Towards co-viability: combining field approaches for understanding - - PowerPoint PPT Presentation

Towards co-viability: combining field approaches for understanding coexistence between subsistence farmers and wildlife at the edge of Hwange National Park

Chloé Guerbois, Eunice Chapanda, Marion Lombard & Hervé Fritz

CNRS - HERD Programme - Hwange LTER CNRS LBBE - France Main Camp Research - Hwange NP - Zimbabwe

9th Savanna Science Network Meeting - 16th March 2011

Rationale - Context

New challenges for protected area management

• Controversy on their efficiency to ensure sustainable African wildlife conservation

(Johannesen 2007, Western et al 2009).

• Losses inside protected areas point to the need to promote integrated landscape practices

that combine parks with private and community based measures (Western et al 2009).

• Expansion of Transfrontier Conservation Areas

with the objectives to interconnect protected areas and promote local development (TFCA, Peace Park Foundation).

• “Integrated protected area paradigm “

Conceptual Approach – Problem Statement

Baumgärtner et al. 2008; Doyen & De Lara 2008

• Mosaic of production systems .(i.e. livestock and crop production, natural resource harvesting,

conservation, education, tourism, mining, ...)

• Integrated landscape practices Co-viability of production systems
• A production system is sustainable when it can satisfy determined “thresholds” ( or

constraints) over space and time

Study area : Hwange National Park – Communal Area Interface

• Hwange National Park , Zimbabwe: ~ 15 000 km² . MAP=606 mm. Unfenced landscape.

Elephant population (~35 000) 85% of the large herbivore biomass.

• Hwange Rural District : Mixed ethnic composition. Main production systems: Subsistence crop

and livestock farming. Low level of employment. rpop=4%, rhh=2%.

Problematic and method

Patterns of apparent coexistence ? Wild animals Subsistence farmers

Problematic and method

Interviews, questionnaires Problem Animal Report Field damage expertises Resource mapping

Distance from hard edge as an illustration

• f the role of

heterogeneity

Wild animals Subsistence farmers

When wild animals become a problem...

Interviews conducted in 28 villages (Ward 14,15,16,17) along a gradient of distance from the hard edge.

• Which animal do you often see ?
• Are they a problem for you ? (Y=1, N=0)

Data analyzes: General Linear Model for binomial data

When wild animals become a problem

Heterogeneity of wildlife occurrence in human dominated landscape (cover, human population densities, roads,...). Heterogeneity in village susceptibility to problem animal (animal behaviour and human practices).

(*) (*) (*) (NS) (NS) (NS)

Crop raiders : study case at a village scale

Magoli village: 195 households No strong field protection, or obvious feature to protect the fields 30 fields randomly selected in Magoli village Field expertises (fixed interval line transect)

• Probability of being impacted by

elephant correlated to distance from the hard edge

(*) Crop raiders : study case at a village scale

• Probability of being impacted by

elephant correlated to distance from the hard edge

• Cumulated livestock damages >

elephant damages !! Tolerance to damages...

(*) Crop raiders : study case at a village scale

Elephant raids : study case at farmers scale Level of damage depends on the farmer + his neighbours effort to protect fields The indirect cost of spending time in the field exceeds the direct cost of crop loss. The presence of men in the household significantly improves the farmer effort Participative experiment: control for distance to the hard edge and the field quality. Interviews + Field damages expertises (N=21)

HETEROGENEITY

Cross scale discussion on problem animals

• Logical hypothesis: Problem animals induce additive costs of living close

to a protected area, the perceived conflict between Human and Wildlife should be greater closer to the hard edge. Wildlife occurrence

• utside protected areas

Wildlife damages Farm susceptibility Defining thresholds for co-viability model might be more complex than a simple distance-gradient rule... ... need to increase the sampling effort...

Wildlife perception Semi directed questionnaires (N=219)

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 2 4 6 8 10 Probability

Distance from hard edge (km)

• Prob. wildlife sightings

(*)

Do you often see wildlife ?

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1 2 3 5 7 9 Probability Distance from hard edge (km)

• Prob. HW conflict

perception

(c**) (a) (b*)

Previous hypothesis not supported. Indeed, significant positive trend between the probability of perception of conflict and distance from the hard edge Do you think there is a HW conflict ? Wildlife perception Semi directed questionnaires (N=219)

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 2 4 6 8 10 Probability Distance from hard edge (km)

• Prob. wildlife sightings

(*)

Do you often see wildlife ?

