diversity Diversity Diversity diversity 1424-2818 MDPI 10.3390/d5010026 diversity-05-00026 Article Dissimilarity of Ant Communities Increases with Precipitation, but not Reduced Land-Use Intensity, in Indonesian Cacao Agroforestry Rizali Akhmad 1 2 * Clough Yann 1 Buchori Damayanti 2 Tscharntke Teja 1 Agroecology, Department of Crop Science, University of Göttingen, Grisebachstrasse 6, D-37077, Göttingen, Germany; E-Mails: yclough@gwdg.de (Y.C.); ttschar@gwdg.de (T.T.) Department of Plant Protection, Faculty of Agriculture, Bogor Agricultural University, Kampus IPB Dramaga, Bogor, 16680, West Java, Indonesia; E-Mail: dami@indo.net.id (D.B.) Author to whom correspondence should be addressed; E-Mail: arizali@gwdg.de; Tel.: +49-551-393-739; Fax: +49-551-398-806. 31 01 2013 03 2013 5 1 26 38 12 11 2012 28 12 2012 22 01 2013 © 2013 by the authors; licensee MDPI, Basel, Switzerland. 2013

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).

Land-use degradation and climate change are well-known drivers of biodiversity loss, but little information is available about their potential interaction. Here, we focus on the effects of land-use and precipitation on ant diversity in cacao agroforestry. In Central Sulawesi, Indonesia, we selected 16 cacao agroforestry plots with a shaded vs. unshaded plot in each of eight villages differing in precipitation (1032–2051 mm annual rainfall). On each plot, 10 cacao trees with similar size and age (7–10 years) were selected for hand collection of ants on each cacao tree and the soil surface. In total, we found 80 ant species belonging to five subfamilies. Land-use intensification (removal of shade trees) and precipitation had no effect on species richness of ants per cacao tree (alpha diversity) and, in an additive partitioning approach, within-plot beta diversity. However, higher precipitation (but not shade) significantly increased ant species dissimilarity across cacao trees within a plot, with ant species showing contrasting responses to precipitation. Reduced precipitation causing drought stress appeared to contribute to convergence of ant community structure, presumably via reduced heterogeneity in cacao tree growth. In conclusion, reduced precipitation greatly influenced ant community dissimilarity and appeared to be more important for ant community structure than land-use intensification.

 alpha diversity beta diversity community dissimilarity land-use precipitation 1. Introduction

Land-use degradation and climate change are well-known drivers of biodiversity loss [1]. Temperature increase and reduced precipitation can have an effect on the distribution, reproduction and behavior of species [2], and may even favor invasive species that are able to adapt to this altered environment [3]. However, little is known of the interaction of land-use degradation and climate change, although both together may greatly increase biodiversity losses [4].

In agricultural ecosystems, land-use intensification, exacerbated by climate change effects, may severely affect functional biodiversity, for example, natural enemies providing successful biological control. Increasing carbon dioxide and temperature can also facilitate the presence of pests and diseases in agricultural habitat and reduce agrobiodiversity [5]. In addition, climate change can have direct effect on crop plant growth through increased temperature, drought, rainfall and tropical storms [5].

Agroforestry systems can provide suitable habitat for biodiversity [6] and may mitigate effects of climate change [7]. However, this depends on the management. Agroforestry intensification by shade tree removal [7,8] and pesticide application [9] has particularly adverse effects on biodiversity. This may have functional consequences, especially if organisms important for pest regulation, such as ants [10], are affected. Bos et al. [11] found that decreasing shade-tree cover negatively affects ant diversity in cacao agroforestry. Wielgoss et al. [12] suggest that ant diversity in cacao agroforestry is affected more by temperature than decreasing numbers of shade trees. In general, however, the joint role of climate and shade-tree loss in affecting ant species communities has not been addressed, despite its potential significance in ecosystem response to changing rainfall patterns and land-use change.

