Sanderson Et Al., the Human Footprint and the Last of the Wild

Articles The Human Footprint and the Last of the Wild

ERICW. SANDERSON,MALANDING JAITEH, MARC A. LEVY,KENT H. REDFORD, ANTOINETTEV. WANNEBO,AND GILLIANWOOLMER

n Genesis,God blesses humanbeings and bids us to take dominion over the fish in the sea,the birdsin the air, THE HUMANFOOTPRINT IS A GLOBAL and other We are entreatedto be fruitful every living thing. MAPOF HUMANINFLUENCE ON THE and multiply,to fill the earth,and subdueit (Gen. 1:28).The bad news, and the good news, is that we have almost suc- LANDSURFACE, WHICH SUGGESTSTHAT ceeded. Thereis little debatein scientificcircles about the impor- HUMANBEINGS ARE STEWARDS OF tance of human influenceon ecosystems.According to sci- WE LIKEIT OR NOT entists'reports, we appropriateover 40%of the net primary NATURE,WHETHER productivity(the greenmaterial) produced on Eartheach year (Vitouseket al. 1986,Rojstaczer et al.2001). We consume 35% thislack of appreciationmay be dueto scientists'propensity of the productivityof the oceanicshelf (Pauly and Christensen to expressthemselves in termslike "appropriation of net pri- 1995), and we use 60% of freshwaterrun-off (Postel et al. maryproductivity" or "exponentialpopulation growth," ab- 1996). The unprecedentedescalation in both human popu- stractionsthat require some training to understand.It may lation and consumption in the 20th centuryhas resultedin be dueto historicalassumptions about and habits inherited environmentalcrises never before encountered in the history fromtimes when human beings, as a group,had dramatically of humankindand the world (McNeill2000). E. O. Wilson less influenceon the biosphere.Now the individualdeci- (2002) claims it would now take four Earthsto meet the consumptiondemands of the currenthuman population,if Eric Sanderson(e-mail: [email protected])is associatedirector, and every human consumed at the level of the averageUS in- W. Gillian Woolmeris programmanager and GIS analyst, in the Landscape habitant.The influenceof human on the planethas be- beings Ecologyand GeographicAnalysis Program at the WildlifeConservation So- to find adultsin coun- come so pervasivethat it is hard any cietyInstitute, 2300 SouthernBlvd., Bronx, NY 10460.Kent H. Redfordis di- trywho havenot seen the environmentaround them reduced rectorof the institute.MalandingJaiteh is a researchassociate and GISspe- in naturalvalues during their lifetimes-woodlots converted cialist,MarcA. Levy is associatedirector for scienceapplications, andAntoinette to lands convertedto suburbande- V Wannebois seniorstaff associate at the Centerfor InternationalEarth Sci- agriculture,agricultural ence Network Columbia 61 Route Pal- suburban convertedto urbanareas. Information (CIESIN), University, 9W, velopment, development isades,NY 10964.Sanderson's research interests include applications of land- local is the The cumulative effect of these many changes scape ecology to conservationproblems and geographicaland historical globalphenomenon of humaninfluence on nature,a new ge- contextsfor modernconservation action; he has recentlypublished scientific con- ological epoch some call the "anthropocene"(Steffen and articleson conservationplanning for landscapespecies and rangewide servation the Woolmer'sresearch interests include the 2001). Human influenceis arguablythe most impor- prioritiesfor jaguar. ap- Tyson and othertechnologies forfield and tant factor life of all kinds in world plicationofgeographic information systems affecting today's (Lande broad-basedconservation activities. Redford has written extensively about the 1998,Terborgh 1999, Pimm 2001, UNEP 2001). theoryand practice of conservation.Levy, a politicalscientist with a background Yetdespite the broadconsensus among biologists about the in internationalrelations and public policy, conducts research on international and importanceof humaninfluence on nature,this phenomenon environmentalgovernance, sustainability indicators, environment-security interactions.Jaiteh's research interests include of remotesensing and its arenot fullyappreciated by the largerhu- applications implications and technologiesin human-environment man which does not them in its eco- geographicinformation systems community, recognize interactions,particularly the dynamics of land useand coverchange in Africa. nomic systems(Hall et al. 2001) or in most of its politicalde- Wannebo'sresearch interests include detecting land useand landcover changes cisions(Soulk and Terborgh 1999, Chapin et al.2000). In part, usingremote sensing. @ 2002 AmericanInstitute of BiologicalSciences.

