Biological Conservation xxx (2014) xxx–xxx

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Biological Conservation

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Impacts of civil conflict on primary forest habitat in northern DemocraticRepublic of the Congo, 1990–2010

http://dx.doi.org/10.1016/j.biocon.2013.12.0330006-3207/� 2014 Published by Elsevier Ltd.

⇑ Corresponding authors. Tel.: +1 301 405 8895 (J. Nackoney). Tel.: +81 0568 630537 (T. Furuichi).

E-mail addresses: jnackone@umd.edu (J. Nackoney), furuichi@pri.kyoto-u.ac.jp(T. Furuichi).

Please cite this article in press as: Nackoney, J., et al. Impacts of civil conflict on primary forest habitat in northern Democratic Republic of the Congo2010. Biol. Conserv. (2014), http://dx.doi.org/10.1016/j.biocon.2013.12.033

Janet Nackoney a,⇑, Giuseppe Molinario a, Peter Potapov a, Svetlana Turubanova a, Matthew C. Hansen a,b,Takeshi Furuichi b,⇑a Department of Geographical Sciences, University of Maryland, 2181 LeFrak Hall, College Park, MD 20742, USAb Primate Research Institute, Kyoto University, Ecology and Social Behavior, Inuyama, Aichi 484-8506, Japan

a r t i c l e i n f o

Article history:Received 6 August 2013Received in revised form 18 December 2013Accepted 23 December 2013Available online xxxx

Keywords:Civil conflictWarDRCCentral AfricaForest monitoringRemote sensingDeforestation

a b s t r a c t

War and civil conflict have been shown to contribute directly to increased wildlife poaching and environ-mental degradation, especially in developing countries. The Democratic Republic of Congo (DRC) sufferedheightened political instability that intensified during its first (1996–1997) and second (1998–2003) civilwars. Ground-based observations reported severe impacts on wildlife from increased human reliance onbushmeat as well as evidence of human populations moving deeper into interior forests to escape con-flict. Both were observed in the study area comprised of forests in and around Luo Scientific Reservelocated in northern DRC, where studies on wild bonobos (Pan paniscus) have been conducted since1973. Using Landsat TM and ETM + satellite imagery, we employed an automated classification tree algo-rithm developed specifically for Central Africa to monitor wartime patterns of human migration andresource use in the study area. We analyzed and compared primary forest loss and degradation ratesacross two decades (1990–2010). Annual rates of primary forest loss occurring during the 1990–2000decade were over double the rates of the mainly post-war 2000–2010 decade, indicating higher humanpressure on the forests during wartime. Maps and analyses of peripheral forests occurring around theedges of forest clearings illustrated an increased prevalence of small, scattered clearings during thewar. We also found evidence showing there was likely less human pressure on interior forests afterthe wars ended. We demonstrate the utility of satellite-based remote sensing techniques for monitoringhuman access in interior forests and examining wartime links to observed declines in wildlife.

� 2014 Published by Elsevier Ltd.

1. Introduction and endangered (IUCN, 2013) bonobo (P. pansiscus). War and civil

Between 1996 and 2003, the Democratic Republic of Congo(DRC) experienced two devastating wars that collapsed its formaleconomy and caused increased social unrest and poverty. Humantolls were enormous; displaced persons numbered in the millionsand fatalities exceeded five million in just the second Congo waralone (Bavier, 2008). The largest country in Central Africa, theDRC comprises about half the area of the Congo Basin rainforest(Wolfire et al., 1998). It serves as critical habitat for a wealth of fau-nal species including large mammals of conservation concern likethe forest elephant (Loxodonta africana) and three types of greatapes: the endangered (IUCN, 2013) eastern chimpanzee (Pantroglodytes schweinfurthii), the endemic and endangered (IUCN,2013) Grauer’s gorilla (Gorilla beringei grauer), and the endemic

conflict have been shown to contribute directly to increased wild-life poaching and environmental degradation (Westing, 1992;Blom et al., 2000; Dudley et al., 2002; Yamagiwa, 2003). In devel-oping countries such as DRC, much of this is caused by displace-ment of human populations who seek refuge in nearby forestedareas and are forced to rely more heavily on their natural sur-roundings for food and shelter (Dudley et al., 2002; Hanson et al.,2009). Increased access to formerly remote forested areas and localproliferation of arms during wartime often contribute to a rise inwildlife poaching, especially when lawlessness and poverty areprevalent and there is a disruption in normal village trade (Dudleyet al., 2002; Draulans and Van Krunkelsven, 2002; McNeely, 2003).

