The challenge of HIV/AIDS: Where does agroforestry fit in? - World ...

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106World Agroforestry into the FutureTable 1.Indicators of watershed functions for Way Besai, comparing actual data (averaged over 20 years) with simulations of differentenvironments: the current LU (land use) mix; an ‘all forest’ approximation of natural vegetation; and a ‘degraded lands’scenario with grass cover on a compacted soil. GenRiver simulations use rainfall data, soil information, land-cover type andsub-catchment structure of the watershed area (van Noordwijk et al. 2003).IndicatorsActual dataGenRiverCurrent LU Current LU Natural vegetation Degraded landTotal discharge fraction 0.61 0.53 0.44 0.62Buffering indicator 0.79 0.82 0.80 0.68Relative buffering indicator 0.66 0.66 0.55 0.49Buffering peak events 0.86 0.81 0.76 0.78Highest monthly discharge relativeto mean rainfallLowest monthly discharge relativeto mean rainfall1.92 2.19 1.65 1.580.39 0.54 0.50 0.46Overland flow fraction * 0.11 0.00 0.36Soil quick-flow fraction * 0.10 0.02 0.00Slow flow fraction * 0.30 0.29 0.25* indicates data not available.Table 2.Indicators of watershed functions for Mae Chaem, comparing actual data (averaged over 20 years) with simulations of differentenvironments: the current LU (land use) mix; an ‘all forest’ approximation of natural vegetation; and a ‘degraded lands’scenario with grass cover on a compacted soil. GenRiver simulations use rainfall data, soil information, land-cover type andsub-catchment structure of the watershed area (van Noordwijk et al. 2003).IndicatorsActual dataGenRiverCurrent LU Current LU Natural vegetation Degraded landTotal discharge fraction 0.21 0.19 0.13 0.32Buffering indicator 0.89 0.90 0.93 0.81Relative buffering indicator 0.49 0.45 0.54 0.40Buffering peak events 0.91 0.88 0.91 0.79Highest monthly discharge relativeto mean rainfallLowest monthly discharge relativeto mean rainfall3.16 3.67 3.01 3.370.20 0.22 0.27 0.24Overland flow fraction * 0.00 0.00 0.00Soil quick-flow fraction * 0.08 0.03 0.17Slow flow fraction * 0.14 0.08 0.12* indicates data not available.
Chapter 12: Watershed functions in productive agricultural landscapes107the dynamics of macropores in the soil tothe dynamics of river flow can fairly wellreproduce the time series of data from intensivelystudied (sub)catchments.Comparing land-use optionson the basis of bufferingfunctionsLong time-series with consistent data ofland-cover change are scarce and muchof the existing variation in land cover inagriculturally used landscape mosaics isnot represented in empirical data. Furtherinference on land-use options has to relyon analysis of the various contributing factorsand on synthetic models. Essentially,watershed functions that relate to the quantity,timing and quality of water flows canbe understood by considering steps in thepathway of water through the landscape(Ranieri et al. 2004). The main factors are:• Green cover – leaves intercept raindropsand modify the drip size (and thereforethe splash power they have when theyreach the ground), keeping a relativelysmall amount of water as water film onwet surfaces for rapid evaporation.• Brown cover – the litter layer on the soilsurface protects the soil from splash erosion,feeds soil biota that enhance soilstructure, and acts as a filter for overlandflow, reducing the sediment load.• Soil structure – at the surface and in thesoil determines the speed at which watercan infiltrate and hence the amount ofexcess rainfall that travels over the soilsurface as overland flow. Depending onslope and connectivity of the horizontalflow pathways (pipes) a substantialamount of water can be passed on tostreams as interflow in a matter of hoursafter a rainstorm.• Soil water deficit – water uptake byvegetation between rain events createsspace in the soil pores to absorb water;if the soil structure allows this water toinfiltrate fast enough, water use can thusreduce overland flow.• The drainage network – the network offurrows, gullies, drains, roads, soil profileintersections along roads, temporarystorage sites in ponds and wetlands,streamlets and streams determines howrapid overland flows and subsurface(inter)flows can reach rivers. Whereland-use change affects the timing offlow at a minutes-to-hours scale, the significanceof changes in pathways loosesimportance with increased spatial scale(say for distances more than 10 km), asthe travel time in the river itself (and itsinfluence by the degree of channelling,propensity for use of flood plains andriparian wetlands) starts to dominate.• Properties of the riverbed – if the riverbedconsists of stones and the riverbanks are stable, it can transport cleanwater at high velocity. Where the riverflows through (or meanders in) a landscapewith alluvial material, the rivercan pick up sediment along its way duringpeak flows and carry high sedimentloads regardless of the degree of soilprotection in the uplands. Landslides(linked, for example, to earthquakes,road construction or decrease in soil anchoringby decay of deep tree roots) andvolcanic ash deposits can provide soilmaterial for transport, over and beyondwhat comes from the hillsides.• Point sources of organic and chemicalpollutants – direct use of surface waterfor drinking and other domestic use isnot generally safe downstream of humanhabitation. Water quality for otherpurposes, as well as for maintenanceor restoration of the aquatic ecosystem,its biodiversity and use values, can benegatively affected by point sources oforganic and chemical pollutants. Use ofpesticides, imbalances between fertilizerinputs, uptake by plants (Cadisch et al.2004) and deposition of harvested productsor manure into streams by domesticlivestock (or domesticated elephants inecotourism areas in northern Thailand)can all make other efforts to maintainwatershed functions useless from a userperspective.Modelling physical degradationand rehabilitation processesin the analysis of trade-offsbetween profitability and watershedfunctionsA range of tools and models (e.g. Matthewset al. 2004; Ranieri et al. 2004) exist to relatethe overall performance of a landscapeto (subsets of) this list of influences, as wellas to the ‘natural capital’ (including rainfallregimen, slope, intrinsic soil conditionsand nature of the vegetation replaced byhuman land use).For the specific analysis of agroforestrymosaics in Southeast Asia we use the Wa-NuLCAS (Water, Nutrient and Light Capturein Agroforestry Systems) model at plot level(Khasanah et al. 2004; van Noordwijk et al.2004c), GenRiver and SpatRain for dailytime steps at watershed scale (Farida andvan Noordwijk 2004) and FALLOW (Forest,Agriculture, Low-value Lands Or Waste;Suyamto et al. 2004) to analyse longer-termtrends in land-use change linked to internaldrivers of change. In the remaining part ofthis chapter we will focus on the changes insoil conditions – as this may be the easiestpart to manage for practitioners of agroforestryand other forms of eco-agriculture.Using the soils under old-growth forestas a reference or baseline, soil degradationinvolves the loss of organic matter, adecline in soil nutrient reserves, a changein soil biota and below-ground food-webs,
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CitationGarrity, D., A. Okono, M. G
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Enhancing Environmental ServicesCha
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viWorld Agroforestry into the Futur
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viiiWorld Agroforestry into the Fut
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Agroforestry and the Future
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Keywords:Millennium Development Goa
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Chapter 1: Science-based agroforest
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Chapter 1: Science-based agroforest
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Trees and Markets
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Keywords:Dacryodes edulis, Irvingia
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Chapter 2: Trees and markets for ag
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Keywords:Perennial tree crops, plan
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Chapter 3: The future of perennial
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38World Agroforestry into the Futur
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“Trees influence landscape scaled
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Keywords:Agroforestry, improved fal
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Page 75 and 76: Chapter 7: Scaling up the impact of
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Page 91 and 92: Chapter 9Land and People:Working Gr
Page 93: Chapter 9: Land and people81• sca
Page 96 and 97: “Forest conservation is no longer
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Page 115 and 116: Keywords:Agroforestry, buffering wa
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Page 127 and 128: Chapter 13: Opportunities for linki
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Page 140 and 141: “Agroforestry can and does playa
Page 147 and 148: Keywords:Educational impact, sustai
Page 149 and 150: Chapter 16: Capacity building in ag
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Page 153 and 154: Keywords:Networking, research-exten
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Chapter 19: Can e-learning support
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Chapter 20Strengthening Institution
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Chapter 20: Strengthening instituti
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168“The biological characteristic
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170World Agroforestry into the Futu
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Author ContactsFahmudin Agusisri@in
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Acronyms and AbbreviationsACIARAFTP
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CreditsFront cover photo: Karen Rob
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World Agroforestry into the Future
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