In this study, we analyze how land-use change and precipitation affect ant diversity in agroforestry. We selected 16 cacao agroforestry plots located in eight villages around Lore Lindu National Park (LLNP) in Central Sulawesi, Indonesia. In each village, we studied one shaded and one unshaded agroforestry system, while the eight villages were situated along a precipitation gradient. We asked the following questions: (i) How does ant community structure change along land-use intensity and precipitation gradients? (ii) Does the ant communities on the cacao tree and on the ground show different responses? (iii) Which ant species show the strongest responses to the precipitation gradient?

 2. Experimental Section 2.1. Study Sites

The 16 studied plots were cacao agroforestry systems located in eight villages around the Lore Lindu National Park (LLNP), Central Sulawesi, Indonesia (Figure 1). The agroforestry systems differed in land-use intensity (shaded vs. unshaded) and the villages in precipitation (1032 to 2051 mm/year) (Table 1).

Location map of the 16 cacao agroforestry plots in eight villages with different precipitation levels. Villages are located around Lore Lindu National Park, Central Sulawesi, Indonesia.

 diversity-05-00026-t001_Table 1

Observed and estimated ant species richness of the 16 plots with different land-use (A: shaded; B: unshaded cacao agroforestry) and different precipitation located in eight villages around Lore Lindu National Park, Central Sulawesi, Indonesia.

No Village Land-use Latitude (°S) Longitude (°E) Altitude (m asl) Precipitation (mm/year) Observed species Estimated species (%)*
1. Berdikari A 01.11693 120.09266 646 2,051 24 28.5 (84.2)
B 01.13420 120.07861 603 17 25.0 (68.0)
2. Sintuwu A 01.16213 120.05642 554 1,430 26 32.8 (79.4)
B 01.16339 120.05790 567 20 52.0 (38.5)
3. Bulili A 01.18261 120.09550 582 1,504 17 29.3 (58.1)
B 01.18738 120.09239 652 18 22.2 (81.2)
4. Pandere A 01.18844 119.95393 179 1,160 21 23.1 (91.0)
B 01.20482 119.94063 102 18 19.5 (92.3)
5. Sidondo A 01.08366 119.89272 41 1,032 23 35.3 (65.2)
B 01.08764 119.87599 27 16 17.5 (91.4)
6. Boladangko A 01.44530 119.98057 523 1,590 24 44.3 (54.2)
B 01.44499 119.98001 558 18 20.7 (87.1)
7. Toro A 01.50238 120.04055 800 1,704 26 32.4 (80.2)
B 01.50237 120.04109 797 21 24.1 (87.0)
8. Lempelero A 01.66104 120.04093 432 1,742 14 16.7 (84.0)
B 01.66035 120.04307 438 22 30.1 (73.1)

* Predicted number of species based on Chao estimator of the 10 cacao trees as sampling unit; %, sampled species as a percentage of predicted number of species.

 2.2. Plots Selection and Ant Sampling

Each cacao agroforestry plot differed in agricultural management because it belonged to a different farmer. On each plot (5 m × 15 m), 10 cacao trees with similar size and age (7–10 years) were selected for ant observation. Ants were sampled on all strata i.e., the tree trunk and the soil surface (within area 1 m distance from base of cacao tree) using hand collecting combine with baiting (using tuna and sugar) lasted a maximum of 10 min per tree and conducted both in the morning and afternoon. Hand collection is the best method to record all of ant species inhabiting an area by searching and collecting ants in different microhabitats [13]. Hand collecting was conducted twice in the same cacao trees, in November 2009 and June 2010, to quantify ant species diversity on each cacao tree per plot in different seasons.

Ant specimens were sorted and identified to genus using [14] or were separated according to their external morphology as morphospecies [15]. Some of the ants could be identified to species level with the help of websites (e.g. [16]).

