Development and implementation of a high nature value (HNV) farming indicator for Denmark

Brunbjerg, Ane Kirstine; Bladt, Jesper; Brink, Martin; Fredshavn, Jesper; Mikkelsen, Peter Høgh; Moeslund, Jesper Erenskjold; Nygaard, Bettina; Skov, Flemming; Ejrnæs, Rasmus

doi:10.1016/j.ecolind.2015.09.027

Cited by 29 publications

(21 citation statements)

References 33 publications

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“…This would allow hitherto unseen possibilities for evidence‐based biodiversity management (Brunbjerg et al. , Mao et al. ), and help to precisely target field‐based biodiversity monitoring nationwide.…”

Section: Discussionmentioning

confidence: 99%

Light detection and ranging explains diversity of plants, fungi, lichens, and bryophytes across multiple habitats and large geographic extent

Moeslund

Zlinszky

Ejrnæs

et al. 2019

Ecological Applications

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Effective planning and nature management require spatially accurate and comprehensive measures of the factors important for biodiversity. Light detection and ranging (LIDAR) can provide exactly this, and is therefore a promising technology to support future nature management and related applications. However, until now studies evaluating the potential of LIDAR for this field have been highly limited in scope. Here, we assess the potential of LIDAR to estimate the local diversity of four species groups in multiple habitat types, from open grasslands and meadows over shrubland to forests and across a large area (~43,000 km2), providing a crucial step toward enabling the application of LIDAR in practice, planning, and policy‐making. We assessed the relationships between the species richness of macrofungi, lichens, bryophytes, and plants, respectively, and 25 LIDAR‐based measures related to potential abiotic and biotic diversity drivers. We used negative binomial generalized linear modeling to construct 19 different candidate models for each species group, and leave‐one‐region‐out cross validation to select the best models. These best models explained 49%, 31%, 32%, and 28% of the variation in species richness (R 2) for macrofungi, lichens, bryophytes, and plants, respectively. Three LIDAR measures, terrain slope, shrub layer height and variation in local heat load, were important and positively related to the richness in three of the four species groups. For at least one of the species groups, four other LIDAR measures, shrub layer density, medium‐tree layer density, and variations in point amplitude and in relative biomass, were among the three most important. Generally, LIDAR measures exhibited strong associations to the biotic environment, and to some abiotic factors, but were poor measures of spatial landscape and temporal habitat continuity. In conclusion, we showed how well LIDAR alone can predict the local biodiversity across habitats. We also showed that several LIDAR measures are highly correlated to important biodiversity drivers, which are notoriously hard to measure in the field. This opens up hitherto unseen possibilities for using LIDAR for cost‐effective monitoring and management of local biodiversity across species groups and habitat types even over large areas.

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Section: Discussionmentioning

confidence: 99%

Light detection and ranging explains diversity of plants, fungi, lichens, and bryophytes across multiple habitats and large geographic extent

Moeslund

Zlinszky

Ejrnæs

et al. 2019

Ecological Applications

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“…Between 2009 and 2013, there was a significant decline of HNV value, in particular in the HNV class III, which represents the lowest value (in terms of species richness and structure). Graph reproduced from (Benzler et al 2015). Systematic EU wide monitoring programmes are being developed for butterflies and pollinators.…”

Section: The German Hnv Monitoring Methodology and Results -Hnv Valuementioning

confidence: 99%

“…Initial results indicate that over only two years the amount of HNV farmland has reduced significantly, mainly as a result of losses of poorer quality HNV arable and grassland areas (see Fig. 6) (Benzler et al 2015).…”

Section: Prospects For Biodiversity Monitoring and Data Use To Informmentioning

confidence: 99%

“…High Nature Value farmland (HNVF) comprises areas where agriculture is a major (usually dominant) land use and where that agriculture supports or is associated with either a high species and habitat diversity, or the presence of species of European and/or national and/ or regional conservation concern (Beaufoy and Cooper 2008). HNVF is under threat from agricultural intensification, land abandonment and urbanisation.…”

Section: High Nature Value (Hnv) Farming Indicator and Mappingmentioning

confidence: 99%

“…Tests that have compared HNV maps produced from land cover data with species and habitat occurrence on the ground have found that accuracy is low, partly because of the land cover spatial resolution and scale but also partly because of uncertainty about which species are the best HNV indicators and lack of data on these indicator species. In the UK, the HNVF map produced for the 2007-2013 RDP using land cover data was compared to local data from three case study regions, which found that the species and habitat mapping was very unreliable at the local level (Beaufoy and Jones 2012). A study in Italy (Morelli et al 2014) compared the HNV distribution mapped from land cover data with species distribution models for breeding farmland birds in a region from point counts.…”

Section: High Nature Value (Hnv) Farming Indicator and Mappingmentioning

confidence: 99%

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The use of biodiversity data in rural development programming

Underwood¹,

Grace²

2017

RIO

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This study focuses on rural development policy implementers and evaluators as users of European biodiversity data. It critically analyses the use of biodiversity data for measuring the impact of agri-environment programmes and related rural development funding, and highlights good practices from a range of countries. The examples show the possibilities for better targeting and evaluation of agricultural funding to biodiversity conservation if sufficient biodiversity data are available and are used in policy. However, many biodiversity datasets exist at the national or regional level but are still not integrated in the RDP monitoring system and thus not accessible to evaluators, and many RDPs still feature only the obligatory EU-level indicators. It is important to differentiate between the need for standardised EU-level datasets that can be used for an overall assessment of the impact of the CAP, where there is still a huge data gap, and the national or regional programming level, where there are often existing data that are not being used for various reasons. The study is part of the EU BON project, which aimed to build an integrated biodiversity information system for Europe.

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The collapse of marsh fritillary ( Euphydryas aurinia ) populations associated with declining host plant abundance

Brunbjerg

Høye

Eskildsen

et al. 2017

Biological Conservation

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Development and implementation of a high nature value (HNV) farming indicator for Denmark

Cited by 29 publications

References 33 publications

Light detection and ranging explains diversity of plants, fungi, lichens, and bryophytes across multiple habitats and large geographic extent

Light detection and ranging explains diversity of plants, fungi, lichens, and bryophytes across multiple habitats and large geographic extent

The use of biodiversity data in rural development programming

The collapse of marsh fritillary ( Euphydryas aurinia ) populations associated with declining host plant abundance

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