Presented by Sarah E. Gergel at the 54th Annual Meeting of the Association for Tropical Biology and Conservation (ATBC) in Mérida, Yucatán (Mexico) on July 11, 2017. This presentation was part of the Agrarian Change Project Symposium: The impacts of agrarian change on local communities: Sharing experience from the field.
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SUMMARY: Can mapping forest loss, fragmentation, and change help improve long-term comparative analyses of livelihoods?
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Mapping forest loss and fragmentation for improved comparative analyses of livelihoods and ecosystem services
1. Mapping forest loss and fragmentation for
improved comparative analyses of
livelihoods and ecosystem services
Sarah E Gergel, Stephanie A Tomscha, Ian MS Eddy,
Kevin Yang, Jean-Yves Duriaux, Frederic Baudron, Terry CH Sunderland
and many others who contributed to the New Agrarian Change Project
2. 70% of the world’s remaining forest
<1 km of an edge (Haddad et al 2015)
Key Challenge:
How do agro-forest mosaics contribute to ecosystem
goods and services as well as livelihoods?
3. 7 Countries x 3 Zones (high/med/low forest)
>2000 HH surveys
4. 7 Countries x 3 Zones (high/med/low forest)
>2000 HH surveys
6. How do agro-forest mosaics contribute to ecosystem goods
and services (EGS) as well as livelihoods?
Today’s Roadmap:
• Visits and use of forests
• Local perceptions of forest loss vs remote sensing estimates
• Changes in EGS with agricultural intensification
forest loss
forest fragmentation
7. Number of forest products is greatest where forest
cover is greatest
• Bamboo and rattan
• Construction material
• Fibers
• Roof thatch
• Thatch
• Timber for construction
• Wood for farm
implements
• Bush meat or small
rodents
• Edible insects
• Fish or crabs
• Fruits
• Leafy vegetables
• Mushrooms
• Root vegetables
• Fuelwood
• Charcoal
• Bees products
• Dye or tanning
• Flowers or plants
• Gaharu
• Gums or resins
• Medicinal
• Reeds and papyrus
• Water
• Wildlife/pet trade
ConstructionMaterialsFoodFuelOther
8. Daily visits to forests declined with agricultural intensification
9. Forest type matters for daily visits
• “Own land” visited most frequently in all zones
• Typically small forest patches (“small forest patches” and “riverine
forest patches”) important in Zones 1 and 2, but their losses may be
difficult to detect changes with Landsat
10. How well do remote sensing estimates of
forest loss reflect local perceptions?
Household surveys
and
remote sensing
results
11. Areas originally selected in the field to control for
amount of contemporary forest cover
%Forest
T1-1986
T2-2001
T3-2015
T1 T2 T3 T1 T2 T3T1 T2 T3
12. Three decades of forest cover reveals areas of
rapid loss vs little change in forest cover
%Forest
T1-1989
T2-2003
T3-2014
T1-1988
T2-1999
T3-2013
T1-1986
T2-2002
T3-2015
T1-1986
T2-1999
T3-2013
T1-1990
T2-2000
T3-2010
T1-1986
T2-2001
T3-2015
T1-1990
T2-2002
T3-2013
T1 T2 T3 T1 T2 T3T1 T2 T3 T1 T2 T3 T1 T2 T3T1 T2 T3 T1 T2 T3 T1 T2 T3T1 T2 T3 T1 T2 T3 T1 T2 T3T1 T2 T3 T1 T2 T3 T1 T2 T3T1 T2 T3T1 T2 T3T1 T2 T3 T1 T2 T3 T1 T2 T3 T1 T2 T3T1 T2 T3
14. R = -0.86
p < 0.001
Reported agricultural activity strongly
correlated with satellite forest loss
R = -0.71
p < 0.001
15. How do ecosystem goods and services change
with agricultural intensification?
Forest
Products
Crops Livestock
While crop richness increases at
moderately intensive levels of
agriculture
Zone 2 >> Zone 1=Zone 3
Forest product and livestock
richness decline with
agricultural intensification
R2=0.56 % R2=0.55R2= 0.39 %
MeanRichnessPerHousehold
16. Impact of agricultural intensification on
EGS differs by country
Zone 1
Zone 2
Zone 3
MeanRichnessPerHousehold
18. Forest edge associated with greater number of
forest products used
Richness of forest products used
(Mean per HH)
Fragmentation
LowHigh
R2 =0.39
p = 0.005
N = 18
19. Except when Nicaragua results came in……
Richness of forest products used (Mean per HH)
Fragmentation
LowHigh
R2 =0.037
p = 0.41
N = 21
20. Construction material use increases with edge density
and decreases with agricultural intensification
• Bamboo and
rattan
• Construction
material
• Fibers
• Roof thatch
• Thatch
• Timber for
construction
• Wood for farm
implements
ConstructionMaterials
*Grey variables not significant and not included in final model
Construction materials (yes/no) = Country (Random effect) + % Contemporary forest cover + Zone + Edge Density
Best model R2 = 48%
Fixed effects only R2 = 6%
21. • Bamboo and rattan
• Construction material
• Fibers
• Roof thatch
• Thatch
• Timber for construction
• Wood for farm
implements
• Bush meat or small
rodents
• Edible insects
• Fish or crabs
• Fruits
• Leafy vegetables
• Mushrooms
• Root vegetables
• Fuelwood
• Charcoal
• Bees products
• Dye or tanning
• Flowers or plants
• Gaharu
• Gums or resins
• Medicinal
• Reeds and papyrus
• Water
• Wildlife/pet trade
ConstructionMaterialsFoodFuelOther
Foods, construction materials
and fuels responded differently
to forest configuration and
agricultural intensification
Forest construction
materials declined
with agricultural
intensification, but
were positively
related to edge
density
Forest foods
declined with forest
loss
Highly variable by country means cross-site comparisons essential for identifying these patterns
Our models were
poor at predicting
forest fuel dynamics
22. • Forest foods linked to forest cover
• Frequent visits to forests decline with intensifying agriculture
• Ag intensification not only affects staple crop diversity but also forest
products and livestock diversity
• Forest detection methods require more high resolution approaches to
account for loss of small but highly utilized forest patches
Summary: How do agro-forest mosaics contribute to ecosystem
goods and services (EGS) as well as livelihoods?
23. Acknowledgements
Funding for this project has been provided by the United States Agency
for International Development (USAID) and the UK’s Department for
International Development (DFID) KnowFor grant to CIFOR.
27. ??? Forest foods gathered more by
households surrounded by more forest
• Bush meat or
small rodents
• Edible insects
• Fish or crabs
• Fruits
• Leafy
vegetables
• Mushrooms
• Root vegetables
ForestFoods
Forest food (yes/no) = Country (Random effect) + % Contemporary forest cover + Zone + Edge Density
Best model R2 = 64.1 %
Fixed effects only R2 = 25.4 %
*Best model does not included grey variables
HH gathers forest foods
HH doesn’t gather forest foods
%forestwithin2kmofhouseholds
PLEASE SEE MY QUESTIONS
28. Protected areas especially important where
subsistence agriculture dominates
Ownland
Forest types
(Angles align with flower diagram)
29. Edge Density (Z-score)
Percent forest (Z-score)
Zone 3
(high intensity
agriculture)
Zone 2
(moderate intensity
agriculture)
Fixed Effects Estimates
Impacts of forest configuration and agricultural
intensification on forest product richness
Forest product richness=
Country (Random effect) + % Contemporary
forest cover + Zone + Edge Density
Full model R2 = 53.4 %
Fixed effects only R2 = 14.7 %
30. Forest fragmentation and use of forest products
Richness of forest products used (Mean per HH)
Fragmentation
LowHigh
31. Statistical analyses- the interplay of forest
configuration and agricultural intensification on the
use of different forest products
• Mixed effects models
• Model selection (pairwise deletion)
• Candidate fixed effects include
• Contemporary forest cover (Z-scores)
• Edge density (Z-scores)
• Agricultural zone
• Random effect
• Country
• Boot-strapped confidence intervals determine
significance of fixed effects
32. Comparative landscape approach
• Total forest cover
• Recent vs historical loss
• Rapid vs gradual change
• Contiguous vs. fragmented
“patchy” forest
15 years of landscape change, Nicaragua
Editor's Notes
Figure 10 shows the mean number of forest products used in each zone for cash and trade, domestic use, or both. Surveys asked about 28 different forest products
• Bamboo and Rattan
• Bees products
• Birds or animals for wildlife or pet trade
• Bush meat or small rodents
• Charcoal
• Construction material
• Dye or tanning
• Edible insects
• Fibers
• Fish or crabs
• Flowers or plants
• Fruits
• Fuelwood
• Gaharu
• Gums or resins
• Leafy vegetables
• Medicinal
• Mushrooms
• Reeds and papyrus
• Roof thatch
• Root vegetables
• Thatch
• Timber for construction material
• Water
• Wood to make farm implements
• SPECIFY_OTHER_FOREST_PRODUCT
I am not sure you will want all of the following slides about frequency of visits, but it shows the variety of ways we could display this information
The
How can we indicate the time frames – a little more detail but not too much details?
