DOI: 10.5061/dryad.t1g1jwt87
title: Environmental impact assessment for large carnivores: a methodological review of the wolf (Canis lupus) monitoring in Portugal

description: The continuous growth of the global human population results in increased
 use and change of landscapes, with infrastructures like transportation or
 energy facilities, being a particular risk to large carnivores.
 Environmental Impact Assessments were established to identify the probable
 environmental consequences of any new proposed project, find ways to
 reduce impacts, and provide evidence to inform decision making and
 mitigation. Portugal has a wolf population of around 300 individuals,
 designated as an endangered species with full legal protection. They
 occupy the northern mountainous areas of the country which has also been
 the focus of new human infrastructures over the last 20 years.
 Consequently, dozens of wolf monitoring programs have been established to
 evaluate wolf population status, to identify impacts, and to inform
 appropriate mitigation or compensation measures. We reviewed Portuguese
 wolf monitoring programs to answer four key questions: do wolf programs
 examine adequate biological parameters to meet monitoring objectives? is
 the study design suitable for measuring impacts? are data collection
 methods and effort sufficient for the stated inference objectives? and do
 statistical analyses of the data lead to robust conclusions? Overall, we
 found a mismatch between the stated aims of wolf monitoring and the
 results reported, and often neither aligns with the existing national wolf
 monitoring guidelines. Despite the vast effort expended and the diversity
 of methods used, data analysis makes almost exclusive use of relative
 indices or summary statistics, with little consideration of the potential
 biases that arise through the (imperfect) observational process. This
 makes comparisons of impacts across space and time difficult and is
 therefore unlikely to contribute to a general understanding of wolf
 responses to infrastructure-related disturbance. We recommend the
 development of standardized monitoring protocols and advocate for the use
 of statistical methods that account for imperfect detection to guarantee
 accuracy, reproducibility, and efficacy of the programs.
description: We reviewed all major wolf monitoring programs developed for
 environmental impact assessments in Portugal since 2002 (Table S1,
 Supplementary material). Given that the focus here is on the adequacy of
 targeted wolf monitoring for delivering conclusions about the effects of
 infrastructure development, we reviewed only monitoring programs that were
 specifically designed for wolves and not those concerned with general
 mammalian assessment. The starting point was a
 compilation from the 2019-2021 National Wolf Census (Pimenta et al.,
 2023), where every wolf monitoring program that occurred between 2014 and
 2019 in Portugal was identified. The list was completed with projects that
 started before 2014 or after 2019 based on personal knowledge, inquires to
 principal scientific teams, governmental agencies, and EIA consultants.
 Depending on duration, wolf monitoring programs can produce several,
 usually annual, reports that are not peer-reviewed and do not appear on
 standard search engines (e.g., Web of Science or Google Schoolar) but are
 publicly available from the Portuguese Environmental Agency (APA – www.apambiente.pt).
 We conducted an online search on APA´s search engine (https://siaia.apambiente.pt/) and identified a total of 30 projects. For each of these projects, we were interested in the first and the last report to identify any methodological changes. If the last report was not present, we reviewed the most recent one. If no report was present, we requested it from the team responsible. Our investigation centred on characterizing and quantifying four components of wolf monitoring programs that are interlinked and that should be ideally determined by the initial objectives: (1) <em>biological parameters</em>, i.e., what wolf parameters were studied to assess impacts; (2) <em>study design</em>, i.e., what sampling schemes were followed to collect and analyse data; (3) <em>data collection</em>, i.e., which sampling methodology and how much effort was used to collect data; and (4) <em>data analysis</em>, i.e., how data were analysed to estimate relevant parameters and assess impact. <em>Biological parameters</em> were identified and classified under two categories: occurrence and demography, which broadly correspond to the necessary inputs to assess impacts like exclusion effect and changes in reproductive patterns. Occurrence-related parameters refer to variables used to measure the presence or absence of wolves, whereas demographic parameters refer to variables that intend to measure population-level effects such as abundance, density, survival, or reproduction. We also recorded whether any effort was made to quantify prey population distribution or abundance as recommended in the guidelines. For <em>study design</em>, we reviewed the sampling design of the project, with specific focus on the spatial and temporal aspect of the study such as total area surveyed, the definition of a sampling site within this region (i.e., resolution), the duration of the study and the number of sampling seasons. The goal here was to determine whether the sampling scheme used was appropriate for assessing infrastructure impacts on wolf distribution or demography, depending on what the focus was. For <em>data collection</em>, we identified the main data collection methodologies used and the corresponding sampling effort. By far the most frequent method used is sign surveys, and specifically scat surveys, and for these studies we recorded whether genetic identification of species or individuals based on faecal DNA was attempted. We compare how sampling effort varies by the various inference objectives and, as above, assess which, if any, project or data collection approach is most likely to produce evidence of impact. We divided the <em>Analysis</em> component into two groups: single-year and multi-year analyses. For single-year analysis we identified how monitoring projects used data to make inferences about the state biological parameters of interest and discuss the associated strengths and weaknesses. For multi-year analyses, we recorded how differences or trends were quantified and associated with infrastructure impacts, commenting on the statistical robustness of the analyses used across the projects.
description: # Environmental impact assessment and large carnivores: a methodological
 review of the wolf (*Canis lupus*) monitoring in Portugal. This is a
 compilation of 30 wolf monitoring programs for Environmental Impact
 Assessment that occurred in Portugal between 2002 and 2022. We
 characterized and quantified four components of each wolf monitoring
 program, namely: (1) *biological parameters*, i.e., what wolf variables
 were meant to be studied to assess impacts; (2) *study design*, i.e., what
 schemes were followed to collect data in the field; (3) *data collection*,
 i.e., which methodologies and effort was used to collect data from the
 field; (4) *data analysis*, i.e., how data from the field were used to
 estimate relevant parameters and assess impacts on the species. * The Tab
 "Projects_Review" corresponds to a descriptive breakdown of the
 reviewed projects. * The Tab "Data" corresponds to a numerical
 breakdown of the reviewed projects, used in descriptive statistics and
 graphs. In the "Data" tab, N/A cells in Multi-Year information
 refer to projects with only one year, hence Not Applicable. * The Tab
 "Graphs" corresponds to graphical outputs generated from the
 "Data" tab, some used in the manuscript and some others that
 were not.