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sions of 6 billion people add up to a globalphenomenon in turbanceindex (Hannahet al. 1994, 1995),which used dig- a way unique to our time. What we need is a way to under- itized maps from Rand-McNallyatlases and other sourcesto stand this influencethat is global in extent and yet easy to classifyareas as "human-dominated"'"partially disturbed," or grasp-what we need is a map. "undisturbed";according to thatindex, nearly three-quarters Until recently,designing such a map was not possible,be- of the habitablesurface of the planet is disturbedat least in causedetailed data on humanactivities at the globalscale were part by human use. The GlobalMethodology for Mapping unavailable.The fortunateconfluence of severalfactors dur- HumanImpacts on the Biosphere(GLOBIO; UNEP 2001) es- ing the 1990schanged this situation.Rapid advances in earth timates the amount of disturbanceon flora and fauna ac- observation,using satellite technology pioneered by NASAand cording to their distance from human infrastructure(e.g., other spaceagencies, meant that,for the firsttime, verifiable roads,pipelines, settlements). Originally focused on scenar- globalmaps of land use and land coverwere available (Love- ios of historic,current, and futureimpact in the Arcticregion, land et al. 2000). The thawingof the cold war and callsfor ef- these analyseshave recently been expanded to the global ficiencyin governmentmeant that other sources of globalge- scale (see www.globio.infofor updates). The human foot- ographic data, for example, on roads and railways,were printhas importantparallels to allthese efforts, which, though releasedto the publicby the US NationalImagery and Map- approachingthe questionusing a varietyof datasources and ping Agency (NIMA 1997). Improvedreporting of popula- methodologies,arrive at largelythe same answer. tion statisticsat subnationallevels enabled geographers to cre- To map the human footprint,we used four types of data ateglobal digital maps of humanpopulation density (CIESIN as proxies for human influence: population density, land et al. 2000). Finally,advances in geographicinformation sys- transformation, accessibility,and electrical power infra- tems (GIS)have provided the integrationtechnology neces- structure.Nine datasetsthat representthese four datatypes sary to combine these data in an efficientand reproducible (table 1) were selectedfor their coverage,consistency, avail- manner.Although the datasetsnow availableare imperfect in- ability,and relevance,but theyprovide only an incompletede- struments,they areof sufficientdetail and completenessthat scriptionof human influenceon nature.For example,most scientists can map the influence of humans on the entire of these datasetsdo not include Antarcticaor many small land'ssurface. oceanicislands, and thus we had to excludethese areasfrom Wecall our map of humaninfluence "the human footprint," our analysis.In addition,we confinedour analysisto the ter- consciousof its similarityto the ecologicalfootprint, a set of restrialrealm, because a differentset of inputs would be re- techniquesfor estimatingthe amount of land or sea neces- quiredto map human influencein the oceans.Effects of pol- saryto supportthe consumptionhabits of one individual,pop- lution, global warming, increased exposure to ultraviolet ulation,product, activity, or service (Wackernageland Rees radiation,and other globalphenomena, although they have 1996).The humanfootprint represents in some sensethe sum importantconsequences for terrestrial ecosystems, are not in- total of ecological footprints of the human population. It cluded. For this analysiswe focused on the directmeasures expressesthat sum not as a single number,however, but as a of human infrastructureand populationthat have the most continuum of human influence stretched across the land immediateimpact on wildlife and wild lands and for which surface,revealing through its variationthe majorpattern of geographicdata were readilyavailable. To combine the nine human influenceon nature. datasets,we needed to (1) presentthem in one map projec- tion, using a consistentset of coastalboundaries and regions; Mapping the human footprint (2) express them as overlaying grids at a resolution of 1 Our techniquefor mappingthe human footprintgrows out squarekilometer (km2); and (3) code each datasetinto stan- of a recenttradition of wildernessmapping (McCloskey and dardizedscores that reflectedtheir estimated contribution to Spalding 1989, Lesslieand Malsen 1995, Aplet et al. 2000, human influenceon a scale of 0 to 10 (0 for low human in- Yaroshenkoet al.2001), which focuseson defininghuman influence, 10 for high). fluencethrough geographic proxies, such as human popula- These codes were based on published scientific studies tion density,settlements, roads, and other accesspoints, and and consultationwith a rangeof biologists,social scientists, includesfactors such as the size and remotenessof an area. and conservationists,as summarizedbelow. However,except for the SierraClub map of wilderness(Mc- Closkeyand Spalding1989) that was createdbefore the wide- Human population density. The numberof people in spread use of GIS and incorporatedonly one of the data a givenarea is frequentlycited as a primarycause of declines types we use here,none of these earlierefforts were made at in speciesand ecosystems (Cincotta and Engelman2000), with the global scale. higherhuman densitiesleading to higherlevels of influence Advanceshave been made in understandinghuman dis- on nature.A recentstudy by Brasharesand colleagues(2001) turbanceglobally since George Marsh first asked,"To what de- showed that 98% of the variationin extinction ratesin na- gree arethe processesof naturethreatened by human activ- tional parks in Ghana over a 30-year period could be ex- ity?"in his 1864 work, Man and Nature(quoted in Hannah plainedby the size of the parkand by the numberof people et al. 1994; see also Lowdermilk1953, Thomas 1956, and living within 50 km of it--the higher the density and the Bennett 1975). More recent effortsinclude the human dis- smallerthe park,the higherthe extinctionrate. Others have

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Table1. Geographicdatasets used to mapthe human footprint.