1.1. Environmental impacts of civil conflict in DRC

Wildlife poaching was especially severe during the DRC wars.De Merode and Cowlishaw (2006) found that the sale of protectedspecies as bushmeat in urban markets located near their field sitein Garamba National Park in northeastern DRC increased by 23%

, 1990–

2 J. Nackoney et al. / Biological Conservation xxx (2014) xxx–xxx

during the war, with observed increases in sales of larger speciessuch as elephant, hippo, and buffalo. Another study found that for-est elephant densities in the Okapi Faunal Reserve (located in east-ern DRC) decreased by half during the wars, from 0.47/km2 to 0.24/km2 due to increased poaching (Beyers et al., 2011). Yamagiwa(2003) found that half of the gorilla population in the Kahuzi-BiegaNational Park, also located in eastern DRC, was killed for bushmeatduring the war. Bonobos were also greatly affected during the DRCwars. About one-third of the wars’ main frontline, where most ofthe fighting occurred, cut through the center of the bonobo range(Draulans and Van Krunkelsven, 2002). Increased incidences ofbonobo poaching were reported in Vogel (2000), Reinartz andInogwabini (2001), and Furuichi et al. (2012), among others.Draulans and Van Krunkelsven (2002) observed soldiers possessinglive monkeys, parrots, baby gorillas and bonobos for the animal pettrade, increased wildlife poaching to feed refugees and militiatroops, and illegal and unsustainable logging.

Internal displacement of human populations in DRC as a resultof the conflicts that began in the 1990s continues to be an issue ofconcern today (Zeender and Rothing, 2010). Internally displacedpeople peaked at 3.4 million toward the end of the second war in2003 (Faubert, 2006). Although many are now returning to theirnatal villages, around 2.7 million are still displaced, though themajority of this is due to continued conflict in eastern DRC (OCHA,2012). During the wars, Draulans and Van Krunkelsven (2002) ob-served human populations taking refuge in interior forests to es-cape conflict with soldiers. This particular type of humandisplacement can put substantial pressure on surrounding naturalenvironments, not only because of increased instances of huntingand poaching as explained above, but also due to forest degrada-tion resulting from the creation of small-scale agricultural clear-ings and temporary camps. The effects of clearings on speciescomposition and forest structure, and their contribution to alteredhabitat around forest edges, known as edge influence, have beenwidely studied (Chen et al., 1995; Laurance et al., 2002; Harperet al., 2005; Laurance et al., 2007). Edge influences can cause mi-cro-climatic differences that lead to drier forests (Chen et al.,1992), reduced soil moisture (Denslow, 1987) and contribute tooverall degradation of interior forests (Wickham et al., 2007). Re-source extraction by humans increase forest edges and make pre-viously undisturbed forests more vulnerable to hunting(Laurance et al., 2000; Peres 2001).

1.2. Forest monitoring and objective

Satellite image interpretation has been used as a timely, objec-tive, cost effective, and verifiable means to monitor humanitarianviolations (Bjørn, 2000; Prins, 2008; Bromley, 2010), presence ofrefugee camps (Lang et al., 2010; Hagenlocher et al., 2012) andenvironmental degradation (Lodhi et al., 1998; Suthakar and Bui,2008; Witmer, 2008; Stevens et al., 2011; Gorsevski et al., 2012)in remote locations during wartime. Witmer (2008) and Gorsevskiet al. (2012) discussed the use of satellite imagery to capture boththe direct (i.e., physical landscape) impacts of civil conflict as wellas the indirect impacts that may result in changes in land usecaused by displaced human populations and their associated envi-ronmental consequences, two components covered by thisresearch.

