Next Article in Journal
High Genetic Diversity in Geographically Remote Populations of Endemic and Widespread Coral Reef Angelfishes (genus: Centropyge)
Previous Article in Journal
Are Land Based Surveys a Useful Tool for Managing Marine Species of Coastal Protected Areas?

Diversity 2013, 5(1), 26-38; doi:10.3390/d5010026

Article
Dissimilarity of Ant Communities Increases with Precipitation, but not Reduced Land-Use Intensity, in Indonesian Cacao Agroforestry
Akhmad Rizali 1,2,*, Yann Clough 1, Damayanti Buchori 2 and Teja Tscharntke 1
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.)
2
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.
Received: 12 November 2012; in revised form: 28 December 2012 / Accepted: 22 January 2013 /
Published: 31 January 2013

Abstract

: 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.
Keywords:
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).

Diversity 05 00026 g001 1024
Figure 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.

Click here to enlarge figure

Figure 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 g001 1024
Table 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.

Click here to display table

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.
NoVillageLand-useLatitude (°S)Longitude (°E)Altitude (m asl)Precipitation (mm/year)Observed speciesEstimated species (%)*
1.BerdikariA01.11693120.092666462,0512428.5 (84.2)
B01.13420120.07861603 1725.0 (68.0)
2.SintuwuA01.16213120.056425541,4302632.8 (79.4)
B01.16339120.05790567 2052.0 (38.5)
3.BuliliA01.18261120.095505821,5041729.3 (58.1)
B01.18738120.09239652 1822.2 (81.2)
4.PandereA01.18844119.953931791,1602123.1 (91.0)
B01.20482119.94063102 1819.5 (92.3)
5.SidondoA01.08366119.89272411,0322335.3 (65.2)
B01.08764119.8759927 1617.5 (91.4)
6.BoladangkoA01.44530119.980575231,5902444.3 (54.2)
B01.44499119.98001558 1820.7 (87.1)
7.ToroA01.50238120.040558001,7042632.4 (80.2)
B01.50237120.04109797 2124.1 (87.0)
8.LempeleroA01.66104120.040934321,7421416.7 (84.0)
B01.66035120.04307438 2230.1 (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).

Table 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.

Click here to display table

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.
ParametersStrata
TotalTreeSoil surface
Alpha diversity
Land-useF1,12 = 0.084, P = 0.777F1,12 = 0.070, P = 0.796F1,12 = 0.006, P = 0.940
PrecipitationF1,12 = 0.003, P = 0.957F1,12 = 0.415, P = 0.532F1,12 = 0.059, P = 0.813
AltitudeF1,12 = 0.001, P = 0.982F1,12 = 0.014, P = 0.907F1,12 = 1.372, P = 0.264
Beta diversity
Land-useF1,12 = 4.950, P = 0.046F1,12 = 1.511, P = 0.243F1,1 = 2.379, P = 0.149
PrecipitationF1,12 = 0.223, P = 0.645F1,12 = 1.708, P = 0.216F1,12 = 0.134, P = 0.721
AltitudeF1,12 = 2.779, P = 0.121F1,12 = 0.286, P = 0.603F1,12 = 1.980, P= 0.185
Ant community similarity
Land-useF1,12 = 0.277, P = 0.608F1,12 = 1.854, P = 0.198F1,12 = 0.576, P = 0.463
PrecipitationF1,12 = 5.032, P = 0.045F1,12 = 7.613, P = 0.017F1,12 = 0.008, P = 0.932
AltitudeF1,12 = 1.025, P = 0.331F1,1 2= 0.588, P = 0.458F1,12 = 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).

Table Table 3. Linear model between precipitation and alpha diversity, beta diversity and community similarity in each stratum, based on 16 cacao agroforestry plots.

Click here to display table

Table 3. Linear model between precipitation and alpha diversity, beta diversity and community similarity in each stratum, based on 16 cacao agroforestry plots.
ParametersStrata
TotalTreeSoil
Alpha diversityr2 = −0.071, F1,14 = 0.003, P = 0.954r2 = −0.036, F1,14 = 0.481, P = 0.450r2 = −0.067, F1,14 = 0.062, P = 0.808
Beta diversityr2 = −0.059, F1,14 = 0.159, P = 0.697r2 = 0.047, F1,14 = 1.733, P = 0.209r2 = −0.063, F1,14 = 0.114, P = 0.740
Ant community similarityr2 = 0.223, F1,14 = 5.296, P =0.037r2 = 0.280, F1,14 = 6.828, P = 0.021r2 = −0.071, F1,14 = 0.009, P = 0.927
Diversity 05 00026 g002 1024
Figure 2. 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.

Click here to enlarge figure

Figure 2. 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.
Diversity 05 00026 g002 1024

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).

Diversity 05 00026 g003 1024
Figure 3. 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).