 2.3. Data Analysis

The completeness of sampling on each plot was calculated using the Chao estimator [17]. To test for spatial autocorrelation, we used the Mantel test [18,19] based on the distance and ant similarity among plots. Alpha diversity was derived from mean ant species richness per tree, whereas beta diversity was calculated based on an additive diversity portioning approach [20] with beta diversity resulting from gamma diversity (total ant species in one plot) minus alpha diversity (species richness per tree). The Bray-Curtis dissimilarity index was used to calculate the dissimilarity of ant species communities between the ten cacao tree on each plot, using vegan package in R software [21]. Then, we calculated the community dissimilarity using ordihull within non-metric multidimensional scaling (NMDS) (vegan package). Analysis of variance (ANOVA) and linear models (LM) were used to relate ant diversity and community similarity to the land-use and precipitation gradients. Logit regression was performed to analyze the relationship between ant species presence or absence and the precipitation level. All analyses were conducted using R software [21].

3. Results 3.1. Ant Community Structure along Land-Use Intensity and Precipitation Gradients

In total, we found 80 species belonging to 5 subfamilies in the 16 cacao agroforestry plots (see supplementary material Table S1). The Chao estimate for each plot on almost all 16 sampled cacao agroforestry indicated that these sampling methods captured most of ant species richness (Table 1). Based on the Mantel test, we did not find spatial autocorrelation between similarity of ant communities with nearness distance of plots (Mantel statistic r = 0.161, P = 0.087). We found that mean ant species richness per tree (alpha diversity), beta diversity (richness per plot minus mean richness per tree) and ant species similarity (on the tree and on the soil surface) across the 10 trees per plot were not affected by the presence or absence of shade trees (Table 2). In contrast, precipitation levels significantly affected ant community similarity on the tree (but not on the soil surface) in the cacao agroforestry (Table 2).

diversity-05-00026-t002_Table 2

Effects of shade-tree removal, precipitation and altitude on species richness per tree (alpha diversity), beta diversity and community similarity of ant communities in each stratum, based on 16 cacao agroforestry plots.

Parameters Strata
Total Tree Soil surface
Alpha diversity
Land-use F1,12 = 0.084, P = 0.777 F1,12 = 0.070, P = 0.796 F1,12 = 0.006, P = 0.940
Precipitation F1,12 = 0.003, P = 0.957 F1,12 = 0.415, P = 0.532 F1,12 = 0.059, P = 0.813
Altitude F1,12 = 0.001, P = 0.982 F1,12 = 0.014, P = 0.907 F1,12 = 1.372, P = 0.264
Beta diversity
Land-use F1,12 = 4.950, P = 0.046 F1,12 = 1.511, P = 0.243 F1,1 = 2.379, P = 0.149
Precipitation F1,12 = 0.223, P = 0.645 F1,12 = 1.708, P = 0.216 F1,12 = 0.134, P = 0.721
Altitude F1,12 = 2.779, P = 0.121 F1,12 = 0.286, P = 0.603 F1,12 = 1.980, P= 0.185
Ant community similarity
Land-use F1,12 = 0.277, P = 0.608 F1,12 = 1.854, P = 0.198 F1,12 = 0.576, P = 0.463
Precipitation F1,12 = 5.032, P = 0.045 F1,12 = 7.613, P = 0.017 F1,12 = 0.008, P = 0.932
Altitude F1,12 = 1.025, P = 0.331 F1,1 2= 0.588, P = 0.458 F1,12 = 0.008, P = 0.932

There is a positive correlation between precipitation and altitude (F1,14 = 21.47, P = 0.0004, r2 = 0.58) (see supplementary material Figure S1). Nevertheless, the better predictor of ant species is precipitation (df = 5, AIC = −1.553) than altitude (df = 5, AIC = 2.465) based on the linear mixed effects model (LME). According to the linear model, we found that precipitation was not related to the number of ant species richness per tree (alpha diversity, Table 3, Figure 2a) and beta diversity on the tree (Table 3, Figure 2b). However, precipitation was closely correlated with the dissimilarity distance among cacao trees on each plot. Increasing precipitation was followed by increasing dissimilarity of ant communities on the tree in the cacao agroforestry systems (Table 3, Figure 2c).

diversity-05-00026-t003_Table 3

Linear model between precipitation and alpha diversity, beta diversity and community similarity in each stratum, based on 16 cacao agroforestry plots.

