Enhancing road verges to aid pollinator conservation: A review

Phillips, Benjamin B.; Wallace, Claire; Roberts, Bethany R.; Whitehouse, Andrew T.; Gaston, Kevin J.; Bullock, James M.; Dicks, Lynn V.; Osborne, Juliet L.

doi:10.1016/j.biocon.2020.108687

Cited by 77 publications

(83 citation statements)

References 104 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The considerable values of roadsides for pollinators, reviewed by Phillips et al . (2020), are evident from numerous studies. Those values are likely to be paralleled for less intensively studied functional groups of insects, such as predators and parasitoids.…”

Section: Biodiversity and Conservation Valuesmentioning

confidence: 93%

“…Mortality for pollinators (Phillips et al . 2020) suggested wider needs to restore roadside habitats to sustain such ecological functions, with additional measures such as widening the distance between roads and roadside vegetation perhaps also useful. Immensely difficult to address, Keilsohn et al .…”

Section: Key Threats and Impacts On Insectsmentioning

confidence: 99%

“…2013), as well as pollinators (Phillips et al . 2020) and other insects in analogous habitats such as linear field margins (New 2005), provide much relevant ecological background.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Roles of roadside vegetation in insect conservation in Australia

2020

View full text Add to dashboard Cite

The extent and variety of roadside environments in Australia in largely anthropogenic landscapes render them substantial remnant habitats for insect biodiversity. The importance of these areas for insect biodiversity conservation and the key threats they face are discussed, as well as the needs for their protection and conservation management. Many rural roadsides harbour significant patches of native vegetation, including rare and threatened flora now scarce elsewhere. Other values of roadside vegetation include habitat remnants, seasonal refuges, corridors and shelters for insect movements and population connectivity. Examples are given of the importance of roadsides for individual threatened insect species. Roadside environments are under substantial threat from clearing, development and unintentional degradation through a variety of activities. The diverse responsibilities of roadside management, increasingly to harmonise human safety and amenity needs with biodiversity conservation, can readily incorporate considerations of insect diversity and occurrence of notable individual species. The conservation of remnant vegetation and ecological restoration of roadside corridors are highlighted as paramount for maintaining biodiversity and connectivity under increased human activity and environmental extremes.

show abstract

Section: Biodiversity and Conservation Valuesmentioning

confidence: 93%

Section: Key Threats and Impacts On Insectsmentioning

confidence: 99%

See 1 more Smart Citation

Roles of roadside vegetation in insect conservation in Australia

2020

View full text Add to dashboard Cite

show abstract

“…The positive relationship between power line corridors and the evenness and number of plant species in the landscape did, however, not translate to an increase in their phylogenetic diversity. Linear infrastructure habitats appear not to have a strong overall effect on grassland biodiversity at the landscape scale, despite their high local diversity 11,22,23 . Neither power line corridors nor road verge density affected species composition of any of the taxa as shown by the ordination analysis.…”

Section: Discussionmentioning

confidence: 91%

“…If contemporary linear infrastructure habitats indeed contribute to landscape level biodiversity in addition to diverse semi-natural grassland habitats, then they constitute a potentially great but currently poorly utilized opportunity for biodiversity conservation 21 . Managing linear infrastructure habitats for promoting diversity of plants and pollinators, and not only for infrastructure maintenance, can be crucial if their core habitat continues to diminish 11,31 .…”

mentioning

confidence: 99%

Linear infrastructure habitats increase landscape-scale diversity of plants but not of flower-visiting insects

Dániel‐Ferreira

Bommarco

Wissman

et al. 2020

Sci Rep

View full text Add to dashboard Cite

Habitats along linear infrastructure, such as roads and electrical transmission lines, can have high local biodiversity. To determine whether these habitats also contribute to landscape-scale biodiversity, we estimated species richness, evenness and phylogenetic diversity of plant, butterfly and bumblebee communities in 32 km2 landscapes with or without power line corridors, and with contrasting areas of road verges. Landscapes with power line corridors had on average six more plant species than landscapes without power lines, but there was no such effect for butterflies and bumblebees. Plant communities displayed considerable evenness in species abundances both in landscapes with and without power lines and high and low road verge densities. We hypothesize that the higher number of plant species in landscapes with power line corridors is due to these landscapes having a higher extinction debt than the landscapes without power line corridors, such that plant diversity is declining slower in landscapes with power lines. This calls for targeted conservation actions in semi-natural grasslands within landscapes with power line corridors to maintain biodiversity and prevent imminent population extinctions.

show abstract

Deep learning object detection to estimate the nectar sugar mass of flowering vegetation

Hicks

Baude

Kratz

et al. 2021

Ecol Sol and Evidence

View full text Add to dashboard Cite

Floral resources are a key driver of pollinator abundance and diversity, yet their quantification in the field and laboratory is laborious and requires specialist skills. Using a dataset of 25,000 labelled tags of fieldwork‐realistic quality, a convolutional neural network (Faster R‐CNN) was trained to detect the nectar‐producing floral units of 25 taxa in surveyors’ quadrat images of native, weed‐rich grassland in the United Kingdom. Floral unit detection on a test set of 50 model‐unseen images of comparable vegetation returned a precision of 90%, recall of 86% and F1 score (the harmonic mean of precision and recall) of 88%. Model performance was consistent across the range of floral abundance in this habitat. Comparison of the nectar sugar mass estimates made by the CNN and three human surveyors returned similar means and standard deviations. Over half of the nectar sugar mass estimates made by the model fell within the absolute range of those of the human surveyors. The optimal number of quadrat image samples was determined to be the same for the CNN as for the average human surveyor. For a standard quadrat sampling protocol of 10–15 replicates, this application of deep learning could cut pollinator‐plant survey time per stand of vegetation from hours to minutes. The CNN is restricted to a single view of a quadrat, with no scope for manual examination or specimen collection, though in contrast to human surveyors its object detection is deterministic and its floral unit definition is standardized. As agri‐environment schemes move from prescriptive to results‐based, this approach provides an independent barometer of grassland management which is usable by both landowner and scheme administrator. The model can be adapted to visual estimations of other ecological resources such as winter bird food, floral pollen volume, insect infestation and tree flowering/fruiting, and by adjustment of classification threshold may show acceptable taxonomic differentiation for presence–absence surveys.

show abstract

Enhancing road verges to aid pollinator conservation: A review

Cited by 77 publications

References 104 publications

Roles of roadside vegetation in insect conservation in Australia

Roles of roadside vegetation in insect conservation in Australia

Linear infrastructure habitats increase landscape-scale diversity of plants but not of flower-visiting insects

Deep learning object detection to estimate the nectar sugar mass of flowering vegetation

Contact Info

Product

Resources

About