Conducting conservation social science surveys online

The coronavirus (COVID-19) pandemic is affecting the environment and conservation research in fundamental ways. Many conservation social scientists are now administering survey questionnaires online, but they must do so while ensuring rigor in data collection. Further, they must address a suite of unique challenges, such as the increasing use of mobile devices by participants and avoiding bots or other survey fraud. We reviewed recent literature on online survey methods to examine the state of the field related to online data collection and dissemination. We illustrate the review with examples of key methodological decisions made during a recent national study of people who feed wild birds, in which survey respondents were recruited through an online panel and a sample generated via a project participant list. Conducting surveys online affords new opportunities for participant recruitment, design, and pilot testing. For instance, online survey panels can provide quick access to large and diverse samples of people. Based on the literature review and our own experiences, we suggest that to ensure high-quality online surveys one should account for potential sampling and nonresponse error, design survey instruments for use on multiple devices, test the instrument, and use multiple protocols to identify data quality problems. We also suggest that research funders, journal editors, and policy makers can all play a role in ensuring high-quality survey data are used to inform effective conservation programs and policies.     

Estimation of the impact of prevailing weather conditions on the occurrence of oil-contaminated dead birds on the German North Sea coast

Chronic oil pollution by illegal oil dumping in the North Sea is difficult to quantify. Beached, oil-contaminated sea birds, however, may be used as an indirect indicator. Reconstructing the drift of oil slicks and sea bird corpses in the southern North Sea for the period 1992-2003 by means of a two-dimensional numerical transport model driven by re-analysed weather data, we show with an example of two common sea bird species that the variability observed within the number of corpses registered during beached bird surveys for the German coast primarily reflects the inter-annual variability of prevailing weather conditions. This should be taken into account when interpreting the data. We propose normalisation of beached bird survey data based on numerical drift simulations to improve the recognition of trends in the level of chronic oil pollution.     

Public Nutrition from an Approach to a Discipline: Concern's Nutrition Case Studies in Complex Emergencies

The Public Nutrition approach, like that of Public Health, is context specific. It places an emphasis on populations rather than individuals and is inter-disciplinary in nature. Both approaches seek to understand the complex aetiology of a clinical outcome such as malnutrition within the widest possible framework. Public Nutrition uses the UNICEF conceptual framework and adapts and expands it. The authors of this article argue – through the examination of a number of case studies taken from the work of Concern Worldwide (hereafter referred to as Concern) in southern Sudan, Rwanda, Angola, Tanzania and DRC – that there are two critical constituents of the Public Nutrition approach. These are: a contextual analysis (including the use of surveillance information for programme design and advocacy) and community involvement at all stages of the project cycle. Some of the key obstacles to the adoption of the Public Nutrition approach are identified by illustrating two practical programme settings. For the Public Nutrition approach to be more widely used, the authors recommend a number of key strategies including the further dissemination of case studies and the clarification of the scope and boundaries of the approach. These strategies will enable Public Nutrition to evolve both as a practical programme framework as well as an academic discipline.     

Incorporating detectability of threatened species into environmental impact assessment

Environmental impact assessment (EIA) is a key mechanism for protecting threatened plant and animal species. Many species are not perfectly detectable and, even when present, may remain undetected during EIA surveys, increasing the risk of site‐level loss or extinction of species. Numerous methods now exist for estimating detectability of plants and animals. Despite this, regulations concerning survey protocol and effort during EIAs fail to adequately address issues of detectability. Probability of detection is intrinsically linked to survey effort; thus, minimum survey effort requirements are a useful way to address the risks of false absences. We utilized 2 methods for determining appropriate survey effort requirements during EIA surveys. One method determined the survey effort required to achieve a probability of detection of 0.95 when the species is present. The second method estimated the survey effort required to either detect the species or reduce the probability of presence to 0.05. We applied these methods to Pimelea spinscens subsp. spinescens, a critically endangered grassland plant species in Melbourne, Australia. We detected P. spinescens in only half of the surveys undertaken at sites where it was known to exist. Estimates of the survey effort required to detect the species or demonstrate its absence with any confidence were much higher than the effort traditionally invested in EIA surveys for this species. We argue that minimum survey requirements be established for all species listed under threatened species legislation and hope that our findings will provide an impetus for collecting, compiling, and synthesizing quantitative detectability estimates for a broad range of plant and animal species. Incorporación de la Capacidad de Detectar una Especie Amenazada a la Evaluación de Impacto Ambiental     

