<scp>EVI</scp>and<scp>NDVI</scp>as proxies for multifaceted avian diversity in urban areas

Benedetti, Yanina; Callaghan, Corey T.; Ulbrichová, I.; Galanaki, Antonia; Kominos, Theodoros; Zeid, Farah Abou; Ibáñez‐Álamo, Juan Diego; Suhonen, Jukka; Dı́az, Mario; Markó, Gábor; Bussière, Raphaël; Tryjanowski, Piotr; Bukas, Nikos; Mägi, Marko; Leveau, Lucas M.; Pruscini, Fabio; Jerzak, Leszek; Ciebiera, Olaf; Jokimäki, Jukka; Kaisanlahti‐Jokimäki, Marja‐Liisa; Møller, Anders Pape; Morelli, Federico

doi:10.1002/eap.2808

Cited by 12 publications

(6 citation statements)

References 146 publications

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“…Besides, highly urbanised areas with entirely impervious surface cover are expected to have a net primary production near zero (Shochat et al, 2006). In this context, we found little support for a latitudinal diversity gradient based on NDVI alone as previously reported for breeding assemblages in natural ecosystems (Hawkins, Field, et al, 2003;Hawkins, Porter, & Diniz-Filho, 2003) or urban ecosystems at continentalscale (Benedetti et al, 2023). Nonetheless, NDVI has been associated with an increase of non-breeding avian taxonomic diversity in tropical urban areas (Leveau et al, 2018), coinciding with our analyses testing the "productivity" hypothesis (Tables S9-S11).…”

Section: Piecewise Structural Equation Modellingcontrasting

confidence: 84%

“…To ensure that our inferences are directly comparable to the results of previous macroecological studies conducted in cities (Pautasso et al., 2011), we use NDVI instead of the Net Primary Productivity Index (NPPI). NDVI is well‐established as the most widely used index to detect changes in vegetation characteristics at different spatial scales (Benedetti et al., 2023; Leveau et al., 2020; Nieto et al., 2015).…”

Section: Methodsmentioning

confidence: 99%

“…H1: Productivity (Benedetti et al, 2023;Hawkins, Field, et al, 2003;Hawkins, Porter, & Diniz-Filho, 2003) Urban centres with higher productivity (available in the form of food) should harbour higher multifaceted diversity than lowproductivity urban centres Urban sites with higher energy support larger population sizes and carrying capacity, promoting higher chance of incidence for migratory species, and lower local extinction rates for permanent resident species NDVI H2: Energy-water balance (Batáry et al, 2018;Hawkins, Field, et al, 2003;Hawkins, Porter, & Diniz-Filho, 2003) Urban centres with higher productivity (represented in form of food) and water availability should harbour higher multifaceted diversity than lowproductivity urban centres with limited water availability Urban sites located near migratory flyways with more energy resources and bodies of water (within or nearby) allow larger population sizes and carrying capacity, promoting higher speciation and seasonal colonisation events at lower cost, and with lower local extinction rates NDVI + Precipitation + Distance to rivers + Distance to coasts H3: Freezing tolerance (Hawkins, Porter, & Diniz-Filho, 2003;Root, 1988;von Humboldt, 1808) Urban areas with higher temperatures and moderate precipitation at southern latitudes should support higher multifaceted diversity than urban centres with lower temperatures and high precipitation at northern latitudes throughout the winter season…”

Section: Hypothesis Prediction Explanation Predictorsmentioning

confidence: 99%

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Disentangling the drivers of urban bird diversity in the non‐breeding season: A general synthesis

Moreno‐Contreras,

Jokimäki,

Kaisanlahti‐Jokimäki

et al. 2024

Global Change Biology

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Current knowledge about the impacts of urbanisation on bird assemblages is based on evidence from studies partly or wholly undertaken in the breeding season. In comparison, the non‐breeding season remains little studied, despite the fact that winter conditions at higher latitudes are changing more rapidly than other seasons. During the non‐breeding season, cities may attract or retain bird species because they offer milder conditions or better feeding opportunities than surrounding habitats. However, the range of climatic, ecological and anthropogenic mechanisms shaping different facets of urban bird diversity in the non‐breeding season are poorly understood. We explored these mechanisms using structural equation modelling to assess how urbanisation affects the taxonomic, phylogenetic and functional diversity of avian assemblages sampled worldwide in the non‐breeding season. We found that minimum temperature, elevation, urban area and city age played a critical role in determining taxonomic diversity while a range of factors—including productivity, precipitation, elevation, distance to coasts and rivers, socio‐economic (as a proxy of human facilitation) and road density—each contributed to patterns of phylogenetic and functional diversity. The structure and function of urban bird assemblages appear to be predominantly shaped by temperature, productivity and city age, with effects of these factors differing across seasons. Our results underline the importance of considering multiple hypotheses, including seasonal effects, when evaluating the impacts of urbanisation on biodiversity.

