Googling Trends in Conservation Biology

Essay

Googling Trends in Conservation Biology RAPHAE¨L PROULX, PHILIPPE MASSICOTTE, AND MARC PE´PINO Centre de recherche sur les interactions bassins versants—écosystèmes aquatiques (RIVE) and Groupe de recherche interuniversitaire en limnologie (GRIL), Université du Québec à Trois-Rivières, C.P. 500, Trois-Rivières, Québec, G9A 5H7, Canada, email [email protected]

Abstract: Web-crawling approaches, that is, automated programs data mining the internet to obtain information about a particular process, have recently been proposed for monitoring early signs of ecosystem degradation or for establishing crop calendars. However, lack of a clear conceptual and methodological framework has prevented the development of such approaches within the field of conservation biology. Our objective was to illustrate how Google Trends, a freely accessible web-crawling engine, can be used to track changes in timing of biological processes, spatial distribution of invasive species, and level of public awareness about key conservation issues. Google Trends returns the number of internet searches that were made for a keyword in a given region of the world over a defined period. Using data retrieved online for 13 countries, we exemplify how Google Trends can be used to study the timing of biological processes, such as the seasonal recurrence of pollen release or mosquito outbreaks across a latitudinal gradient. We mapped the spatial extent of results from Google Trends for 5 invasive species in the United States and found geographic patterns in invasions that are consistent with their coarse-grained distribution at state levels. From 2004 through 2012, Google Trends showed that the level of public interest and awareness about conservation issues related to ecosystem services, biodiversity, and climate change increased, decreased, and followed both trends, respectively. Finally, to further the development of research approaches at the interface of conservation biology, collective knowledge, and environmental management, we developed an algorithm that allows the rapid retrieval of Google Trends data. Keywords: biodiversity, ecosystem services, Google Trends, phenology, public awareness, species distribution, web crawling

Resumen: Los métodos de navegación en la red, esto es, programas automatizados de miner´ıa de datos para obtener informaci´ on de un proceso determinado, han sido propuestos recientemente para monitorear se˜ nales tempranas de la degradaci´ on de ecosistemas o para el establecimiento de calendarios de cosecha. Sin embargo, la falta de un marco conceptual y metodol´ ogico ha prevenido el desarrollo de tales métodos en el campo de la biolog´ıa de la conservaci´ on. Nuestro objetivo fue ilustrar como Google Trends, una plataforma de rastreo en la red accesible gratuitamente, puede ser utilizado para seguir los cambios de cronolog´ıa en procesos biol´ ogicos, distribuci´ on espacial de especies invasoras y el nivel de conciencia p´ ublica acerca de temas clave de conservaci´ on. Google Trends reporta el n´ umero de b´ usquedas por internet realizadas para una palabra clave en una regi´ on determinada del mundo en un per´ıodo definido. Mediante el uso de datos recuperados para 13 pa´ıses, ejemplificamos como se puede usar Google Trends para estudiar la cronolog´ıa de procesos biol´ ogicos, como la recurrencia estacional de liberaci´ on de polen o brotes de mosquitos en un gradiente latitudinal. Mapeamos la extensi´ on espacial de los resultados de Google Trends para cinco especies invasoras en Estados Unidos y encontramos patrones geogr´ aficos de invasiones que son consistentes con su distribuci´ on de grano grueso a nivel estatal. De 2004 a 2012 Google Trends mostr´ o que el nivel de interés y conciencia del p´ ublico sobre temas de conservaci´ on relacionados con servicios del ecosistema, biodiversidad y cambio clim´ atico incrementaron, disminuyeron y siguieron ambas tendencias, respectivamente. Finalmente, para promover el desarrollo de métodos de investigaci´ on en la interfaz de la biolog´ıa de la conservaci´ on, el conocimiento colectivo y la gesti´ on ambiental, desarrollamos un algoritmo que permite la r´ apida recuperaci´ on de datos de Google Trends.

Paper submitted January 16, 2013; revised manuscript accepted April 12, 2013.