Dataset type Dataset name Year Sources Reference

Populationdensity GriddedPopulation of the World 1995 CIESIN CIESIN2000

Landtransformation GlobalLand Use/Land Coverversion 2 1992-1993 USGS/UNL/JRC Lovelandet al. 2000 VectorMap Level 0 Built-UpCenters 1960s-1990s NIMA NIMA1997 VectorMap Level 0 Population 1960s-1990s NIMA Settlements VectorMap Level0 Roads and Railways 1960s-1990s NIMA

Access VectorMap Level0 Roads and Railways 1960s-1990s NIMA NIMA1997 VectorMap Level0 Coastline VectorMap Level0 Rivers (majorrivers defined as rivers represented by continuous polygonsto the sea)

Electricalpower Defense MeteorologicalSatellite 1994-1995 NOAA/NGDC Elvidgeet al. 1997a infrastructure Program,Stable Lights

Biome normalization TerrestrialBiomes 2001 WWF Olson et al. 2001 TerrestrialBiogeographic Realms 2001 WWF

CIESIN,Center for InternationalEarth Science Information Network, Columbia University; JRC, Joint ResearchCentre of the EuropeanCommission; NGDC, National GeophysicalData Center;NIMA, National Imageryand MappingAgency; NOAA, National Oceanic and AtmosphericAdministration; UNL, Universityof Nebraska,Lincoln; USGS, US GeologicalSurvey; WWF, World Wildlife Fund for Nature,United States Note:Although the VectorMap Level0, ed. 3, datasetswere published in 1997, the datasetson which they are based are derivedfrom Defense MappingAgency Operational Navigational Charts developed from the mid-1960s through the early 1990s. found similarresults for nationalparks in the westernUnited types (Vitousek1997). Moreover, fragmentation often facil- Statesand small reservesacross Africa (Parks and Harcourt itatesadditional negative consequences to speciesand ecosys- 2002, Harcourtet al. 2001, respectively).Robinson and Ben- tems beyondthe simpleloss of habitat,in concertwith other nett (2000) note that, in termsof sustainablehunting levels, processesand over time (Crooksand Soule 1999,Laurance the land'scarrying capacity for peoplewho dependexclusively and Cochrane2001). Humanbeings transform land to build on gamemeat will not greatlyexceed one personper km2, even settlements,grow food, and produceother economic goods under the most productivecircumstances. Simple mathe- (e.g., Geist and Lambin2002); differentland uses, however, matics suggeststhat the greaterthe number of people, the differin the extentto whichthey modifyecosystem processes more resourcesthat will be requiredfrom the land,as medi- and affectthe qualityof habitatfor differentspecies (Goudie atedby theirconsumption rate (Malthus1798, Wackernagel 1986,Forman 1995). Growthof agricultureover the last 30 and Rees 1996). yearshas led to largechanges in worldwiderates of nitrogen Beyond this general understanding,there is little guid- fixation and phosphorus accumulationin soils and water ancein the literatureabout how humaninfluence exactly scales and increaseddemands on freshwater for irrigation(Tilman with humanpopulation density (Forester and Machlis1996). et al. 2001). The consequencesof interactionsbetween human population We assignedthe maximum score (10) to built-up envi- densityand the environmentdepend on the natureof the in- ronments;lower scores (6, 7, or 8, dependingon level of in- teractionand the particularspecies, ecosystems, or processes put) to agriculturalland cover;and lower scoresstill (4) to in question.In this study,we used a continuumapproach, in mixed-usecover. Other types of land use, notablyextensive whichhuman influence scores for densitiesbetween 0 and 10 grazinglands in aridareas, are difficult to map and are most personsper km2 increased linearly from 0 to 10 and the score likelyunderestimated in our analysis.We assigneda valueof above10 personsper km2 was held constantat 10.We assume 0 to all other land cover types-forests, grasslands, and that human influenceattributable solely to human popula- Mediterraneanecosystems, for example-although those tion density reachesan asymptoteat some level, though at covertypes are subjectto various kinds of human uses. what densitythat influenceevens out is uncertain;we chose Land transformationalso includes the direct effects of 10 personsper km2as an estimate. roadsand railwayson speciesand ecosystems.Not all species and ecosystemsare equally affected by roads,but overallthe Land transformation. Calledthe single greatest threat to presenceof roadsis highlycorrelated with changesin species biologicaldiversity, land transformationhas resultedin loss composition,including increases in nonnativeinvasive species, in- and fragmentationof habitat in many differentecosystem decreasednative species populations through direct and

