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Globalization and the connection of remote communities: A review of household effects and their biodiversity implications

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Globalization and the connection of remote communities: A review of household effects and their biodiversity implications
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  Survey Globalization and the connection of remote communities: A review of householdeffects and their biodiversity implications Daniel Boyd Kramer a, ⁎ , Gerald Urquhart b , Kristen Schmitt c a  370 North Case Hall, James Madison College and the Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, United States b  35 East Holmes Hall, Lyman Briggs College, Michigan State University, East Lansing, MI 48824, United States c  32 Natural Resources, Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, United States a b s t r a c ta r t i c l e i n f o  Article history: Received 6 November 2008Received in revised form 26 June 2009Accepted 27 June 2009Available online 3 August 2009 Keywords: GlobalizationBiodiversityHouseholdsMarketsMigrationTechnology The remote regions of the world provide refuge to a disproportionate amount of the Earth's biodiversity. Asglobalization continues, isolated human communities in these regions are increasingly connected to globalmarket, migration, and technology networks. We review the diffuse literature on the household effects of changing market access, migration, and technology adoption in remote regions and implications for nativebiodiversity. Market access affects biodiversity in remote communities through changes in householdeconomics and social networks. Migration, either to or from remote settlements, affects biodiversity throughchanges in population, remittances, human capital, and social networks. Finally, we consider effects due toproduction, public infrastructure, and information and communication technologies. There is muchambiguity surrounding these causal pathways, and thus we also examine the roles of various ecological,household, community, and institutional mediating factors in determining the impacts of global connection.Finally, we explore the limitations of our current knowledge and research practices and propose directionsfor future work to address key uncertainties in theory and evidence as well as weaknesses in methodologicalapproaches. We recommend a broad and interdisciplinary mode of inquiry as the best means towardclarifying globalization's impacts on human settlements and the biodiversity harbored in the Earth'sremaining remote regions.© 2009 Elsevier B.V. All rights reserved. 1. Introduction Globalization's manifestations are increasingly penetrating theremote human settlements of the world and are profoundly affectingthe local use of natural resources in complex ways (Dietz et al., 2003). Remote communities, those lying at the periphery of global market,migration, and technology networks, are increasingly becoming lessremote. Here, human impacts are less, and resources are relativelyabundant and intact (Sanderson et al., 2002). Biodiversity hotspot countries, those with at least 100,000 ha of hotspots (Fisher andChristopher, 2007), meaning areas with at least 1500 endemic plantspecies having lost at least 70% of their srcinal habitat extent, havelarger and faster growing rural populations, have more emigration,and are less connected in terms of infrastructure and technology thannon-hotspot countries (Table 1). These metrics will change withconnection. The proximity of remote human settlements to biodiver-sity hotspots (Fig.1) suggests that the effects of global connection areof great importance for conservation.Connection to global networks occurs via new roads, rails, portsand increasingly through communication technologies. Much of theextant conservation literature has focused on the direct effects onbiodiversity of transportation infrastructure such as mortality fromconstruction and vehicle collisions, wildlife behavior modi 󿬁 cation,spread of exotics, and alteration of physical and chemical environ-ments (Trombulak and Frissell, 2000). Less attention has been given to how the connection of remote communities indirectly affects bio-diversity through changes in household behavior. It is clear, however,that household dynamics are important (Liu et al., 2003). There is little consensus though on the magnitude or direction of these effectslet alone an understandingof the processes by which these effects aremanifested. Causal pathways are complex and are mediated by nu-merous factors.Our primary purpose is to review how households in remote areasrespond to new market access, migration, and introduced technolo-gies (Fig. 2). Analysis of these three primary drivers and theirhouseholdeffectsareoftenaddressedseparatelywheninfacttheyareinseparable.Thesecondpurposeofthisreview,therefore,istoprovidean integrative account of the linkages between these causal processesby identifying common mediating factors. Our  󿬁 nal purpose is toimplicitly revisit many of the well known tensions between economicdevelopment and environmental sustainability from the householdperspective, which provides a unique lens for determining how thecalculus of global connection affects the attainment of economic andenvironmental goals. Ecological Economics 68 (2009) 2897 – 2909 ⁎  Corresponding author. Tel.: +1 517432 2199; fax: +1 517432 1804. E-mail address:  dbk@msu.edu (D.B. Kramer).0921-8009/$  –  see front matter © 2009 Elsevier B.V. All rights reserved.doi:10.1016/j.ecolecon.2009.06.026 Contents lists available at ScienceDirect Ecological Economics  journal homepage: www.elsevier.com/locate/ecolecon  We do not explicitly review the effects of household decisions onbiodiversityotherthanbriefmentionoftheselinkssincegoodreviewsare available (Wilson, 1999). Furthermore, it is not our intent toreviewall human and biodiversity interactions but rather those likelyto change as a result of connection. Our working de 󿬁 nition of biodi-versity is  “ the variation of life at all levels of biological organization ” (Gaston and Spicer, 2004) and for the purposes of this paper, we usethe term to mean native biodiversity. For each causal pathway wediscuss existing evidence and then identify important mediatingfactors. We refer mainly to empirically-based studies and totheoretical research when the former are unavailable. Much previouswork has focused on deforestation in the tropics and thus inevitably,our review re 󿬂 ects this bias. Our review relies on insights from theliterature on colonists' expansion of the agricultural frontier but isdistinct in that our concern is with changes in existing remote com-munities. We end with a discussion of the linkages between causalpathways and suggestions for research design and methodology toimprove our understanding of the impacts on biodiversity due to theglobal connection of remote human settlements. 2. Market access Market access affects biodiversity through changes in households'production and consumption of natural resources; transitions to cashand credit-based economies; livelihood diversi 󿬁 cation; and changesin income and income inequality. We have distilled these effects intotwocausalpathways: 1)householdeconomies and2)social networks(Fig. 2).  2.1. Market access and household economies Market access to remote human settlements is limited by under-developed transportation networks. Infrastructure developmentreduces transportation costs (Edmonds, 2002) and therefore costs for production inputs like fertilizers, pesticides, equipment, and technolo-gies while raising prices for local outputs like crops, timber,  󿬁 sh, andwildlife ( Jacoby, 2000). As a result, market access affects households' production decisions. Farmers may intensify production or increasetheir land holdings through deforestationwith the associated effects of habitat loss, nutrient runoff, pollution, and species decline (Geist andLambin, 2002). Households may shift from traditionally produced foodcropsandharvestedspeciestothosebetter-suitedforexportwithoftenharmfulecological consequences (Amadi,1988). Decreased transporta- tion costs to rural Indonesian villages led to the growth of rubbermonocultures (Miyamoto, 2006). In Cameroon, farmers facing rising plantain prices switched from cocoa and subsequently increased forestclearing(Gockowski,1997).FarmersnearertheTrans-AmazonHighwaytransitioned to cattle and perennials from food crops (Walker et al.,2002).Market access and changing price incentives may also lead to theunsustainable harvest of wildlife. In Africa, new logging roads anddemand from urban centers have led to the overexploitation of bushmeat (Fa et al., 2000). Falling transportation costs and rising Asian demand have accelerated the harvest of sea urchins for foodmarkets(Berkesetal.,2006)andcoralreef  󿬁 shfortheaquariumandlivereef food- 󿬁 sh trades (Scales et al., 2006) from remote Paci 󿬁 c islands. InPapua New Guinea, proximity to markets has resulted in  󿬁 shing downthe food chain (Cinner and McClanahan, 2006). Several factors mediate the effects of market access on householdproduction decisions and biodiversity. First, households may responddifferently to market access depending on their aversion to risk.Whereas poorer, subsistence-orientated households seek to minimizerisk while meeting their basic food needs (Fafchamps,1992), wealth- ier, market-orientated households maximize pro 󿬁 ts (Angelsen andKaimowitz,1999).Asoutputpricesincreaseandinputpricesdecrease,market orientated farmers may engage in more intensive and exten-sive cash cropping. Subsistence farmers, alternatively, may reducethe extent of their farming and associated risks while still meetingtheir food security needs by selling a portion of their crops at higherprices.  