1 Conservation Biology, Volume 00, No. 00, 1–8 C 2013 Society for Conservation Biology DOI: 10.1111/cobi.12131

Trends in Conservation Biology

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Palabras Clave: Biodiversidad, conciencia pública, distribución de especies, fenolog´ıa, rastreo en la red, servicios del ecosistema, Tendencias de Google

Introduction With the recent advents of highly distributed mobile networks and online social platforms, combined with the establishment of online search engines, access to information has never been so extensive and immediate (e.g., Barroso et al. 2003; Butler 2006; Aanensen et al. 2009). Paradoxically, gathering data on the distribution and abundance of species at high spatial and temporal resolution is still a major shortcoming of current ecosystems, or species, monitoring programs (Morisette et al. 2009; Cleland et al. 2012). Online data streams are increasingly being used by economists (Vosen & Schmidt 2011; Choi & Varian 2012), politicians (Relly et al. 2012), and epidemiologists (Carneiro & Mylonakis 2009; Ginsberg et al. 2009; Dugas et al. 2012) alike to provide data on market and public opinion trends or the spread of human infectious diseases. However, this continuous stream of freely available data remains underexploited by conservation biologists, perhaps because the link between biological processes in nature and data driven by human behavior is not as obvious as in other disciplines (e.g., Martin et al. 2012). We used Google Trends, a freely accessible search engine, to track changes in the temporal pattern (phenology) of biological processes and the spatial distribution of invasive species.

Google Trends Google is currently the most-used search engine on the World Wide Web; nearly 5 billion queries are submitted every day. As a part of the array of Google online products, Google Trends returns the usage volume of a particular search term for a specific region of the world over a defined period. Search-term hits are recorded at the spatial resolution of individual cities within a region (e.g., France > Bretagne > Brest) and at the temporal resolution of a week. A query in Google Trends first returns a world map of the search-term hits per country and a monthly time series of the search-term hits dating back to 2004. By default, the results returned by Google Trends are rescaled by dividing the search-term hits obtained for a given week by the maximum number of hits obtained at any moment over the period of interest. Query results are accessed by logging into a Google account and downloading a csv file of the data. Manually downloading the many files generated by entering separate search-term queries is cumbersome. Hence, we have developed an R package that allows for the rapid retrieval of Google Trends data (Supporting Information).

Conservation Biology Volume 00, No. 00, 2013

Timing of Biological Processes Phenology is the study of the causes and consequences of advancing or delaying the timing of biological processes, such as plant greening and flowering, pest outbreak, animal migration, or breeding time. For example, trends in the phenology of hundreds of plant species showed earlier spring onset in Europe between 1971 and 2000, advancing at a rate of 2.5 d/decade in response to increased air temperature (Menzel et al. 2006). Despite the importance of phenological records for studying the effects of climate change on biological processes, current monitoring programs often only actively follow a limited number of biological processes at a low temporal and spatial resolution. With these limitations in mind, Google Trends may be viewed as a source of up-to-date collective knowledge about biological processes. The precision of Google Trend data for assessing the timing of biological processes was recently demonstrated by Dugas et al. (2012), who reported a high correlation (Pearson’s r = 0.87) between postprocessed Google Trends data and clinical cases of confirmed influenza in adults and no apparent time lags between the 2 sources of information. To illustrate how Google Trends may be used to track the phenology of biological processes, we queried the search terms mosquitoes and pollen for 4 English speaking countries: Australia, Canada, England, and the United States. Moreover, to provide a geographically comprehensive picture, we entered the same search terms translated into the official languages of 9 additional countries (in parentheses): mosquitoes and pollen (Brazil, Mexico, Spain); dd and dd (China); moustique and pollen (France); m¨ ucken and bl¨ uten (Germany); zanzare and and polline (Italy); d d and d (Japan); and (Thailand). We obtained the timing of biological processes associated with keywords pollen and mosquitoes in each country by extracting for each year from 2008 to 2012, the week associated with the maximum number of search-term hits. Weekly time series of the relative number of search-term hits returned by Google Trends revealed recurring temporal patterns for pollen and mosquitoes (Fig. 1). The seasonal timing of these biological processes at the country level is captured by the broad latitudinal gradient of environmental conditions, at least, for temperate countries of Europe and North America (Fig. 2). The temperate countries of Canada, Germany, England, France, United States, and Australia display clear cyclical patterns of search-term hits. In contrast, such seasonality is difficult to detect in subtropical