October2002 / Vol.52 No. 10 - BioScience 893 Articles 4 direct mortality,and modification of hydrologicand geo- Human access. Roads,major rivers, and coastlines provide morphic processesthat shape aquaticand ripariansystems opportunitiesfor hunting and extractionof other resources, (Trombulakand Frissell2000). Lalo (1987) estimatedthat 1 pollution and waste disposal,and disruptionof naturalsys- million vertebratesa day are killed on roads in the United tems,as well as socialand economicgain (Gucinski et al.2001). States.Forman and Deblinger(2000) estimatedthat the ef- As a result,designating areas of remotenessis a common el- fectsof Americanroads extend over a bandapproximately 600 ementof manywilderness-mapping exercises (e.g., Lesslie and meters (m) wide. The nominal spatialaccuracy of all of the Malsen 1995,Aplet et al.2000). Hunting of wildlife no longer NIMAdatasets (table 1) is 2 km. Therefore,we assigneda score suppliesa significantsource of food in the westernworld, but (8) for the directeffect of roads and railwayswithin a 2 km it does in most of the rest of the world. Such hunting,with bufferto ensurethat we capturedthe actuallocation of the its associateddisruption of ecosystems,is of majorconcern road as mapped, although we may be overestimatingthe (Robinsonand Bennett2000), because it could resultin some spatialextent of influence.While we recognizedthat roadin- forestsecosystems being "emptied" by overhunting(Redford fluencedepends on the type of road and the amount of traf- 1992).In tropicalecosystems, access from rivers and the coast fic passingalong it, we were unable to include these factors maybe moreimportant than access from roads (Peres and Ter- in our analysisbecause of the imprecisionof the datasets.The borgh 1995). effect of overlappinginfluence from multiple roads on the Tomeasure the areaaffected by access,we estimatedthe dis- same location was not included. tancea personcould walk in one dayin a difficult-to-traverse We also usedthe independentlyderived NIMA datasets on ecosystem (e.g., moist tropical forests) as 15 km (see, e.g., settlements(represented by points with 2 km buffers) and Wilkie et al. 2000). We acknowledge,however, that this ap- built-up areas.The settlementdata include a largevariety of proachoversimplifies the complexrelationship between hu- settlementtypes, such as camps,buildings, and monuments, man beingsand roads,a relationshipthat varies by ecosystem but the vastmajority of featuresare of unknowntype. We as- type and culturalcontext. All areas within 2 to 15km of a road, signed each point a score of 8. The built-up areas,which majorriver, or coastwere assigned a modesthuman influence typicallyrepresent the largestcities as polygonsin the NIMA score (4) that reflectsintermittent use. Majorrivers were de- database,were assigneda score of 10. fined roughlyas those thatreach the sea and arewide enough

0 - 5 5-10 10-20 20-25 25-35 35-72 ___ Figure1. Thehuman influence index. Scores range from 0 to a maximumof 72;higher scores indicate greater human influence,lower scores less human influence. Analysis indicates that 83% of theland surface is influencedby one or moreof the followingfactors: human population density greater than one person per square kilometer (kin2); agricultural land use; built-upareas or settlements; access within 15 kmof a road,major river, or thecoastline; and nighttimelight bright enough to be detectedby satellite sensor. Almost 98% of theareas where rice, wheat, or maizecan begrown (FAO 2000) is influenced by oneor moreof thesefactors. The analysis excludes Antarctica and mostoceanic islands, and nationalboundaries are not authoritative.

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Afro I Indo' Ne 'ica Malay A sia i<

Tropicaland subtropicalmoist broadleafforests S Boreal forest/taigas Tropicaland subtropicaldry broadleaf forests Floodedgrasslands Tropicaland subtropicalconiferous forests ? Montanegrasslands Temperatebroadleaf and mixed forests Tundra Temperateconiferous forests Mediterraneanscrub Temperategrasslands, savannas, and shrublands Desertsand xeric shrublands Tropicaland subtropicalgrasslands, savannas, Mangroves and shrublands Snow, ice and lakes

Figure2. Biomesand biogeographicrealms that are usedto normalizehuman influence (Olson et al. 2001).Figure usedwith permission from WorldWildlife Fund-United States. to be recordedas polygonsin theNIMA database, although withlights visible less than 40% of nights,and 0 to areaswhere thisdefinition most likely underestimates the extent of access no lightswere visible. alongrivers, since any river wide enough to floata dugoutca- noeis a potentialaccess point. We did not includethe effects Summing the scores. Wesummed the human influence of waterfallsor dams,which limit accessupriver, because scoresfor each of the ninedatasets to createthe human in- datawere inadequate. Thus, access along some waterways may fluenceindex (HII) on the land'ssurface (figure 1). Overall, be overestimated. 83%of theland's surface, and 98% of thearea where it is pos- sibleto growrice, wheat, or maize(FAO 2000), is directlyin- Powerinfrastructure. Many of thedramatic changes in fluencedby humanbeings (HII > 0). Thetheoretical maxi- humaninfluence that are due to landuse change and access mum(72) is reachedin onlyone area, Brownsville, Texas, USA, duringthe 20th century have literally been fueled by fossil en- but thetop 10%of thehighest scoring areas looks like a list ergy.Before the industrial revolution, the human capacity to of theworld's largest cities: New York, Mexico City, Calcutta, modifythe environment was limited .by human and animal Beijing,Durban, Sao Paulo, London, and so on.The minimum musclepower, what McNeill (2000) called the "somatic en- score(0) is foundin largetracts of landin theboreal forests ergyregime." Today one humanbeing with a bulldozercan of Canadaand Russia, in thedesert regions of Africaand Cen- applythe powerof 300 horsesto modifythe environment. tralAustralia, in theArctic tundra, and in theAmazon Basin. Electricalpower provides an excellentestimate of the tech- Themajority of theworld (about 60%), however, lies along nologicaldevelopment of a localarea (Elvidge et al. 1997a) thecontinuum between these two extremes, in areasof mod- andthe use of fossilfuels. In the United States, where electrical eratebut variable human influence. poweris availablenearly everywhere, the lightsvisible at Thehuman influence index, like the GLOBIO methodol- nightfrom satellites provide a proxyof populationdistribu- ogyor thehuman disturbance index, treats the land surface tionand have been correlated with human settlements (Sut- asif it werea blankslate on whichhuman influence is writ- ton et al. 1997,Elvidge et al. 1997b).We assigned a scoreof ten,but we know this is not thecase. The distribution of ma- 10to areasthat have lights visible more than 89% of nights, jorecosystem types and the human histories of differentre- 8 to areaswith lights visible 40% to 88%of nights,4 to areas gionsmodify the biological outcomes of humaninfluence (cf.