A Bayesian hierarchical model for monitoring harbor seal changes in Prince William Sound, Alaska

Bayesian hierarchical models were used to assess trends of harbor seals, Phoca vitulina richardsi, in Prince William Sound, Alaska, following the 1989 Exxon Valdez oil spill. Data consisted of 4–10 replicate observations per year at 25 sites over 10 years. We had multiple objectives, including estimating the effects of covariates on seal counts, and estimating trend and abundance, both per site and overall. We considered a Bayesian hierarchical model to meet our objectives. The model consists of a Poisson regression model for each site. For each observation the logarithm of the mean of the Poisson distribution was a linear model with the following factors: (1) intercept for each site and year, (2) time of year, (3) time of day, (4) time relative to low tide, and (5) tide height. The intercept for each site was then given a linear trend model for year. As part of the hierarchical model, parameters for each site were given a prior distribution to summarize overall effects. Results showed that at most sites, (1) trend is down; counts decreased yearly, (2) counts decrease throughout August, (3) counts decrease throughout the day, (4) counts are at a maximum very near to low tide, and (5) counts decrease as the height of the low tide increases; however, there was considerable variation among sites. To get overall trend we used a weighted average of the trend at each site, where the weights depended on the overall abundance of a site. Results indicate a 3.3% decrease per year over the time period.     

Survey methods for assessing land cover map accuracy

The increasing availability of digital photographic materials has fueled efforts by agencies and organizations to generate land cover maps for states, regions, and the United States as a whole. Regardless of the information sources and classification methods used, land cover maps are subject to numerous sources of error. In order to understand the quality of the information contained in these maps, it is desirable to generate statistically valid estimates of accuracy rates describing misclassification errors. We explored a full sample survey framework for creating accuracy assessment study designs that balance statistical and operational considerations in relation to study objectives for a regional assessment of GAP land cover maps. We focused not only on appropriate sample designs and estimation approaches, but on aspects of the data collection process, such as gaining cooperation of land owners and using pixel clusters as an observation unit. The approach was tested in a pilot study to assess the accuracy of Iowa GAP land cover maps. A stratified two-stage cluster sampling design addressed sample size requirements for land covers and the need for geographic spread while minimizing operational effort. Recruitment methods used for private land owners yielded high response rates, minimizing a source of nonresponse error. Collecting data for a 9-pixel cluster centered on the sampled pixel was simple to implement, and provided better information on rarer vegetation classes as well as substantial gains in precision relative to observing data at a single-pixel.     

Groundwater quality: Responsible agriculture and public perceptions

The chief sources of groundwater contamination on farms come from point sources and diffuse sources. Possible point sources are feedlots, poorly-sited manure piles, septic sewage-treatment systems—all of which can release nitrate, phosphates and bacteria— and sites of chemical spills. Diffuse sources are typified by excess fertilizer leaching from a number of arable fields. The basis of quality standards for drinking-water is discussed in relation to common contaminants present on farms. Samples of drinking-water were collected in 1991–1992 from wells on about 1,200 farms in order to study the quality of rural groundwater in Ontario. Analysis showed that approximately one third of wells were contaminated with bacteria, 14% were contaminated with nitrate, two wells were contaminated with pesticide, but 40% were considered unsafe because of the presence of at least one contaminant. These values were similar to those reported for similar regions in the U.S. There was no significant effect of agricultural practice on the proportion of contaminated samples. One response of Ontario's farmers to information on water quality has been to initiate their own program, the Environmental Farm Plan, which has 23 modules by which the risk of environmental contamination can be assessed. Government policies for agriculture can be expected to influence farming practices. However, the literature suggests that the consequences of policies aimed at reducing environmental contamination are poorly understood, not least because the instruments used for implementation can have widely differing impacts. The need for discussions on the ethics surrounding the relationship between food producers and consumers with regard to environmental contamination is identified.     

