The Effect of Positive Interactions on Temporal Turnover of Community Composition along an Environmental Gradient

et al. (2013) The Effect of Positive Interactions on Temporal Turnover of Community Composition along an Environmental Gradient. PLoS ONE 8(11): e78698. doi:10.1371/journal.pone.0078698 The Effect of Positive Interactions on Temporal Turnover of Community Composition along an Environmental Gradient Youshi Wang 0 Zhiyong Yang 0 Shurong Zhou 0 Janne Soininen 0 Dexiecuo Ai 0 Yali Li 0 Chengjin Chu 0 Maura Geraldine Chapman, University of Sydney, Australia 0 1 Ministry of Education Key Laboratory of Western China's Environmental Systems, Research School of Arid Environment and Climate Change, Lanzhou University , Lanzhou , China , 2 State Key Laboratory of Grassland and Agro-Ecosystems, School of Life Sciences, Lanzhou University , Lanzhou , China , 3 Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, School of life Sciences, Fudan University , Shanghai , China , 4 Department of Geosciences and Geography, University of Helsinki , Helsinki , Finland , 5 Xikehe Sire Breeding Farm of Euler Sheep of Maqu County in the Gansu Province , Maqu , China It has been demonstrated that the interplay between negative and positive interactions simultaneously shapes community structure and composition. However, few studies have attempted to examine the effect of facilitation on compositional changes in communities through time. Additionally, due to the difficulties in collecting the long-term data, it would be useful to indicate the rate of temporal turnover using a readily obtainable metric. Using an individual-based model incorporating plant strategies, we examined the role of facilitation on the temporal turnover of communities located at different positions along an environmental gradient for three model scenarios: CM without facilitation; CFM-U, a unimodal relationship between facilitation and environmental severity; and CFM-L, a positively linear relationship between facilitation and environmental severity. Our results demonstrated that facilitation could increase, decrease or have no remarkable effect on temporal turnover. The specific outcome depended on the location of the focal community across the environmental gradient and the model employed. Compared with CM, the inclusion of positive interactions (i.e. CFM-U and CFM-L), at intermediate environmental stress levels (such as S = 0.7 and 0.8) resulted in lower Bray-Curtis similarity values; at other severity levels, facilitation slowed down (such as S = 0.3 and 0.4 at low to medium stress levels, and S = 0.9 at high stress levels) or had only a subtle effect (such as at S = 0.1) on temporal turnover. We also found that the coefficient of variation (CV) in species abundances and the rate of temporal variability showed a significant quadratic relationship. Our theoretical analysis contributes to the understanding of factors driving temporal turnover in biotic communities, and presents a potential metric (i.e. CV in species abundances) assessing the consequences of ongoing environmental change on community structure. - Funding: This research was financially supported by the National Natural Science Foundation of China (31000199, 41201050), and the Fundamental Research Funds for the Central Universities (lzujbky-2012-133, lzujbky-2013-k15). CC was also supported by the Program for New Century Excellent Talents in University (NCET-12-0248). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. Compositional turnover of communities has attracted more attention in recent years. Such studies help to unravel the causes and consequences of biodiversity in nature, and the patterns of compositional changes provide valuable information to many ecological and evolutionary questions, as well as to conservation planning [18]. It has been suggested that addressing biotic community turnover can no longer be approached soley from a spatial aspect, but also be understood from a temporal aspect. This is because projected environmental change in the future is expected to cause large shifts both in species spatial distributions, and in temporal assemblage patterns [9,10]. Though the spatial dataset of community composition/turnover has been well collected and documented, the scarcity of temporal data has hindered the comprehensive exploration of potential factors contributing to the compositional variation through time, especially for terrestrial communities [5]. It has been proposed that like the spatial variation, temporal variability is also likely to be driven by multiple biotic and abiotic factors [9,1113]. For example, Korhonen et al. [9] demonstrated that sampling duration, body size, ecosystem size and type, and latitude correlated with the observed degree of temporal variation in aquatic assemblages. Adler et al. [11] reported that the general pattern of the species-time-area relationship was derived from demographic processes and ecological interactions which played out on a template of environmental variation. Wang et al. [13] argued that at the level of entire communities, facilitation could make species more prone to extinction on average due to the smaller mean population size (i.e. the total number of individuals divided by species richness) [1418] and thus increase the temporal turnover in communities. Compared with other biotic and abiotic factors, however, the role of facilitation has been overlooked in the studies of compositional changes in time [13]. Studies over the last 20 years have shown that positive interactions are common in plant communities in physically harsh Figure 1. Changes of community composition with the same simulation time (here the time interval is 200 steps) for three environmental levels: low (S = 0.0; A), medium (S = 0.5; B) and high (S = 1.0; C). For each environmental level, three models were presented: CM, CFM-U, and CFM-L. The parameter values used in models are rmax = 1, rmin = 0.2, f = 0.5, Sm = 0.8, I = 30, d = 0.2, rs = 20.1 and c = 1. Each data point represents the mean6SE. doi:10.1371/journal.pone.0078698.g001 conditions, through ameliorating locally stressful environments by increasing temperature in alpine regions [13,1921] and increasing soil water content in arid and semi-arid areas [22,23]. Though a growing amount of work has been conducted to test the effect of facilitation on population dynamics [2430], community structure [21,31,32], and ecosystem functioning [3335], to our knowledge, few studies have investigated the potential impact of positive interactions on the temporal turnover of community composition [13]. As the occurrence and magnitude of positive interactions are closely associated with the environmental conditions and speciesspecific life-history characteristics, exploring the potential role of facilitation on temporal turnover could shed light on the consequences of ongoing global (...truncated)