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0 U,-. zNj 0

1- 10 10-20 20-30 30-40 40-60 60-80 80 S0-1 0 f 0 0j -100 I NoData

Figure3. Thehuman footprint, a quantitativeevaluation of humaninfluence on theland surface, based on geographicdata describing human population density, landtransformation, access, and electrical power infrastructure, and normalizedto reflectthe continuum of humaninfluence across each terrestrial biome defined withinbiogeographic realms. Further views and additional information are available at "Atlasof theHuman Footprint" Web site, www.wcs.org/humanfootprint. Data areavailable atwww.ciesin.columbia.edu/wild_areas/. National boundaries are not authoritative. Articles

Chapinet al. 2000). For example,an absolutescore of 25 in print to find the "10%wildest areas"in each biome in each the mixed broadleafforests of North Americamight have a realmaround the world (the biomes that fell within the 10% differenteffect, and definitelyhas a differentbiological con- cutoff on the HII are listed in table 2). From this set of text,than the samescore in the rainforests of theAfrican trop- wildest areas,we selectedthe 10 largestcontiguous areasas ics.Because we wereinterested in the interactionbetween hu- the "last of the wild" (figure 5), because such large, intact man influenceand the naturalenvironment, we normalized tracts of relativelyundisturbed ecosystems are particularly human influencescores within large,regionally defined bio- important for conserving biological diversity (Newmark mes, which were differentiatedwithin still larger biogeo- 1987,Grumbine 1990). Some of the areasdefined as the last graphicrealms (e.g., Palearctic, Indo-Malay, Neotropic), in ac- of the wild are well over 100,000 km2 in some biomes; in cordancewith the geographicdefinitions provided by the other biomes, we could not find even 10 areaslarger than World Wildlife Fund-US Conservation Science Program 5 km2. The size of areas depends on the spatial pattern of (figure2; Olson et al. 2001). We assigneda revisedscore of 0 human influence above the 10% level; in most biomes, to the gridcell with minimumHII value in eachbiome in each however,roads or patternsof settlementare sufficientto di- realm and a score of 100 to the cell with maximum value, vide one wild areafrom another.The proportionof arearep- stretching intermediatevalues linearly between these ex- resentedby the last of the wild varies dramaticallyamong tremes (table2, pp. 901, 902). biomes, depending on the statistical distribution of hu- The resultis the human footprint (figure3). The human man influence. Thus, over 67% of the area in the North footprintexpresses as a percentagethe relativehuman influ- American tundra is captured as last of the wild, while the encein everybiome on the land'ssurface. A scoreof 1 in moist 10%wildest areaof the Palearctictropical and subtropical tropicalforests in Africaindicates that that grid cell is part of moist broadleaf forests (all in China) encompasses less the 1%least influenced or "wildest"area in its biome,the same than 0.03% of that biome. as a scoreof 1 in North Americanbroadleaf forest (although In total, we selected 568 last-of-the-wild areas, repre- the absoluteamount of influencein those two placesmay be sentingall biomes in all the realms.A completelisting of the quitedifferent). In fact,there is considerablevariation in lev- last-of-the-wildareas can be found on our Web sites,where els of both overalland mean human influencebetween bio- we characterize each of these wild areas by population mes (table2). Examiningthe humanfootprint on a largerscale density, road density,biome, and region (Atlas of the Hu- showsthe patternsof roads,settlements, land uses, and pop- man Footprint: www.wcs.org/humanfootprint;geographic ulation density for a particulararea-the geographyof hu- datasets: www.ciesin.columbia.edu/wild_areas/). Many of man influence.For example,on a map of the northeastern these wild areascontain existing protectedareas, but many United States(figure 4), urbanizationin the coastalregion is do not, just as some contain roads and settlements, while clearlyvisible, as aremajor highway corridors along the shore others do not. The list of last-of-the-wild areas is a guide and up the HudsonRiver and ConnecticutRiver valleys. Rel- to opportunities for effective conservation-these are the ativelywilder areas appear in the Catskills,Adirondacks, and places where we might conserve the widest range of biodi- GreenMountains. versity with a minimum of conflict. They are not and We propose that this geographyof human influence is should not be interpretedas a self-contained prescription the roughly the inverse of the geographyof natural processes for complete nature conservation. For example, in the and patternsin the region.Given what we know aboutthe ef- Afrotropicalrealm, all 10 of the last-of-the-wildareas in fects of the input factorson nature,we expectthat where hu- tropical and subtropicalmoist broadleafforests biome fall man influenceis highest,ecosystems will be most modified in Central Africa (figure 6). Other parts of the African are and species under the most pressurefrom human activity. moist broadleafforests, in West Africa or Madagascar, Wherethe humanfootprint values are lower, we expectmore also important for conservation, but their conservation intact and functionalnatural communities. The exact con- takes place in the context of higher levels of human influ- sequencesof human influencein anygiven location are com- ence. human to de- plicated,however, and dependon the historyof the place,the Thereare many ways of using the footprint typesof the currentinfluence, and the partsof naturethat we fine areasof interestfor conservation,depending on the de- areconcerned with (Redfordand Richter1999). We know that siredconservation objectives. Although area size is often im- some aspectsof naturesurvive, and even thrive,in the midst portant, for some applications,it may be useful to identify of our cities,while even in the wildest places,human influ- the wildest areas in each biome, regardlessof size, for ex- ence frequentlyhas reducedor is reducingnatural values. Yet ample, the wildest 1%of areas ("seedsof wildness"). Oth- it is in thesewildest places that the greatestfreedom and op- ers might use the human footprint to find the areasfacing portunityto conservethe full rangeof naturestill exists. the greatestthreat, although those areasmay alreadyhave lost much of what made them biologicallydistinct. Whether Findingthe last of the wild defining "seeds"or the "last of the wild" or measuring It follows from mapping the human footprint that it is threats, the human footprint provides a flexible tool for also possible to map the least influenced, or "wildest,'ar- identifying areas at different points along the human in- eas in each biome. We searchedthrough the human foot- fluence continuum.