We used the Luo Scientific Reserve and adjacent Iyondji Com-munity Bonobo Reserve (both located in Equateur Province innorthern DRC) as a case study to investigate both the direct im-pacts of DRC’s wars on land cover and land use, and indirect im-pacts of the wars on primary forest habitats for species such asthe bonobo, a flagship species for this particular geographic areaand that depends on large tracts of undisturbed forest. To do this,we employed a twenty-year spatio-temporal analysis (1990–2010)

Please cite this article in press as: Nackoney, J., et al. Impacts of civil conflict on p2010. Biol. Conserv. (2014), http://dx.doi.org/10.1016/j.biocon.2013.12.033

of land use and land cover change using satellite image interpreta-tion. We quantified and mapped both the rate of primary forestloss and the increase in peripheral (edge) forests that occurredboth during war and non-war periods in order to investigate thedegree that civil conflict affected human migration and resourceuse patterns. We hypothesized that the wars increased deforesta-tion and promoted greater human access to remote forested areasin this region, patterns that were likely consistent for other for-ested regions of DRC. The research will contribute to an increasedunderstanding of the effects of DRC’s wars on deforestation anddegradation of core primary forest habitats as detected and moni-tored by satellite.

2. Methods

2.1. Study area

The study took place in Luo Scientific Reserve (referred hereaf-ter as ‘‘Luo SR’’) and the Iyondji Community Bonobo Reserve (re-ferred hereafter as ‘‘ICBR’’) located in Equateur Province innorthern DRC (centered at 0�020N, 22�350E) (Fig. 1). Approximately81% of the study area consists of both primary and old secondarylowland rainforest, while 17% is comprised of swamp forest. Thetotal area of the study site is 1510 km2 (Luo SR extends approxi-mately 480 km2 to the northwest, while ICBR extends approxi-mately 1030 km2 to the southeast). The northern part of Luo SRcontains a roughly 21 km2 stretch of agricultural complexes andyoung secondary forest (almost 2% of the study area) surroundinga road, shown in Fig. 1. This area contains about six homesteadsand supports a local population of approximately 6500 people.Small hunting camps are scattered in the southern part of thereserve.

Luo SR was officially recognized in 1992 by the DRC Ministry ofthe Environment. A management plan allows local communities tolive within its boundary and abide by certain land use policies. Themembers of these communities are allowed to hunt animals otherthan primates using traditional means, but they are not allowed tohunt primates or hunt or trap other animals using guns, poisonarrows, or metallic snares (Kano et al., 1996; Idani et al., 2008;Furuichi et al., 2012). The management plan also disallows thecreation of new agricultural fields for commercial products in theprimary forest area, although the re-use of fields and the creationof new fields for cassava or other subsistence products is allowedwithin 1 km from the road in the north. Since the formal creationof the reserve and its management plan, the bonobo research teamand Centre de Recherche en Ecologie et Forestrie (CREF) of the DRCMinistry of Scientific Research have been supporting local commu-nity development, including provision of support for local schoolsand medical services, in order to compensate for the limitationsregarding forest use. ICBR was recognized as a Community Reserveby the DRC Government in April 2012 (Sakamaki et al., 2012;Dupain et al., 2013). It was therefore not under any sort of protec-tion or management plan during the course of the dates studied inthis research. Because it has been so recently established, acommunity-based natural resources management plan, which willregulate usage of the ICBR forests, is still being formalized.

2.2. Period of civil conflict in Luo SR and ICBR

A distinctive quality of Luo SR is that it can be considered tocontain several of the longest and most consistently studied bono-bo populations in the world (bonobo populations living there havebeen studied and monitored since 1973). The study area has there-fore produced a wealth of historical data on bonobos, including re-search on the impacts of DRC’s war on the populations living

rimary forest habitat in northern Democratic Republic of the Congo, 1990–

Fig. 1. The study area consists of Luo Scientific Reserve and the Iyondji Community Bonobo Reserve. Data source: OSFAC, 2010; Bwangoy et al., 2010.