Click here to enlarge figure

Figure 3. 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).
Diversity 05 00026 g003 1024

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

  1. 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.; et al. Biodiversity-Global biodiversity scenarios for the year 2100. Science 2000, 287, 1770–1774. [Google Scholar] [CrossRef]
  2. Lovejoy, T.E. Climate change. In Conservation Biology for All; Sodhi, N.S., Ehrlich, P.R., Eds.; Oxford University Press: Oxford, UK, 2010; pp. 153–162. [Google Scholar]
  3. 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. [Google Scholar] [CrossRef]
  4. 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. [Google Scholar] [CrossRef]
  5. 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. [Google Scholar] [CrossRef]
  6. 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. [Google Scholar] [CrossRef]
  7. 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. [Google Scholar] [CrossRef]
  8. Clough, Y.; Barkmann, J.; Juhrbandt, J.; Kessler, M.; Wanger, T.C.; Anshary, A.; Buchori, D.; Cicuzza, D.; Darras, K.; Putra, D.D.; et al. Combining high biodiversity with high yields in tropical agroforests. Proc. Natl. Acad. Sci. USA 2011, 108, 8311–8316. [Google Scholar]
  9. Wanger, T.C.; Rauf, A.; Schwarze, S. Pesticides and tropical biodiversity. Front. Ecol. Environ. 2010, 8, 178–179. [Google Scholar]
  10. 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. [Google Scholar] [CrossRef]
  11. 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. [Google Scholar] [CrossRef]
  12. 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. [Google Scholar] [CrossRef]
  13. 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. In Ants: Standard Methods for Measuring and Monitoring Biodiversity; Agosti, D., Majer, J.D., Alonso, L.E., Schultz, T.R., Eds.; Smithsonian Institution Press: Washington, DC, USA, 2000; pp. 122–144. [Google Scholar]
  14. Bolton, B. Identification Guide to the Ant Genera of the World; Harvard University Press: Cambridge, UK, 1994; p. 222. [Google Scholar]
  15. Lattke, J.E. Specimen processing: building and curating an ant collection. In Ants: Standard Methods for Measuring and Monitoring Biodiversity; Agosti, D., Majer, J.D., Alonso, L.E., Schultz, T.R., Eds.; Smithsonian Institution Press: Washington, DC, USA, 2000; pp. 155–171. [Google Scholar]
  16. Antweb. Available online: http://www.antweb.org (accessed on 20 January 2010).
  17. Colwell, R.K.; Coddington, J.A. Estimating terrestrial biodiversity through extrapolation. Philos. Trans. R. Soc. Lond. Ser. B 1994, 345, 101–118. [Google Scholar] [CrossRef]
  18. Mantel, N. The detection of disease clustering and a generalized regression approach. Cancer Res. 1967, 27, 209–220. [Google Scholar]
  19. Legendre, P.; Legendre, L. Numerical ecology, 2nd English ed.; Elsevier: Dordrecht, The Netherlands, 1998. [Google Scholar]
  20. 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. [Google Scholar] [CrossRef]
  21. R Development Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2011.
  22. 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. [Google Scholar] [CrossRef]
  23. 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.; et al. Climatic drivers of hemispheric asymmetry in global patterns of ant species richness. Ecol. Lett. 2009, 12, 324–333. [Google Scholar] [CrossRef]
  24. Dunn, R.R.; Guenard, B.; Weiser, M.D.; Sanders, N.J. Geographic gradients. In Ant Ecology; Lach, L., Parr, C.L., Abbott, K.L., Eds.; Oxford University Press: New York, NY, USA, 2010; pp. 38–58. [Google Scholar]
  25. Andersen, A.N. Global ecology of rainforest ants: functional groups in relation to environmental stress and disturbance. In Ants: Standard Methods for Measuring and Monitoring Biodiversity; Agosti, D., Majer, J.D., Alonso, L.E., Schultz, T.R., Eds.; Smithsonian Institution Press: Washington, DC, USA, 2000; pp. 25–34. [Google Scholar]
  26. 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. [Google Scholar] [CrossRef]
  27. MacArthur, R.; Levins, R. The limiting similarity, convergence, and divergence of coexisting species. Am. Nat. 1967, 101, 377–385. [Google Scholar]
  28. Brown, W.L., Jr. Diversity of ants. In Ants: Standard Methods for Measuring and Monitoring Biodiversity; Agosti, D., Majer, J.D., Alonso, L.E., Schultz, T.R., Eds.; Smithsonian Institution Press: Washington, DC, USA, 2000; pp. 45–79. [Google Scholar]
  29. Gerold, G.; Leemhuis, C. Effects of “ENSO-events” and rainforest conversion on river discharge in Central Sulawesi (Indonesia). In Tropical Rainforests and Agroforests under Global Change: Ecological and Socio-economic Valuations; Tscharntke, T., Leuschner, C., Veldkamp, E., Faust, H., Guhardja, E., Bidin, A., Eds.; Springer-Verlag: Berlin, 2010; pp. 327–350. [Google Scholar]
  30. McGlynn, T.P. The worldwide transfer of ants: geographical distribution and ecological invasions. J. Biogeogr. 1999, 26, 535–548. [Google Scholar] [CrossRef]

Supplementary Material

Table Table S1. 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.

