EMILIO F. MORAN ANTHROPOLOGICAL CENTER FOR TRAINING AND RESEARCH ON GLOBAL ENVIRONMENTAL CHANGE INDIANA UNIVERSITY

Transcription

1 EMILIO F. MORAN ANTHROPOLOGICAL CENTER FOR TRAINING AND RESEARCH ON GLOBAL ENVIRONMENTAL CHANGE INDIANA UNIVERSITY

2 GIS Tools for Advancing Anthropological Research Spatial and Biophysical Dimensions of Land Use and Land Cover Change in Amazonia Emilio F. Moran

3 Human Inprint in a Landscape How people use the land is highly heterogeneous and patchy This constitutes a challenge to field research and analytical procedures How do we design our sampling? How much spatial and temporal scope do we include? How do we link (i.e. infer) human behavior to the inprint of human actions on the landscape

4 Goals of this presentation: Examine the process of land use and land cover change in a frontier region of the Brazilian Amazon Show the methodological approaches taken to make spatially-explicit analyses And also to cover a period of over 25 years of change And infer the trajectories of land use associated with spatial and biophysical dimensions, as well as demographic determinants

5 Land Use and Land Cover Change Why focus on Land use and Land cover Change? It is the top priority for research that brings together physical, biological and social scientists (IGBP and IHDP: LUCC) Largest source of anthropogenic change in biogeochemical cycles Deforestation and conversion to agropastoral use accounts for most land use and land cover change globally

6 It matters! E.g.Deforestation in the Amazon Rapid rates of forest destruction since 1975 Carbon emissions from tropical deforestation account for a growing portion of the total carbon emissions to the earth s atmosphere Lets take a quick look at what happened in the study area since 1970

7 1970

8 1973

9 1976

10 1978

11 1985

12 1988

13 1991

14 CLOUD 1996

15 Deforestation and Reforestation Deforestation is not the whole story. In this study area we see both deforestation, and reforestation Understanding these dynamic changes requires multi-scale spatial and temporal approaches It also requires a focus on the individual, household, community and region to understand how people make decisions and their cumulative impact at landscape and regional scale Requires the use of methods that allow for up-scaling and down-scaling: not business as usual Key method: scale- and spatially-explicit data collection

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17 Space, time, and decisionlevel affect what can be observed, explained and changed

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23 Opportunity: Multiple Research Locations, with heterogeneous human inprints 1. Altamira 2. Marajo 3. Tome-Acu 4. Igarape-Acu 5. Yapu 6. Rondonia 7. Santarem

24 Altamira

25 Ponta de Pedras, Marajo Island

26 Tome-acu

27 Bragantina / Igarape Acu

28 Yapu

29 Rondonia

30 Santarem

31 Elements Conditioning Landscape Configuration and Composition in Amazonia Biophysical soil type and distribution watershed and access to water topography land cover type Socioeconomic, cultural Composition of land use systems and their spatial-temporal characteristics Settlement spatial pattern and demographics Land tenure structure Institutional arrangements and resource appropriation

32 Secondary Succession and the Composition of Land Cover Altamira 30 yrs colonization Igarape-Acu 100 yrs colonization % of total cover Water Forest SS 3 SS 2 SS 1 Bare Other % of total cover Water Forest SS 3 SS 2 SS 1 Bare Other Marajo Caboclo populations Yapu Indigenous population % of total cover % of total cover Water Forest SS 3 SS 2 SS 1 Bare Other Water Forest SS 3 SS 2 SS 1 Bare Other

33 Inter-regional Comparison Best discriminator of rate of secondary succession was height increment Nutrient-rich site consistently faster height increment Difference accelerates through time

34 Basal Area and Soil Fertility SS3 Nutrient-rich soils (alfisols) are associated with greater overstory basal area Nutrient-poor soils (oxisols) are associated with greater understory development But total basal area is similar

35 Figure CROPS AND TERRA ROXA Alfisols Pasture (%) Cocoa and Sugar Cane (%) Other (%) What are my land use options in these soils? Crops (%) None 1-25% 26-50% 51-75% 76-99% 100% Terra Roxa (%) Source: Survey in Altamira 1998, N=402 H h ld Oxisols

36 Example Landscape and farm level deforestation trajectories Colonization area, TransAmazon highway, PA Colonization stages, time of arrival, and farm consolidation Role of cohort and period effects Soil influence on land use decisions (at farm- Types of land cover transitions (by farm and landscape) Area measures, Number, type, size, density of patches Site: Altamira, Key variables: cycles of level) Spatial indicators: whole

37 Landscape-scale Land Cover in 1996 INCRA Colonization area: Altamira, Brasil Novo, Medicilandia 1996 Landscape Composition (Forest, SS, Production estimated from remote sensing data, Cacao estimated from CEPLAC data) (Colonization area = Hectares) Percentage of total colonization area Forest 96 S.S. 96 Cacao Production (Bare Soil + Pasture 96) Background (water, cloulds,..)

38 FARM COHORT ARRIVAL & DEFORESTATION Deforestation by cohorts Results and discussion 1. Deforestation : colonization landscape INCRA Colonization: Altamira, Brasil Novo, Medicilandia Distribution of Colonization Cohorts and % Deforestation (estimated from multiple source remote sensing data and colonization property grid) N Farm lots = Percentage new Cohort by time of initial clearing (5%) Cohorts % Deforestation

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40 Cohort and Period Effects Cohorts are groups of individuals and families that arrive to the Amazon frontier during a period of time Cohort effects are those explanations that can be traced to similarities in the behavior of the group Period effects refers to the impact of events taking place at particular moments such as shifts in credit policy, commodity prices, or inflation

41 Consequences of Period and Cohort Effects To better understand how population interacts with environment, it is useful to try to separate cohort from period effects in explanations Cohort effects result from shared experiences of the group Period effects affect all cohorts equally at a given moment of time

42 Developmental Cycle of Domestic Groups (Goody 1962 and 1976) The development cycle is intrinsic to domestic organization Focus is on the reproductive dimensions of the domestic unit and how this affects its relations to the environment and the economy There are life cycle considerations and shifts in economic strategies Each phase of the cycle is the outcome of pushes and pulls that result in particular outcomes Land use decisions by households are affected by stages in the developmental cycle

43 A Young Colonist Family on the Agricultural Frontier: Clearing Forest for Annual Cash Crop Production The theory of the developmental cycle of domestic groups posits that households follow a cycle in which a young couple marry, have young children, and form a household

44 Pasture Formation and Raising Cattle: Need for Capital As they all age, they undertake different activities because they have changing needs as households, and they also gain in capacity to do different things as they accumulate capital, and their labor force grows with children growing to young adults

45 Agroforestry and Perennial Crops: A Later Strategy? As heads of households age and begin to lose labor, they again reallocate their production priorities and favor less labor demanding activities Cocoa Coffee Fruit Crops Hardwood Trees

46 Integrating Land Cover Data with Parcel Boundaries

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49 Integrating Social Survey Data with Parcel Boundaries

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51 Average Distribution of Deforestation Events by Cohorts The colonist footprint: Average deforestation trajectories across cohorts Average percentage deforested on farm lots def70 def73 def75 def78 def79 def85 def88 def91 def96 deforestation periods cohort 1, < 1973 (n=121) cohort 2, (n=1033) cohort 3, (n=791) cohort 4, (n=443) cohort 5, (n=176) cohort 6, (n=90) cohort 7, (n=531) cohort 8, new (n=533)

52 Average Distribution of Deforestation Events by Cohorts The colonist footprint: Average deforestation trajectories across cohorts Average percentage deforested on farm lots def70 def73 def75 def78 def79 def85 def88 def91 def96 deforestation periods cohort 1, < 1973 (n=121) cohort 2, (n=1033) cohort 3, (n=791) cohort 4, (n=443) cohort 5, (n=176) cohort 6, (n=90) cohort 7, (n=531) cohort 8, new (n=533)

53 Average Distribution of Deforestation Events by Cohorts The colonist footprint: Average deforestation trajectories across cohorts Average percentage deforested on farm lots def70 def73 def75 def78 def79 def85 def88 def91 def96 deforestation periods cohort 1, < 1973 (n=121) cohort 2, (n=1033) cohort 3, (n=791) cohort 4, (n=443) cohort 5, (n=176) cohort 6, (n=90) cohort 7, (n=531) cohort 8, new (n=533)

54 Average Distribution of Deforestation Events by Cohorts The colonist footprint: Average deforestation trajectories across cohorts Average percentage deforested on farm lots def70 def73 def75 def78 def79 def85 def88 def91 def96 deforestation periods cohort 1, < 1973 (n=121) cohort 2, (n=1033) cohort 3, (n=791) cohort 4, (n=443) cohort 5, (n=176) cohort 6, (n=90) cohort 7, (n=531) cohort 8, new (n=533)

55 Average Distribution of Deforestation Events by Cohorts The colonist footprint: Average deforestation trajectories across cohorts Average percentage deforested on farm lots def70 def73 def75 def78 def79 def85 def88 def91 def96 deforestation periods cohort 1, < 1973 (n=121) cohort 2, (n=1033) cohort 3, (n=791) cohort 4, (n=443) cohort 5, (n=176) cohort 6, (n=90) cohort 7, (n=531) cohort 8, new (n=533)

56 Average Distribution of Deforestation Events by Cohorts The colonist footprint: Average deforestation trajectories across cohorts Average percentage deforested on farm lots def70 def73 def75 def78 def79 def85 def88 def91 def96 deforestation periods cohort 1, < 1973 (n=121) cohort 2, (n=1033) cohort 3, (n=791) cohort 4, (n=443) cohort 5, (n=176) cohort 6, (n=90) cohort 7, (n=531) cohort 8, new (n=533)

57 Average Deforestation of Farm Lot: Cohort Trajectories Average percentage deforested on farm lots The colonist footprint: Average deforestation trajectories across cohorts cohort 1, < 1973 (n=121) def70 def73 def75 def78 def79 def85 def88 deforestation periods def91 def96 cohort 2, (n=1033) cohort 3, (n=791) cohort 4, (n=443) cohort 5, (n=176) cohort 6, (n=90) cohort 7, (n=531) cohort 8, new (n=533)

58 TABLE 1 CHOOSING TERRA ROXA BY COHORT* % terra roxa Before After 1985 Total None % % % % % Total *cohort is based on the year of arrival in the lot Source: Survey in Altamira 1998, N=402 households

59 Conclusions There is a consistent generational trajectory to deforestation by households in the Amazon frontier (cohort effect) in which households follow an initial period of high rates of deforestation, followed by a steadily declining reliance on mature forest deforestation The cohort effect persists in spite of period effects. Events such as tight credit, hyperinflation, and other market signals affect the magnitude of deforestation but not its trajectory

60 Conclusions While our study supports the notion that there is a development cycle trajectory evident in the trajectory of deforestation and land use, this study also finds that the choice between pasture and perennial crops in stages III and IV is less a product of the life cycle and more a product of the soil endowments on the household s property that favor one kind of land use over the other.

61 Conclusions Spatially-explicit analysis of property-level processes permits a refined understanding of land use and demographic dynamics Improves prediction of deforestation rates and successional processes Makes possible robust generalizations about trajectories of land use based on household dynamics (for example, testing theory on the developmental cycle of domestic groups)

62 Using Spatially-explicit studies in anthropology spatially-explicit case studies allow for refined understanding of complex interactions otherwise difficult to study Data collection needs to be spatially-, and temporallyexplicit and nested at multiple scales Spatially-explicit studies over large regions allow us to identify which driving forces are broadly generalizable, and which are case-specific Expands the spatial and temporal scope of anthropological investigations without any necessary loss of detail, as long as data is nested at a variety of scales if collected in a spatially-explicit manner

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