Parameters Strata
Total Tree Soil
Alpha diversity r2 = −0.071, F1,14 = 0.003, P = 0.954 r2 = −0.036, F1,14 = 0.481, P = 0.450 r2 = −0.067, F1,14 = 0.062, P = 0.808
Beta diversity r2 = −0.059, F1,14 = 0.159, P = 0.697 r2 = 0.047, F1,14 = 1.733, P = 0.209 r2 = −0.063, F1,14 = 0.114, P = 0.740
Ant community similarity r2 = 0.223, F1,14 = 5.296, P =0.037 r2 = 0.280, F1,14 = 6.828, P = 0.021 r2 = −0.071, F1,14 = 0.009, P = 0.927

Linear model between precipitation and (a) the mean number species per tree (alpha diversity, r2 = −0.036, F1,14 = 0.481, P = 0.450), (b) beta diversity (r2 = 0.047, F1,14 = 1.733, P = 0.209) and (c) community dissimilarity (r2 = 0.280, F1,14 = 6.828, P = 0.021) based on species found on all 10 trees per plot.

 3.2. Ant species Responses to Precipitation Gradients

Based on logit regressions for each species, we found that three ant species were related to the precipitation gradients. Crematogaster sp.04 (df = 1, Chi-square = 3.84, P = 0.04, Figure 3a) and Tapinoma melanocephalum (df = 1, Chi-square = 4.59, P = 0.03, Figure 3c) was mainly found in cacao agroforestry with low precipitation (Fig 3c). In contrast, Dolichoderus sp.01 was mainly found in cacao plots with high precipitation (df = 1, Chi-square = 5.06, P = 0.02, Figure 3b). The dominant Dolichoderinae, Philidris cordata, did not show a clear pattern related to precipitation (df = 1, Chi-square = 2.41, P = 0.12, Figure 3d).

Logit regression of ant species with precipitation. (a) Crematogaster sp.04 (df = 1, Chi-square = 3.84, P = 0.04), (b) Dolichoderus sp.01 (df = 1, Chi-square = 5.06, P = 0.02), (c) Tapinoma melanochephalum (df = 1, Chi-square = 4.59, P = 0.03) and (d) Philidris cordata (df = 1, Chi-square = 2.41, P = 0.12).

 4. Discussion

Our results showed that higher levels of precipitation were associated with higher dissimilarity, but not species richness, of ant communities in cacao agroforestry systems, whereas land-use changes such as losses of shade trees from the cacao agroforestry systems were not related to ant community dissimilarity or diversity. These findings support the results of Wielgoss et al. [12] in the same study region that decreasing shade trees did not affect ant diversity. However, the study by Bos et al. [11] showed that reduced numbers of shade trees can negatively affect ant diversity, in particular of forest ants, in cacao agroforestry. In the study region of Bos et al. [11], but not Wielgoss et al. [12], natural rainforest surrounded their cacao agroforestry systems. Adjacent rainforests (of the national park) provide high forest ant diversity colonizing cacao agroforestry if characterized by high canopy cover from shade-trees. Therefore, shade trees presumably to be particularly important when rainforest habitat is surrounding cacao agroforestry as a nearby source of forest ants. In this study, the cacao agroforestry systems were not surrounded by, but rather isolated from rainforests, explaining why shade-tree level was not a predictor of ant diversity.

Precipitation did not affect number of ant species per tree (alpha diversity) in cacao agroforestry. This result is similar to that of Delsinne et al. [22], who did not find a relationship between precipitation and local ant species richness in arid ecosystems. In our research, the gradient of precipitation was limited (1032 to 2051 mm/year), which may explain why alpha diversity did not show a positive correlation of precipitation and ant diversity [23,24]. Nevertheless, we found that increasing precipitation decreased similarity of ant communities in the cacao agroforestry systems.