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Week (since 1 January 2008) Figure 1. Weekly time series (2008–2012) of the relative number of search-term hits returned by country after querying in Google Trends the keywords pollen and mosquitoes (terms were translated into the official language of the country). A loess smoothing (span of 0.05) was applied to each time series. or tropical countries such as Brazil, Thailand, and Mexico, which are characterized by a large interannual variability in the timing date of both biological processes (large error bars in Fig. 2). Finally, the seasonal inversion of pollen release or mosquitoes outbreak events in southern (e.g., Australia) versus northern hemisphere countries (e.g., Untied States) is also manifest (Figs. 1 & 2). The phenological trends in a country may be explained by the feedback between people’s physiological responses to mosquito bites (cutaneous itching) or pollen exposure (allergic reaction) and their motivation

to search for a remedy on the internet. To further investigate this point, we correlated the query results we obtained for mosquitoes to the search-term hits returned by querying deet and citronella, the 2 main active ingredients in most commercial insect-repellent lotions. We also correlated the query results returned for pollen with those for Zyrtec, Claritin, and Reactin, the 3 main allergytreating drugs sold in Canada and the United States. Using the data from all weeks since 1 January 2008 (n = 253), we obtained high Pearson’s coefficients (r) of 0.90 and 0.91 for the United States and 0.88 and 0.87 (for Canada) for the mosquitoes and pollen correlations,



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England

Canada Spain

Germany USA

Italia France

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Figure 2. Latitudinal variation in the annual peak of search-term hits returned after querying in Google Trends the keywords pollen and mosquitoes for the period 2008–2012. For each country, the annual peak is expressed as the mean date (SD) of search-hit maximum reported each year starting on 1 November. Latitude coordinates were obtained online from the NationMaster database, with the exception of Canada, which was assigned a value of 45◦ N to reflect the strong southward asymmetry in the repartition of human population centers.

respectively, a result that suggests a causal relation between the seasonal recurrence of pollen release or mosquito outbreak and people’s behavioral responses to these 2 processes.

Spatial Distribution of Invasive Species Biodiversity and economic losses caused by newly introduced, rapidly spreading non-native species, is an issue of growing concern in conservation biology, most notably because globalization, and in particular increased inter-


national trading, accelerates the dispersion of species around the world (Puth & Post 2005; Crowl et al. 2008; Pysek et al. 2010). Early detection of invasive non-native species is therefore a fundamental component of preventing their establishment and spread. Because at their introduction populations are generally composed of few individuals, the initial stage of dispersion is a critical step toward the establishment of a non-native invasive species (Puth & Post 2005; Blackburn et al. 2011). However, governmental agencies often lack the resources to detect species introductions at their early stage of dispersion. Moreover, in cases of established invasive species, a considerable amount of public and scientific resources are invested annually to monitor the distribution of these populations. Galaz et al. (2010) proposed combining web-crawling and expert-knowledge approaches for the early detection of ecosystem change or degradation. In the context of our study, a first step in that direction is to determine whether web crawlers, such as Google Trends, can be used to map the spatial distribution of invasive species at the country level. Google Trends spatially disaggregates the volume of returned search-term hits at the level of cities or regions within a country. To illustrate this feature and its potential to address the shortfalls of species detection and tracking, we mapped the distribution of search-term hits for 5 invasive species in the United States. We entered in Google Trends the following search-term queries: ash borer (Agrilus planipennis), Asian carp (Cyprinus carpio, Hypophthalmichthys molitrix, Hypophthalmichthys nobilis, Mylopharyngodon piceus), fire ants (Solenopsis invicta), Africanized bees (Apis mellifera scutellata), and pine beetle (Dendroctonus ponderosae). The resulting maps show the relative volume of search terms returned by state for each of the search terms we queried (Fig. 3). The large number of search-term hits in states bordering the Great Lakes for the emerald ash borer (Haack et al. 2002) and in the upper Mississippi basin for the Asian carp (Koel et al. 2000) reflects their respective areas of origin and current dispersion range in the United States. In the case of Asian carp, the elevated number of search-term hits in the northernmost states also implies apprehension about the invasion of Great Lakes by these fish. The search-term distribution of fire ants and Africanized bees reflects their introduction and dispersal patterns; they were first imported to southern United States in the mid-1990s and have since dispersed to neighboring states (Woodward & Quinn 2011). Finally, it is well documented that current pine beetle outbreaks have occurred and continue to spread eastward across the Rocky Mountain states such as Montana, Wyoming, and Colorado (Evangelista et al. 2011) (Fig. 3). A more thorough validation of Google Trends maps is beyond the scope of this essay, but will be needed in future applications (see also “Google Trends Limitations” below).