Electrofishing in boatable rivers: Does sampling design affect bioassessment metrics?

Data were collected from 60 boatable sites using an electrofishing design that permitted comparisons of the effects of designs and distances on fish assemblage metrics. Sites were classified a priori as Run-of-the-River (ROR) or Restricted Flow (RF). Data representing four different design options (i.e., 1000 and 2000 m for both single and paired banks) were extracted from the dataset and analyzed. Friedman tests comparing metric values among the designs detected significant differences for all richness metrics at both types of sites and for catch per unit effort and percent tolerant species at ROR sites. Richness metrics were generally higher for the two 2000-m designs than for the two 1000-m designs. When plotted against cumulative electrofishing distance, the percent change in metrics declined sharply within approximately 1000 m, after which metrics usually varied by less than 10%. These data demonstrate that designs electrofishing 1000 m of shoreline are sufficient for bioassessments on boatable rivers similar to those in this study, regardless of whether the shoreline is along a single bank or distributed equally among paired banks. However, at sites with depths greater than 4 m, it may be advisable to employ nighttime electrofishing or increase day electrofishing designs to 2000 m.The U.S. Governments right to retain a non-exclusive, royalty free licence in and to any copyright is acknowledged.     

Dealing with the Clandestine Nature of Wildlife‐Trade Market Surveys

Abstract: Illegal international trade in wildlife (excluding fisheries and timber) has been valued at more than US$20 billion. A more precise figure has not been determined in part because of the clandestine nature of the trade, and for this same reason even regional and local levels of wildlife trade are difficult to assess. The application of recent developments in wildlife field‐survey methods (e.g., occupancy) now allows for a more‐accurate estimation of wildlife trade occurrence, including its hidden components at a variety of scales (e.g., regional, local) and periods (e.g., single season, 1 year, multiple years). Occupancy models have been applied in wildlife field studies to address the problem of false absences when conducting presence–absence surveys. Occupancy surveys differ from traditional presence–absence surveys because they incorporate repeat surveys, allowing for the likelihood of detecting a species (the probability of detection) to be estimated explicitly (in contrast to traditional surveys that often incorrectly treat this probability as close to one to allow for estimation of presence). Occupancy methods can be applied to a variety of wildlife‐trade surveys, including, for example, single‐species availability, links between two illegally traded species (i.e., co‐occurrence), and disease occurrence in live trade. In addition, free user‐friendly software (i.e., PRESENCE) allows even nonstatisticians to adequately address this issue. I simulated a hypothetical wildlife‐trade market survey that resulted in an apparent 20% decline in naïve occupancy (proportion of surveyed towns engaged in the trade) over 2 years, but when I accounted for change in probability of detection over the years the difference in occupancy was not statistically significant. As more sophisticated methods, such as occupancy, are applied to wildlife‐trade market surveys, results will be more robust and defensible and therefore, theoretically, more powerful when presented to conservation policy and decision makers.     

Wind farm and fauna interaction: detecting bird and bat wing beats through cyclic motion analysis

Recent Government announcements have implied that wind power will play a major part in providing energy for the UK (BBC 2007 BBC. 2007. Wind ‘could power all UK homes’ [online], British Broadcasting Corporation. Available from: http://news.bbc.co.uk/1/hi/uk_politics/7135930.stm [Accessed 20 January 2008] [Google Scholar]). However, there is much concern that wind farms can have a significant impact on flying fauna (bats and birds) using the area, particularly at night. As part of an Environmental Impact Assessment, thorough appropriate surveys are necessary for quantifying and minimising any risk wind farms may cause flying fauna. Manual surveys that are commonly used are not always cost‐effective, efficient or practical. Remote systems based on motion detection are increasingly being used to monitor wildlife.

Fast‐moving airborne targets such as aeroplanes can falsely trigger motion‐detection based remote systems. As birds and bats repetitively flap their wings, this oscillating motion can be used to distinguish them from other airborne targets. Time periods between wing oscillations are not always constant, and hence the motion is not periodic. A method to detect cyclic motion based on similarity matrices is proposed, and synthetic and real data are used.