High precipitation may influence ant communities because of its negative relationship to ant nesting site availability, which is an important stressor for ants [25]. Nesting site limitation can shape ant community composition, affecting co-existence in addition to factors such as competition, environmental stress and disturbance [26]. In addition, higher precipitation caused higher heterogeneity of ant communities, which should be due to higher heterogeneity of cacao tree growth when drought stress is no longer a dominant and homogenizing factor. Reduced precipitation can be an important stress shaping ant communities in a similar way, i.e., converging ant communities, whereas higher precipitation appeared to allow divergence of ant community structure across trees. Higher precipitation is part of environmental instability affecting the similarity of coexisting species [27].

The ant species differed in their response to the precipitation level. Dolichoderus sp.01 tended to be mainly found in cacao agroforestry with higher precipitation. As generalized foragers and distributed mainly in tropical region [28], this species can be expected to suffer most from El Nino (ENSO) droughts, which are common in the region [29]. In contrast, T. melanocephalum, a tramp or human commensal species [30] and Crematogaster sp.04, an arboreal species and nesting in hollow tree trunks [28] were only found in cacao agroforestry with low precipitation, benefiting from droughts. The dominant and invasive species P. cordata was not affected by high precipitation and drought, which may be a reason why this species spread widely and became dominant in cacao agroforestry in Sulawesi.

 5. Conclusions

Land-use intensity and precipitation gradients did not affect the ant diversity per cacao tree (alpha diversity) and beta diversity in agroforestry systems in Sulawesi. However, high precipitation enhanced ant community dissimilarity, presumably via increased heterogeneity in cacao growth with increasing precipitation and subsequent differences in ant colonization, with ant species responding differently to precipitation level. Our results show that changes of precipitation, which are expected to occur in the study region due to El Nino (ENSO) droughts, should contribute to the homogenization of ant community structure.

Acknowledgments

Thanks to our field assistants (Fifin, Moh. Fadlan, Akhmad Syakur and Hadiprayitno) and our laboratory assistants (Nur Ivon and Dewi Utaminingsih). Thanks to the owners of cacao agroforestry in Berdikari (Yosias Nthu and Yosep Sapangan), Sintuwu (Tahana M. Suari and Iskandar), Bulili (Sofyan and Tahang), Pandere (Kunci and Nusrin Abd. Samad), Sidondo (Asran Hadoha and H. Manno), Boladangko (Hamzah and Toruba), Toro (Faldin) and Lempelero (Mursan and Pohabe). Thanks also to the staff of the Center for Tropical Forest Margin (CTFM), University of Tadulako, especially to Pak Abdul Rauf and Mbak Anti who were helping with administration during the research. This research project was funded by the German Science Foundation (DFG), Bogor Agricultural University (IPB), and Directorate General of Higher Education, Ministry of National Education of the Republic of Indonesia.