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for instance-that also tend to cloud our view of theextent and severity of humaninfluence. More- 46 I A over,there are simplymistakes in these global 3. datasets:Chunks of roadsare missing, rivers are , AdirLondacks ho more(or less)accessible than they appear, population densitiesvary unusually across national boundaries,agricultural areas are inaccurately mapped,and so on.Because of theseproblems, the qr Mo_tains, readershould take care in drawingconclusions fromthe human footprint for local areas, while not losingsight of theglobal pattern and its significance. Finally,our ability to interpretpatterns of human influencethat arebased on geographicfeatures is constrainedby the complexitiesof human interactions with natureand our limited understand- ingof them.For example, we know that the distance peopletravel from roads and riversis less in the temperatezone thanin the tropicsand thatper capitaconsumption in the developedworld results in impactsnot just locally,but acrossthe New York City globe.Yet we don'tknow enough about either of S50 0 50Km theseto assessthem globally in a consistentman- ner.We make no strongclaims about any of our EI] 0- 1 [DLI 10 L 0 -20 0120-30 =130-40 40-60 Mn60 80 Mn80-100 coding systems,except to suggestthat under- how measures 4. The "human in the northeasternUnited States. standing surrogate quantitatively Figure footprint" translateinto impacts,or how they shouldbe weightedagainst each other, is an importantarea Interpretingthe human footprint of research.As Rojstaczerand colleagues(2002) recently and t-helast of the wild pointedout, our understanding of theglobal environmental The measuresof humaninfluence used in this studyhave impactof humanbeings is in itsinfancy, and therefore all mea- manyshortcomings that the reader needs to be cognizantof suresshould be consideredcautiously. However, we alsoneed when interpretingthe results.First, it is importantto ac- to be awarethat, though we don'tunderstand everything knowledgethat although population density, land use changes, abouthuman influence on nature,we understand enough to accessto roadsand rivers, and lights visible at night,for ex- be concerned. ample,have been and continue to bedrivers of thehuman im- In the near term,one avenuefor refiningour under- pacton nature,drivers are not inevitably harmful. The human standingof thehuman footprint is to studyhuman influence footprintdoes not measureimpact per se; rather, it suggests at regional,national, and local levels. By restricting the area areasof influencewhere humans have more or lessrespon- of interest,scientists can use more accurateand detailed sibilityfor biologicaloutcomes. Thoughtful practices and datasets;modify the codingfunctions to respectregional, carefulplanning can mitigate the human influence on ecosys- cultural,and biological differences; and define normalization tems,as conservationbiology and restoration ecology have criteriain waysappropriate for local conservation and man- shown(Stevens 1995). In fact, one of themore interesting uses agementgoals. The methods of definingthe human footprint of thehuman footprint may be to identifyplaces where sen- andthe last of thewild are general and can be appliedlocally sitivespecies thrive despite high levels of humaninfluence and aswell as globallyto understandwhere nature may be most determinewhich human behaviors enable coexistence. pressedand how that pressure may be released. Second,even with modernmapping tools, tremendous effortand expense are required to developthe input datasets Implicationsfor conservationpractice usedhere-in fact,many of thesedata were developed for the Thehuman footprint and last of thewild should give us all firsttime only in the 1990sand only through large, govern- pauseas we consider our relationship to natureand the types ment-fundedprojects. As a result,the datasets tend to lagbe- of conservationefforts that we mightpursue in the21st cen- hindthe patternsthey seek to depict:growing populations, tury.This analysisindicates that conservationtoday pro- newroad construction, and clearing of newland for human ceedsin the contextof dramatic,and in someplaces over- uses.Similarly, the methodsused to developthe datasets whelming,human influence. For most ecosystems, the greatest haveshortcomings that result in imperfectrepresentations- near-termthreats are from direct human activities like those underestimatesof the amount of grazinglands or insufficient measuredby the human footprint: transformation of land for detailabout the kinds of settlementsor the locations of roads, agricultureand for suburban and urban development, direct

