The species richness/abundance–area relationship of bees in an early successional tree plantation

Taki, Hisatomo; Murao, Ryuki; Mitai, Katsushi; Yamaura, Yuichi

doi:10.1016/j.baae.2017.09.002

Cited by 20 publications

(13 citation statements)

References 33 publications

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“…2009), and, more generally, is in line with broad ecological laws that relate organism diversity and abundance to habitat patch area (Lawton 1999, MacArthur & Wilson 2001, Taki et al . 2018). Large wetlands can provide more microhabitats (Paszkowski & Tonn, 2000) and more open water, and therefore can be more attractive to waterbird species and individuals (Gibbs et al .…”

Section: Discussionmentioning

confidence: 99%

“…Two general ecological laws, known as species–area and abundance–area relationships, predict that species richness and organism abundance, respectively, are primarily determined by habitat patch surface area through simple linear regressions on the log–log scale (Lawton 1999, MacArthur & Wilson 2001, Taki et al . 2018). We thus expected water surface area to be a prime predictor of both waterbird abundance and species richness.…”

Section: Methodsmentioning

confidence: 99%

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Improving waterbird monitoring and conservation in the Sahel using remote sensing: a case study with the International Waterbird Census in Sudan

Suet

Lozano‐Arango

Rau

et al. 2021

Ibis

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In several regions of the world, the remoteness of potential bird hotspots and lack of trained observers have often prevented countries from effectively designing proper monitoring schemes at a national scale. For many countries, it is not known whether certain bird strongholds have been missed that should be included for more complete censuses. Such gaps at national scales, sometimes large, may be detrimental for global monitoring schemes. To address this, we used the irregular participation of Sudan to the International Waterbird Census (IWC) as a case study. We designed and tested a method based on remote‐sensing data of the country’s lowlands to detect open water bodies in order to develop predictive models of the potential distribution of waterbird abundance and diversity. To identify open water bodies and their flooding duration, we used a Modified Normalized Difference Water Index (MNDWI) derived from Landsat 8 data. Field ornithological surveys were then used as ground‐truth data to estimate the method’s accuracy. The statistical results (overall accuracy = 0.972; Kappa index = 0.93) confirmed its effectiveness. Remotely sensed water bodies and additional environmental covariates were then used to build simple habitat models of the distribution of waterbird abundance and diversity based on IWC field survey data. Of the 3119 remotely sensed clusters of open water bodies, three were predicted to host more than 10 000 waterbirds, 89 more than 1000 waterbirds and five more than 30 waterbird species. Located mainly in the southern agricultural floodplains along the main rivers, these predicted waterbird strongholds are therefore recommended for inclusion in the next IWC survey in Sudan. Our findings indicate that using remote sensing to identify open water bodies combined with simple statistical modelling is likely to be a cost‐effective solution to improve IWC sampling and to enhance both waterbird and wetland monitoring in vast under‐surveyed regions.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Improving waterbird monitoring and conservation in the Sahel using remote sensing: a case study with the International Waterbird Census in Sudan

Suet

Lozano‐Arango

Rau

et al. 2021

Ibis

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“…No differences among conservation levels were found. Restoration may favour the presence of wild bees (Araújo et al 2018;Taki et al 2018;Alvarenga et al 2020) and parasitoids (Marrec et al 2018), but some hymenopteran assemblages from restored areas may be functionally similar to those from forests (Montoya-Pfeiffer et al 2020), and their diversity has been found to be lower in forests compared to more open areas (Pardo and Gonzalez 2007). Therefore, it seems that, even when the areas labeled as low conservation presented a high degree of perturbation, being embedded into a preserved area matrix helped to increase diversity in these areas, since the hymenopteran diversity is positively affected by the proximity to forest (Banks et al 2013).…”

Section: Discussionmentioning

confidence: 99%

Hymenoptera functional groups’ shifts in disturbance gradients at Andean forests in Southern Ecuador