 References Sala O.E. Chapin F.S. Armesto J.J. Berlow E. Bloomfield J. Dirzo R. Huber-Sanwald E. Huenneke L.F. Jackson R.B. Kinzig A. Biodiversity-Global biodiversity scenarios for the year 2100 Science 2000 287 1770 1774 10.1126/science.287.5459.1770 Lovejoy T.E. Climate change Conservation Biology for All Sodhi N.S. Ehrlich P.R. Oxford University Press Oxford, UK 2010 153 162 Hellmann J.J. Byers J.E. Bierwagen B.G. Dukes J.S. Five potential consequences of climate change for invasive species Conserv. Biol. 2008 22 534 543 10.1111/j.1523-1739.2008.00951.x Tylianakis J.M. Didham R.K. Bascompte J. Wardle D.A. Global change and species interactions in terrestrial ecosystems Ecol. Lett. 2008 11 1351 1363 10.1111/j.1461-0248.2008.01250.x Gornall J. Betts R. Burke E. Clark R. Camp J. Willett K. Wiltshire A. Implications of climate change for agricultural productivity in the early twenty-first century Philos. Trans. R. Soc. Lond. Ser. B 2010 365 2973 2989 10.1098/rstb.2010.0158 Bhagwat S.A. Willis K.J. Birks H.J.B. Whittaker R.J. Agroforestry: a refuge for tropical biodiversity? Trends Ecol. Evol. 2008 23 261 267 10.1016/j.tree.2008.01.005 Tscharntke T. Clough Y. Bhagwat S.A. Buchori D. Faust H. Hertel D. Holscher D. Juhrbandt J. Kessler M. Perfecto I. Scherber C. Schroth G. Veldkamp E. Wanger T.C. Multifunctional shade-tree management in tropical agroforestry landscapes- a review J. Appl. Ecol. 2011 48 619 629 10.1111/j.1365-2664.2010.01939.x Clough Y. Barkmann J. Juhrbandt J. Kessler M. Wanger T.C. Anshary A. Buchori D. Cicuzza D. Darras K. Putra D.D. Combining high biodiversity with high yields in tropical agroforests Proc. Natl. Acad. Sci. USA 2011 108 8311 8316 2153687310.1073/pnas.1016799108 Wanger T.C. Rauf A. Schwarze S. Pesticides and tropical biodiversity Front. Ecol. Environ. 2010 8 178 179 Philpott S.M. Armbrecht I. Biodiversity in tropical agroforests and the ecological role of ants and ant diversity in predatory function Ecol. Entomol. 2006 31 369 377 10.1111/j.1365-2311.2006.00793.x Bos M.M. Steffan-Dewenter I. Tscharntke T. The contribution of cacao agroforests to the conservation of lower canopy ant and beetle diversity in Indonesia Biodivers. Conserv. 2007 16 2429 2444 10.1007/s10531-007-9196-0 Wielgoss A. Tscharntke T. Buchori D. Fiala B. Clough Y. Temperature and a dominant dolichoderine ant species affect ant diversity in Indonesian cacao plantations Agric. Ecosyst. Environ. 2010 135 253 259 10.1016/j.agee.2009.10.003 Bestelmeyer B.T. Agosti D. Alonso L.E. Brandão C.R.F. Brown W.L. Jr. Delabie J.H.C. Silvestre R. Field techniques for the study of ground-dwelling ants: an overview, description, and evaluation Ants: Standard Methods for Measuring and Monitoring Biodiversity Agosti D. Majer J.D. Alonso L.E. Schultz T.R. Smithsonian Institution Press Washington, DC, USA 2000 122 144 Bolton B. Identification Guide to the Ant Genera of the World Harvard University Press Cambridge, UK 1994 222 Lattke J.E. Specimen processing: building and curating an ant collection Ants: Standard Methods for Measuring and Monitoring Biodiversity Agosti D. Majer J.D. Alonso L.E. Schultz T.R. Smithsonian Institution Press Washington, DC, USA 2000 155 171 Antweb Available online:http://www.antweb.org(accessed on 20 January 2010) Colwell R.K. Coddington J.A. Estimating terrestrial biodiversity through extrapolation Philos. Trans. R. Soc. Lond. Ser. B 1994 345 101 118 10.1098/rstb.1994.0091 Mantel N. The detection of disease clustering and a generalized regression approach Cancer Res. 1967 27 209 220 6018555 Legendre P. Legendre L. Numerical ecology 2nd English Elsevier Dordrecht, The Netherlands 1998 Gering J.C. Crist T.O. The alpha-beta-regional relationship: providing new insights into local-regional patterns of species richness and scale dependence of diversity components Ecol. Lett. 2002 5 433 444 10.1046/j.1461-0248.2002.00335.x R Development Core Team R: A Language and Environment for Statistical Computing R Foundation for Statistical Computing Vienna, Austria 2011 Delsinne T. Roisin Y. Herbauts J. Leponce M. Ant diversity along a wide rainfall gradient in the Paraguayan dry Chaco J. Arid Environ. 2010 74 1149 1155 10.1016/j.jaridenv.2010.03.014 Dunn R.R. Agosti D. Andersen A.N. Arnan X. Bruhl C.A. Cerdá X. Ellison A.M. Fisher B.L. Fitzpatrick M.C. Gibb H. Climatic drivers of hemispheric asymmetry in global patterns of ant species richness Ecol. Lett. 2009 12 324 333 10.1111/j.1461-0248.2009.01291.x Dunn R.R. Guenard B. Weiser M.D. Sanders N.J. Geographic gradients Ant Ecology Lach L. Parr C.L. Abbott K.L. Oxford University Press New York, NY, USA 2010 38 58 Andersen A.N. Global ecology of rainforest ants: functional groups in relation to environmental stress and disturbance Ants: Standard Methods for Measuring and Monitoring Biodiversity Agosti D. Majer J.D. Alonso L.E. Schultz T.R. Smithsonian Institution Press Washington, DC, USA 2000 25 34 Andersen A.N. A classification of Australian ant communities, based on functional groups which parallel plant life-forms in relation to stress and disturbance J. Biogeogr. 1995 22 15 29 10.2307/2846070 MacArthur R. Levins R. The limiting similarity, convergence, and divergence of coexisting species Am. Nat. 1967 101 377 385 10.1086/282505 Brown W.L. Jr. Diversity of ants Ants: Standard Methods for Measuring and Monitoring Biodiversity Agosti D. Majer J.D. Alonso L.E. Schultz T.R. Smithsonian Institution Press Washington, DC, USA 2000 45 79 Gerold G. Leemhuis C. Effects of “ENSO-events” and rainforest conversion on river discharge in Central Sulawesi (Indonesia) Tropical Rainforests and Agroforests under Global Change: Ecological and Socio-economic Valuations Tscharntke T. Leuschner C. Veldkamp E. Faust H. Guhardja E. Bidin A. Springer-Verlag Berlin 2010 327 350 McGlynn T.P. The worldwide transfer of ants: geographical distribution and ecological invasions J. Biogeogr. 1999 26 535 548 10.1046/j.1365-2699.1999.00310.x Supplementary Material diversity-05-00026-t004_Table 4