898 BioScience - October2002 / Vol.52 No. 10 C0 Tropicaland subtropical moist broadleaf forests Tropicaland subtropical grasslands, savannas, and shrublands Tundra Tropicaland subtropical dry broadleaf forests Temperategrasslands, savannas, and shrublands Borealforest/taigas Tropicaland subtropical coniferous forests Floodedgrasslands Desertsand xeric shrublands Temperatebroadleaf and mixed forests i Montanegrasslands Mangroves coniferousforests h, Temperate Mediterraneanscrub Snow,ice andlakes

Figure5. The"last of thewild," showing the ten largest"10% wildest cutoff" areas by biome and realmon theland surface. The full list is availableat C,,o www.wcs.org/humanfootprint;geographic data is availableatwww.ciesin.columbia.edu/wild_areas/.

Co ,r Articles4

Cameroon C9

Republic of Congo DRC 200 0 200K

Angola 200 0 200 Km

[ Tropicaland subtropical moist W Tropicaland subtropical grasslands, 100 40-6060-80 80-100 broadleafforests savannas,and shrublands Do0-1 O-io-10 -220[20.30[-]3040 Tropicaland subtropical dry [ Floodedgrasslands broadleafforests Figure6. Thehuman footprint and thelast of thewild in CentralAfrica.

effects of roads and indirecteffects of the accessthat roads afford, a power infrastructurethat not only pollutes and modifies the climate but also enables extensiveland transformation and road construction, and, ultimately,greater Mokabi Forestry of resources an human Dzanda-Sangha consumption by increasing popula- Special Reserven . tion billionnow (C.A.R) (6 and estimatedto be 8 billionby 2020;UN R v •Coneson PopulationDivision 1993).Although not a completecatalog NdokiNational Park (C.A.R) of conservationchallenges, the human footprint provides .. an importantbasis for understandingconservation efforts on •----,v•~ ...Concs..on.. ForetForestry a global scale. KabLoungoudou The human footprint permits us to organize conservation effortsalong an axis of human influence.The kinds of conservationactions that are and the of con- possible types Concession servationtargets that are availablewill often depend on the S intensity of human influence. Where human influence is --I/ i ? . high, conservationwill be limited in terms of the kinds and .k-• PokolaForest Concession numbersof conservationtargets available (for example,elk, cougar,and wolves have alreadybeen extirpatedfrom the of northeast United States). Conservationpractice will typi- Republic Congo cally focus on restoring ecosystems, reconnecting habitat fragments, and reintroducing extirpated species in land- 25 0 25 50 Km scapescumulatively influenced by roads,human land uses, and high human populationdensity. Where human influenceis Primaryroads Trinationalprotected areas low (e.g., last-of-the-wildareas), a wider rangeof conserva- Secondaryroads L Congoforesty units tion targetsand actionsmay be possible.These targets and actions could include creatingand managingareas of limited Figure 7. The Ndoki-LikoualaLandscape Conservation humanuse (i.e., protectedareas) and workingwith relatively Area in the trinational region of the Republicof Congo, smallerpopulations of local people and their institutionsto Cameroon,and CentralAfrican Republic (C.A.R.). Pri- moderate the outcomes of human influence, while main- mary roads, like those that are used to map the human taining existing conservationtargets, as in CentralAfrica. footprint, are shown as a thick line. Most conservation Intermediatelevels of human influencelend themselvesto threatsin the region are a result of accessalong sec- mixed strategiesof preservation,conservation, and restora- ondary roads, however,which are shown as thin lines tion, which are most efficientlyplanned at landscapeor re- and are not currentlycaptured by global datasets. gional scales(Noss 1983,Sanderson et al. 2002). The cumu- Roads data are courtesyof FredericGlannaz (2001), lative nature of the human footprint means that, in areas CongoleseIndustrielle des Bois, northern Congo.

900 BioScience * October2002 / Vol.52 No. 10 Table2. Summaryof thehuman influence index scores by realmand biome.

Area Standard 10%wildest Realm Biome (km2) Minimum Maximum Mean deviation cutoff

Afro-tropical Tropicaland subtropicalmoist broadleafforests 3,487,709 0 60 12.42 6.47 6 Afro-tropical Tropicaland subtropicaldry broadleafforests 189,751 1 37 11.11 5.57 5 Afro-tropical Tropicaland subtropicalgrasslands, savannas, and shrublands 13,983,895 0 60 11.81 5.95 6 Afro-tropical Temperategrasslands, savannas, and shrublands 25,615 1 36 13.12 5.14 5 Afro-tropical Floodedgrasslands 458,499 0 54 11.59 5.41 5 Afro-tropical Montanegrasslands 863,265 0 56 16.20 5.37 6 Afro-tropical Mediterraneanscrub 93,732 0 60 15.85 7.86 6 Afro-tropical Deserts and xeric shrublands 2,398,645 0 56 9.07 5.87 6 Afro-tropical Mangroves 74,585 2 60 20.10 6.30 8