Table 1 A comparison of means between biodiversity hotspot and non-hotspot countries for various measures of remoteness.Hotspot countries Non-hotspot countries Independent means  p -valueRural proportion of population (2005) a 0.47 0.37 0.002( n =122) (95)Percentage growth of rural population (1995 – 2000) a 0.45  − 0.04 0.039(124) (94)Proportion of population with electricity access (2000) b 0.65 0.79 0.049(78) (37)Road network in km (1999) per land area (2003) in 1000 ha c 3.48 10.32  b 0.000(111) (65)Impervious surface area in m 2 per person (2000 – 01) d 90.69 131.14  b 0.000(121) (92)Proportion of rural population with access to improved sanitation (2004) e 0.52 0.69 0.001(104) (70)Proportion of rural population with access to improved water (2004) e 0.71 0.82 0.001(106) (75)Mobile phone subscribers as proportion of total population (2005) f  0.34 0.64  b 0.000(112) (69)Internet subscribers as proportion of population (2005) f  0.14 0.31  b 0.000(104) (62)Net number of migrants (2000 – 05) per total population (2006) in 1000s g − 0.60 5.86 0.197(122) (69)Hotspot countries are those containing greater than 100,000 ha of hotspots based on Conservation International's (CI) 34 global hotspots. CI de 󿬁 nes a hotspot as an area that bothcontains at least 1500 endemic plant species and has lost at least 70% of its srcinal habitat extent. Remoteness data are aggregated at the country level whereas hotspot data ignorepolitical boundaries. Therefore, the scale mismatch makes the comparison between hotspot and non-hotspot countries imperfect. a United Nations, Department of Economic and Social Affairs, Population Division, 2006.  World Urbanization Prospects: The 2005 Revision. b International Energy Agency (IEA), 2002.  World Energy Outlook: Energy and Poverty. c International Road Federation (IRF), 2002.  Word Road Statistics  & Food and Agricultural Organization (FAO). d National Geophysical Data Center, National Oceans and Atmospheric Agency (NOAA). e WorldHealthOrganization(WHO)&TheUnitedNation'sChildren'sFund(UNICEF),2006. Meetingthe MDGDrinking WaterandSanitationTarget:The UrbanandRural Challenge of the Decade. f  International Telecommunication Union (ITU), 2007.  World Telecommunication Indicators 2006. g United Nations Department of Economic and Social Affairs Population Division, 2007. World Population Prospects: The 2006 Revision. 2898  D.B. Kramer et al. / Ecological Economics 68 (2009) 2897  –  2909  Fig. 1.  An overlay of biodiversity hotspot countries, those with at least 100,000 ha of hotspots according to Fisher and Christopher, 2007 (indicated with crosshatching) on an aggregatemeasure of remoteness based on a weighting of eight variables (darker shades indicate greater remoteness). The eight variables and their respective weights are: 1) urban populationproportion(0.10);2)electricityaccessproportion(0.10);2)netnumberofmigrants(0.10);3)kmofroadnetwork(0.30);4)impervioussurfacesareaperperson(0.10);5)ruralaccesstoimprovedsanitationproportion(0.10);6)ruralaccesstoimprovedwatersourceproportion(0.10);7)mobilephonesubscribersper1000people(0.10);8)Internetusersper1000people(0.10).Eachvariablewasnormalizedtoanumberbetween0and1usingthefollowingtransformation:(  x −  x MIN )/(  x MAX −  x MIN ).ThePearson'scorrelationcoef  󿬁 cientbetweenremotenessand the proportion of hotspot area in a country was 0.411 (  p b 0.01). Unshaded countries had insuf  󿬁 cient data to include. Fig. 2.  The household effects and causal pathways of market access, migration, and technology on biodiversity.2899 D.B. Kramer et al. / Ecological Economics 68 (2009) 2897  –  2909  Second, land and resource rights and tenure regimes mediatehousehold production processes and their effects. Increasing marketaccess is often accompanied by state imposed changes in propertyrights from customary land tenure to individual property rights andtitling in order to accommodate commercial exchanges. Also, risingoutput prices, increasing the value of land relative to labor, mayinduceindividualstodemandresourcerights(Heltberg,2002).Secure land tenure is thought to encourage investment and act as collateralfor credit (Meinzen-Dick et al., 1997). Granting formal land title, one method of securing land tenure, is thought to decrease deforestationby farmers hoping to establishing usufruct rights. Also, risk-aversefarmers with poorly de 󿬁 ned and dif  󿬁 cult to defend land rights mayavoid more pro 󿬁 table perennial crops which are less amenable tomodi 󿬁 cation due to changing economic or ecological conditions butmoresupportiveofsoilnutritionandecosystemservicesthanannuals(Hyde et al.,1996). It is important to note, however, that secure land tenure is not synonymous with formal land titling. Moreover, a num-ber of studies have called into question the links between secure landrights and investments (Bromley, 2008). Customary tenure systems may provide as effective security (Deininger and Feder, 2001). Also,the effects of titling on biodiversity may be negative if, for example,enforcement is lacking or if the titling of agricultural lands is givenpriority over forested lands (Broegaard, 2005).Different land tenure and ownership regimes may be associatedwith different production methods. For example, livestock in centralMali are increasingly owned and managed by outside investors withlittle knowledge of traditional methods of livestock husbandry suchas highly mobile grazing which reduces the degradation of drylandecosystems (Turner, 1999). Some resource rights regimes restrict access to and transfer, leasing, and ownership of natural resources bywomen and ethnic groups who may interact with resources muchdifferently than those granted resource rights (Meinzen-Dick et al.,1997).Third, householdproductionprocessesandtheireffectsdependontheavailabilityofhouseholdassetswhichaffectinvestments.Inyoungsettlements, land is typically abundant and labor scarce. A land-poorhouseholdmayhavedif  󿬁 cultyobtainingcreditforinvestmentsinlandimprovements and agricultural intensi 󿬁 cation, relying instead onclearing communal land or exploitingother resources such as wildlife(Hecht,1984). Small farms typically use their land intensivelyand aretherefore more likely to deforest, if feasible, to increase productionand less likely to hold their land inpasture than large farms (Pinchon,1997). Households lacking the resources to invest in land conversionmay substitute other inputs for land thereby reducing the extentof their cultivation while increasing its intensity (Holden, 1997).Labor-poor households or those without access to labor may havedif  󿬁 culty in engaging in labor-intensive production systems like coca(Kaimowitz, 1997). On the other hand, households with only laborresources may have less  󿬂 exibility in converting their labor into otherproductive assets (Reardon and Vosti, 1995) other than through migration. Labor-rich households are also more likely to deforest andto plant perennial crops and less likely to raise cattle than labor-poorhouseholds (Pinchon, 1997). Households lacking appropriate assets can look elsewhere however functioning markets for land, labor,credit, and technology are required.Household assetsmayalsodetermine the effects onbiodiversityof certain production decisions. Households with abundant laborresourcesandfacinglimitedopportunitiesforagriculturalextensi 󿬁 ca-tion may deplete soil nutrients more rapidly due to denser croppingthan households with abundant capital resources used to purchaseinputs such as fertilizers to avoid soil depletion and land improve-ments to prevent erosion and runoff (Boserup, 1965) although theecologicallydestructiveeffectsofagricultural intensi 󿬁 cationhave alsobeen well documented (Matson et al.,1997). Lastly, ecological and biophysical conditions affect productiondecisions and biodiversity. Agriculture is more likely at lower eleva-tions,  󿬂 atter slopes, and on larger land patches (Munroe et al., 2002). Some  󿬁 nd that deforestation is more likely in areas of low soil qualityas households try to maintain agricultural productivity through landclearing. Others  󿬁 nd that land clearing is more associated withfarming on high quality soils since pro 󿬁 ts are often reinvested in landclearing for other uses such as cattle pasture (Pinchon, 1997). Similarly,ecologicalconditionswillaffecthouseholdharvestdecisionspertaining to terrestrial and marine species.In addition to changing household production decisions, marketaccessintroduces competition to local producers and more substitutionpossibilitiesforlocalconsumers.Althoughthepavingofanexistingroadin Guatemala led to no noticeable change in output prices nor im-provements in local market conditions, imported agricultural andcommercial goods from other regions dramatically increased, threaten-ing to constrain agricultural diversi 󿬁 cation opportunities for localfarmers (Shriar, 2006). In West Africa, new roads facilitated the im- portationofwheattoremotecommunitieswhichdisplacedthegrowingof alternative food crops such as millet resulting in expanded cottoncultivation (Wagner, 1986). Increased competition's effects on house-holds and biodiversity depend on local consumers' preferences for newimports, constraints onproducer investmentas a reaction to intensi 󿬁 edcompetition, and the comparative ecological effects of alternative cropsand production methods.Market access is often accompanied by the transition from sub-sistence and barter-based economies to market, credit, and cash-basedeconomies which may affect the temporal allocation of resources andspurhouseholdinvestment.Cashallowsresourceuserstostorewealthinmorefungibleandenduringformswhichcanleadtoproductionbeyondsubsistencelevels.Creditcanlengthentimehorizonsandinducepeopletoputgreatervalueonfuturebene 󿬁 ts.Thus,ifthefuturebene 󿬁 tsofnon-timber forest products (NTFP) are greater than those of cash-cropping,investments in NTFP will increase or vice versa (Barbier and Burgess,1996). Longer time horizons may also induce households to invest inmore sustainable production methods and management like organicfarming, integrated pest management, selective logging, shade-growncoffee, or the sustainable harvest of wildlife (Godoy et al., 1997). Alternatively, credit may precipitate more destructive investments