Why not lump by zone, then in each zone show 3 times periods?
The
How can we indicate the time frames – a little more detail but not too much details?
Why not lump by zone, then in each zone show 3 times periods?
What is the NS floating in space?
Zone explains little of variance relative to country – is that the secondary message? Couldn’t you also say that…after controlling for country, zone still is statistically significant, no? Yes
Just an FYI, since this analysis was completed for the paper looking solely at agricultural intensification, and then just recently moved to the forest paper (and potentially cut from both papers) no forest cover information is included in the model. There was no model selection process either. Simply 1 fixed effect (zone) and one random effect (country)
Forest product richness = Country (Random effect) + Zone
Full model R2= 55.5 %
R2(GLMM(M)) = 5.6 %
Livestock richness = Country (Random effect) + Zone
Full model R2= 54.9 %
R2(GLMM(M)) = 0.9 %
Crop richness = Country (Random effect) + Zone
Full model R2= 38.8 %
Fixed Effects R2 = 3.1 %
I think we still need a specific message here, by product type
Forest product richness ALWAYS higher in Zone 1 - CONSISTENT
Crop richness sometimes highest in Zone 2 (BNG, BF), sometimes even highest in zone 1 (NICA), or zone 3 (CMR)
Livestock – doesn’t differ much across zones except where it’s highest in Zone 2 (ETH, ZAM) Zone 1 (BANG, BF)
This is my interpretation – do stats up hold this interpretation or do we not have those?
Stephanie – when you say highly variable….that’s a bit of a cop-out…vague…could mean variable over time. What do you really mean? I mean zone influences are variable by country. If we looked at this questions using individual case studies, we may find a different result. For example, in Cameroon, forest products don’t change much by zone (even increase slightly in zone 2), while we see a very clear reduction in Indonesia.
agricultural intensification best explains changes in forest products ?and livestock?, which we link to forest configuration next
CANT READ THE X AXIS…..OR THE Y AXIS REALLY
When I control for forest cover in my models, edge density is associated with a very slight decrease in forest product richness….see previous slide
REALLY LIKE THIS SLIDE BUT I AM CURIOUS ABOUT CONTROLLING FOR PROPORTION FOREST BEFORE SHOWING EDGES……….
Edge density
Forest edge plays an important role in human-forest interactions. Forests with a high amount of edge may provide habitat for different types of species, and thus, provide different ecosystem services than highly intact forests; however the relationship between edge density and ecosystem services are poorly understood. Here, we show how edge density changes across countries and zones to explore how this forest edge may influence the livelihoods and diets of forest dependent people. Edge density is normalized by area, which allows for comparison across different sized landscapes.
Type equation here. Here, eik is the total edge of the landscape in meters and A is the total landscape area in m2. The metric ranges from zero to unlimited.