J. Nackoney et al. / Biological Conservation xxx (2014) xxx–xxx 3

within Luo SR. The environmental consequences of the warsaround Luo SR did not become apparent until bonobo researchersreturned to the area in 2002 at the end of the second war (theyhad been forced to leave the site between 1991 and 1994, andagain between 1996 and 2002). The researchers discovered thatbonobo losses had been substantial; from 1991 to 2005 threegroups of bonobos had disappeared altogether, and the numberof bonobos in the study area had declined by over half (Hashimotoet al., 2008) (Fig. 2). They also observed increased instances ofbonobos injured by snares, as well as increased prevalence of hunt-ing camps and temporary huts (located particularly within coreforests in what is now ICBR) where human populations lived andcleared surrounding forests to grow small-scale cassava crops. Lo-cal people reported that they had been forced to rely more heavilyon bushmeat during the war because of the collapse of transporta-tion networks for market access (Sakamaki et al., 2012), and manywere asked to hunt bonobos for soldiers (Furuichi et al., 2012).Though not confirmed, there is a possibility that even local peoplehunted bonobos for food or as a source of income during the war(Furuichi et al., 2012), despite local taboos against killing them

Fig. 2. Bonobo populations in the study area suffered substantial losses duringDRC’s wars.

Please cite this article in press as: Nackoney, J., et al. Impacts of civil conflict on p2010. Biol. Conserv. (2014), http://dx.doi.org/10.1016/j.biocon.2013.12.033

(Lingomo and Kimura, 2009). Even today, bonobo researchers sta-tioned in ICBR report that human populations that moved to re-mote forest locations during wartime are still living therepermanently, and some of the children growing up in scatteredsmall settlements have never visited the villages located alongthe roads where the schools and medical facilities are located(Sakamaki et al., 2012).

Three groups of the studied bonobos, Sema, Bokela, and Kofola,disappeared completely during the war (Fig. 2). The Plantation, E2and E1 groups fared better, although their numbers decreased. Thethree groups that survived the wars ranged closer to the biologicalresearch station and to the center of the nearby village (Wamba),home to a community that had benefited from the presence ofthe researchers and who advocated for the bonobos’ protection,even though the research station was occupied by soldiers duringparts of the wars (Furuichi et al., 2012). The home range of oneof the three groups that disappeared was located farther north ofLuo SR, close to a village that was less receptive to the idea of pro-tecting the bonobos, and the remaining two groups that disap-peared ranged further in the remote forests east of Luo SR, wheresmall temporary camps and settlements were found. It has beenconcluded that all three groups likely disappeared due to poaching.

2.3. Satellite-based change detection

We used data derived from 30-m Landsat TM/ETM+ satelliteimagery to analyze and map changes in primary forest across thestudy area for the years 1990, 2000, 2005 and 2010. The four years

Fig. 3. Landsat images were analyzed for 1990, 2000, 2005 and 2010. Civil conflictin the study area and DRC’s two wars lasted from 1991 until 2003.

rimary forest habitat in northern Democratic Republic of the Congo, 1990–

4 J. Nackoney et al. / Biological Conservation xxx (2014) xxx–xxx

were selected to correspond as closely as possible to DRC’s historyof civil conflict and war since 1990 and include a post-war periodsince 2003 (Fig. 3). Ideally, we would have liked to include an anal-ysis for circa 1995, but sufficient cloud-free imagery were notavailable.

In total, 23 TM and 112 ETM+ images were selected across thestudy site for the four dates mentioned. We converted the imagesto at-sensor reflectance and employed a normalization algorithmthat used reference surface reflectance derived from multi-yearMODIS sensor observations (Hansen et al., 2008). The radiometricnormalization algorithm reduced reflectance differences betweenimage dates caused by variations in atmospheric conditions andsurface anisotropy. We also identified cloud- and cloud shadow-contaminated pixels using a set of classification models and re-moved them from the data pool. To create time-sequential imagecomposites, we selected the median reflectance value per bandfrom five cloud- and cloud shadow-free observations closest tothe middle date (July 1) of the studied years on a per-pixel basis(Potapov et al., 2012).