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 2 4 6 8 10 Probability Distance from hard edge (km)

• Prob. wildlife sightings
• Prob. HW conflict

perception

Perception

• Cost – Benefits ?

Wildlife perception : A gradient of distance Alternative hypothesis: The people perception is influenced by the difference between the protected area services and disservices ?

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 2 4 6 8 10 Probability Distance from hard edge (km)

• Prob. wildlife sightings
• Prob. HW conflict

perception 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 2 4 6 8 10 Probability Distance from hard edge (km) Apparent perceived "benefit"

There should be a realized or perceived benefit on a gradient of distance from the protected areas !

Perception

• Cost – Benefits ?

Alternative hypothesis: The people perception is influenced by the difference between the protected area services and disservices ? Wildlife perception : A gradient of distance

Participative Resource Mapping N= 8 villages on a distance gradient 54 village heads Free listing of resources Benefits from protected areas

Benefits from protected areas What are the key resources of the system and their trends ?

1 2 3 4 5 6 7 8 9 10 2 4 6 8 10

Negative trends index Distance from hard edge Benefits from protected areas (NS) No significant effect of the distance

• n the “resource depletion stress”.

What are the key resources of the system and their trends ?

Benefits from protected areas Where do you get these resources ?

GRAZING AREAS

Benefits from protected areas Where do you get these resources ?

Benefits from protected areas

0.2 0.4 0.6 0.8 1 1.2 2 4 6 8 10

Provided by protected area Distance from hard edge

Fire wood / Fruits / Medicinal plants/ Thatching Grass

0.2 0.4 0.6 0.8 1 1.2 2 4 6 8 10 Provided by protected area Distance from hard edge

Poles / Grazing Area / Pan

0.2 0.4 0.6 0.8 1 1.2 2 4 6 8 10 Provided by protected area Distance from hard edge

Mushrooms / Worms

Protected areas provide direct (controlled or not) benefits to the closest communities.

Benefits from protected areas

0.2 0.4 0.6 0.8 1 1.2 2 4 6 8 10

Provided by protected area Distance from hard edge

Fire wood / Fruits / Medicinal plants/ Thatching Grass

0.2 0.4 0.6 0.8 1 1.2 2 4 6 8 10 Provided by protected area Distance from hard edge

Poles / Grazing Area / Pan

0.2 0.4 0.6 0.8 1 1.2 2 4 6 8 10 Provided by protected area Distance from hard edge

Mushrooms / Worms

Protected areas provide direct (controlled or not) benefits to the closest communities. Need to increase the sample size for testable dataset !

Discussion: Towards co-viability ?

Participative reporting in Magoli village Nov 2009 – Nov 2010 Minimum benefits per household per year= 165 USD 195 Households Benefits: 32 175 USD

Discussion: Towards co-viability ?

Participative reporting in Magoli village Nov 2009 – Nov 2010 Minimum benefits per household per year= 165 USD 195 Households Benefits: 32 175 USD

Thresholds ?

Discussion

• This approaches allows to identify and quantify links between the social and the ecological

system (reconciliation ?).

• Next step: adequate thresholds for co-viability model.
• Socio-ecological system heterogeneity can be explanatory for human-wildlife coexistence

variable ( resilience), but can also result from human wildlife interactions ( sustainability). Feedback loops need to be investigated.

• How to deal with non valuable services and externalities ? (ex: grazing area vs disease

transmission).

• The counter intuitive observed patterns of

“tolerance” close to the hard edge is consistent with hypothesis of protected area attractiveness (Wittemeyer et al 2008, Joppa 2008, Scholte & De Groot 2009).

• Need to understand the “role” of PA

Design Buffer / Interaction zones with specific adaptive management objectives.

• Thanks to the Zimbabwe Parks and Wildlife Management Authority, the Research Council of Zimbabwe, the

Hwange Rural District Council and Chief Nelukoba for supporting this research. Also many thanks to the HERD team, the farmers and the community around Hwange NP for their enthusiastic participation !