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Figure 3. Spatial distribution of the relative number of search-term hits returned for each U.S. state of the conterminous United States after querying 5 invasive species keywords in Google Trends: Africanized bees, Ash borer, Asian carp, Fire ants, and Pine beetle. The numbers have been scaled such that the state with the maximum of search-term hits has a value of 100. The white line was drawn from the reference spatial distribution of each species available at the following websites: Africanized bees, www.nationalatlas.gov/mld/afrbeep; ash borer, www.aphis.usda.gov/plant_health/plant_pest_info/emerald_ash_b; Asian carp, nas.er.usgs.gov/queries/speciesmap.aspx?SpeciesID=551; fire ants, www.aphis.usda.gov/plant_health/plant_pest_info/fireants; pine beetle, www.barkbeetles.org/mountain/fidl2.htm.

Public Awareness of Conservation Issues A central objective of conservation biology is to ensure that best management practices, or environmental threats to biodiversity, are efficiently communicated to decision makers and stakeholders (Malcevschi et al. 2012). Public awareness is often a key component of conservation agendas because the public may not only be stakeholders themselves, but they may also have the power to influence decision makers. In this light, 2 international panels have been established by the United Nations to improve communication among the public, conservation biologists, and policy makers: the Intergovernmental Panel on Climate Change (IPCC) and the Intergovernmental Panel of Biodiversity and Ecosystem Services (IPBES). These panels provide an interface between scientists and policy makers in order to better inform the larger community (e.g., parties involved, stakeholders, and the public) through the publication of periodic reports. Thus, if public interest and awareness is a key ingredient in achieving conservation goals, it leads to the question: are climate change-, biodiversity-, and ecosystem-related issues pro-

gressively garnering more public attention as they become more important, or is interest waning over time? To illustrate how Google Trends can be used to track changes in the level of public interest and awareness about key conservation issues, we entered the keywords climate change, biodiversity, and ecosystem services and graphed their temporal trends between 2004 and 2012 (Fig. 4). Recent conservation issues, such as the ecosystem services concept, are on an overall increasing search trend in English-speaking countries, whereas relatively older conservation issues, such as those related to climate change, are attracting less attention since 2008 (Fig. 4). Moreover, the relative search-term volume of biodiversity stopped declining after 2010, which incidentally was declared the international year of biodiversity. Although interpreting the human-driven motives behind such broad temporal trends is far from trivial, the sole existence of a trend should be seriously considered because Google Trends data are routinely corrected for the total number of web queries made over a given week. Hence, the observed temporal trend in the number of search hits cannot be attributed to baseline changes in the total



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Keyword Biodiversity Climate change Ecosystem services

Search hits

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1 June 2006

1 June 2008

1 June 2010

1 June 2012

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Figure 4. Weekly time series (2004–2012) of the relative number of search-term hits returned after querying in Google Trends the keywords biodiversity, climate change, and ecosystem services. A loess smoothing (span of 30) was applied to each time series to extract the long-term trends of these conservation issues. number of people searching the web. For instance, although the number of persons actively searching the web has substantially increased since 2004, we verified that common search terms such as weather and news do not show temporal trends over the 2004–2012 period. We conducted this verification by entering the 2 keywords (weather and news) in Google Trends and observed no tendency.