Next, we employed a supervised bagged classification tree mod-el (Breiman, 1996; Potapov et al., 2012) to map primary forests at30-m resolution for circa year 1990. We defined two classes: a pri-mary forest class (consisting of mature forest with greater than60% canopy cover and including primary and old secondary forest),and a combined non-forest and young secondary forest class (con-sisting of villages, agricultural lands and secondary forestregrowth). Hereafter, we will refer to this latter class as the‘‘non-primary’’ class. The supervised classification relied on manu-ally selected training sites where primary forests were visuallyinterpreted by experts using all available external informationsources (Potapov et al., 2012). We next mapped primary forest cov-er loss that occurred within the 1990 primary forest mask for1990–2000, 2000–2005, and 2005–2010. A bagged classificationtree model was trained and applied to map change for each timeinterval.

2.4. Deforestation and fragmentation spatio-temporal analyses

We used a GIS to calculate the area of primary forest for eachtime period as well as the annual rate of primary forest loss be-tween time intervals (1990–2000, 2000–2005 and 2005–2010)for Luo SR and ICBR separately. We extracted the 2010 extent ofthe large stretch of agricultural complexes located in northernLuo SR and removed them from our core forest analysis (we con-sidered all primary forest falling within the study area but locatedoutside of this agricultural complex as core forest). We then com-pared 1990–2000 and 2000–2010 annualized rates of primary for-est loss taking place within both the core forest and theagricultural complex in order to better understand whether coreprimary forest areas were more severely affected by deforestationduring the conflict and war periods than the agricultural complex,and if so, to what extent.

Finally, we conducted an analysis of forest fragmentation usingthe Landscape Fragmentation Tool (LFT) version 2.0 (Vogt et al.,2007), developed by the Center for Land Use Education andResearch (CLEAR) at the University of Connecticut. LFT is aspatially-explicit tool used as an extension to ESRI ArcGIS softwarethat uses four metrics to map forest fragmentation, identifyinglocations of forest patches, edge forests, perforated forests, andcore forests (the core forests are further subdivided into threecategories of small (<250 acres), medium (250–500 acres) andlarge size (>500 acres). The tool requires a parameter to definethe edge width that describes the distance over which a forestdisturbance can degrade the core forest. Many studies use 100 m(Laurance and Yensen, 1991; Broadbent et al., 2008); we chose90 m because it corresponded most closely with our 30 m pixel

Please cite this article in press as: Nackoney, J., et al. Impacts of civil conflict on p2010. Biol. Conserv. (2014), http://dx.doi.org/10.1016/j.biocon.2013.12.033

resolution (i.e., a 3-pixel depth). We ran the tool for a larger areacontaining the entire study site (thus avoiding extraneous edge ef-fects caused by the edge of the study area) and produced a sequen-tial series of forest fragmentation maps over time.

3. Results

3.1. Evaluation of forest loss

An overall increase in small, isolated clearings over time wasclearly visible when comparing sequential maps of the study area(Fig. 4 shows these results for a portion of ICBR). The area of pri-mary forest loss in core forest areas increased continuously in bothLuo SR and ICBR across all four years studied (Table 1). Percent areaof the non-primary class within each reserve was actually quitesmall for each interval studied (generally less than 1% of the totalarea of each reserve), reflecting the small-scale nature of the forestclearings that occurred during the course of the two decades.While percent area of the non-primary class was similar for bothLuo SR and ICBR in 1990, this changed dramatically between1990 and 2000 as percent area of the non-primary class for ICBRrose more quickly than for Luo SR and continued in this fashionover the course of the next decade, averaging about 60% higherat each time step.

Annual increase in the non-primary class area for both Luo SRand ICBR during the 1990–2000 decade was about 67 ha/year,while during the 2000–2010 decade it was only about 30 ha/year.Looking more closely at the 2000–2010 decade, both Luo SR andICBR exhibited a slightly higher annual increase in the non-primaryclass area during the first half of the decade (about 33 ha/year,computed over five years), compared to the second half (about27 ha/year, computed over five years).

