Evidence map›Paper›PMID 42414671›Full record

ArticleEnvironmental management2026

How landscape factors relate to biodiversity-economic performance in an Estonian grassland-rich region.

Takamasa Nishizawa, Johannes Schuler, Miguel Villoslada, Claudia Bethwell, Michael Glemnitz, Maaria Semm, Monika Suškevičs, Kalev Sepp, Rando Värnik, Florian Kestel and 4 more

Abstract read
In one paragraph

Article in Environmental management, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Takamasa NishizawaLeibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany. takamasa.nishizawa@gmail.com.
Johannes SchulerLeibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany.
Miguel VillosladaDepartment of Biology, School of Experimental Sciences and Technology, Rey Juan Carlos University, Madrid, Spain.
Claudia BethwellLeibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany.
Michael GlemnitzLeibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany.
Maaria SemmInstitute of Agricultural and Environmental Sciences, Chair of Environmental Protection and Landscape Management, Estonian University of Life Sciences, Tartu, Estonia.
Monika SuškevičsInstitute of Agricultural and Environmental Sciences, Chair of Environmental Protection and Landscape Management, Estonian University of Life Sciences, Tartu, Estonia.
Kalev SeppInstitute of Agricultural and Environmental Sciences, Chair of Environmental Protection and Landscape Management, Estonian University of Life Sciences, Tartu, Estonia.
Rando VärnikInstitute of Agriculture and Environment, Chair of Rural Economics, Estonian University of Life Sciences, Tartu, Estonia.
Florian KestelLeibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany.
Meelis OtsInstitute of Veterinary Medicine and Animal Science, Chair of Animal Nutrition, Estonian University of Life Sciences, Tartu, Estonia.
Peter ZanderLeibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany.
Zander VenterNorwegian Institute for Nature Research - NINA, Oslo, Norway.
Sandra UthesLeibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany.

Funding

Bundesministerium für Bildung und Forschung 01LC1809ABundesministerium für Bildung und Forschung 16LW0319Estonian Research Competency Council 4-8/19/10
6 · The paper itself

Abstract

Halting biodiversity loss on semi-natural grassland has become a key priority of agri-environmental policies in Estonia. However, to what extent current schemes are sufficient to achieve biodiversity targets and the role of landscape factors is still insufficiently understood in this context. This study explored trade-offs between profitability and biodiversity conservation across heterogeneous Estonian agricultural landscapes to support the development of economically effective grassland conservation schemes. To this end, we selected twelve 'landscape windows' in a grassland-rich region that represent a gradient of several biodiversity-related landscape factors (semi-natural grassland share, yield potential and landscape complexity). Profitability was assessed using total gross margins derived from a bio-economic model, while biodiversity was evaluated through habitat values for different bird species, based on model outputs. We found that landscapes with higher complexity, which currently maintain higher biodiversity levels, had a corresponding lower farm profitability. In particular, landscape windows dominated by semi-natural grasslands with low grass yields showed the lowest profitability, largely due to limited capacity for feeding beef cattle. In contrast, arable land-dominated landscapes (i.e. those with higher yield potential) demonstrated considerable potential for enhancing biodiversity outcomes while minimising profitability losses. Therefore, conservation policy faces two main challenges: 1. preserving landscapes with high biodiversity value against further decline in profitability, 2. highlighting the need to explore and design biodiversity measures in arable-dominated landscapes that could improve biodiversity outcomes while limiting impacts on farm profitability. This study illustrates that landscape factors deserve greater attention in conservation planning.

Indexed as

BiodiversityConservation of Natural ResourcesGrasslandAgricultureAnimalsEstoniabiodiversity conservationbiodiversity-economic performancelandscape factorsremote sensingsemi-natural grassland

Identifiers

PMID42414671
PMCPMC13342203

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.