inagricultural,livestock,unsustainablehunting,oraquaculture(Pendletonand Howe, 2002). Whether households can take advantage of availablecreditoftendependsonwhethertheyhavesuf  󿬁 cientcollateraltoobtaincredit.Highlyeducated(Pinchon,1997)andlessriskaverse(Guirkinger, 2008) households may participate more in credit markets. The effect of credit usage on biodiversity depends greatly on the direction of investment which depends on ecological conditions, available technol-ogies, and functioning markets for land, labor, and capital. Thus, theoverall impact on biodiversity due to changes in household behaviorstemming from the transition to market, credit, and cash-basedeconomies is unclear.Livelihood diversi 󿬁 cation is encouraged by new market access.Livelihood diversi 󿬁 cation, like credit, insulates people from the risksof seasonal, environmental, and economic shocks associated withnatural resource-based livelihoods (Ellis and Allsion, 2004), dimin- ishing returns to laborand land, high transaction costs, and immaturemarkets for land and labor (Barrett et al., 2001). Through livelihood diversi 󿬁 cation, households may either disassociate from natural re-sources, for example into non-farmwage labor (Smith et al., 2001), orincorporate more resource-intensive activities like cash-cropping. Or,diversi 󿬁 cation may entail environmental tradeoffs such as transitionsfrom farming and forest clearing to  󿬁 shing (Dodds, 1998; Freemanet al., 2004). Generally the process of livelihood diversi 󿬁 cation and itsbiodiversityeffectsdependona suiteof factors thatlimit theabilityof households toundertakesuchopportunities. First,a lack ofhouseholdassets including land, labor, education, technology, and access tocredit may prevent diversi 󿬁 cation (Barrett et al., 2001). Asset-rich households often diversify into non-farm sectors whereas asset-poorhouseholds diversify into off-farm wage labor on other farms which 2900  D.B. Kramer et al. / Ecological Economics 68 (2009) 2897  –  2909  may do little to reduce their exposure to risk and reliance on naturalresources (Rigg, 2006). Second, land tenure regimes which do not easilyallowlandtransferorrentalmayinhibitentryorexitfromsomeactivities such as farming. Of particular importance are rules whichlimit ownership or inheritance of resources by women. Also, diver-si 󿬁 cation opportunities may be limited when large amounts of idleland are held by wealthy absentee land owners (Berry and Cline,1979). Third, local governance may create bureaucratic roadblockswith mandatory licensing, fees,  󿬁 nes, and bribes that sti 󿬂 e householdmobility and adaptability (Ellis and Allsion, 2004). Finally, market access may accelerate the growth of personalincomes. There exists a lively debate on the environmental effects of income growth. The environmental Kuznet's curve (EKC) suggeststhat as per capita incomes increase, initial environmental degradationreverses due to shifts in consumer preferences, government capaci-ties and priorities, and industry composition. Furthermore, wealthierhouseholdsmayexhibitlonger time horizons fordecision makingandadopt more sustainable practices (Tiffen et al.,1994). While most EKC analysesconsidercross-countrycomparisons,thesamedynamicsmayapply at smaller spatial scales (Godoy et al.,1997). On the other hand, increasedincomeisoftenreinvestedintoproduction,exacerbatingtheunsustainable use of natural resources (Mulley and Unruh, 2004). As noted, the direction of investment depends on ecological conditions,available technologies, risk aversion, land tenure arrangements, andfunctioning markets for land, labor, and capital.  2.2. Market access and social networks Household behavior is embedded in social networks (Granovetter,1975), and therefore the household effects of market access on bio-diversity depend in part on existing social networks. Social networksfacilitate and regulate access to resources through social capital(Woolcock, 1998), the bonds between individuals in terms of trust, sharednorms,andreciprocitywhichareoftenencouragedbygiftgivingin remote communities (Gurven et al., 2000). Social capital fosters “ mutualcoercion,mutuallyagreedupon ” (Hardin,1968)andisthought to increase the likelihood of cooperation in the commons (Krishna andUphoff,1999;Kramer,2007).Socialcapitalmaybeasimportantafactoras secure land tenure in maintaining natural resources (Katz, 2000).Increasedmarketaccessmayaffectthesocialnetworksofhouseholdsinremotecommunitiesbyincreasing1)incomeinequalityand2)accesstocredit markets.Evidence shows that households within communities of greaterincome equality demonstrate greater trust andfollowcivic normsmoreclosely than others (Knack and Keefer, 1997). Because households' abilities to capitalize on market opportunities vary, market access mayexacerbateincomeinequality( Jacoby,2000)andunderminecommunity norms and the stewardship of natural resources. Income inequality hasbeenassociatedwithgreaterbiodiversitylossesalthoughthecausallinksare unclear (Mikkelson et al., 2007). One possibility is that income