Annual increase in the area of the non-primary class inside coreforests between 1990 and 2000 was over five times higher thanthat occurring in the agricultural complex during the same timeperiod (Table 2). While annual increase of the non-primary classinside core forests was over twice as high during the 1990–2000decade as compared to the 2000–2010 decade, annual increase ofthe non-primary class inside the agricultural complex was greaterduring the 2000–2010 decade. In fact, the agricultural complexexperienced a slightly higher annual increase in the area of thenon-primary class during the second half of the 2000–2010 decadecompared to the first (18.6 ha/year for 2000–2005 and 22.4 ha/yearfor 2005–2010, both figures computed over 5 years). Meanwhile,this number decreased in the core forests during 2005–2010.

3.2. Evaluation of forest fragmentation metrics

Results of the fragmentation analysis showed that the studyarea contained only one category of core forest, that being the larg-est category defined by the LFT tool as greater than 500 acres(roughly 2 km2). The LFT tool classified forests located within90 m of small forest clearings as perforated forests. Edge forestswere defined as those surrounding large forest clearings (Vogtet al., 2007). We generated maps that combined both types offorest into one category of peripheral forest for better visual clarityat this scale (Fig. 5).

During 1990–2000, annual increase in peripheral forests was164 ha/year compared to only 75 ha/year during 2000–2010(Table 3). Consistent with the primary forest loss analysis, annualincreases in peripheral forests were higher overall in ICBR thanin Luo SR. Peripheral forests increased by approximately 2382 habetween 1990 and 2010, with 1656 ha (70%) consisting ofperforated forests and 726 ha (30%) consisting of edge forests,showing the prevalence of smaller clearings in the study area.

rimary forest habitat in northern Democratic Republic of the Congo, 1990–

Fig. 4. Sequential subset maps for a small part of ICBR across all four time periods show an increase in small, isolated clearings over time.

Table 1Area statistics for the non-primary class for 1990, 2000, 2005 and 2010 for both Luo SR and ICBR.

Reserve name Total area (ha) Non-primary class area (ha) Percent non-primary class area (%) Annual increase in non-primary class (ha/yr)

1990 2000 2005 2010 1990 2000 2005 2010 1990–2000 2000–2010 2000–2005 2005–2010

Luo SR 46127.2 104.7 230.9 259.6 283.6 0.23 0.50 0.56 0.61 12.6 5.3 5.7 4.8ICBR 103440.7 256.1 803.5 940.7 1051.0 0.25 0.78 0.91 1.02 54.7 24.8 27.4 22.1

Total 149567.9 360.8 1034.4 1200.2 1334.6 0.24 0.69 0.80 0.89 67.4 30.0 33.2 26.9

Table 2Area statistics for the non-primary class for the time periods under study for both core forest areas and the agricultural complex, which is located in northern Luo SR.

Geographic area Non-primary class area (ha) Annual increase in non-primary class (ha/yr)

1990 2000 2005 2010 1990–2000 2000–2010 2000–2005 2005–2010

Agricultural complex 1804.0 1925.0 2018.0 2130.0 12.1 20.5 18.6 22.4Core forest 360.8 1034.4 1200.2 1334.6 67.4 30.0 33.2 26.9

J. Nackoney et al. / Biological Conservation xxx (2014) xxx–xxx 5

However, the magnitude of the increase in edge forests during1990–2000 (calculated as the difference in edge forest surface areabetween 1990 and 2000 divided by edge forest surface area for1990) was almost four times higher than that of perforated forestsduring the same decade, which shows that larger clearings ex-panded more quickly than smaller ones. Because interior forestsare affected by the increased light and drier and warmer micro-cli-mate imposed by peripheral edges, larger clearings will have amore negative impact on forest habitats than smaller clearings(Turner et al., 1998). In this context, edge forests can thereforebe considered more degraded than perforated forests.