Click here to display table

Table S1. 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.
NoSpeciesVillage
12345678
ABABABABABABABAB
Dolichoderinae
1.Dolichoderus sp.01 0.50.40.50.20.7 0.90.20.50.20.10.2
2.Dolichoderus thoracicus 1 1
3.Philidris cordata 0.7111 1 0.710.9111
4.Tapinoma melanocephalum 0.20.7 0.30.30.91 0.2
5.Tapinoma sp.010.410.2 0.7 0.90.10.70.80.7 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 10.80.30.50.4
9.Camponotus recticulatus 0.40.90.20.70.10.1 0.30.60.1 0.5
10.Camponotus sp.010.9 0.10.10.10.10.1 0.10.1 0.1
11.Camponotus sp.02 0.1
12.Echinopla lineata0.1 0.8 0.5
13.Oecophylla smaragdina 0.10.20.1 1
14.Paratrechina longicornis 1 0.4
15.Nylanderia sp.011 0.91110.610.8 10.81110.9
16.Nylanderia sp.02 1
17.Nylanderia sp.03 0.7
18.Nylanderia sp.040.10.8 0.3 1
19.Plagiolepis sp.010.9
20.Polyrachis abdominalis0.3 0.2
21.Polyrachis dives 0.70.50.3 0.2 0.2 0.1
22.Polyrachis sp.01 0.30.4
23.Polyrachis sp.02 0.5 0.4
24.Polyrachis sp.030.1
25.Polyrachis sp.04 0.2
26.Polyrachis sp.050.8
27.Polyrachis sp.06 0.1 0.20.1
28.Polyrachis sp.070.4
29.Pseudolasius sp.01 0.2 0.30.1
30.Pseudolasius sp.02 0.3
Myrmicinae
31.Crematogaster sp.010.6 0.10.7 0.6
32.Crematogaster sp.02 0.60.1 0.10.20.20.60.10.10.70.30.20.80.20.6
33.Crematogaster sp.03 0.2
34.Crematogaster sp.04 0.2 0.90.8
35.Crematogaster sp.05 0.30.1
36.Monomorium floricola 0.7 0.7 10.310.30.20.1
37.Monomorium sp.01 0.20.10.2
38.Monomorium sp.020.4 0.1 0.3
39.Monomorium sp.03 0.2
40.Monomorium sp.04 0.1 0.1
41.Monomorium sp.05 0.10.2
42.Monomorium sp.06 0.1 0.1
43.Pheidole sp.010.30.70.10.30.30.30.70.70.70.60.3 0.50.2
44.Pheidole sp.020.9 0.10.10.1 0.1 0.60.40.1
45.Pheidole sp.030.40.9 0.7 0.70.50.10.40.10.30.1
46.Pheidole sp.04 0.1
47.Pheidole sp.05 0.5 0.1 0.6
48.Pheidole sp.060.1 0.40.1 0.1 0.20.20.2
49.Pheidole sp.07 0.1
50.Pheidole sp.08 0.10.1
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 0.10.4
56.Tetramorium pasificum0.2 0.9 0.5 0.3
57.Tetramorium smithi 0.4 0.3 0.10.10.1 0.1
58.Tetramorium sp.01 0.5
59.Tetramorium sp.02 0.2 0.2
60.Tetramorium sp.030.2 0.3
61.Tetramorium sp.040.4 0.1 0.1
62.Tetramorium sp.05 0.10.1 0.3 0.10.1 0.10.1
63.Tetramorium sp.06 0.3 0.4 0.1
64.Tetramorium sp.07 0.3
65.Tetramorium sp.08 0.20.1
Ponerinae
66.Anochetus graeffei 0.30.30.40.2 0.3 0.2
67.Diacamma rugosum 0.40.10.60.9
68.Hypoponera sp.010.2 0.10.1 0.2 0.1 0.2
69.Hypoponera sp.02 0.80.90.30.1 0.60.80.90.50.70.3
70.Hypoponera sp.03 0.1 0.4 0.2
71.Hypoponera sp.04 0.2 1
72.Leptogenys sp.010.1 0.2 0.10.3
73.Odontomachus simillimus0.20.50.70.71 0.10.40.3 0.70.310.910.2
74.Pachycondyla sp.010.4 0.10.2 0.2 0.1 0.20.4
75.Pachycondyla sp.020.1
76.Pachycondyla sp.03 0.2
77.Pachycondyla sp.04 0.1
78.Platythyrea sp.01 0.10.10.1 0.20.1 0.1
Pseudomyrmicinae
79.Tetraponera sp.01 0.1
80.Tetraponera sp.02 0.2 0.1
Diversity 05 00026 g004 1024
Figure S1. Correlation between precipitation and altitude of the 16 plots of the study area (F1,14 = 21.47, P = 0.0004, r2=0.58).

Click here to enlarge figure

Figure S1. Correlation between precipitation and altitude of the 16 plots of the study area (F1,14 = 21.47, P = 0.0004, r2=0.58).
Diversity 05 00026 g004 1024
Diversity EISSN 1424-2818 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert