Species interactions and population density mediate the use of social cues for habitat selection

1. The perspective that populations and communities are structured by antagonistic interactions among individuals has dominated much of ecology. Yet how animals use social information to guide decisions, such as habitat selection, may be influenced by both positive and negative interactions among individuals. Recent theory also suggests that the way animals use social information may be substantially influenced by population density, which alters the potential costs and benefits of such behaviours. 2. I manipulated cues of two competitors, the dominant least flycatcher Empidonax minimus (Baird & Baird) and the subordinate American redstart Setophaga ruticilla (Linnaeus), to assess the use of conspecific and heterospecific cues during habitat selection, and if population density influences these strategies. The experiment consisted of surveying birds during a pre-treatment year, which allows for the control and testing the effect of baseline densities, and a treatment year, in which treatments were applied just prior to settlement. Treatments included broadcasting songs of flycatchers and redstarts, and were compared with controls. 3. When controlling for pre-treatment densities, bird densities, and to a lesser extent arrival dates, during the treatment year suggested that flycatchers were attracted to both conspecific and heterospecific cues during settlement. Furthermore, attraction was strongest for flycatchers in plots with moderate pre-treatment densities. American redstarts were rare in the study area but showed apparent attraction to conspecifics and avoidance of heterospecifics. 4. These results provide experimental evidence for the use of multiple social cues in habitat selection and suggest that heterospecific attraction may operate under broader contexts than originally envisioned. In such instances, nontarget effects can potentially occur when manipulating social cues to elicit settlement in conservation strategies. The impact of population density on the use of social cues shown here can also influence our understanding of metapopulation dynamics by causing complex threshold effects on the likelihood of rescue, which may influence metapopulation stability and the likelihood of local extinction.     

Who is in the neighborhood? Conspecific and heterospecific responses to perceived density for breeding habitat selection

Theoretical models of habitat selection often incorporate negative density dependence. Despite strong negative density‐dependent effects on habitat selection, more recent studies indicate that animals settle near members of their own (conspecific) and other species (heterospecific) when selecting habitat with social cues. Social cue use for habitat selection is particularly common among songbirds, but few studies have investigated if songbirds use social cues to assess conspecific or heterospecific density (as opposed to just presence/absence) when making settlement decisions. We conducted a playback experiment to evaluate if yellow warblers (Setophaga petechia) and willow flycatchers (Empidonax traillii), two potential competitors for breeding habitat, use social cues to assess density (conspecific for warblers and heterospecific for flycatchers) when selecting breeding locations at two spatial scales. We simulated yellow warbler density to be high or low at multiple treatment plots (3.14 ha) with song playback and then evaluated settlement decisions by comparing yellow warbler and willow flycatcher abundances across plots (broad‐scale habitat selection) and individual space use within plots (fine‐scale territory establishment). Yellow warbler density treatments did not affect habitat selection by yellow warblers at the broad scale, but caused individuals to cluster territories at high‐density treatments. Willow flycatchers were most abundant at high‐density treatment plots, but yellow warbler density treatments did not affect territory locations. The results indicate that perceived density affects the habitat selection process for both conspecifics and heterospecifics.     

基于Logistic回归模型的黄河三角洲淡水恢复湿地大型底栖生物种群分布模拟

掌握大型底栖生物种群分布的时空变化对正确把握湿地生态修复效率、揭示湿地生态演替过程具有重要理论与实践意义。选择黄河三角洲地区一千二自然保护区的淡水恢复湿地为研究区,在2014—2015年大型底栖生物野外采样和优势物种的基础上,选择了琥珀刺沙蚕、中华蜾蠃蜚、摇蚊幼虫作为典型优势物种,构建了基于Logistic回归的淡水恢复湿地大型底栖生物种群分布模拟模型。其中,琥珀刺沙蚕和摇蚊幼虫的模拟结果较好,模拟准确率分别为84.9%和77.9%,而中华蜾蠃蜚的模拟结果不甚理想。对比生态补水前后大型底栖生物的模拟分布结果发现,琥珀刺沙蚕主要集中在潮间带区域,且在春、秋两季的生存概率分布差异不显著;而淡水恢复湿地中摇蚊幼虫的分布概率显著提高,其中高于分割值0.5的栖息面积增长了9.9—10.8倍,表明退化湿地生境正处于向淡水湿地演替进程中。     

冬季水鸟对崇明东滩水产养殖塘的利用

自然湿地的丧失和退化给依赖湿地生存的水鸟带来了严重威胁,人工湿地作为水鸟栖息地的功能日益受到关注.水产养殖塘是人工湿地的重要类型之一.通过研究崇明东滩水产养殖塘冬季水鸟群落组成及其栖息地特征,发现大面积养殖塘比小面积养殖塘吸引更多种类和更高密度的水鸟.养殖塘在放水前水位较高时吸引更多游禽栖息,而在放水后水位较低时吸引更多涉禽;在放水过程中,养殖塘中水鸟的种类最多,密度最大.另外,在放水的不同时期,不同的环境因子对水鸟群落的影响不同:放水之前,养殖塘水面面积和平均水深是水鸟种类和数量的主要影响因子,其中游禽种类和数量受水面面积影响较大,涉禽种类和数量受平均水深影响较大;放水过程中,裸地面积、芦苇面积、干扰程度、平均水深和水深变异对水鸟、游禽和涉禽的种类和数量起主要作用;放水之后,水深变异对水鸟种类和数量的影响较大,而影响游禽种类和数量的主要因子是水面面积,影响涉禽种类和数量的主要因子是水深变异.研究表明,通过对影响水鸟栖息地利用的主要因子的有效管理,养殖塘在提供经济效益的同时也能为水鸟提供适宜的栖息地.     