4. Discussion

We presented a method for monitoring forest loss and struc-tural change in large and relatively inaccessible landscapes, usingthe study area as a case study to better understand patterns of

Please cite this article in press as: Nackoney, J., et al. Impacts of civil conflict on p2010. Biol. Conserv. (2014), http://dx.doi.org/10.1016/j.biocon.2013.12.033

human migration and altered resource use during a period ofintense civil conflict. Clearings within core forests increased sub-stantially in the study area during wartime, and confirmed fieldobservations that human populations living around the study areamigrated into interior forests during the war. Nackoney andWilliams (2012) also found similar wartime patterns of deforesta-tion in the region. Of particular note is that while the rate ofprimary forest loss taking place within the core forest areasdecreased after the conclusion of DRC’s war in 2003, the rate ofprimary forest loss taking place within the agricultural complexincreased. This illustrates a key human migration pattern likelysignificant to the post-war period: the return of local populations(with possibly larger families) from remote forested areas to theirnatal villages, clearing new fields in order to revitalize and increasefood production. Because our analysis did not consider forestregrowth, however, it is difficult to draw too many conclusionsabout post-war human migration. For example, we do not yetunderstand what proportion of the clearings may have been

rimary forest habitat in northern Democratic Republic of the Congo, 1990–

Fig. 5. Maps show an increase in peripheral forests (located around the outside periphery of forest clearings) over time.

Table 3Increases in edge and peripheral forests for the time periods under study for both Luo SR and ICBR.

Reserve name Edge forest area (ha) Annual increase in edge forest area (ha/yr)

1990 2000 2005 2010 1990–2000 2000–2010 2000–2005 2005–2010

Luo SR 24.9 136.4 180.6 192.7 11.2 5.6 8.8 2.4ICBR 83.3 475.6 555.5 641.3 39.2 16.6 16.0 17.2Total edge forest 108.2 612.0 736.1 833.9 50.4 22.2 24.8 19.6

Perforated forest area (ha) Annual increase in perforated forest area (ha/yr)

Luo SR 250.9 446.9 497.8 560.8 19.6 11.4 10.2 12.6ICBR 701.1 1636.6 1855.1 2047.3 93.5 41.1 43.7 38.4

Total perforated forest 952.0 2083.5 2352.9 2608.1 113.1 52.5 53.9 51.0

Total peripheral forest 1060.2 2695.5 3089.0 3442.1 163.5 74.7 78.7 70.6

6 J. Nackoney et al. / Biological Conservation xxx (2014) xxx–xxx

abandoned after the war, and during which year(s). In addition, asmentioned previously, field observations support that some of theclearings that occurred in ICBR during the war have becomepermanent settlements where human populations still live to thisday (Sakamaki et al., 2012).

Results of the analysis quantified and enabled spatial visualiza-tion of proxies that are indicative of increased wildlife poaching,one of the most pertinent indirect impacts of DRC’s wars (Dudleyet al., 2002; Draulans and Van Krunkelsven, 2002; McNeely,2003). The DRC wars forced local people to rely more heavily onbushmeat for food as the economic and transport sectors collapsed.The dramatic increases in peripheral forests caused by humanmovement patterns during the war as evidenced by our studycan be linked to increased human access in remote forest habitats,and are likely also related to the disappearance of the three bonobopopulations in Luo SR. Such human movement patterns can alsobring about changes in social beliefs and traditional practices thatmight influence hunting patterns (Kano et al., 1996). As early as1992, it was discovered that local communities living in andaround Luo SR hunted bonobos for their meat (Kano et al., 1996),despite local taboos against it (Lingomo and Kimura, 2009). Kanoet al. (1996) speculated that those who were killing the bonoboswere likely the same people who, in order to avoid the political

Please cite this article in press as: Nackoney, J., et al. Impacts of civil conflict on p2010. Biol. Conserv. (2014), http://dx.doi.org/10.1016/j.biocon.2013.12.033

conflicts that began in other areas in 1991, had migrated back toLuo SR from the bigger cities where they had previously beenliving. During the war, soldiers that occupied the villages aroundthe study site put increased pressure on local human populationsto hunt bonobos (Furuichi et al., 2012). The rapid change in culturalbeliefs from outside pressures and cross-cultural influences helpedto encourage the demise of taboos that had traditionally protectedbonobos from being hunted and demonstrated the profoundimpact that the civil conflicts and war had in this region.

Monitoring and mapping forest degradation will be increasinglyimportant as human populations, and consequently anthropogenicpressures on natural systems, increase, as these have direct impli-cations for terrestrial species that require large tracts of matureforest to persist. The field observations that noted decreases in,and in some cases altogether disappearances of, bonobo ranginggroup populations in Luo SR during the war illustrate the impor-tance of continued monitoring of undisturbed forest habitats.Although information on bonobo habitat preferences is limited(but see Reinartz et al., 2006, 2008), we do know that bonoboscan occupy wide ecological niches encompassing younger second-ary and inundated forests (Kano, 1983; Hashimoto et al., 1998) aswell as forest-savannah mosaics in the southern portion of theirrange (Thompson, 1997). Nevertheless, we also know that bonobos

rimary forest habitat in northern Democratic Republic of the Congo, 1990–

J. Nackoney et al. / Biological Conservation xxx (2014) xxx–xxx 7

prefer to nest in primary forests (Reinartz et al., 2006), and arerelatively absent from areas containing human signs (Kano,1983; Dupain et al., 2000; Dupain and Van Elsacker, 2001). Further,Hickey et al. (2012) and Hickey et al. (2013) found that bonobonesting habitat is highly influenced by forest edge density, yieldinghigher nest occurrence in areas with lower forest edge density. Ma-ture primary forest is a key habitat requirement for other terres-trial mammals besides bonobos; Wilkie and Finn (1990) foundthat out of 19 species recorded in Ituri Forest in northwest DRC,12 were more abundant in primary forests, including some speciesof duiker (Philantomba monticola and Cephalophus sylvicultor) andthe leopard (Panthera pardus), all of which are found in the studyarea.

Remote sensing played a crucial role in our study. The collectionand subsequent analysis of satellite imagery for four distinct timeperiods enabled the detection of changes in forest cover and pro-vided a foundation for continued monitoring of deforestation overtime. Since 2008, Landsat data have been distributed free of chargeby the United States Geological Survey (USGS). With this develop-ment, there has been much progress in automating Landsat dataprocessing and compositing in order to produce cloud-free imagesthat can be classified and compared across time periods (Hansenet al., 2008; Roy et al., 2010; Potapov et al., 2011). The supervisedforest cover and change classification method using Landsat data iswell-developed, with typical accuracies ranging between 75% and91% (Coppin and Bauer, 1994; Saksa et al., 2003). The mapping ofboth primary forest and primary forest loss conducted for thispaper was performed using an established method for CentralAfrica (Potapov et al., 2012) that has recently been validated byTyukavina et al. (2013). Our results would benefit from furthervalidation using high spatial resolution satellite imagery or fielddata. Unfortunately, field data were not collected systematicallyfor this purpose, and high spatial resolution data are virtuallyabsent for the study area for the 1990s, precluding rigorousvalidation. Although certain biodiversity health indicators such asover-hunting require in situ measurements to properly monitor,quantifying deforestation using satellite-based remote sensingtechniques can provide a useful gauge to monitor human accessin, and degradation of, interior forests remotely, especially duringperiods of intense civil conflict when anthropogenic pressuresare highest. Spatial analyses of primary forest cover extent andforest conversion patterns will be increasingly important forunderstanding how forests are affected by altered patterns ofhuman movement and resource use, improving forest resourcemanagement, and developing appropriate land use planningstrategies in areas most vulnerable to hunting and habitat loss.

Acknowledgements

This work was funded by the Central Africa Regional Programfor the Environment (CARPE) of the United States Agency for Inter-national Development (USAID), the Grant-in-Aid for ScientificResearch and Asia-Africa Science Platform Program by JapanSociety of Promotion of Science (JSPS), and the EnvironmentResearch and Technology Development Fund from the JapanMinistry of the Environment. We thank Brian Barker from theUniversity of Maryland for his assistance with acquiring satelliteimagery during early stages of this work.

Appendix A. Supplementary data

Supplementary data associated with this article can be found,in the online version, at http://dx.doi.org/10.1016/j.biocon.2013.12.033. These data include Google maps of the most importantareas described in this article.

Please cite this article in press as: Nackoney, J., et al. Impacts of civil conflict on p2010. Biol. Conserv. (2014), http://dx.doi.org/10.1016/j.biocon.2013.12.033

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