The occurrence of ant species (proportion of trees occupied, 10 cacao trees observed) collected in the 16 cacao agroforestry plots in eight villages (1: Berdikari, 2: Sintuwu, 3: Bulili, 4: Pandere, 5: Sidondo, 6: Boladangko, 7: Toro, and 8: Lempelero) with different land-use (A: shaded, B: unshaded cacao agroforestry). Morphospecies were based on the different of external morphology.

No Species Village
1 2 3 4 5 6 7 8
A B A B A B A B A B A B A B A B
Dolichoderinae
1. Dolichoderus sp.01 0.5 0.4 0.5 0.2 0.7 0.9 0.2 0.5 0.2 0.1 0.2
2. Dolichoderus thoracicus 1 1
3. Philidris cordata 0.7 1 1 1 1 0.7 1 0.9 1 1 1
4. Tapinoma melanocephalum 0.2 0.7 0.3 0.3 0.9 1 0.2
5. Tapinoma sp.01 0.4 1 0.2 0.7 0.9 0.1 0.7 0.8 0.7 0.2
6. Technomyrmex albipes 0.3 1 0.9 0.2
7. Technomyrmex sp.01 0.3
Formicinae
8. Anoplolepis gracilipes 0.1 0.5 1 0.8 0.3 0.5 0.4
9. Camponotus recticulatus 0.4 0.9 0.2 0.7 0.1 0.1 0.3 0.6 0.1 0.5
10. Camponotus sp.01 0.9 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
11. Camponotus sp.02 0.1
12. Echinopla lineata 0.1 0.8 0.5
13. Oecophylla smaragdina 0.1 0.2 0.1 1
14. Paratrechina longicornis 1 0.4
15. Nylanderia sp.01 1 0.9 1 1 1 0.6 1 0.8 1 0.8 1 1 1 0.9
16. Nylanderia sp.02 1
17. Nylanderia sp.03 0.7
18. Nylanderia sp.04 0.1 0.8 0.3 1
19. Plagiolepis sp.01 0.9
20. Polyrachis abdominalis 0.3 0.2
21. Polyrachis dives 0.7 0.5 0.3 0.2 0.2 0.1
22. Polyrachis sp.01 0.3 0.4
23. Polyrachis sp.02 0.5 0.4
24. Polyrachis sp.03 0.1
25. Polyrachis sp.04 0.2
26. Polyrachis sp.05 0.8
27. Polyrachis sp.06 0.1 0.2 0.1
28. Polyrachis sp.07 0.4
29. Pseudolasius sp.01 0.2 0.3 0.1
30. Pseudolasius sp.02 0.3
Myrmicinae
31. Crematogaster sp.01 0.6 0.1 0.7 0.6
32. Crematogaster sp.02 0.6 0.1 0.1 0.2 0.2 0.6 0.1 0.1 0.7 0.3 0.2 0.8 0.2 0.6
33. Crematogaster sp.03 0.2
34. Crematogaster sp.04 0.2 0.9 0.8
35. Crematogaster sp.05 0.3 0.1
36. Monomorium floricola 0.7 0.7 1 0.3 1 0.3 0.2 0.1
37. Monomorium sp.01 0.2 0.1 0.2
38. Monomorium sp.02 0.4 0.1 0.3
39. Monomorium sp.03 0.2
40. Monomorium sp.04 0.1 0.1
41. Monomorium sp.05 0.1 0.2
42. Monomorium sp.06 0.1 0.1
43. Pheidole sp.01 0.3 0.7 0.1 0.3 0.3 0.3 0.7 0.7 0.7 0.6 0.3 0.5 0.2
44. Pheidole sp.02 0.9 0.1 0.1 0.1 0.1 0.6 0.4 0.1
45. Pheidole sp.03 0.4 0.9 0.7 0.7 0.5 0.1 0.4 0.1 0.3 0.1
46. Pheidole sp.04 0.1
47. Pheidole sp.05 0.5 0.1 0.6
48. Pheidole sp.06 0.1 0.4 0.1 0.1 0.2 0.2 0.2
49. Pheidole sp.07 0.1
50. Pheidole sp.08 0.1 0.1
51. Pheidologeton sp.01 0.1
52. Pyramica paradoxa 0.1
53. Solenopsis geminata 0.4
54. Strumigenys sp.01 0.1 0.1 0.1 0.1
55. Tetramorium bicarinatum 0.9 0.1 0.4
56. Tetramorium pasificum 0.2 0.9 0.5 0.3
57. Tetramorium smithi 0.4 0.3 0.1 0.1 0.1 0.1
58. Tetramorium sp.01 0.5
59. Tetramorium sp.02 0.2 0.2
60. Tetramorium sp.03 0.2 0.3
61. Tetramorium sp.04 0.4 0.1 0.1
62. Tetramorium sp.05 0.1 0.1 0.3 0.1 0.1 0.1 0.1
63. Tetramorium sp.06 0.3 0.4 0.1
64. Tetramorium sp.07 0.3
65. Tetramorium sp.08 0.2 0.1
Ponerinae
66. Anochetus graeffei 0.3 0.3 0.4 0.2 0.3 0.2
67. Diacamma rugosum 0.4 0.1 0.6 0.9
68. Hypoponera sp.01 0.2 0.1 0.1 0.2 0.1 0.2
69. Hypoponera sp.02 0.8 0.9 0.3 0.1 0.6 0.8 0.9 0.5 0.7 0.3
70. Hypoponera sp.03 0.1 0.4 0.2
71. Hypoponera sp.04 0.2 1
72. Leptogenys sp.01 0.1 0.2 0.1 0.3
73. Odontomachus simillimus 0.2 0.5 0.7 0.7 1 0.1 0.4 0.3 0.7 0.3 1 0.9 1 0.2
74. Pachycondyla sp.01 0.4 0.1 0.2 0.2 0.1 0.2 0.4
75. Pachycondyla sp.02 0.1
76. Pachycondyla sp.03 0.2
77. Pachycondyla sp.04 0.1
78. Platythyrea sp.01 0.1 0.1 0.1 0.2 0.1 0.1
Pseudomyrmicinae
79. Tetraponera sp.01 0.1
80. Tetraponera sp.02 0.2 0.1

Correlation between precipitation and altitude of the 16 plots of the study area (F1,14 = 21.47, P = 0.0004, r2=0.58).