soil, which influences its ability to hold water and support plant growth.
Soil organic carbon
The amount of carbon stored in soil organic matter, measured by spectrometry.
Stocking density
The number or mass of animals within a portion of available pasture for a certain portion of time.
Stocking rate
The number or mass of animals on a given amount of land over a certain period of time.
Study area
A defined geographic region of interest within which one or more surveys investigate ecological patterns at one or more sites.
Survey
A set of simultaneous deployments or related deployment groups of remote sensors over a defined period of time at a coordinated set of stations for the purposes of collecting data on the environment and its biological communities as part of a NS project.
Survey design
The theoretical and practical methods for choosing the spatiotemporal distribution of sampling units in a survey.
Time-lapse camera
A camera-trap which is nt motion triggered but instead captures images at specific, pre-defined time intervals.
Transect
A one-dimensional, discrete spatial unit where sampling occurs.
Treatment
Spatial management effects with ‘control’ indicating the absence of the management effect.
Vegetation structure
Variation in height and woodiness of vegetation that extends above the grass.

3. PROJECT OVERVIEW

3.1 PROJECT AIMS

The Regenerative Grazing Experiments at Kupona Farm aim to:

  1. Investigate the effects of grazing intensity on soil health and carbon sequestration, biodiversity and beef production.
  2. Investigate the effects of compost and biochar additions on soil health and carbon sequestration, biodiversity and beef production.
  3. Improve our understanding of the timeframes required for ecological restoration through regenerative grazing practices.
  4. Provide a testing ground for research and development projects.

3.2 PROJECT BACKGROUND

Natural State’s overarching goal is to catalyze large-scale ecological restoration globally by revolutionizing impact monitoring, generating innovative, new, nature-based financial mechanisms and supporting capacity development in the green economy space. This requires efficient, scalable monitoring systems and an understanding of what changes are driven by different restoration interventions, and how long these changes take to occur.

Regenerative grazing, a form of holistic land management, is a restoration intervention which can improve stewardship of tropical rangelands. By carefully managing livestock movements and mimicking high-density non-selective natural grazing patterns, this approach aids to improve soil health, increase biodiversity, and enhance ecosystem resilience. Through adaptive multi-paddock grazing cattle are grazed at high densities for short durations across numerous paddocks with long intervals of rest. This approach catalyses intensive, non-selective feeding that stimulates grass growth, nutrient cycling, and ecological function while allowing for vegetation to recover, preventing overgrazing, reducing soil erosion, and promoting the survival of diverse, palatable grass species. The trampling action of grazing animals aids in organic matter decomposition and nutrient cycling, fostering soil fertility. This management approach preserves wildlife habitat and improves hydrological cycling, critical in water scarce landscapes like those in Kenya. Embracing regenerative grazing practices not only enhances the productivity of rangelands but also contributes to sustainable and resilient land management, ensuring the preservation of Kenya’s unique ecosystems and livelihoods dependent on them. However, non-selective grazing entails a tradeoff between stocking rate and individual animal performance, with cattle grazed at higher densities providing less performance per head, but more head of cattle supported by the same area of land. Optimizing this tradeoff to produce maximum yield per hectare of land rather than yield per animal while promoting ecological restoration could have massive benefits both socially and environmentally.

While regenerative grazing is being implemented as an intervention for land restoration in certain Kenyan rangelands already, the magnitude and rate of its impact on carbon sequestration, biodiversity and social wellbeing are yet to be fully discovered. The lack of comprehensive data regarding the effects of regenerative grazing in Kenya stems from the fact that the Savory Method, upon which many regenerative grazing practices are based, was developed primarily in North America. While the principles of regenerative grazing have shown promise in various contexts, including arid and semi-arid environments similar to those found in Kenya, the applicability and effectiveness of these methods may vary depending on local ecological, social, and economic factors. Limited research and practical implementation specific to Kenyan rangelands have hindered a thorough understanding of how regenerative grazing, particularly utilizing the Savory Method, might impact soil health, biodiversity, and community livelihoods in this region. As a result, there is a pressing need for targeted studies and adaptive management approaches that consider the unique characteristics and challenges of Kenyan landscapes to fully assess the potential benefits and limitations of regenerative grazing practices in this context. There is also a need to further innovate within the field of grazing through trialing new approaches and ideas that could speed up landscape function. Potential for ancillary funding streams, for example through integrated carbon-biodiversity credits, further complicate the evaluation process but could strengthen the case for regenerative grazing practices due to emphasis on long-term stewardship and ecological resilience.