Australia-AsiaPacific Tropicaland subtropicalmoist broadleafforests 1,156,438 0 50 10.88 5.83 5 Australia-AsiaPacific Tropicaland subtropicaldry broadleafforests 87,813 4 44 18.19 5.07 8 Australia-AsiaPacific Temperatebroadleaf and mixed forest 733,539 0 64 12.89 7.81 6 Australia-AsiaPacific Tropicaland subtropicalgrasslands, savannas, and shrublands 2,164,911 0 54 3.71 3.85 5 Australia-AsiaPacific Temperategrasslands, savannas, and shrublands 629,594 0 50 6.32 6.19 5 Australia-AsiaPacific Montanegrasslands 67,639 0 32 7.03 3.56 3 Australia-AsiaPacific Mediterraneanscrub 803,405 0 64 9.37 6.77 6 Australia-AsiaPacific Deserts and xeric shrublands 3,572,106 0 64 2.40 3.21 5 Australia-AsiaPacific Mangroves 26,592 2 32 9.22 3.23 5

Indo-Malay Tropicaland subtropicalmoist broadleafforests 5,395,598 0 60 17.60 7.23 6 Indo-Malay Tropicaland subtropicaldry broadleafforests 1,528,071 2 58 19.89 5.99 8 Indo-Malay Tropicaland subtropicalconiferous forests 96,028 5 50 17.65 4.84 10 Indo-Malay Temperatebroadleaf and mixed forest 148,763 0 46 13.63 6.67 5 Indo-Malay Temperateconiferous forests 64,075 0 46 15.47 7.67 5 Indo-Malay Tropicaland subtropicalgrasslands, savannas, and shrublands 34,681 14 52 22.54 5.84 18 Indo-Malay Floodedgrasslands 27,855 0 48 13.60 6.72 5 Indo-Malay Montanegrasslands 4,337 4 34 17.43 4.90 7 Indo-Malay Deserts and xeric shrublands 1,085,536 4 56 21.25 6.12 9 0 Indo-Malay Mangroves 114,232 4 54 21.11 5.94 9

0 Neotropical Tropicaland subtropicalmoist broadleafforests 9,226,889 0 64 8.04 7.74 6 Neotropical Tropicaland subtropicaldry broadleafforests 1,779,363 0 60 12.63 8.08 6 Neotropical Tropicaland subtropicalconiferous forests 321,948 1 56 17.24 5.48 7 Neotropical Temperatebroadleaf and mixed forest 395,543 0 56 9.87 6.82 6 Neotropical Tropicaland subtropicalgrasslands, savannas, and shrublands 3,410,947 0 64 10.66 6.86 6 oz and shrublands 64 6 r? Neotropical Temperategrasslands, savannas, 1,636,497 0 11.22 7.80 Neotropical Floodedgrasslands 323,357 0 64 11.72 7.86 6 Neotropical Montanegrasslands 811,134 0 46 8.47 5.44 5 0 64 C, Neotropical Mediterraneanscrub 148,516 17.91 8.17 6 Deserts and xeric shrublands 1,168,615 0 64 15.96 6.12 6 r? Neotropical 121,156 1 62 0 Neotropical Mangroves 19.63 7.89 7 t•

"NINr* fAjmS Articles

with intermediatelevels of influence,often one factor of influence(e.g., roadsor land use) may pre- dominateand thus conservationmeasures should o be targeted toward that factor. It is possible to Q0l rO I LOJ0 r'• 0Q0 Q0 0 I (01,- (0L-. LO l (.0O( imagine conservationstrategies mapped out for - E different parts of the human influence contin- "-I '-I 0 0m0mm r Lw0 01N. m0 (0 00m Q' (0 r- 0 CiN 0 %to Nt"m O0rwr r 0 mL0 0mo0 m O 1 .0, 01N uum, based on the hypothesisthat if human in- fluenceincreases as it hasfor the last 100years, conservation strategieswill increasinglyshift from preservationto restoration-with the concomitant ,•1 00 o) 00 - 00 LO 00 C) LOO C q q C00) C) CY0 •) •O r-.- increasesin cost, time, and difficulty-much as 0 "- C "- CNL O 00 r"- 00 0) LO • O 0) ,. ,1, NO1T, (D m0 00 they alreadyhave in the United States and Eu- rope. Meanwhile,we needto be carefulnot to readthe of the human and the last of the E maps footprint E is no doubt that ql 0 w wo0

902 BioScience - October2002 / Vol.52 No. 10 Articles rather than against, nature is to acknowledgethe human ProspectHill Foundation,and softwaresupport from ESRI footprint. (EnvironmentalSystems Research Institute) Conservation Part of that acknowledgmentis a commitment to con- Program. servingthe lastof the wild--those few places,in allthe biomes aroundthe globe,that arerelatively less influencedby human Referencescited beings-before they aregone. In largepart, this conservation ApletG, Thomson J,Wilbert M. 2000. Indicators ofwildness: Using attrib- effortwill enforcedlimits on humanuses of nat- utesof the land to assess the context of wilderness. InCole DN, McCool requirelegal, eds. WildernessScience in a Timeof uralareas and the and to well in SF, Proceedings: Change.Ogden knowledge capacity manage (UT):USDA Forest Service, Rocky Mountain Research Station. Proc. all of the world'sbiomes. 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