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Moisture and nutrients determine the distribution and richness of India's large herbivore species assemblage

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Moisture and nutrients determine the distribution and richness of India's large herbivore species assemblage
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  This article appeared in a journal published by Elsevier. The attachedcopy is furnished to the author for internal non-commercial researchand education use, including for instruction at the authors institutionand sharing with colleagues.Other uses, including reproduction and distribution, or selling orlicensing copies, or posting to personal, institutional or third partywebsites are prohibited.In most cases authors are permitted to post their version of thearticle (e.g. in Word or Tex form) to their personal website orinstitutional repository. Authors requiring further informationregarding Elsevier’s archiving and manuscript policies areencouraged to visit:http://www.elsevier.com/copyright  Author's personal copy Basic and Applied Ecology 12 (2011) 634–642 Moisture and nutrients determine the distribution and richness of India’slarge herbivore species assemblage Farshid S. Ahrestani a , b , ∗ , Ignas M.A. Heitkönig a , Frank van Langevelde a , SrinivasVaidyanathan c , M.D. Madhusudan d , Herbert H.T. Prins a a  Resource Ecology Group, Wageningen University, The Netherlands b Frontier Wildlife Conservation, Pune, India c Foundation for Ecological Research, Advocacy and Learning, Puducherry, India d  Nature Conservation Foundation, Mysore, India Received 12 April 2011; accepted 23 August 2011 Abstract Thegoalofthisstudywastotestwhetherbody-massbasedforagingprinciples,guidedbyplantavailablemoisture(PAM)andplant available nutrients (PAN), could explain large mammalian herbivore species distribution and richness in India. We tested(1) whether the occurrence of larger-bodied herbivore species increases with PAM, but is independent of PAN, (2) whether theoccurrence of smaller-bodied herbivore species decreases with PAM, but increases with PAN, and (3) whether herbivore speciesrichness is highest in areas with intermediate PAM and high PAN. We analyzed the distribution and richness of the 16 large(>10kg) herbivore species found in sub-Himalayan mainland India. Since the distributions of large herbivores in India havebeen altered by historic human activity, we only used India’s largest 76 protected areas as data points, with respect to PAM(log 10 (rainfall/potential evapotranspiration)), PAN (soil cation exchange capacity), elevation, tree cover, and fire frequency.Using regression and null models to analyze the data, we found positive relations between PAM and the occurrences of thelarger-bodied species (elephant and gaur), and negative relations between PAM and the occurrences of smaller-bodied species(chinkara, four-horned antelope and blackbuck). We also found positive relations between the occurrence of the smaller-bodiedspecies and PAN. Large herbivore species richness in India is highest in Kanha and Indravati, areas with high PAN andintermediate PAM. We found that elevation, tree cover and fire frequency were insignificant predictors of herbivore speciesrichness, although elevation and tree cover explained the distribution of a few species. Based on our null model analyses results,we conclude that moisture and soil nutrients are important in determining large herbivore species distribution and richness insub-Himalayan India. Zusammenfassung Das Ziel dieser Untersuchung war es zu prüfen, ob Körpergewicht-basierte Prinzipien der Futtersuche, gesteuert durchpflanzenverfügbare Feuchtigkeit (PAM) und Nährstoffverfügbarkeit (PAN), die Verbreitung und den Artenreichtum herbivorerGroßsäuger in Indien erklären können. Wir testeten, (1) ob das Auftreten der großen Herbivoren mit der PAM zunahm, währendes unabhängig von PAN sein sollte, (2) ob das Auftreten der kleineren Herbivorenarten mit der PAM abnahm, aber mit derPAN zunahm, und (3) ob der Artenreichtum der Herbivoren am höchsten in Gebieten mit mittlerer PAM und hoher PAN war. ∗ Corresponding author at: Department of Ecology, Evolution and Environmental Biology, Columbia University, USA. Tel.: +1 9083136180;fax: +1 2128548188.  