Various edge response of ground beetles in edges under natural versus anthropogenic influence: A meta-analysis using life-history traits
Various edge response of ground beetles in edges under natural versus anthropogenic influence: A meta-analysis using life-history traits
复制标题
自然与人为影响下边缘地面甲虫的各种边缘响应:使用生活史特征的荟萃分析
DOI:
10.17109/azh.65.suppl.3.2019
复制
发表时间:
2019
影响因子:
0.8
通讯作者:
B. Tóthmérész
中科院分区:
文献类型:
--
作者:
T. Magura;G. Lövei;B. Tóthmérész
Edges are on the increase world-wide due to increasing fragmentation and loss of natural habitats. After formation, edges are maintained by various processes (natural vs. contin ued anthropogenic interventions: forestry, agriculture, urbanization) which influence the reaction of individual species to edge effects (history-based edge effect hypothesis), and this will be reflected in the diversity of assemblages. Diversity, however, is not the most appropriate indicator of the edge effect because species with different traits may respond differently to the edges. To further articulate the history-based edge effect hypothesis, we evaluated the edge effect on one of the most commonly used life-history traits, the feed ing habit of ground beetles in forest edges. A meta-analysis based on 28 publications and 422 comparisons showed that natural vs. continued anthropogenic interventions as edge-maintaining processes reflected at the trait level. Abundance of herbivorous, omnivorous, and predatory ground beetle species were all higher in the natural edges than in the forest interiors, while no similar pattern occurred in edges with continued anthropogenic influ -ence. These results suggest that structural and environmental changes at edges sustained by repeated anthropogenic influence adversely influencing ecosystem functions, with neg ative effects on ecosystem services like pest or weed control. To heterogeneity, complementary measures of Q and I 2 calculated renstein Q is the weighted sum of squares within a data set. For significant het erogeneity, it can be tested against the expected deviation assuming that all studies share a common effect size. I 2 measures the proportion of the observed variance that reflects real differences in effect size between studies. Total variance ( Q total ) was partitioned into within- ( Q within ) and between group ( Q between ) variances and these were tested for statistical significance (Borenstein et al. 2009). Significant variance between groups ( Q between ) means that edge effect on abundance significantly differed according to the maintaining processes of edges. During the calculations, subgroups with less than five cases were excluded from analyses. Publication bias was tested using funnel plots and the Egger test (Borenstein et al. 2009). In the case of significant asymmetry, the trim and fill method was used (Duval & Tweedie 2000). During the calculations, the MAd (version 0.8-2, Del Re & Hoyt 2014) and metafor packages (version 1.9-9, Viechtbauer 2010) were used in R programming environ ment (version 3.4.3; R Core Team 2017).