Published March 1, 2017 | Version v1
Journal article

A modelling framework to predict bat activity patterns on wind farms: An outline of possible applications on mountain ridges of North Portugal

  • 1. Laboratory of Applied Ecology, CITAB - Centre for the Research and Technology of Agro-Environment and Biological Sciences, University of Trás-os-Montes e Alto Douro, 5000-911 Vila Real (Portugal)
  • 2. Fluvial Ecology Laboratory CITAB, Centre for Research and Technology of Agro-Environment and Biological Sciences, University of Trás-os-Montes and Alto Douro, 5000-911 Vila Real (Portugal)

Description

Worldwide ecological impact assessments of wind farms have gathered relevant information on bat activity patterns. Since conventional bat study methods require intensive field work, the prediction of bat activity might prove useful by anticipating activity patterns and estimating attractiveness concomitant with the wind farm location. A novel framework was developed, based on the stochastic dynamic methodology (StDM) principles, to predict bat activity on mountain ridges with wind farms. We illustrate the framework application using regional data from North Portugal by merging information from several environmental monitoring programmes associated with diverse wind energy facilities that enable integrating the multifactorial influences of meteorological conditions, land cover and geographical variables on bat activity patterns. Output from this innovative methodology can anticipate episodes of exceptional bat activity, which, if correlated with collision probability, can be used to guide wind farm management strategy such as halting wind turbines during hazardous periods. If properly calibrated with regional gradients of environmental variables from mountain ridges with windfarms, the proposed methodology can be used as a complementary tool in environmental impact assessments and ecological monitoring, using predicted bat activity to assist decision making concerning the future location of wind farms and the implementation of effective mitigation measures. - Highlights: • A holistic methodology was developed to predict bat activity on windfarms. • Bat activity was associated with specific environmental conditions and scenarios. • Model framework outputs could estimate the attractiveness of wind turbines. • Attractiveness could support management of windfarms for conservation.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.scitotenv.2016.12.135

Additional details

Identifiers

DOI
10.1016/j.scitotenv.2016.12.135;
PII
S0048-9697(16)32813-3;

Publishing Information

Journal Title
Science of the Total Environment
Journal Volume
581-582
Journal Page Range
p. 337-349
ISSN
0048-9697
CODEN
STENDL

INIS

Country of Publication
Netherlands
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
49065842
Subject category
S54: ENVIRONMENTAL SCIENCES; S17: WIND ENERGY;
Descriptors DEI
ACOUSTIC MONITORING; BATS; DECISION MAKING; ENVIRONMENTAL IMPACT STATEMENTS; FORECASTING; MOUNTAINS; PORTUGAL; RISK ASSESSMENT; SIMULATION; STOCHASTIC PROCESSES; WIND TURBINE ARRAYS
Descriptors DEC
ANIMALS; DEVELOPING COUNTRIES; DOCUMENT TYPES; EUROPE; MAMMALS; MONITORING; VERTEBRATES; WESTERN EUROPE

Optional Information

Copyright
Copyright (c) 2016 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.