E-mail address:  farshid.ahrestani@gmail.com (F.S. Ahrestani).1439-1791/$ – see front matter © 2011 Gesellschaft für Ökologie. Published by Elsevier GmbH. All rights reserved.doi:10.1016/j.baae.2011.08.008  Author's personal copy F.S. Ahrestani et al. / Basic and Applied Ecology 12 (2011) 634–642 635 Wir analysierten die Verbreitung und den Artenreichtum der 16 großen (>10kg) Herbivorenarten, die in der Sub-Himalaya-Region Indiens gefunden werden. Da die Verbreitung der großen Herbivoren in Indien anthropogen beeinflusst wurde, nutztenwir nur die 76 größten Schutzgebiete Indiens als Datenpunkte und berücksichtigten PAM (log (Niederschlag/potentielleEvapotranspiration)),PAN(KationenaustauschkapazitätdesBodens),Höhe,Kronenbedeckung,unddieHäufigkeitvonFeuern.Wir setzten Regression und Null-Modelle ein, um die Daten zu analysieren, und wir fanden positive Beziehungen zwischenPAM und dem Auftreten der größeren Herbivoren (Elefant, Gaur) und negative Beziehungen zwischen PAM und dem Auftretender kleineren Arten (Indische Gazelle, Vierhornantilope, Hirschziegenantilope). Wir fanden außerdem positive Beziehungenzwischen dem Auftreten der kleineren Arten und PAN. Der Artenreichtum der großen Herbivorenarten ist am größten inKanha und Indravati, Regionen mit hoher PAN und mittlerer PAM. Wir fanden, dass die Höhe, Kronenbedeckung und Feuer-häufigkeit unbedeutende Prädiktoren des Artenreichtums der Herbivoren waren, auch wenn Höhe und Kronenbedeckung dieVerbreitung einiger Arten erklärten. Aus den Ergebnissen unserer Null-Modell-Analysen schlossen wir, dass Feuchtigkeit undNährstoffe im Boden wichtig sind für die Bestimmung der Verbreitung und den Artenreichtum der großen Herbivoren in derSub-Himalaya-Region Indiens.© 2011 Gesellschaft für Ökologie. Published by Elsevier GmbH. All rights reserved.  Keywords:  Body mass; Diversity; Elevation; Fire frequency; Plant available moisture; Plant available nutrients; Soil fertility; Tree cover Introduction Understandingthedistributionofspeciesandspeciesrich-ness has been central to ecology and remains an activeand dynamic research area given the changing patterns inlocal and global biodiversity (Rahbek 2005; Field et al.2009). Studies from Africa, where large mammalian her-bivore species richness is the highest in the world, haveshown that the variation in the distribution of large herbi-vore species correlates significantly with the variation in thequality and quantity of forage (Coe, Cumming, & Phillipson1976; East 1984; Fritz & Duncun 1994). An herbivore mustencounter forage of sufficient quality (nutrient concentra-tions) and quantity (biomass density) to persist in an area.Since plant available moisture (PAM) and plant availablenutrients (PAN) are the two principal determinants of plantquantity and quality (Milchunus, Forwood, & Lauenroth1994; Milchunus, Varnamkhasti, Lauenroth, & Goetz 1995),PAM and PAN are therefore considered key determinants of the distribution of large herbivore species and richness.Two foraging principles that relate species body mass toplant quality and quantity are integral to models that explainlarge herbivore species distribution, composition and rich-ness(McNaughton,Ruess,&Seagle1988;Prins&Olff1998;Olff, Ritchie, & Prins 2002): larger-bodied species are capa-ble of surviving on resources of lower quality better thansmaller-bodiedspecies;and,smaller-bodiedspeciesarecapa-ble of surviving in areas where plant quantity is insufficientto support larger-bodied species (Bell 1971; Jarman 1974;Demment & Van Soest 1985). The most recent model—Olff,Ritchie, & Prins 2002—argues that large herbivore speciescomposition and richness on a continental scale can beexplained on principles that relate species body mass, plantquantity and quality, and PAM and PAN. For example, therequirement for forage quantity increases with increasingspecies body mass, and given that plant quantity is pos-itively related to PAM, it follows that the occurrence of larger-bodied herbivore species is positively related to PAM.Also, despite the positive relation of forage quality and PAN,the occurrence of larger-bodied herbivore species should beindependentofPANbecauselarger-bodiedherbivorespeciesare tolerant of lower forage quality. Therefore, the diver-sity of different-sized herbivores capable of surviving at thecombination of PAM and PAN levels in an area reflectshow many herbivore species (richness) can persist in thatarea.Other environmental variables—like elevation (McCain2007), tree cover (Riginos & Grace 2008), and fire fre- quency (Klop & Prins 2008)—are also known to explainthe variation in large herbivore species richness. For exam-ple, Klop and Prins (2008) found that evapotranspiration andsoil nutrients alone failed to predict the diversity patternsof grazing herbivores in West Africa; rather it was anthro-pogenic fires that modify the quality and structure of theherbaceous sward. The goal of this study is to test whetherlarge mammalian herbivore species distribution and richnessin the Indian sub-continent can be explained either by thebody-mass based foraging principles, guided by PAM andPAN, or by other environmental variables (elevation, treecover, and fire frequency). The Indian sub-continent with itsrich large herbivore species assemblage—that is distributedoverwidemoistureandsoilnutrientgradientsandhasabodymass range comparable to what is found in Africa—providesanidealcasefortestingthefollowingpredictionswithrespectto the distribution of large mammalian species and their rich-ness:(1)theoccurrenceoflarger-bodiedherbivorespecies(a)increaseswithPAM,but(b)isgenerallyindependentofPAN.Since smaller-bodied herbivores require high quality forage,and plant quality is negatively correlated to PAM, but is pos-itively correlated to PAN (Walker & Langridge 1997), (2)the occurrence of a smaller-bodied herbivore species should(a) decrease with PAM, but (b) increase with PAN. Basedon predictions 1 and 2, we also tested whether (3) the meanbody mass of all species (not individuals) in an area wouldincrease with PAM and then level off, but would decreasecontinuously with PAN. Finally we tested (4) whether large  Author's personal copy 636 F.S. Ahrestani et al. / Basic and Applied Ecology 12 (2011) 634–642 mammalian herbivore species richness should be highest inareas with high PAN and intermediate PAM. Methods Data collection We omitted India’s Trans-Himalaya, Himalaya, andCoastal biogeographic zones from the analysis becauseof their inherent confounding abiotic factors of snow andflooded terrain. The study area, therefore, included the com-bined extent (2,500,000km 2 land cover) of India’s other 6mainland biogeographic zones (Rogers & Panwar 1988): theWestern Ghats and Northeast zones that are characterized byhighrainfallandhighbiodiversity;theDeccanPeninsula,thelargest zone, is characterized by volcanic soils and distinctwet and dry seasons; the Gangetic Plain encompasses theflood plain of the Ganges river; and the Indian Desert andSemi-arid zones are characterized by reduced rainfall.We restricted our analyses to large mammalian herbivorespecies with mass >10kg as the distribution data on themousedeer( Tragulusmeminna ),whichis<10kg,isnotwelldocumented and had to be excluded. Therefore, the datasetincluded occurrence data of 16 large herbivores species fromall ( n =76) protected areas >200km 2 within the study area(see Appendix A: Tables 1 and 2; Fig. 1). The reason forchoosing protected areas of a relatively large size was toreduce the probability of selecting areas that might haveexperienced recent extirpations, particularly of the largestspecies (Karanth, Nichols, Karanth, Hines, & Christensen2010). The presence/absence of the species in the protectedareas was determined by thoroughly referring to individualprotected area reports and were verified by leading Indianwildlife experts (A. J. T. Johnsingh, J. C. Daniel, and T. R.Shankar Raman).PAM for each protected area was calculated aslog 10 (annual rainfall/annual potential evapotranspiration).The values of PAM spanned many orders of magnitudeand therefore we log transformed the PAM ratio (whichincreased its explanatory power in regressions). Rainfalldata were derived from Hijmans, Cameron, Parra, Jones,and Jarvis (2005) WorldClim database at a spatial reso-lution 0.5 × 0.5arcmin (1km ∼ 0.5arcmin), and potentialevapotranspiration (PET) from Ahn and Tateishi (1994) ata spatial grid cell resolution of 30 × 30arcmin. We choseAhn and Teteishi’s data despite its relatively coarse scale fortwo reasons: (1) because it has been used in other studiessimilar to ours (e.g., Klop & Prins 2008), and (2) becauseother well-known climatic and ecological datasets of finerscale, like WorldClim and MODIS NPP, do not have evap-otranspiration data. Estimates of PAN were derived at ascale of 5 × 5arcmin from International Soil Reference andInformation Centre’s (ISRIC) global soil database (Batjes2006). The ISRIC database provides data for total nitro-gen (gkg − 1 ), organic carbon content (gCkg − 1 ), and cationexchange capacity (cmol c  kg − 1 ), but not for phosphorous.To enable a comparison with predictions made by Olff et al.(2002) we used cation exchange capacity of the top 20cm of soil as an index of PAN (Mengel & Krikby 2001). The PAMindex for our sites ranged from − 0.84 to 0.52 (see AppendixA: Fig. 2A) and the PAN index ranged from 3.2 to 42.5 (seeAppendix A: Fig. 2B).The coarse scale of the PET dataset allowed us to deriveonly one PET value for ∼ 70% of the protected areas. Also,all the three datasets (rainfall, evapotranspiration, and cationexchange capacity) were of different spatial resolutions.Therefore,giventheconstrainingnatureoftheavailabledata,we derived environmental data from a single centroid point(provided by UNEP’s World Database on Protected Areas)in each protected area.Data for elevation (m) were derived from the Global LandOne-Kilometre Base Elevation (GLOBE) Digital ElevationModel (Hastings & Dunbar 1998); data for tree cover (%)from the Global Land Cover facility database (Hansen et al.2003); and data for fire frequency (number of fires in sevenyears) from the Institute for Environment and Sustainability,Global Burnt Area database (Carmona-Moreno et al. 2005). Statistical analysis Since species occurrence data are binary in nature, predic-tions 1 and 2 were tested using multiple logistic regressionmodels that analyzed the occurrence of individual species(see Appendix A: Table 1) as a function of PAM, PAN, treecover, and elevation (We had to omit fire as a predictor vari-able in our logistic regression models as the range of the firefrequency data was small (0–3) and 67 sites had the value0). Logistic regression models do not satisfactorily fit dataof species that are either rare or widely distributed. There-fore, we present logistic regression results for those speciesthat were found in 10–90% of the 76 areas analyzed, i.e., wedo not report the inaccurate fits of logistic regression modelsfor species found in less than 10% (rhino, wild buffalo, wildass, barasingha, hog deer and Nilgiri Tahr) nor those foundin over 90% (sambar, chital and wild pig).To test prediction 3, we analyzed the mean body mass(mean BM) of all 16 large herbivore species (across species,not across individuals) present in each protected area as afunction of PAM and PAN using ordinary least square (OLS)regression models. Elephants, because of their large bodymass, have the capacity to significantly impact the mean BMof an area; to account for this effect, the presence of elephantwas included as a binary factor in these models.To test prediction 4, simple and multiple OLS regressionmodelswithstepwisevariableselectionwereusedtoanalyzespecies richness (of all 16 species) as a function of PAM,PAN,treecoverandelevationacrosssites.Sincethedatawerespatialinnature,werepeatedthemultipleregressionanalysiswith spatial simultaneous autoregressive (SAR) models thatcorrectforpotentialspatialauto-correlationbiasesindatasets  Author's personal copy F.S. 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