In response to the paucity of information on the effects of regenerative grazing in Kenyan rangelands as well as the best way to monitor these effects, Natural State has partnered with True Range to establish a regenerative grazing testing ground at Kupona Farm.

3.3 STUDY AREA

Kupona Farm is at 300 hecare farm located on the western boundary of Lolldaiga Conservancy. It forms part of the Northern Kenyan rangeland system within which Natural State is already working. Kupona has a recent history of unregulated grazing. This unregulated grazing will be halted by the erection of a perimeter fence during the first half of 2024. While Kupona will be fenced off from the large wildlife that usually roams these lands, the highly controlled experimental treatments will provide valuable insights into the most effective ways of implementing regenerative grazing in African rangelands and monitoring the associated effects while providing a safe environment for research and education. All lessons learnt will be continually rolled out across the 20,000 hectare Lolldaiga Ranch as well as the 100,000 hhectares of AgWild member properties that are also a mixture of ranches and conservancies in the same county.

Kupona Farm lies directly adjacent to Lolldaiga Conservancy, a part of the Lewa-Lolldaiga-Borana-Ngare Ndare (LLBN) landscape which has been the focus of Natural State’s work to date. Kupona as therefore environmentally very similar to the LLBN landscape. Kupona is located in the central highlands within Laikipia county, at a lattitude of 0.16 - 0.19° and a longitude of 37.05 - 37.07°.

Rainfall is highly variable, but is typically between 400 and 600 mm annually. During droughts, total annual rainfall can drop below 200 mm. The landscape sits at 1800m above sea level. Soil is sandy in the north of Kupona, transitioning to clay dominated soil in the south of the farm. Vegetation communities are predominantly Acacia-Commiphora bushlands, with Euclea dominated thicket towards the western corner of the farm.

3.4 PROJECT TIMELINE

  • Kupona farm was purchased by AgWild and Natural State in 2023.
  • The perimeter fence will be erected in the first half of 2024.
  • True Range undertook initial EOV sampling in November/December 2023 and began the collection of Soilmentor data in early 2024.
  • Natural State will undertake a baseline carbon and biodiversity survey through soil sampling, pitfall trapping, acoustic recordings and drone imagery in May and June 2024.
  • Bush thinning will occur in mid-late 2024 to ensure that all paddocks contain a similar quantity of woody vegetation to start with.
  • Cattle will be introduced and regenerative grazing will begin in mid-late 2024, once the bush thinning has been completed.

4. SURVEY DESIGN

As a highly experimental farm and labratory for early-stage R&D, some work at Kupona will be rigidly subscribed while other projects will be highly adaptive.

4.1 SPATIAL DESIGN

The farm will be fenced off to prevent unregulated grazing, and has been subdivided into 29 virtual paddocks, each approximately eight hectares in size. Paddock locations and treatment allocations are shown in the map below. Cattle movement through these paddocks will be strictly regulated using portable electric fencing, allowing for different paddocks to be subject to different treatments as described below:

  • Stocking densities:
    • 500 cattle per hectare (3 paddocks)
    • 1000 cattle per hectare (3 paddocks)
    • 2000 cattle per hectare (3 paddocks)
    • 3000 cattle per hectare (3 paddocks)
  • Effect of compost/Biochar:
    • Compost from bush thinning introduced to paddocks @ 100 cattle per hectare (3 paddocks)
    • Biochar added as a supplement to the cattle’s feed @ 100 cattle per hectare (3 paddocks)
    • Compost and biochar combined @ 100 cattle per hectare (3 paddocks)
  • Adaptive stocking densities based on real-time observation of paddock intactness (9 paddocks)
  • Halted grazing control: This will consist of three (3) 1 hectare control sites within Kupona which will not be grazed.

One sampling site within each paddock has been manually selected as a short term EOV site (30 in total) and half of these, located in alternating paddocks, have been designated as long term EOV sites. Natural State will contuct carbon monitoring within all paddocks. AudioMoths will be deployed in 4 paddocks (9B, 10A, 10B, 11A). Pitfall trapping will occur in the 3 control sites and the three ultra high density sites.

