research article land-cover legacy effects on arbuscular...

Research ArticleLand-Cover Legacy Effects on ArbuscularMycorrhizal Abundance in Human and WildlifeDominated Systems in Tropical Savanna

Geofrey E Soka1 and Mark E Ritchie2

1Department of Wildlife Management Sokoine University of Agriculture PO Box 3073 Morogoro Tanzania2Department of Biology Syracuse University New York NY 13244 USA

Correspondence should be addressed to Geofrey E Soka gesokagmailcom

Received 27 November 2015 Accepted 11 January 2016

Academic Editor Dafeng Hui

Copyright copy 2016 G E Soka and M E RitchieThis is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited

Arbuscular mycorrhizal fungi (AMF) can be important mutualists to plant hosts in acquiring soil nutrients Past work has notexplored whether previous land-cover history influences current AMF abundance in croplands and whether different land-coverhistories in grazed but not cultivated areas influenceAMFThis studywas conducted to assess the effects of land-cover history in andnear Serengeti National Park on AMF abundance in areas with three different land usesThe results showed that land-cover historyinfluenced a number of soil physicochemical properties following conversion of grassland to cropland or woodland to croplandduring the past 27 years Different original land cover generally did not significantly influence current AMF abundance in croplandsor livestock-grazed soils However livestock-grazed current grasslands that were formerly woodlands had lower AMF abundancethan sites that had been grasslands since 1984 These results suggest that lower AMF abundance in livestock-grazed and croplandareas as compared to protected wildlife-grazed areas may reflect reduced total carbon inputs and higher disturbance and are notstrongly influenced by the legacy of previous land cover Given that recent studies have detected legacy effects on AMF such effectsmay reflect more the impact on the taxonomic composition of AMF rather than their total abundance

1 Introduction

Arbuscular mycorrhizal fungi (AMF) are ubiquitous soilfungi forming mutualistic symbiosis with a majority ofterrestrial plant species [1ndash3] AMF are promising candidatesfor universal indicators of land management legacies andsoil quality degradation [4ndash6]The connection between land-use legacies and AMF abundance has been a subject ofgreat interest to the scientific community Legacy effects ofland-use changes have been considered among the mostinfluential disturbances affecting diversity community struc-ture and ecosystem functioning and services of microbialcommunities [7 8] Legacy effects occur when the presenceof previous vegetation or land use alters soil propertiesor organism species pools in ways that persist even if theprevious vegetation is changed due to succession deliberateconversion or restoration [8ndash12] For example land-use

changes have been found to alter the soil characteristicsand aboveground species dynamics [13ndash16] and consequentlyinfluence microbial community structure and function [16ndash20] A chronosequence study along successional gradient hasshown that microbial communities tend to become moresimilar to those in native soils over time [21] Howeverresidual influence of prior conversion to agriculture has beenobserved in microbial communities even many years afterrestoration of forests after agricultural cultivation [22ndash24]

Soils often continued to reflect their history of previousvegetation and disturbance for many years through per-sistent changes in soil chemical and structural properties[7 9 25 26] For example historical farming in tropicregion has resulted in higher soil phosphorous contents andlower soil carbon and nitrogen contents compared to siteswith a long continuity of forest cover [9 27 28] Becausemicrobial adaptation and recovery may play a significant

Hindawi Publishing CorporationAdvances in EcologyVolume 2016 Article ID 1260702 10 pageshttpdxdoiorg10115520161260702

2 Advances in Ecology

role in ecosystem responses to human impacts [29ndash33] thelong-term consequences of past land-use decisions on soilmicrobial communities are crucial for predicting current andfuture ecosystem functioning and services [18 34] Whilemany studies have found that microbial communities differin response to land-use legacy [15 21 35ndash40] there is poorunderstanding of the association between land-use historyand the abundance of AMF in tropical soils

To help understand the association between land-coverhistory and soil microbes the abundance of AMF associatedwith different land-cover histories in and near the Serengetiwas comparedThere are threemain land uses in the Serengetiregion protected area wildlife-grazed savannas uncultivatedopen areas used for livestock grazing and cultivated fieldsConsequently there are different land-cover histories foreach land use such as transitions from grassland to wood-land versus persistent woodland transition from savannawoodland to grassland versus persistent grassland or recentconversion of woodland or grassland to cultivation versuspersistent cultivationThese land-cover transitions are poten-tially associated with different current soil properties such asextractable P total soil N and pH For example grasslandsrecently arising from loss of woodland may have higherresidual N or P in organic matter compared to grasslandsthat have not recently converted from woodland [41] Suchresidual differences among different land-use histories couldinfluence AMF abundance as a prior study in the Serengetiregion [41] found that soil properties varied among differentland uses and explained significant variation in AMF hyphaldensities Consequently AM hyphal abundance was hypoth-esized to bemore strongly influenced by current land-use andless associated with land-cover history because of physicalsoil disturbance from tillage and reduction in host plantbiomass and potentially C inputs in livestock-grazed sites

In this study land-cover classifications of 1984 and 2011Landsat imagery were used to determine histories for 112 sitesin the Serengeti region that were currently (in 2011) in oneof the three major land uses AMF abundance was sampledfrom multiple soil cores at each site along with severalhypothetically important soil properties such as extractableP total soil N and pH The association of AMF abundancewith land-cover histories for each of the different land useswas determined with ANCOVA to search for influences ofland-use histories independent of current differences in soilproperties This paper has significant potential in helping toshape our understanding of the abundance and dynamics ofAMF in soils under different land-usecover classes

2 Materials and Methods

21 Study Site Description Samples were collected inside(wildlife-grazed) Serengeti National Park (SNP) Tanzania inEast Africa (34∘ndash36∘E longitude and 1∘-2∘S latitude Figure 1)and on adjacent open lands that were used either for livestockgrazing (livestock grazed) or for cultivated crops (croplands)The area lies approximately about 240 km south of the equa-tor resulting in a fairly constant mean monthly temperatureand an annual change of only 4ndash6∘C [42] The ecosystem is

Location of the study area

Grassland in SNPGrassland outside SNPWoodland outside SNPCultivated farm outside SNPWoodland in SNP

Park boundary

0 30 6015(km)

34∘09984000998400998400 E 35

∘09984000998400998400 E

34∘09984000998400998400 E 35

∘09984000998400998400 E

1∘09984000998400998400 S

2∘09984000998400998400 S

3∘09984000998400998400 S

1∘09984000998400998400 S

2∘09984000998400998400 S

3∘09984000998400998400 S

NW E

S

Figure 1 Map of study sites and location of study area withinTanzania

characterized by a bimodal rainfall pattern with the shortrains occurring typically from November to December thelong rains usually taking place between March and May anda long dry season from June to October The southeasternSerengeti consists of C

4-grass dominated grasslands that

shift from short to medium to tallgrass plains towards thenorth and westward [43] The northern and western partsof the Serengeti consist predominantly of Acacia woodlandspunctuated by large patches of open C

4grassland This wide

variety in vegetation types allows the Serengeti to supportover 30 species of ungulates numbering close to 3 millionindividuals including 2 million migratory wildebeest (Con-nochaetes taurinus) zebra (Equus burchellii) and Thomsonrsquosgazelles (Gazella thomsonii) that impose the majority ofgrazing impact [44] which averages 63 of abovegroundbiomass each year [43]