Variation in wetland invertebrate communities in lowland acidic fens and swamps

1. Invertebrates were collected semi‐quantitatively from four relatively undisturbed wetlands in the west coast of New Zealand’s South Island: two acidic fens and two swamps. Samples were collected from up to four discrete habitats within each wetland: large open‐water channels, small leads (small, ill‐defined channels with emergent vegetation in them) and large (>10 m diameter) or small (<10 m diameter) ponds. Samples were also collected from different plant species within each wetland, each with different morphology, and from areas without vegetation. This was done to determine whether invertebrate communities varied more between‐wetlands than within‐wetlands, as the results had implications for future wetland monitoring programmes. 2. Principal components analysis of water chemistry data revealed striking differences in pH, conductivity and nutrients between the four wetlands. Not surprisingly, pH was lowest in one of the acidic fens, and highest in one of the swamps, where conductivity was also high. Midges (Tanytarsus, Tanypodinae, Orthocladiinae and Ceratopogonidae), nematodes, harpactacoid copepods and the damselfly Xanthocnemis dominated the invertebrate fauna. Orthoclad midges and mites were the most widespread taxa, found in 91 of 94 samples. Diptera were the most diverse invertebrate group, followed by Trichoptera and Crustacea. 3. Ordination analysis of the invertebrate data showed that the four wetlands supported different invertebrate communities. However, species composition did not change completely along the ordination axes, suggesting that a relatively species‐poor invertebrate fauna was found in the wetlands. Taxa such as molluscs were restricted to wetlands with high pH. Multi‐response permutation procedures (MRPP) was used to analyse resultant ordination scores to see how they differed according to five terms: ‘Wetland’, ‘Habitat’, ‘Growth Form’, ‘Morphology’ and ‘Plant’. Most of the sample separation along ordination axes reflected differences between wetland, although the ‘Habitat’ and ‘Plant’ terms also explained some of the variation. The ‘Growth Form’ and ‘Morphology’ terms had only minor effects on community composition. 4. A multivariate regression tree modelled invertebrate assemblages according to the five predictor terms. The resultant model explained 54.8% of the species variance. The ‘Wetland’ term contributed most to the explanatory power, followed by ‘Habitat’. ‘Growth type’ and ‘Morphology’ explained only a small amount of variance to the regression tree, while the different plant species explained none of the variation. 5. Variation in these New Zealand wetland invertebrate communities appears to be controlled most by large‐scale factors operating at the level of individual wetlands, although different habitats within individual wetlands contributed slightly to this variation. Based on these results, sampling programmes to describe wetland invertebrate communities do not need to sample specific habitats or plant types within a wetland. Instead, samples can be collected from a wide range of habitats within individual wetlands, and pooled. Within each habitat, it is unnecessary to collect individual samples from different macrophytes or un‐vegetated areas. Our results suggest that collecting replicate pooled samples from different habitats within each wetland will be sufficient to characterize the invertebrate assemblage of each wetland.     

A comparison of statistical approaches for modelling fish species distributions

SUMMARY 1. The prediction of species distributions is of primary importance in ecology and conservation biology. Statistical models play an important role in this regard; however, researchers have little guidance when choosing between competing methodologies because few comparative studies have been conducted. 2. We provide a comprehensive comparison of traditional and alternative techniques for predicting species distributions using logistic regression analysis, linear discriminant analysis, classification trees and artificial neural networks to model: (1) the presence/absence of 27 fish species as a function of habitat conditions in 286 temperate lakes located in south‐central Ontario, Canada and (2) simulated data sets exhibiting deterministic, linear and non‐linear species response curves. 3. Detailed evaluation of model predictive power showed that approaches produced species models that differed in overall correct classification, specificity (i.e. ability to correctly predict species absence) and sensitivity (i.e. ability to correctly predict speciespresence) and in terms of which of the study lakes they correctly classified. Onaverage, neural networks outperformed the other modelling approaches, although all approaches predicted species presence/absence with moderate to excellent success. 4. Based on simulated non‐linear data, classification trees and neural networks greatly outperformed traditional approaches, whereas all approaches exhibited similar correct classification rates when modelling simulated linear data. 5. Detailed evaluation of model explanatory insight showed that the relative importance of the habitat variables in the species models varied among the approaches, where habitat variable importance was similar among approaches for some species and very different for others. 6. In general, differences in predictive power (both correct classification rate and identity of the lakes correctly classified) among the approaches corresponded with differences in habitat variable importance, suggesting that non‐linear modelling approaches (i.e. classification trees and neural networks) are better able to capture and model complex, non‐linear patterns found in ecological data. The results from the comparisons using simulated data further support this notion. 7. By employing parallel modelling approaches with the same set of data and focusing on comparing multiple metrics of predictive performance, researchers can begin to choose predictive models that not only provide the greatest predictive power, but also best fit the proposed application.