Monitoring environmental effects on farmland Lepidoptera: Does necessary sampling effort vary between different bio-geographic regions in Europe?
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In: Ecological Indicators, Vol. 102, 07.2019, p. 791-800.
Research output: Journal contributions › Journal articles › Research › peer-review
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TY - JOUR
T1 - Monitoring environmental effects on farmland Lepidoptera
T2 - Does necessary sampling effort vary between different bio-geographic regions in Europe?
AU - Lang, Andreas
AU - Kallhardt, Franz
AU - Lee, Marina S.
AU - Loos, Jacqueline
AU - Molander, Mikael A.
AU - Muntean, Iulia
AU - Pettersson, Lars B.
AU - Rákosy, László
AU - Stefanescu, Constantí
AU - Messéan, Antoine
PY - 2019/7
Y1 - 2019/7
N2 - In agro-ecosystems, environmental monitoring is fundamental to detect and survey changes related to land use change and management practices. Butterflies and moths have often been suggested as suitable indicators for monitoring environmental effects on biodiversity in farmlands. Here, we estimated the required sample size and monitoring effort necessary to run a Lepidoptera survey in European farmland, assessing in particular if monitoring investment would differ between representative bio-geographical regions.We operated linear 1-km long transect routes in farmland of Romania, Spain and Sweden from 2013 to 2015, and recorded butterflies and burnet moths (Papilionoidea, Zygaenidae). The transects were walked back and forth four times a season, and replicated yearly. The lepidopteran diversity was high in farmlands of Romania and Spain, but comparatively low in Sweden. The coefficient of variation (CV) of recorded species number differed between countries being lowest in Sweden and highest in Spain. In general, the CV dropped above a transect length of 400–800 m, thus indicating an increase in statistical power. Assuming a non-parametric test for matched samples, power calculations were conducted with the raw count data and with log-transformed count data for comparison. When using log-transformed data, the required sample size to detect an effect was less than 10 transects per country or region (in order to detect a 10% loss of species or a decrease of 30% in total abundance). Specific subgroups of species, e.g. protected species or specific indicator groups, showed a higher variance, thus requiring a higher sample size to detect effects ranging from 12 to 16 transects (equivalent to 21–29 working days per country and year). When using original, untransformed count data a considerably larger sample size would be needed. Actual time to be invested in field work differed between countries due to contrasting regional constraints and conditions. Nevertheless, the final monitoring effort in working days was similar between countries as the factors involved balanced out each other, in particular due to the differing year-to-year variations.Our study demonstrated the feasibility of an environmental monitoring programme in arable land using farmland butterflies across Europe. We present a suitable approach and guidelines as well as the necessary effort to be invested in future Europe-wide monitoring programmes of butterflies in agro-ecosystems, based on predictions of statistical power.
AB - In agro-ecosystems, environmental monitoring is fundamental to detect and survey changes related to land use change and management practices. Butterflies and moths have often been suggested as suitable indicators for monitoring environmental effects on biodiversity in farmlands. Here, we estimated the required sample size and monitoring effort necessary to run a Lepidoptera survey in European farmland, assessing in particular if monitoring investment would differ between representative bio-geographical regions.We operated linear 1-km long transect routes in farmland of Romania, Spain and Sweden from 2013 to 2015, and recorded butterflies and burnet moths (Papilionoidea, Zygaenidae). The transects were walked back and forth four times a season, and replicated yearly. The lepidopteran diversity was high in farmlands of Romania and Spain, but comparatively low in Sweden. The coefficient of variation (CV) of recorded species number differed between countries being lowest in Sweden and highest in Spain. In general, the CV dropped above a transect length of 400–800 m, thus indicating an increase in statistical power. Assuming a non-parametric test for matched samples, power calculations were conducted with the raw count data and with log-transformed count data for comparison. When using log-transformed data, the required sample size to detect an effect was less than 10 transects per country or region (in order to detect a 10% loss of species or a decrease of 30% in total abundance). Specific subgroups of species, e.g. protected species or specific indicator groups, showed a higher variance, thus requiring a higher sample size to detect effects ranging from 12 to 16 transects (equivalent to 21–29 working days per country and year). When using original, untransformed count data a considerably larger sample size would be needed. Actual time to be invested in field work differed between countries due to contrasting regional constraints and conditions. Nevertheless, the final monitoring effort in working days was similar between countries as the factors involved balanced out each other, in particular due to the differing year-to-year variations.Our study demonstrated the feasibility of an environmental monitoring programme in arable land using farmland butterflies across Europe. We present a suitable approach and guidelines as well as the necessary effort to be invested in future Europe-wide monitoring programmes of butterflies in agro-ecosystems, based on predictions of statistical power.
KW - Sustainability Science
KW - Buterflies
KW - Farmland
KW - Survey
KW - Monitoring
KW - Power analysis
KW - Sample Size
KW - Cost efficiency
KW - Data transformation
UR - http://www.scopus.com/inward/record.url?scp=85063437014&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/63320667-edbc-34a5-b6db-d037de7f128c/
U2 - 10.1016/j.ecolind.2019.03.035
DO - 10.1016/j.ecolind.2019.03.035
M3 - Journal articles
VL - 102
SP - 791
EP - 800
JO - Ecological Indicators
JF - Ecological Indicators
SN - 1470-160X
ER -