The land-use system in and near Serengeti comprisesnatural woodlands and grasslands inside and outside thepark and croplands outside the park Natural woodlandand grassland inside the park are characterized by minimalwildlife grazing intensities while woodland and grasslandoutside the park are characterized by heavy grazing intensi-ties associated with overgrazing (by cattle) and other humanrelated activities such as charcoal burning cutting of treesfor timber fire wood and harvesting of nontimber productsLivestock (mostly cattle but with some sheep and goats) aremaintained at relatively high densities sufficient to consume70ndash90 of aboveground biomass (McSherry and Ritchie inpreparation) Agricultural systems outside the park comprisesmall-scale subsistence varieties (Zea mays and Phaseolus

Advances in Ecology 3

Table 1 Brief description of land-usecover classes in and near SNP

Land usecover Location Management Description

Grassland in Inside SNP Protected areaHerbaceous vegetation generally below 2m includinggrasses and sedges for wildlife conservation Fullyprotected with strict conservation measures

Woodland in Inside SNP Protected areaAreas covered by natural trees (single-stem woodyplants generally taller than 15m at densities lt50canopy cover) for wildlife conservation Fully protectedwith strict conservation measures

Cultivated land Outside SNP Private landIncludes areas used for annual crop cultivationMaize-bean intercropping system characterized by lowinorganic inputs (an estimate of 30 kg P and Nha)combined with farm yard manure

Grassland out Outside SNP Public land Herbaceous vegetation generally below 2m includinggrasses and sedges used for communal grazing

Woodland out Outside SNP Public landRepresents areas covered by trees (single-stem woodyplants generally taller than 15m at densities lt50canopy cover) used for communal grazing

Table 2 Remotely sensed data used in the analysis of land-usecover change in and near SNP

Sensor Acquisition date Image ID Pathrow SeasonLandsat TM August 1984 LT51690611984047XXX02 16961 DryLandsat TM August 1984 LT51690621984183XXX08 16962 DryLandsat TM August 1984 LT51700611984366XXX01 17061 DryLandsat TM August 1984 LT51700621984158XXX01 17062 DryLandsat TM and ETM+ August 2011 LT51690612011017MLK00 16961 DryLandsat TM and ETM+ August 2011 LT51690622011017MLK00 16962 DryLandsat TM and ETM+ August 2011 LT51700612011184MLK01 17061 DryLandsat TM and ETM+ August 2011 LT51700622011184MLK01 17062 DryNote TM thematic mapper ETM+ enhanced thematic mapper plus

vulgaris) grown with applications of external inorganic fer-tilizer inputs (estimate of 30 kg nitrogen and phosphorus perhactare combined with farm yard manure) (Table 1)

22 Field Soil Sampling and Soil Laboratory Analyses Theeffects of land usecover changes on AM hyphal abundanceacross 112 sites (20 times 20m plot) in the Serengeti region(Figure 1) were studied Field soil sampling and soil labora-tory analyses are detailed in Soka et al [41] The extractionanddetermination ofAMhyphal abundance from soils whichwere collected at each site are summarized in Soka et al[41] Soil pH total nitrogen (N) and available phosphorus(P) were measured at each site to determine how these soilproperties were associated with land-cover changes

23 Remote Sensing Data Collection

231 Image Selection Acquisition and Analysis Spatial pat-terns of land usecover changes using remote sensing data(1984ndash2011) derived from the satellite imagery to determinethe influence of land-cover history on AM hyphal abundancewere established Landsat 5 TM and 7 ETM+ cloud-freewith spatial resolution of 30m for the Greater Serengetiwere acquired from the US Geological Survey (USGS)

archive (httpearthexplorerusgsgov) Landsat imagerywasselected because it is readily and freely available and fre-quently used for land-cover classification [45]The dates weredetermined by image availability and were paired relativelyclose in time to help ensure consistency in cover classes andphenology (Table 2) The image processing and classificationwere performed using the topographical map and land-use map obtained from Tanzania Wildlife Research Institute(TAWIRI) These maps were also used to conduct groundobservations to verify the classification results from satelliteimagery (Figure 2) To ensure accurate identification of land-cover changes and geometric compatibilitywith other sourcesof information the images were geometrically correctedusing a 1 50000 scale topographical map and resampled toa local Tanzania UTM coordinate system in UTM zone 36south of the equator in which Serengeti is locatedThe imageswere georeferenced in WGS84 system UTM zone 36S

Atmospheric correction was performed to remove theeffects of the atmosphere on the reflectance values of imagesIn order to reinforce visual interpretability of images a colourcomposite (Landsat TMbands 3 4 and 5)was prepared basedon their ability to distinguish various vegetation covers A3 times 3 high pass filter was applied to the colour compositeto further enhance visual interpretation of linear featuressuch as vegetation features Supervised classification using


Table 3 Confusion matrix validation of land-cover map 2011

Classification dataReference data Woodland Grassland Farmland Sum Producerrsquos accuracyWoodland 28 0 2 30 933Grassland 0 32 4 36 889Farmland 2 3 26 31 839Sum 30 35 32 97Userrsquos accuracy 933 914 813Overall accuracy 887

Ground truth

Ground truth

Satellite images of 1984 and 2011

Preprocessing of satellite images(radiometric and geometric correction of satellite images)

Development of classification scheme

Formulation of training dataset

Spectral separability analysis

Classification of satellite imagesupervised maximum likelihood classification

Classified image

Final LULC map

Accuracy assessment

Manual corrections

Figure 2 Flowchart shows methodology adopted for LULC map-ping by Mondal et al [71]

Maximum Likelihood Classifier was performed (Figure 2)The training sites on the image which represent specific landclasses to be mapped were generated by on-screen digitizingof the selected areas for each land-cover class identified oncolour composite

Unsupervised classification for the 1984 Landsat imagerywas performed and thereafter subjected to supervised clas-sification using the 2011 training points No land-cover mapswere available for 1984 or around this period Areas of similarcharacteristics in both images were visually identified and forthese areas the class of the 2011 image was assigned to the1984 image Finally the classes identified for both 2011 and1984 were grouped into three land-cover classes woodlandgrassland and cropland (Table 1) To map land-use changebetween 1984 and 2011 the following seven land-cover tran-sitions were detected for each land-use category grasslandto grassland woodland to woodland cropland to croplandgrassland to cropland woodland to cropland grassland towoodland and woodland to grassland Transitions fromcropland to woodland and cropland to grassland were notdetected

232 Ground Truth Land-cover types classified for 2011were validated with field measurements A hand held Global

Positioning System (GPS) was used to map locations of vari-ous features and sampled land-cover observations Using thecollected ground-truth data a final classification was doneusing supervisedMaximumLikelihoodClassifier (MLC) intothree classes of interest (woodland grassland and cropland)(Table 1) Each observation plot was given a number andits land cover was recorded on the survey form togetherwith the coordinate location The development of vegetationcover classes was based on their clear differences in termsof physiognomy observed during the ground truthing andverification A total of 254 ground-truth points were collectedin June 2012 to serve as training samples for the classificationthese points were taken in and near Serengeti (Figure 1)Training samples (number of locations and number of pixels)were distributed evenly across classes where 70 of the datapoints were used for training that is for classification and30 were used for validation purposes (Table 3)

233 Classification Accuracy Assessment The accuracy ofthematic map was determined by the constructedmatrices inorder to test whether any difference exists in the interpreta-tion workThe results of the image classification are validatedby creating an error (confusion) matrix from which differentaccuracy measures are derived [46] The confusion matrix isused to compare spatially coincident ground control pointsand pixels of the classified image Table 3 shows a confusionmatrix that was established using 86 ground control points(GCP) which were not used in the classification of the 2011image The overall accuracy userrsquos accuracy and producerrsquosaccuracy were estimated from the confusion matrix Theoverall accuracy which is the number of correctly classifiedpixels was divided by the total number of GCP (ie referencedata) used for validation The overall accuracy in the presentstudy is 887 (Table 3)

24 Statistical Analyses AM hyphal abundance associatedwith land-cover history was compared in three differentland uses wildlife-grazed system livestock-grazed systemand cultivated soils in and near Serengeti National Parkusing analysis of covariance (ANCOVA) This approach testswhether or not AM hyphal abundance differed among sitesthat differed in their original land cover in 1984 compared todifferent land-usecover transitions after controlling for rela-tionships between AM hyphal response and three differentcovariates (soils P N and pH) found to be most importantin a previous study Candidate covariates were previouslyidentified from among a much larger set of potential soil and


AG cropland outside SNPGT grassland outside SNPGL grassland inside SNPWD woodland inside SNPWT woodland outside SNP

1984 land-cover classesWoodlandsGrasslandsCroplands

0 30 6015(km)

N

W E

S

Figure 3 Land-cover map in and near Serengeti in 1984

climate variables in previous work at the same study site asshown in Soka et al [41] Pairwise comparisons of treatmentmeans associated with different land usecover changes weremade by using Fisherrsquos Protected Least Significant Difference(LSD) at 119901 lt 005 confidence level All statistical analy-ses were performed using SPSS 170 (IBM Corp ChicagoUS)

3 Results

31 Land-UseCover Changes in and near the Park Gen-erally the maps (Figures 3 and 4) show the variation inland coverage between the two periods (1984ndash2011) underconsideration There were visually evident changes in landcover in and near Serengeti outside the park areas covered bywoodlands have declined while land covers under grasslandsand cultivation have expanded Less visually apparent werefrequent transitions from grassland to woodland and viceversa in uncultivated lands both inside and outside the parkA transition matrix (Table 4) summarizes the different land-cover conversions detected at the 112 sampling sites

0 30 6015(km)

N

W E

S



WD9 WD8

WD7WD6

WD5WD4

WD3

WD2

WD1

WD20

WD19

WD18WD17

WD16

WD15 WD14

WD13WD12

WD11

GT9

GT8GT7

GT6

GT5

GT4GT3

GT2

GT20

GT19

GT18GT17 GT16GT15

GT14

GT13 GT12

GT11

GT10

WT9WT8 WT7WT6 WT5WT4

WT3 WT2

WT1

WT24WT23

WT22WT21

WT20 WT19 WT18WT17

WT16WT15WT14

WT13WT12WT11

AG9AG8AG7AG6AG5

AG4

AG3 AG2

AG1

AG26

AG25

AG24 AG23

AG22 AG21AG20

AG19 AG18AG17 AG16

AG15 AG14

AG13AG12AG11AG10

GL9

GL8

GL7GL6

GL5

GL4

GL3 GL2

GL1

GL24 GL23

GL22

GL21GL20

GL19

GL18

GL17

GL16

GL15GL14

GL13

GL12

GL11

GL10


32 Influence of Land-Cover History on Soil Properties Therewas no significant influence of land-cover history on soil P(1198651 20= 317 119901 = 009) soil pH (119865

1 20= 011 119901 = 074)

or soil N (1198651 20= 042 119901 = 052) among the different

transitions to croplands or to grassland or to woodland inlivestock-grazed sites (119865

2 20= 256 119901 = 010) However

there was a significant influence of land-cover history on soilpH among the different transitions in livestock-grazed soils(1198653 44= 229 119901 = 004) There was a significant influence of

land-cover history on soil P in wildlife-grazed soils (1198653 43=

305 119901 = 004) but not on soil N or pH (1198653 43= 206 119901 =

012)

33 Linking Land-Use Legacies and AM Hyphal AbundanceThere were significant negative correlations between AMhyphal abundance and P (119903 = minus029 119901 = 002) and N (119903 =minus025 119901 = 002) No significant correlation was observedbetween AM hyphal abundance and pH (119903 = 008 119901 = 038)After controlling for the overall influence of soil properties onAMF abundance there was no significant association of land-cover historywithAMhyphal abundance among the different


Table 4 Transition matrix between 1984 and 2011 in and near Serengeti

Land-use type Land-coverhistory

Number ofplots

AM hyphaldensity

(mcm3) rangeSoil pH range TN-Kjeld ()

rangeP (mgkg)range

Agriculture AG-AG 11 1743ndash5838 513ndash738 001ndash019 032ndash127Agriculture GL-AG 8 2889ndash9208 540ndash770 006ndash021 028ndash168Agriculture WL-AG 6 2130ndash9312 569ndash825 004ndash019 053ndash174Livestock-grazed system GL-GL 15 3013ndash5627 606ndash786 006ndash015 035ndash106Livestock-grazed system GL-WL 8 2382ndash7710 559ndash757 009ndash020 004ndash181Livestock-grazed system WL-GL 7 2522ndash7364 553ndash823 007ndash018 021ndash103Livestock-grazed system WL-WL 14 3440ndash8048 515ndash656 011ndash024 026ndash187Wildlife-grazed system GW-GW 11 6470ndash10634 579ndash711 003ndash028 056ndash173Wildlife-grazed system GW-WW 8 2522ndash9772 580ndash689 009ndash026 031ndash104Wildlife-grazed system WW-GW 15 4719ndash9481 559ndash761 012ndash028 050ndash188Wildlife-grazed system WW-WW 9 4645ndash7535 542ndash784 011ndash032 050ndash206AG agriculture GL livestock-grazed grassland WL livestock-grazed woodland GW wildlife-grazed grassland WW wildlife-grazed woodland

transitions in croplands (Figure 4) (1198652 20= 256 119901 = 013)

Within different land uses therewas no significant correlationof soil P soil N or soil pH on AM hyphal abundanceamong different transitions in croplands (119865

1 20= 317

119901 = 009) Land-cover history in livestock-grazed areas wassignificantly associated with AMF abundance (119865

3 44= 456

119901 = 0008) (Figure 5) Post hoc LSD multiple comparisonsrevealed higher AM hyphal abundance at sites that persistedas grasslands since 1984 as compared to sites that changedfrom woodland to grassland (119901 = 002) Also sites thatchanged from grasslands to woodlands had significantlylower AMF abundance in livestock-grazed system comparedto sites that persisted as woodlands since 1984 (119901 = 005)The unchanged woodlands had the highest abundance ofAMF (5639 plusmn 236mcm3) while sites that changed fromwoodlands to grasslands had the least abundance of AMF(3461 plusmn 425mcm3) There were significant main effectsof land-cover history on AM hyphal abundance among thedifferent transitions in livestock-grazed soils after controllingfor soils properties (119865

3 37= 337 119901 = 004) There was no

significant main effects of soil P soil N or soil pH on AMhyphal abundance among different transitions in livestock-grazed soils (119865

1 37= 075 119901 = 039)

After controlling for the influence of soil properties therewere significant differences in AM hyphal abundance associ-ated with land-cover history among the different transitionsin wildlife-grazed soils (119865

3 43= 441 119901 = 0009) Post hoc

LSD multiple comparisons revealed significantly greater AMhyphal abundance between sites that have persisted as grass-lands compared to woodlands that transitioned to grasslandsThere were significant main effects of land-cover history onAM hyphal abundance among the different transitions inwildlife-grazed soils (119865

3 36= 381 119901 = 002) There were no

significant main effects of soil P soil N or soil pH on AMhyphal abundance among different transitions in wildlife-grazed soils (119901 gt 005 in all cases)

4 Discussion

41 Land-UseCover Changes in and near SerengetiThe results of the spatial analysis from the supervised

0

20

40

60

80

100

G-G

aa

a

b

bc c

c

G-W W-G W-WLand-cover history

Livestock-grazed systemWildlife-grazed system

AM

hyp

hal a

bund

ance

(mc

m3 )

Figure 5 Mean (plusmnSE) arbuscular mycorrhizal hyphal abundancein soils associated with various land-cover history in livestockand wildlife-grazed systems (G grassland W woodland) Differentletters a b and c indicate significant differences at 119901 lt 005

classification of the images (Figures 3 and 4) indicatenoticeable losses and gains in various land-use and land-cover types From the classified images it is apparent that thearea covered by woodland was reduced drastically between1984 and 2011 with an increase in grasslands and croplands(Figures 3 and 4) Natural vegetation around Serengetiecosystem has been fragmented by human disturbancesthrough clearance for agricultural activities and pasture [47]

The results of this study suggest that different land-cover transitions that is legacy effects had relatively weakimpact on AMF abundance Only transitions fromwoodlandto grassland in both wildlife-grazed and livestock-grazedsystems were associated with 15 lower AMF abundancethan that found in persistent grasslands (Figure 5) Notablysites with transitions from grassland to woodland containedsimilar AMF abundance as sites that were persistent wood-lands and sites that were converted from either grasslandor woodland to cropland (Figure 6) contained similar AMFabundance to persistent croplands


AG-AG G-AG W-AGLand-cover history

0

10

20

30

40

50

60

70

a

a

a

AM

hyp

hal d

ensit

y (m

cm

3 )

Figure 6 Mean (plusmnSE) arbuscular mycorrhizal abundance in soilsassociated with various land-cover history in agricultural sites (AGagriculture G grasslandW woodland) Means with the same letterare not significantly different from each other (119901 lt 005)

42 Association between Land-Cover History and Soil Proper-ties The lack of influence of land-cover transitions on AMFabundance may reflect the general lack of association in thisSerengeti system between woodland and grassland and keysoil properties A history of woodland resulted in a smalldepression of pH that might explain the small reductionin AMF abundance associated with woodland-grasslandtransitions compared to persistent grasslands in livestock-grazed sites but the change in pH is much lower than what isobserved in other woodland to grassland transitions subjectto use by humans [33 47ndash49] One reason for minor shiftsin soil properties was that most woodlands in the Serengetiwere more closed canopy savannas with C

4grasses in the

understory similar to open grasslands To the extent thatgrass understory supports AMF and maintains elevated pHthrough the pumping of cations from deep root layers andthe recycling of cations in litter the loss of trees in Serengetiwoodlands might have only minor shifts In protected areassubject to wildlife grazing there was an increase in soil Pat sites shifting from woodland to grassland as compared topersistent grasslands

43 Association between Land-Use Legacies and AM HyphalAbundance However the overall weak land-cover historyhad more influence on AM hyphal abundance in livestock-grazed soils than was the case with either wildlife-grazed orcropland soils The pattern is similar to the one reported byAguilar-Fernandez et al [50] who found that forest sites hadsignificantly higher AMF abundance than was the case withlivestock-grazed pastures Several studies conducted someyears after forest conversion to pastures have documented adecrease in soil organicmattermicrobial biomass soilmicro-bial activity and nutrient losses associated with the loss ofplant cover [51 52] However in Serengeti grasslands appearto contain greater AMF abundance than woodlands perhapsbecause of greater belowgroundC inputs Also the disruption

of soil aggregates and of the processes maintaining long-term soil nutrient and water availabilities contributes tosoil deterioration [53] This study suggests that site-specificdifferences in soil properties may play a greater role in AMhyphal abundance as observed elsewhere [54ndash56]

There were significant differences in AM hyphal abun-dance associated with land-cover history among the differenttransitions in wildlife-grazed soils Also there was a signifi-cant main effect of land-cover history on AM hyphal abun-dance among the different transitions in wildlife-grazed soilsafter controlling for soils properties This study found thatwildlife-grazed grasslands supported the highest AM hyphalabundance possibly due to the presence of more host plantbiomass suggesting that AMhyphal abundancemay increasewith an increase of host plant biomass and diversity Wood-lands generate a light limited environment under the canopywhich contributed to less ground plant cover (less host plants)leading to grass species suppression This is in agreementwith Burrows and Pfleger [57] who observed an increase inAMF abundance with an increase in plant species diversityJohnson et al [58] hypothesize that host plant species may beimportant for the diversity of AMF species communities

In this study many of the transitions may have occurreda few years prior to 2011 and some transitions may haveoccurred a decade or two earlier Legacy effects of land-use changes in ecosystem functioning and services maylast several hundred years [6 7] Different past land-covertypes have long-term impacts on soil conditions and AMFabundance [6] as observed in this study

44 Effects of Fire on Land Cover Fire is recognized as anatural and important ecological factor of grassland ecosys-tems [59] Fire affects nutrient cycling [60ndash62]modifies plantspecies composition [59 63 64] and may have legacy effectson the AMF abundance Woodland to grassland transitionsobserved in this study were likely caused by fire in the parkand settlement outside the park Park managers within theSerengeti ecosystem use fire as a valuable tool to maintainthe balance between grasslands and woodlands that createthe iconic landscapes of the savanna [65 66] The constantpresence of fire in the ecosystem has resulted in the evolutionof fire-resistant communities of plants that are dependent onperiodic burning for their existence [67] Sometimeswildfiresoriginate from settlement outside the park its frequency andintensity may have effects on the biotic and abiotic compo-nents of grassland and savanna ecosystems [66 68] Thereare accounts of fire effects on ectomycorrhizal density andsoil microfungi (eg [69]) Gibson andHulbert [63] reportedthat the impact of fire has a profound effect on the vegetationBy altering soil temperatures soil water potential and plantspecies composition burning may have both indirect anddirect effects on AM fungal species composition [70]

5 Conclusions

It can be concluded that a relatively weak association betweenland-cover history and soil properties (pH P and N) amongthe different transitions in and near Serengeti National Park


was observed Furthermore results from this study suggestthat there were no relationships between AMF abundanceand soil properties (pH P and N) regardless of the previousland-use history AMF abundance in croplands was notsignificantly associatedwith land-cover history For livestock-grazed areas current grasslands that were converted fromwoodland since 1984 showed lower AMF abundance thanareasmaintained as grasslandsThis suggests that overgrazingby livestock causes the reduction in AM hyphal abundancein the soils by decreasing carbon inputs Overall the datasuggest that while current land use has a strong associationwith AMF abundance land-use history has apparently littleeffect on AMF abundance although it might have a muchstronger influence on species composition than the overallAM hyphal abundance

Low AMF abundance in livestock areas may reflect adecrease in total carbon inputs and disturbance rather thanthe legacy of past land useThe degree of current disturbance(tillage and fertilizer) for croplands and reduced carboninputs from overgrazing might make AMF abundance morevulnerable to legacy effects A deeper understanding ofvarious past-land-use legacies is crucial because of theiressential role for aboveground and belowground interactions

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] S Smith and D Read Mycorrhizal Symbiosis Academic PressLondon UK 1997

[2] M C Rillig ldquoArbuscular mycorrhizae and terrestrial ecosystemprocessesrdquo Ecology Letters vol 7 no 8 pp 740ndash754 2004

[3] S Smith and D Read Mycorrhizal Symbiosis Academic PressAmsterdam The Netherlands 3rd edition 2008

[4] L K Abbott and A D Robson ldquoFactors influencing theoccurrence of vesicular-arbuscular mycorrhizasrdquo AgricultureEcosystems and Environment vol 35 no 2-3 pp 121ndash150 1991

[5] A C Kennedy and R I Papendick ldquoMicrobial characteristicsof soil qualityrdquo Journal of Soil and Water Conservation vol 50no 3 pp 243ndash248 1995

[6] J Jansa A Erb H-R Oberholzer P Smilauer and S Egli ldquoSoiland geography are more important determinants of indigenousarbuscular mycorrhizal communities than management prac-tices in Swiss agricultural soilsrdquo Molecular Ecology vol 23 no8 pp 2118ndash2135 2014

[7] A Fichtner G von Oheimb W Hardtle C Wilken and J LM Gutknecht ldquoEffects of anthropogenic disturbances on soilmicrobial communities in oak forests persist for more than 100yearsrdquo Soil Biology and Biochemistry vol 70 pp 79ndash87 2014

[8] R A Lankau J T Bauer M R Anderson and R C AndersonldquoLong-term legacies and partial recovery of mycorrhizal com-munities after invasive plant removalrdquo Biological Invasions vol16 no 9 pp 1979ndash1990 2014

[9] I Celik ldquoLand-use effects on organic matter and physicalproperties of soil in a southern Mediterranean highland ofTurkeyrdquo Soil and Tillage Research vol 83 no 2 pp 270ndash2772005

[10] A Kulmatiski K H Beard and J M Stark ldquoSoil history as aprimary control on plant invasion in abandoned agriculturalfieldsrdquo Journal of Applied Ecology vol 43 no 5 pp 868ndash8762006

[11] P Kardol N J Cornips M M L van Kempen J M TBakx-Schotman andW H van der Putten ldquoMicrobe-mediatedplant-soil feedback causes historical contingency effects in plantcommunity assemblyrdquo Ecological Monographs vol 77 no 2 pp147ndash162 2007

[12] J de Chazal and M D A Rounsevell ldquoLand-use and climatechange within assessments of biodiversity change a reviewrdquoGlobal Environmental Change vol 19 no 2 pp 306ndash315 2009

[13] J A Foley R DeFries G P Asner et al ldquoGlobal consequencesof land userdquo Science vol 309 no 5734 pp 570ndash574 2005

[14] N Blaum E Rossmanith and F Jeltsch ldquoLand use affectsrodent communities in Kalahari savannah rangelandsrdquo AfricanJournal of Ecology vol 45 no 2 pp 189ndash195 2007

[15] C L Lauber M S Strickland M A Bradford and N FiererldquoThe influence of soil properties on the structure of bacterialand fungal communities across land-use typesrdquo Soil Biology andBiochemistry vol 40 no 9 pp 2407ndash2415 2008

[16] M Aubert P Margerie J Trap and F Bureau ldquoAboveground-belowground relationships in temperate forests plant littercomposes and microbiota orchestratesrdquo Forest Ecology andManagement vol 259 no 3 pp 563ndash572 2010

[17] G Chen L Gan S Wang Y Wu and G Wan ldquoA comparativestudy on the microbiological characteristics of soils underdifferent landmdashuse conditions from Karst areas of SouthwestChinardquo Chinese Journal of Geochemistry vol 20 no 1 pp 52ndash58 2001

[18] F L Carpenter S PMayorga E GQuintero andM SchroederldquoLand-use and erosion of a Costa Rican Ultisol affect soilchemistry mycorrhizal fungi and early regenerationrdquo ForestEcology and Management vol 144 no 1ndash3 pp 1ndash17 2001

[19] S J Grayston and H Rennenberg ldquoAssessing effects of forestmanagement on microbial community structure in a centralEuropean beech forestrdquo Canadian Journal of Forest Researchvol 36 no 10 pp 2595ndash2604 2006

[20] K S Ramirez J M Craine and N Fierer ldquoConsistent effectsof nitrogen amendments on soil microbial communities andprocesses across biomesrdquo Global Change Biology vol 18 no 6pp 1918ndash1927 2012

[21] K Jangid M A Williams A J Franzluebbers T M SchmidtD C Coleman and W B Whitman ldquoLand-use history has astronger impact on soilmicrobial community composition thanaboveground vegetation and soil propertiesrdquo Soil Biology andBiochemistry vol 43 no 10 pp 2184ndash2193 2011

[22] K E Giller M H Beare P Lavelle A-M N Izac andM J Swift ldquoAgricultural intensification soil biodiversity andagroecosystem functionrdquo Applied Soil Ecology vol 6 no 1 pp3ndash16 1997

[23] Y-J Jiang D-X Yuan C Zhang et al ldquoImpact of land-usechange on soil properties in a typical karst agricultural region ofSouthwest China a case study of Xiaojiang watershed YunnanrdquoEnvironmental Geology vol 50 no 6 pp 911ndash918 2006

[24] J M Fraterrigo T C Balser and M G Turner ldquoMicrobialcommunity variation and its relationship with nitrogen miner-alization in historically altered forestsrdquo Ecology vol 87 no 3pp 570ndash579 2006

[25] K Verheyen B Bossuyt M Hermy and G Tack ldquoThe landuse history (1278ndash1990) of a mixed hardwood forest in western


Belgium and its relationship with chemical soil characteristicsrdquoJournal of Biogeography vol 26 no 5 pp 1115ndash1128 1999

[26] J H Jussy W Koerner E Dambrine J L Dupouey and MBenoit ldquoInfluence of former agricultural land use on net nitrateproduction in forest soilsrdquo European Journal of Soil Science vol53 no 3 pp 367ndash374 2002

[27] J L Dupouey E Dambrine J D Laffite and C Moares ldquoIrre-versible impact of past land-use on forest soils and biodiversityrdquoEcology vol 83 no 11 pp 2978ndash2984 2002

[28] G von Oheimb W Hardtle P S Naumann C WestphalT Assmann and H Meyer ldquoLong-term effects of historicalheathland farming on soil properties of forest ecosystemsrdquoForest Ecology andManagement vol 255 no 5-6 pp 1984ndash19932008

[29] E F Lambin B L Turner II H J Geist et al ldquoThe causes ofland-use and land-cover changemdashmoving beyond the mythsrdquoGlobal Environmental Change Human and Policy Dimensionsvol 11 pp 261ndash269 2001

[30] E F Lambin H J Geist and E Lepers ldquoDynamics of land-useand land-cover change in tropical regionsrdquo Annual Review ofEnvironment and Resources vol 28 pp 205ndash241 2003

[31] S D Allison M D Wallenstein and M A Bradford ldquoSoil-carbon response to warming dependent on microbial physiol-ogyrdquo Nature Geoscience vol 3 no 5 pp 336ndash340 2010

[32] M D Wallenstein and E K Hall ldquoA trait-based frameworkfor predicting when and where microbial adaptation to climatechange will affect ecosystem functioningrdquo Biogeochemistry vol109 no 1ndash3 pp 35ndash47 2012

[33] R L B Hooke and J F Martın-Duque ldquoLand transformationby humans a reviewrdquo GSA Today vol 22 no 12 pp 4ndash10 2012

[34] B Sun Z-X Dong X-X Zhang Y Li H Cao and Z-L CuildquoRice to vegetables short-versus long-term impact of land-usechange on the indigenous soil microbial communityrdquoMicrobialEcology vol 62 no 2 pp 474ndash485 2011

[35] K L Steenwerth L E Jackson F J Calderon M R Strombergand K M Scow ldquoSoil microbial community composition andland use history in cultivated and grassland ecosystems ofcoastal Californiardquo Soil Biology amp Biochemistry vol 34 no 11pp 1599ndash1611 2002

[36] J N Klironomos ldquoFeedback with soil biota contributes to plantrarity and invasiveness in communitiesrdquo Nature vol 417 no6884 pp 67ndash70 2002

[37] K M Batten K M Scow and E K Espeland ldquoSoil microbialcommunity associated with an invasive grass differentiallyimpacts native plant performancerdquo Microbial Ecology vol 55no 2 pp 220ndash228 2008

[38] R H A van Grunsven W H van der Putten T M Bezemer FBerendse and E M Veenendaal ldquoPlant-soil interactions in theexpansion and native range of a poleward shifting plant speciesrdquoGlobal Change Biology vol 16 no 1 pp 380ndash385 2010

[39] J Burton C R Chen Z H Xu and H Ghadiri ldquoSoil microbialbiomass activity and community composition in adjacentnative and plantation forests of subtropical Australiardquo Journalof Soils and Sediments vol 10 no 7 pp 1267ndash1277 2010

[40] A M Koch P M Antunes and J N Klironomos ldquoDiversityeffects on productivity are stronger within than between trophicgroups in the arbuscular mycorrhizal symbiosisrdquo PLoS ONEvol 7 no 5 Article ID e36950 2012

[41] G E Soka M E Ritchie and E P Mayemba ldquoInfluence ofcurrent land use and edaphic factors on arbuscular mycorrhizal(AM) hyphal abundance and soil organic matter in and near

Serengeti National Parkrdquo Journal of Ecology and the NaturalEnvironment vol 7 no 5 pp 158ndash169 2015

[42] S JMcNaughton ldquoSerengeti grassland ecology the role of com-posite environmental factors and contingency in communityorganizationrdquo EcologicalMonographs vol 53 no 3 pp 291ndash3201983

[43] S J McNaughton ldquoEcology of a grazing ecosystem theSerengetirdquo Ecological Monographs vol 55 no 3 pp 259ndash2941985

[44] A R E Sinclair J G C Hopcraft H Olff S A R MdumaK A Galvin and G J Sharam ldquoHistorical and future changesto the Serengeti ecosystemrdquo in Serengeti III Human Impactson Ecosystem Dynamics A R E Sinclair C Packer S A RMduma and J M Fryxell Eds pp 7ndash46 University of ChicagoPress Chicago Ill USA 2008

[45] M A Wulder J C White S N Goward et al ldquoLandsatcontinuity issues and opportunities for land covermonitoringrdquoRemote Sensing of Environment vol 112 no 3 pp 955ndash9692008

[46] R G Congalton and K Green Assessing the Accuracy ofRemotely Sensed Data Principles and Practices Lewis LondonUK 1999

[47] A B Estes T Kuemmerle H Kushnir V C Radeloff and HH Shugart ldquoLand-cover change and human population trendsin the greater Serengeti ecosystem from 1984ndash2003rdquo BiologicalConservation vol 147 no 1 pp 255ndash263 2012

[48] WM Post and L KMann ldquoChanges in soil organic carbon andnitrogen as a result of cultivationrdquo in Soil and the GreenhouseEffect A F Bowman Ed pp 401ndash407 JohnWiley amp Sons NewYork NY USA 1990

[49] D Murty M U F Kirschbaum R E McMurtrie and HMcGilvray ldquoDoes conversion of forest to agricultural landchange soil carbon and nitrogen A review of the literaturerdquoGlobal Change Biology vol 8 no 2 pp 105ndash123 2002

[50] M Aguilar-Fernandez V J Jaramillo L Varela-Fregoso andM E Gavito ldquoShort-term consequences of slash-and-burnpractices on the arbuscular mycorrhizal fungi of a tropical dryforestrdquoMycorrhiza vol 19 no 3 pp 179ndash186 2009

[51] E B Allen M F Allen D J Helm J M Trappe R Molina andE Rincon ldquoPatterns and regulation of mycorrhizal plant andfungal diversityrdquo Plant and Soil vol 170 no 1 pp 47ndash62 1995

[52] V B Santos A S F Araujo L F C Leite L A P LNunes and W J Melo ldquoSoil microbial biomass and organicmatter fractions during transition from conventional to organicfarming systemsrdquo Geoderma vol 170 pp 227ndash231 2012

[53] F Garcıa-Oliva R L Sanford Jr and E Kelly ldquoEffect of burningof tropical deciduous forest soil in Mexico on the microbialdegradation of organic matterrdquo Plant and Soil vol 206 no 1pp 29ndash36 1998

[54] D A Bossio M S Girvan L Verchot et al ldquoSoil microbialcommunity response to land use change in an agriculturallandscape of western Kenyardquo Microbial Ecology vol 49 no 1pp 50ndash62 2005

[55] E D C Jesus T L Marsh J M Tiedje and F M D SMoreira ldquoChanges in land use alter the structure of bacterialcommunities in Western Amazon soilsrdquoThe ISME Journal vol3 no 9 pp 1004ndash1011 2009

[56] C J Eaton M P Cox and B Scott ldquoWhat triggers grassendophytes to switch from mutualism to pathogenismrdquo PlantScience vol 180 no 2 pp 190ndash195 2011


[57] R L Burrows and F L Pfleger ldquoArbuscular mycorrhizal fungirespond to increasing plant diversityrdquo Canadian Journal ofBotany vol 80 no 2 pp 120ndash130 2002

[58] N C Johnson D Tilman and D Wedin ldquoPlant and soilcontrols on mycorrhizal fungal communitiesrdquo Ecology vol 73no 6 pp 2034ndash2042 1992

[59] S D Fuhlendorf and D M Engle ldquoApplication of the fire-grazing interaction to restore a shifting mosaic on tallgrassprairierdquo Journal of Applied Ecology vol 41 no 4 pp 604ndash6142004

[60] N T Hobbs and D S Schimel ldquoFire effects on nitrogenmineralization and fixation in mountain shrub and grasslandcommunitiesrdquo Journal of Range Management vol 37 no 5 pp402ndash405 1984

[61] R S Singh ldquoEffect of winter fire on primary productivity andnutrient concentration of a dry tropical savannardquoVegetatio vol106 no 1 pp 63ndash71 1993

[62] C A D M van de Vijver P Poot and H H T Prins ldquoCausesof increased nutrient concentrations in post-fire regrowth in anEast African savannardquo Plant and Soil vol 214 no 1-2 pp 173ndash185 1999

[63] D J Gibson and L C Hulbert ldquoEffects of fire topographyand year-to-year climatic variation on species composition intallgrass prairierdquo Vegetatio vol 72 no 3 pp 175ndash185 1987

[64] D J Gibson ldquoRegeneration and fluctuation of tallgrass prairievegetation in rresponse to burning frequencyrdquo Bulletin of theTorrey Botanical Club vol 115 no 1 pp 1ndash12 1988

[65] R A P Pellew ldquoThe impacts of elephant giraffe and fire uponthe Acacia tortilis woodlands of the Serengetirdquo African Journalof Ecology vol 21 no 1 pp 41ndash74 1983

[66] H T Dublin ldquoVegetation dynamics in the Serengeti-MaraEcosystem the role of elephants fire and other factorsrdquo inSerengeti II Dynamics Management and Conservation of anEcosystem A R E Sinclair and P Arcese Eds pp 71ndash90University of Chicago Press Chicago Ill USA 1995

[67] P M Olindo ldquoFire and conservation of the habitat in Kenyardquo inProceedings of the Annual Tall Timbers Fire Ecology Conferencevol 11 pp 243ndash257 Tallahassee Fla USA June 1971

[68] W J Bond and B W van Wilgen Fire and Plants Chapman ampHall London UK 1996

[69] P Reddell and N Malajczuk ldquoFormation of mycorrhizae byjarrah (Eucalyptus marginataDonn ex Smith) in litter and soilrdquoAustralian Journal of Botany vol 32 no 5 pp 511ndash520 1984

[70] D J Gibson and B A D Hetrick ldquoTopographic and fire effectson the composition and abundance of VA-mycorrhizal fungi inTallgrass prairierdquoMycologia vol 80 no 4 pp 433ndash441 1988

[71] M SMondal N SharmaMKappas and P KGarg ldquoModelingof spatio-temporal dynamics of land use and land cover in a partof Brahmaputra River basin using Geoinformatic techniquesrdquoGeocarto International vol 28 no 7 pp 632ndash656 2013

Submit your manuscripts athttpwwwhindawicom

Forestry ResearchInternational Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Environmental and Public Health

Journal of



EcosystemsJournal of


MeteorologyAdvances in

EcologyInternational Journal of


Marine BiologyJournal of


Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Advances in


Environmental Chemistry

Atmospheric SciencesInternational Journal of



Waste ManagementJournal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics


Geological ResearchJournal of

EarthquakesJournal of


BiodiversityInternational Journal of


ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OceanographyInternational Journal of


The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014


ClimatologyJournal of


role in ecosystem responses to human impacts [29ndash33] thelong-term consequences of past land-use decisions on soilmicrobial communities are crucial for predicting current andfuture ecosystem functioning and services [18 34] Whilemany studies have found that microbial communities differin response to land-use legacy [15 21 35ndash40] there is poorunderstanding of the association between land-use historyand the abundance of AMF in tropical soils

To help understand the association between land-coverhistory and soil microbes the abundance of AMF associatedwith different land-cover histories in and near the Serengetiwas comparedThere are threemain land uses in the Serengetiregion protected area wildlife-grazed savannas uncultivatedopen areas used for livestock grazing and cultivated fieldsConsequently there are different land-cover histories foreach land use such as transitions from grassland to wood-land versus persistent woodland transition from savannawoodland to grassland versus persistent grassland or recentconversion of woodland or grassland to cultivation versuspersistent cultivationThese land-cover transitions are poten-tially associated with different current soil properties such asextractable P total soil N and pH For example grasslandsrecently arising from loss of woodland may have higherresidual N or P in organic matter compared to grasslandsthat have not recently converted from woodland [41] Suchresidual differences among different land-use histories couldinfluence AMF abundance as a prior study in the Serengetiregion [41] found that soil properties varied among differentland uses and explained significant variation in AMF hyphaldensities Consequently AM hyphal abundance was hypoth-esized to bemore strongly influenced by current land-use andless associated with land-cover history because of physicalsoil disturbance from tillage and reduction in host plantbiomass and potentially C inputs in livestock-grazed sites

In this study land-cover classifications of 1984 and 2011Landsat imagery were used to determine histories for 112 sitesin the Serengeti region that were currently (in 2011) in oneof the three major land uses AMF abundance was sampledfrom multiple soil cores at each site along with severalhypothetically important soil properties such as extractableP total soil N and pH The association of AMF abundancewith land-cover histories for each of the different land useswas determined with ANCOVA to search for influences ofland-use histories independent of current differences in soilproperties This paper has significant potential in helping toshape our understanding of the abundance and dynamics ofAMF in soils under different land-usecover classes

2 Materials and Methods

21 Study Site Description Samples were collected inside(wildlife-grazed) Serengeti National Park (SNP) Tanzania inEast Africa (34∘ndash36∘E longitude and 1∘-2∘S latitude Figure 1)and on adjacent open lands that were used either for livestockgrazing (livestock grazed) or for cultivated crops (croplands)The area lies approximately about 240 km south of the equa-tor resulting in a fairly constant mean monthly temperatureand an annual change of only 4ndash6∘C [42] The ecosystem is

Location of the study area

Grassland in SNPGrassland outside SNPWoodland outside SNPCultivated farm outside SNPWoodland in SNP

Park boundary

0 30 6015(km)

34∘09984000998400998400 E 35

∘09984000998400998400 E

34∘09984000998400998400 E 35

∘09984000998400998400 E

1∘09984000998400998400 S

2∘09984000998400998400 S

3∘09984000998400998400 S

1∘09984000998400998400 S

2∘09984000998400998400 S

3∘09984000998400998400 S

NW E

S

Figure 1 Map of study sites and location of study area withinTanzania

characterized by a bimodal rainfall pattern with the shortrains occurring typically from November to December thelong rains usually taking place between March and May anda long dry season from June to October The southeasternSerengeti consists of C

4-grass dominated grasslands that

shift from short to medium to tallgrass plains towards thenorth and westward [43] The northern and western partsof the Serengeti consist predominantly of Acacia woodlandspunctuated by large patches of open C

4grassland This wide

variety in vegetation types allows the Serengeti to supportover 30 species of ungulates numbering close to 3 millionindividuals including 2 million migratory wildebeest (Con-nochaetes taurinus) zebra (Equus burchellii) and Thomsonrsquosgazelles (Gazella thomsonii) that impose the majority ofgrazing impact [44] which averages 63 of abovegroundbiomass each year [43]

The land-use system in and near Serengeti comprisesnatural woodlands and grasslands inside and outside thepark and croplands outside the park Natural woodlandand grassland inside the park are characterized by minimalwildlife grazing intensities while woodland and grasslandoutside the park are characterized by heavy grazing intensi-ties associated with overgrazing (by cattle) and other humanrelated activities such as charcoal burning cutting of treesfor timber fire wood and harvesting of nontimber productsLivestock (mostly cattle but with some sheep and goats) aremaintained at relatively high densities sufficient to consume70ndash90 of aboveground biomass (McSherry and Ritchie inpreparation) Agricultural systems outside the park comprisesmall-scale subsistence varieties (Zea mays and Phaseolus




















Ground truth

Ground truth







Classified image

Final LULC map

Accuracy assessment

Manual corrections











0 30 6015(km)

N

W E

S



3 Results


0 30 6015(km)

N

W E

S



WD9 WD8

WD7WD6

WD5WD4

WD3

WD2

WD1

WD20

WD19

WD18WD17

WD16

WD15 WD14

WD13WD12

WD11

GT9

GT8GT7

GT6

GT5

GT4GT3

GT2

GT20

GT19

GT18GT17 GT16GT15

GT14

GT13 GT12

GT11

GT10


WT3 WT2

WT1

WT24WT23

WT22WT21

WT20 WT19 WT18WT17

WT16WT15WT14

WT13WT12WT11

AG9AG8AG7AG6AG5

AG4

AG3 AG2

AG1

AG26

AG25

AG24 AG23

AG22 AG21AG20

AG19 AG18AG17 AG16

AG15 AG14

AG13AG12AG11AG10

GL9

GL8

GL7GL6

GL5

GL4

GL3 GL2

GL1

GL24 GL23

GL22

GL21GL20

GL19

GL18

GL17

GL16

GL15GL14

GL13

GL12

GL11

GL10



1 20= 011 119901 = 074)



2 20= 256 119901 = 010) However




012)





Number ofplots

AM hyphaldensity


rangeP (mgkg)range




1 20= 317


3 44= 456


3 37= 337 119901 = 004) There was no


1 37= 075 119901 = 039)


3 43= 441 119901 = 0009) Post hoc


3 36= 381 119901 = 002) There were no


4 Discussion


0

20

40

60

80

100

G-G

aa

a

b

bc c

c



AM

hyp

hal a

bund

ance

(mc

m3 )






0

10

20

30

40

50

60

70

a

a

a

AM

hyp

hal d

ensit

y (m

cm

3 )



4grasses in the







5 Conclusions







References
















































































Journal of












Volume 2014

Advances in









Geophysics

































Ground truth

Ground truth







Classified image

Final LULC map

Accuracy assessment

Manual corrections











0 30 6015(km)

N

W E

S



3 Results


0 30 6015(km)

N

W E

S



WD9 WD8

WD7WD6

WD5WD4

WD3

WD2

WD1

WD20

WD19

WD18WD17

WD16

WD15 WD14

WD13WD12

WD11

GT9

GT8GT7

GT6

GT5

GT4GT3

GT2

GT20

GT19

GT18GT17 GT16GT15

GT14

GT13 GT12

GT11

GT10


WT3 WT2

WT1

WT24WT23

WT22WT21

WT20 WT19 WT18WT17

WT16WT15WT14

WT13WT12WT11

AG9AG8AG7AG6AG5

AG4

AG3 AG2

AG1

AG26

AG25

AG24 AG23

AG22 AG21AG20

AG19 AG18AG17 AG16

AG15 AG14

AG13AG12AG11AG10

GL9

GL8

GL7GL6

GL5

GL4

GL3 GL2

GL1

GL24 GL23

GL22

GL21GL20

GL19

GL18

GL17

GL16

GL15GL14

GL13

GL12

GL11

GL10



1 20= 011 119901 = 074)



2 20= 256 119901 = 010) However




012)





Number ofplots

AM hyphaldensity


rangeP (mgkg)range




1 20= 317


3 44= 456


3 37= 337 119901 = 004) There was no


1 37= 075 119901 = 039)


3 43= 441 119901 = 0009) Post hoc


3 36= 381 119901 = 002) There were no


4 Discussion


0

20

40

60

80

100

G-G

aa

a

b

bc c

c



AM

hyp

hal a

bund

ance

(mc

m3 )






0

10

20

30

40

50

60

70

a

a

a

AM

hyp

hal d

ensit

y (m

cm

3 )



4grasses in the







5 Conclusions







References
















































































Journal of












Volume 2014

Advances in









Geophysics

















0 30 6015(km)

N

W E

S



3 Results


0 30 6015(km)

N

W E

S



WD9 WD8

WD7WD6

WD5WD4

WD3

WD2

WD1

WD20

WD19

WD18WD17

WD16

WD15 WD14

WD13WD12

WD11

GT9

GT8GT7

GT6

GT5

GT4GT3

GT2

GT20

GT19

GT18GT17 GT16GT15

GT14

GT13 GT12

GT11

GT10


WT3 WT2

WT1

WT24WT23

WT22WT21

WT20 WT19 WT18WT17

WT16WT15WT14

WT13WT12WT11

AG9AG8AG7AG6AG5

AG4

AG3 AG2

AG1

AG26

AG25

AG24 AG23

AG22 AG21AG20

AG19 AG18AG17 AG16

AG15 AG14

AG13AG12AG11AG10

GL9

GL8

GL7GL6

GL5

GL4

GL3 GL2

GL1

GL24 GL23

GL22

GL21GL20

GL19

GL18

GL17

GL16

GL15GL14

GL13

GL12

GL11

GL10



1 20= 011 119901 = 074)



2 20= 256 119901 = 010) However




012)





Number ofplots

AM hyphaldensity


rangeP (mgkg)range




1 20= 317


3 44= 456


3 37= 337 119901 = 004) There was no


1 37= 075 119901 = 039)


3 43= 441 119901 = 0009) Post hoc


3 36= 381 119901 = 002) There were no


4 Discussion


0

20

40

60

80

100

G-G

aa

a

b

bc c

c



AM

hyp

hal a

bund

ance

(mc

m3 )






0

10

20

30

40

50

60

70

a

a

a

AM

hyp

hal d

ensit

y (m

cm

3 )



4grasses in the







5 Conclusions







References
















































































Journal of












Volume 2014

Advances in









Geophysics

















Number ofplots

AM hyphaldensity


rangeP (mgkg)range




1 20= 317


3 44= 456


3 37= 337 119901 = 004) There was no


1 37= 075 119901 = 039)


3 43= 441 119901 = 0009) Post hoc


3 36= 381 119901 = 002) There were no


4 Discussion


0

20

40

60

80

100

G-G

aa

a

b

bc c

c



AM

hyp

hal a

bund

ance

(mc

m3 )






0

10

20

30

40

50

60

70

a

a

a

AM

hyp

hal d

ensit

y (m

cm

3 )



4grasses in the







5 Conclusions







References
















































































Journal of












Volume 2014

Advances in









Geophysics
















0

10

20

30

40

50

60

70

a

a

a

AM

hyp

hal d

ensit

y (m

cm

3 )



4grasses in the







5 Conclusions







References
















































































Journal of












Volume 2014

Advances in









Geophysics



















References
















































































Journal of












Volume 2014

Advances in









Geophysics




































































Journal of












Volume 2014

Advances in









Geophysics














research article land-cover legacy effects on arbuscular...

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