  • White = 500 head density (low density)
  • Yellow = 1000 ( Medium)
  • Blue = 2000 (high)
  • Green = 3000 (ultra high)
  • Red = Adaptive (different densities)
  • Pink = Compost and adaptive density
  • Brown = Bio char and Adaptive density
  • Orange = Biochar Compost and adaptive density
  • Sky Blue = No treatment prescribed
  • Black = Non grazing land
  • Control 1 2 and 3 = Small 1 hectare blocks for non disturbance (no grazing)

4.2 TEMPORAL DESIGN

True Range will conduct short term EOV sampling occurs yearly in December, and long term EOV sampling occurs every 5 years, also in December. EOV baseline sampling occured in December 2023.

Natural State will conduct baseline monitoring in May/June 2024. Repeated monitoring eforts will occur every 1/3/5 years, depending on the type of sampling and timescale upon which those variables are expected to change. Timelines of repeat monitoring are yet to be determined.

Currently, baseline monitoring is only planned to occur at the end of the wet season. However, it is possible that some sampling will be repeated during the dry season, in September.

5. SAMPLING DESIGN

Natural State’s impact monitoring team’s involvement in Kupona is twofold: i) to monitor the effects of the different grazing regimes on certain variables that will provide insights into ecosystem restoration and ii) as a testing ground for research and development projects.

In terms of monitoring the effects of regenerative grazing, Natural State’s monitoring at Kupona Farm is concentrated around 3 focal areas: soil, vegetation and fauna. Each paddock will contain an EOV site and 4 fixed sampling points. For long rectangular paddocks sampling points will run in a line from east to west. For triangle shaped paddocks there will be a sampling point in the centroid of the paddock and three more sampling points radiating outwards from the centroid. Control sites will be sampled in the same layout a 50m X 50m Carbon Pool Plot, with the centroid of the plot located in the centroid of the control site and the four sampling points in a square shape around the centroud, spaced 50m apart. Details on the monitoring of each core focus are provided below.

Soil: Sampling in May 2024
Soil parameters will be monitored within all paddocks at Kupona, as well as the 3 control sites inside Kupona. These include:

  • Soil organic carbon:
    • 1 sample taken at each depth (0-15 & 15-30 & 30-50) at each of the 4 sampling points per paddock.
    • total of 12 samples per paddock
  • Soil bulk density:
    • 1 sample taken at each of the 4 sampling points plus 1 sample taken at a random location in the paddock.
    • total of 5 samples per paddock.
  • Fine roots:
    • 1 sample taken at each of the 4 sampling points plus 2 samples taken at random locations in the paddock.
    • total of 6 samples per paddock.
  • Bare ground:
    • 5 bare ground measurements taken with the 1m X1m quadrat at each of the 4 sampling points, with one at the sampling point itself and the other 4 5m from the sampling point in each of the 4 cardinal directions.
    • total of 20 bare ground measurements per paddock.
  • Disk pasture meter:
    • 25 DPM measurements in a snake pattern around each of the 4 sampling points.
    • total of 100 DPM measurements per plot.

Vegetation: Timing Budget dependent
Vegetation monitoring at Kupona will be done exclusively via drone. Drone imagery will include:

  • RGB: This will be used to quantify bare ground, and ground-truthed using bare ground data collected by True Range using Soilmentor.
  • LiDAR: This will be used to quantify above ground biomass.
  • Multispectral Imagery: This will be used for tree species identification.

Fauna: Bird sampling in May 2024, Invertebrate sampling in June 2024
The two main faunal groups of focuse are invertebrates and birds. These will be monitored in a subset of paddocks. Monitoring techniques will be as follows:

  • Birds: Monitored in paddocks 9B, 10A, 10B, 11A using 2 AudioMoths placed in each paddock, one at the eastern-most sampling point and one at the western-most sampling point.
    • Sampling rate of 48kHz.
    • Gain of low-medium.
    • Recording duration of 3570 seconds.
    • Sleep duration of 30 seconds.
    • Quiet periods from 08:00 – 12:00 UTC and 21:00 – 24:00 UTC.
  • Invertebrates: Monitored using pitfall traps in paddocks 2B, 6B, 11A and control 1, control 2 and control 3.