Mazón¹,

López²,

Romero³

2020

JHR

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Ecosystems under ecological restoration should be monitored in order to investigate if the ecosystem is being functionally recovered, especially in highly vulnerable biodiversity hotspots like Andean forests. Here we sampled Hymenoptera families in four Andean forest reserves above 1800 masl from Southern Ecuador, in three conservation levels in each forest: low (degraded), medium (10–15 years of recovery) and high (well-conserved forest). All Hymenoptera families were classified into four functional groups: predators, herbivores, pollinators and parasitoids. A total of 32 hymenopteran families were collected, with parasitoids clearly dominating in the samples. Family assemblages were not statistically different, neither in abundance nor family richness. Assemblages were more similar between them in the high and medium areas than in low conservation areas, where assemblages were very variable and showed a higher functional diversity in two of the reserves. The low presence of pollinators may be due to the high humidity during the sampling and the sampling method. Although some results are promising for the restoring trajectory, especially for parasitoids, we should keep in mind that this is at family level, so it would be interesting to know if these patterns persist at lower taxonomic levels.

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“…For example, HCMs can be written using a negative binomial distribution or including random site effects to account for unexplained variations in abundance (Taki et al. , Farr et al. ).…”

Section: Methodsmentioning

confidence: 99%

“…Note that HCMs are flexible both in the way they can handle the structure of the community data (e.g., they can be applied to binary presence/absence using a binomial distribution) but also in how the linear predictors and associated distributions are defined (K ery and Royle 2016). For example, HCMs can be written using a negative binomial distribution or including random site effects to account for unexplained variations in abundance (Taki et al 2018, Farr et al 2019. Similarly, normal (Gaussian) distribution could be used for continuous data .…”

Section: Abundance-based Hcmmentioning

confidence: 99%

Analyzing community structure subject to incomplete sampling: hierarchical community model vs. canonical ordinations

Yamaura

Blanchet

Higa

2019

Ecology

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Citation: Yamaura, Y., F. G. Blanchet, and M. Higa. 2019. Analyzing community structure subject to incomplete sampling: hierarchical community model vs. canonical ordinations. Ecology 100(8):Abstract. Recently developing hierarchical community models (HCMs) accounting for incomplete sampling are promising approaches to understand community organization. However, pros and cons of incorporating incomplete sampling in the analysis and related design issues remain unknown. In this study, we compared HCM and canonical redundancy analysis (RDA) carried out with 10 different dissimilarity coefficients to evaluate how each approach restores true community abundance data sampled with imperfect detection. We conducted simulation experiments with varying numbers of sampling sites, visits, mean detectability and mean abundance. Performance of HCM was measured by estimates of "expected" (mean) abundance (k ij ) and realized abundance (N ij : direct estimate of site-and species-specific abundance). We also compared HCM and different types of RDA (normal, partial, and weighted), all performed with the same ten different dissimilarity coefficients, with unequal number of visits to sampling sites. In addition, we applied the models to a virtual survey carried out on the Barro Colorado Island tree plot data for which we know true community abundance. Simulation experiments showed thatN ij yielded by HCM best restored the underlying abundance of constituent species among 12 abundance estimates by HCM and RDA regardless if the sampling was equal or unequal. Mean abundance predominantly affected the performance of HCM and RDA whilek ij yielded by HCM had comparable performance to percentage difference and Gower dissimilarity coefficients of RDA. Relative performance of RDA types depended on the combination of dissimilarity coefficients and the distribution of sampling effort. Best performance ofN ij followed byk ij , percentage difference and Gower dissimilarity were also observed for the analysis of tree plot data, and graphical plots (triplots) based onk ij rather thanN ij clearly separated the effects of two environmental covariates on the abundance of constituent species. Under our conditions of model evaluation and the method, we concluded that, in terms of assessing the environmental dependence of abundance, HCMs and RDA can have comparable performance if we can choose appropriate dissimilarity coefficients for RDA. However, since HCMs provide straightforward biological interpretations of parameter estimates and flexibility of the analysis, HCMs would be useful in many situations as well as conventional canonical ordinations.

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The species richness/abundance–area relationship of bees in an early successional tree plantation

Cited by 20 publications

References 33 publications

Improving waterbird monitoring and conservation in the Sahel using remote sensing: a case study with the International Waterbird Census in Sudan

Improving waterbird monitoring and conservation in the Sahel using remote sensing: a case study with the International Waterbird Census in Sudan

Hymenoptera functional groups’ shifts in disturbance gradients at Andean forests in Southern Ecuador

Analyzing community structure subject to incomplete sampling: hierarchical community model vs. canonical ordinations

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