Google Trends Limitations First, online keyword queries in Google Trends within a country are sent from highly populated cities, which do not form a representative (spatially extensive, random, unbiased) sample of a region. Second, one cannot know the real motives behind each internet search recorded by Google Trends. For example, we did not know whether search-term queries returned for Asian carp were en-


tered by anglers, researchers studying the topic, or by web surfers looking for a popular Asian carp video. Third, temporal or spatial patterns may be mistakenly interpreted as being driven by biological processes. For example, the Google Trends search-term volume in the United States for pollen correlated identically (Person’s r = 0.85) to both plant flowers and pine straw search hits. Although there may be a direct causal association between pollen and flowering plants, the link between pollen and pine straw is more tenuous. Although substantial, some of these limitations could be counterbalanced if keyword queries are crossvalidated so that they all relate to the same process (e.g., correlating search hits between pollen and plant flowers) or if search trends of irrelevant keywords were removed (e.g., Asian carp youtube). This is what the search engine Google Flu does. In Google Flu, a list of associated search terms are used to estimate seasonal trends in the progression of influenza cases (Dugas et al. 2012).

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Table 1. Main advantages of using Google Trends over conventional field-monitoring programs for tracking changes in the timing of biological processes (T), distribution of invasive species (D), and level of public awareness about conservation issues (P). Added value of Google Trends Cost-effective Rapid assessment High temporal resolution Standardized protocol Multiple spatial scales (local, regional, global)

Associated examples P, D, T P, D, T P, D, T P, D, T P, D, T

communities is impaired if biological processes become less synchronized over time, could also be tested more extensively. Moreover, governmental agencies may have interest in monitoring the invasion front of a recently introduced species. What is more, they may want to publish maps showing where the temporal trends of a species search term is increasing, decreasing, or remains stable and use this information to take actions. Increasing public awareness would also lead to an increased volume of internet searches, thus strengthening the use of webcrawling approaches for studying conservation issues.

Google Trend Advantages

Acknowledgments

A thoughtful selection and thorough consideration of keywords apropos of a research question, cultural heritage, and regional differences are therefore the most fundamental steps in this analytical approach (Al-Eroud et al. 2011; Al-Kabi et al. 2012). Once the keywords associated with a particular biological process are defined, temporal and spatial trends for a region can be validated by the governmental agencies or research laboratories that own the data. For example, pollen release is measured as part of public-health monitoring programs, and scientific protocols are routinely established by firms specialized in mosquito control. However, in an era of open access, validation, testing, and use of web-crawling approaches is not limited to data owners. Because the information returned by Google Trends is disaggregated at the city level (Supporting Information), integrating its results with global or regional data sets is a straightforward operation. If one uses cities’ geographic coordinates as an anchor point, Google Trends results can be matched to georeferenced data sets on, for example, climate (Climate Research Unit), topography (Shuttle Radar Topography Mission), land cover, and land use (National Aeronautics and Space Administration’s [NASA] Earth Observing System), species and ecosystem conservation status (World Wildlife Fund; International Union for Conservation of Nature), and socioeconomic data (NASA’s Socioeconomic Data and Applications Center). Google Trends offers several advantages over conventional field-monitoring programs for tracking changes in timing of biological processes, distribution of invasive species, and level of public awareness about conservation issues (Table 1). The list of questions that conservation biologists may tackle with results obtained through internet searches of specific keywords is potentially endless. Questions associated with the effect of climate (e.g., climate warming, drought severity) on advancing or delaying the timing of biological processes could be addressed with such data (Sherman-Morris et al. 2011; van der Velde et al. 2012). The mismatch hypothesis (Durant et al. 2005; Thackeray et al. 2010; Donnelly et al. 2011), which stipulates that the functioning of populations and

We thank all the graduate students and scientists at the RIVE who enjoy thinking outside the box. We thank I. Seiferling, Y. Paradis, and students from the Geomatics and Landscape Ecology Laboratory (Carleton University) for providing engaged comments on the manuscript. R.P., P.M., and M.P. participated in the writing of this essay. R.P. and M.P. contributed the figures, and P.M. has developed the R package for automatically retrieving Google Trends data. This research was supported by a grant from The Natural Sciences and Engineering Research Council of Canada (NSERC).

Supporting Information Googling Trends in Conservation Biology Using R (Appendix S1) is available online. The authors are solely responsible for the content and functionality of these materials. Queries (other than absence of the material) should be directed to the corresponding author.

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