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Section: Piecewise Structural Equation Modellingcontrasting

confidence: 84%

Section: Methodsmentioning

confidence: 99%

Section: Hypothesis Prediction Explanation Predictorsmentioning

confidence: 99%

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Disentangling the drivers of urban bird diversity in the non‐breeding season: A general synthesis

Moreno‐Contreras,

Jokimäki,

Kaisanlahti‐Jokimäki

et al. 2024

Global Change Biology

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“…The estimation of vegetation cover is accomplished using the EVI, which utilizes remote sensing data from the visible and near-infrared bands 24 . EVI serves as an effective index for assessing vegetation cover and is characterized by specific computational processes, as depicted in Fig.…”

Section: Research Theory and Improved Random Forest Modelmentioning

confidence: 99%

Improved random forest classification model combined with C5.0 algorithm for vegetation feature analysis in non-agricultural environments

Wang

2024

Sci Rep

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In response to the challenges posed by the high computational complexity and suboptimal classification performance of traditional random forest algorithms when dealing with high-dimensional and noisy non-agricultural vegetation satellite data, this paper proposes an enhanced random forest algorithm based on the C5.0 algorithm. The paper focuses on the Liaohe Plain, selecting two distinct non-agricultural landscape patterns in Shenbei New District and Changtu County as research objects. High-resolution satellite data from GF-2 serves as the experimental dataset. This paper introduces an ensemble feature method based on the bagging concept to improve the original random forest classification model. This method enhances the likelihood of selecting features beneficial to classifying positive class samples, avoiding excessive removal of useful features from negative samples. This approach ensures feature importance and model diversity. The C5.0 algorithm is then employed for feature selection, and the enhanced vegetation index (EVI) is utilized for vegetation coverage estimation. Results indicate that employing a multi-scale parameter selection tool, combined with limited field-measured data, facilitates the identification and classification of plant species in forest landscapes. The C5.0 algorithm effectively selects classification features, minimizing information redundancy. The established object-oriented random forest classification model achieves an impressive accuracy of 94.02% on the aerial imagery for forest classification dataset, with EVI-based vegetation coverage estimation demonstrating high accuracy. In experiments on the same test set, the proposed algorithm attains an average accuracy of 90.20%, outperforming common model algorithms such as bidirectional encoder representation from transformer, FastText, and convolutional neural network, which achieve average accuracies ranging from 84.41 to 88.33% in identifying non-agricultural artificial habitat vegetation features. The proposed algorithm exhibits a competitive edge compared to other algorithms. These research findings contribute scientific evidence for protecting agricultural ecosystems and restoring agricultural ecosystem biodiversity.

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“…While the concept of incorporating UGS into city planning has long been understood, the importance of species diversity has only been recently brought to the fore ( Hunter et al., 2019 ). This is particularly important, as the diversity of animals in urban areas may be linked to the diversity of the plant life ( Hughes et al., 2022 ; Nava-Diaz et al., 2022 ; Benedetti et al, 2023 ). Therefore, understanding influences on urban plant diversity (UPD) is crucial as a driver of overall urban biodiversity.…”

Section: Introductionmentioning

confidence: 99%

Distribution patterns and drivers of urban green space and plant diversity in Haikou, China

Zhang,

Guo,

Nizamani

et al. 2023

Front. Plant Sci.

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Investigating historical and ongoing changes in urban green space (UGS) and urban plant diversity (UPD) provides critical insights into urban ecology and urban planning development. The present study illuminates some of the transformations which can occur in rapidly developing urban landscapes. In this work, we used 30 m resolution images from the Landsat 5 satellite from 2015 to investigate UGS patterns in Haikou City, China. Metrics of UPD were obtained using field surveys, allowing the proportion of UGS and UPD to be determined in each urban functional unit (UFU) of Haikou. The results revealed that leisure and entertainment areas (such as parks) had the highest diversity, whereas roads and transportation hubs had the lowest. More frequent anthropogenic maintenance had a positive effect on the total number of species, including cultivated, tree, and herb species. Similarly, increased watering frequency had a positive impact on the diversity of cultivated and shrub species. By providing demonstrating a crucial link between UGS and UPD, the results provide valuable information for planning sustainable urban development in Haikou City and other tropical regions. They highlight the important role of UGS in maintaining biodiversity and providing a range of ecosystem services. This research will inform policymakers and urban planners about the need to consider UGS and UPD in urban planning and management process, in order to promote sustainability and conservation of biodiversity.

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EVIandNDVIas proxies for multifaceted avian diversity in urban areas

Cited by 12 publications

References 146 publications

Disentangling the drivers of urban bird diversity in the non‐breeding season: A general synthesis

Disentangling the drivers of urban bird diversity in the non‐breeding season: A general synthesis

Improved random forest classification model combined with C5.0 algorithm for vegetation feature analysis in non-agricultural environments

Distribution patterns and drivers of urban green space and plant diversity in Haikou, China

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