inequality undermines the social cohesion underlying conformance tocommunity rules and customs (Ostrom,1990). Second, the sustainable use of resources through bargaining among individuals (Coase,1960) is perhaps more likely among income homogeneous communities. Third,income inequality may lead to the imposition of one ecologically-destructive technology path on a community (Boyce, 1994). Fourth, community elites may become myopic and rapacious if their gains inwealthandpowerareperceivedastenuous(Sawyer,2004;Tsing,2004). Finally, growing income inequality may coincide with a reallocation of time from social interactions to work, which may weaken socialnetworks (Gross et al., 1979). On the other hand, theoretical work suggests that contributions to public goods such as biodiversityconservation may increase with income inequality since additionalcontributionsfromthenewlyrichmayoffsetreducedcontributionsfromthe poor (Itaya et al., 1997). Moreover, the wealthy may coerce conservation-friendly behavior from others (Ruttan and Mulder,1999).Additionally, results from game theoretic experiments in remotecommunities suggest that market exposure is associated with moregenerous, less self-interested offers in public good games (Henrich,2000; Gurven, 2004).Credit markets may also undermine social networks and the ste-wardship of resources. Households may substitute credit for socialnetworks which have traditionally played a role in mitigating house-hold risk, because the gifts which invigorate social networks aremorecostly (Rosenzweig, 1988). If so, community norms and reciprocity that provide the foundation for local resource management mayweaken. In Papua New Guinea for example, communities with highlyexclusive customary marine tenure systems, those that successfullyexcluded non-owners, were found farther away from major marketswhere credit was more available (Cinner, 2005). Also, non-market mechanisms for risk sharing may allow greater monitoring and en-forcement of household behavior in close-knit societies and thereforetheirloss mightadverselyaffect local resources (Besley,1995). Finally, credit programs may exacerbate existing power structures and in-equalities particularly along gender lines (Rahman, 1999). On the other hand, credit markets may strengthen social networks if lendingincreases interactions, creates new norms, and fosters more trustamong community members (Dowla, 2005). 3. Migration The connection of remote communities facilitates migration.Migrants are pushed to destination areas by thedegradation of, scarcityof, or lack of access to resources; poverty; populationpressures; naturaldisasters; and con 󿬂 ict in srcin areas. Most migration is rural to urban,seasonal, circular, or international. Rural to rural migrants, however,pulled by cheap land, abundant resources (Carr, 2004), employment opportunities, security, access to new markets, and existing socialnetworks in destination areas are also common (Rudel and Richards,1990; Oglethorpe et al., 2007). Four causal pathways illustrate thehouseholdeffectsof migrationonbiodiversity:1)populationdynamics,2) remittances, 3) human capital, and 4) social networks (Fig. 2).  3.1. Migration, population, and population density Global connection often leads to population increases in remotecommunities, which can contribute to natural resource degradation(Lambin et al., 2003) and the weakening of traditional resource management ( Jodha, 1985). For example, increased population densities in remote African communities near protected areas havecaused the degradation of forests, wildlife, and  󿬁 sheries (Scholte,2003). The links between population and environmental degradationare further evidenced in emigration-induced forest re-growth (Grauet al., 2003).Some, however,  󿬁 nd no effect (Inman, 1993) and others positive effects of population growth on natural resources (Cropper andGrif  󿬁 ths, 1994; Heilig, 1994). In an extensive review of deforestationmodels, these uncertainties were upheld (Angelsen and Kaimowitz,1999). One explanation for contrarian accounts is that environmentalimpacts are mediated by the types of technologies introduced byimmigrants (Muradiana et al., 2006). Population growth may spurtechnological development and innovative resource managementtechniques (Binswanger and Pingali, 1989). Another explanation isthat local governance may mitigate the detrimental effects of popula-tion growth. The lackof forest degradation despitepopulation growthinNepal,forexample,wasexplainedbytheexistenceofeffective,localcollective action (Varughese, 2000). In rural communities in India, local institutions played an important role in mitigating the environ-mental effects wrought by population-induced demographic andsocioeconomic changes (Agrawal and Yadama,1997). Another explanation for contrarian accounts is that immigrationinduced population growth and density increases may lead to 2901 D.B. Kramer et al. / Ecological Economics 68 (2009) 2897  –  2909
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