In addition to monitoring the effects of regenerative grazing, Natural State will use Kupona as a testing ground for R&D projects, which will measure change in the landscpae but will not be able to be used to measure the impact of regenerative grazing on the ecosystem as they will not be included in the baseline survey.

R&D:
R&D projects planned for trialling in Kupona are listed below:

  • Time lapse cameras: Time lapse camera traps, set to take photos at specific time intervals, will be deployed on trees or fence posts to determine whether time lapse cameras provide a means of estimating absolute mammal abundance via space-to-event cameras. Kupona is an ideal testing ground for time lapse cameras as the abundance of cattle in each paddock will be known.
  • Metabarcoding of invertebrate samples: Invertebrate samples will be collected using a combination of pitfall traps, pan traps, malaise traps and sweep netting. Samples will then be sent to labs for DNA extractiond and sequencing, and for the developpment of reference libraries which will allow for metabarcoding to be used instead of manual invertebrate identification.
  • Aboveground invertebrate bioacousics: Audio files will be collected using AudioMoths and ground truth data will be collected using a combination of invertebrate traps mentioned above.
  • Belowground invertebrate bioacoustics: AudioMoths will be burried underground to determine whether belowground sounds or soundscpaes are able to provide an indication of soil health.
  • Aerial vegetation monitoring: Kupona will be scanned using unpiloted aerial vehicles outfitted with active lidar sensors and passive multi-spectral sensors to quantify vegetation mass and structure and to estimate vegetation productivity and diversity.

6. ANALYTICAL FRAMEWORK

Analysis of data will vary greatly depending on the typoe of data collected:

  • Soil data will be used to estimate belowground carbon storage in a rangeland system subject to regenerative grazing practices.
  • Vegetation data will be used to look as the effects of regenerative grazing on grass cover, above ground biomass and plant species assemblages.
  • Faunal data will be used to determine what changes in invertebrate and bird communities can be expected when regenerative grazing practices are introducedd, and how long these changes take to materialize.
  • R&D projcets will be testing the ability of the method in question to detect change across the landscape.

7. EXPECTED OUTPUTS

  1. Estimate of quantity of carbon stored underground in Kupona prior to interventions, and over time after regenerative grazing is implemented.
  2. Estimate of % bare ground in Kupona, and annual change in % bare ground after regenerative grazing is implemented.
  3. Estimate of above ground biomass in Kupona from LiDAR data.
  4. Map of tree species in Kupona based on multispectral imagery.
  5. List of invertebrate taxa (species/genus/family/order) present initially, and changes to this list as the land is restored.
  6. List of bird species present initially, and changes to this list as the land is restored.
  7. Comparison of pre and post intervention above ground soundscapes.

8.1 STANDARD OPERATING PROCEDURE

8.2 OUTPUTS

None currently available.

8.3 DATA ELEMENTS

Survey Design

Data Collection

Data Layers

None currently available.

Dashboard

None currently available.

8.4 ADMINISTRATIVE DOCUMENTS

None currently available.

9. REVISION AND VERSION HISTORY AND DESCRIPTION

No history available.

10. SIGNATURES OF CONFIRMATION

Principal Investigator: ______________             Date: ___________

Director of Impact Insights: ____________             Date: ___________

11. BIBLIOGRAPHY

  1. Savory, Allan, and Joan Butterfield. Holistic management. Washington, DC: Island press, 1998.
  2. Wiethase, J.H., Critchlow, R., Foley, C., Foley, L., Kinsey, E.J., Bergman, B.G., Osujaki, B., Mbwambo, Z., Kirway, P.B., Redeker, K.R. and Hartley, S.E., 2023. Pathways of degradation in rangelands in Northern Tanzania show their loss of resistance, but potential for recovery. Scientific reports, 13(1), p.2417.
  3. Johnson, D.C., Teague, R., Apfelbaum, S., Thompson, R. and Byck, P., 2022. Adaptive multi-paddock grazing management’s influence on soil food web community structure for: increasing pasture forage production, soil organic carbon, and reducing soil respiration rates in southeastern USA ranches. PeerJ, 10, p.e13750.

12. APPENDICES

None currently available