CAN YOU FIX THIS TO MATCH PREVIOUS SLIDE IN TERMS OF LEGIBILITY
When I control for forest cover in my models, edge density is associated with a very slight decrease in forest product richness….see previous slide
REALLY LIKE THIS SLIDE BUT I AM CURIOUS ABOUT CONTROLLING FOR PROPORTION FOREST BEFORE SHOWING EDGES……….
Edge density
Forest edge plays an important role in human-forest interactions. Forests with a high amount of edge may provide habitat for different types of species, and thus, provide different ecosystem services than highly intact forests; however the relationship between edge density and ecosystem services are poorly understood. Here, we show how edge density changes across countries and zones to explore how this forest edge may influence the livelihoods and diets of forest dependent people. Edge density is normalized by area, which allows for comparison across different sized landscapes.
Type equation here. Here, eik is the total edge of the landscape in meters and A is the total landscape area in m2. The metric ranges from zero to unlimited.
Ok, so the story is:
Edge effects impact the richness of forest products used as well as % HH using various construction materials– More edge is associated with a greater likelihood of a household using some type of construction material)—This is different than the effect of edge on total forest product richness---the opposite relationship
Both are positively related to edge? No, total forest product richness is negatively related to edge, while the use of construction materials (yes/no) is positively related to edge
Until you control for forest cover, in which case:
Edge is slightly inversely related to richness of forest products
I would say the main message is edge may affect forest products differently—It is negatively related to total richness of forest product use, but positively related to construction material use. Landscape configuration may affect specific products more than others
OK – I LOVE this figure – it does summarize things nicely, and lets us drop slides 20 and 21 and 22? Or at least move the end of prezzie? I don’t think we need to show all the stats here
This figure needs updating, which will change the arrangement and alignment of text. This slide would probably benefit from some animations as well
Some key findings thus far.
Ok, now I am confused….where is richness of forest foods on the graph? Ah, I see why you are confused. My response variable was binary-forest food/no forest food (fixed). There is no richness on this graph, only presence/ absence, Green-A household gathers some type of forest food, Black/grey a household does not. (FYI, I also fixed this for the forest construction materials slide, which said richness of forest foods as well). I pooled the forest products into these different categories (construction materials, foods, fuels), because some of the forest foods were very rare and couldn’t be modeled individually with such a small sample I love this work but I think I am confused by this one. This was slide 7, in my last email I asked you to take a look at it
Stephanie – can you clarify if zone and edge density were in final model? Sounds like not, so w/o its 64% or 25? (No, forest zone and edge density did not make the final model. They were not significant in explaining forest food (present/absence)—I changed full to “best” as you used later in the slide
Clarify what is full, best, fixed----(best model =Country (random)+ % contemporary forest cover (fixed)---the only fixed effect is % forest
I was hoping to show results here – early in the talk, without edges……..just forest cover and country – is that 64% ?
Also, can you delete the “doesn’t gather forest foods” I think we just need the “gathers forest foods” – the black, gray, bars--The green bars are the households in each zone that gather forest foods, while the black bars are the ones that don’t. This graph shows that the percent forest within 2km of the households that gather forest foods is higher than the percent forest for households that don’t gather forest foods, regardless of the zone. I added HH in front of the legend. Does that help?
When I control for forest cover in my models, edge density is associated with a very slight decrease in forest product richness….see previous slide
REALLY LIKE THIS SLIDE BUT I AM CURIOUS ABOUT CONTROLLING FOR PROPORTION FOREST BEFORE SHOWING EDGES……….
Edge density
Forest edge plays an important role in human-forest interactions. Forests with a high amount of edge may provide habitat for different types of species, and thus, provide different ecosystem services than highly intact forests; however the relationship between edge density and ecosystem services are poorly understood. Here, we show how edge density changes across countries and zones to explore how this forest edge may influence the livelihoods and diets of forest dependent people. Edge density is normalized by area, which allows for comparison across different sized landscapes.
Type equation here. Here, eik is the total edge of the landscape in meters and A is the total landscape area in m2. The metric ranges from zero to unlimited.
You can delete the part in red, Sarah, I just added that FYI
Edge density (Z-scores) (Other configuration variables were too correlated with forest cover to include in our model)