10.5061/DRYAD.X95X69PGK
Lenda, Magdalena
0000-0001-7824-7220
University of Queensland
Skórka, Piotr
Institute of Nature Conservation
Kuszewska, Karolina
Jagiellonian University
Moroń, Dawid
Institute of Systematics and Evolution of Animals
Bełcik, Michał
Institute of Nature Conservation
Baczek Kwinta, Renata
University of Agriculture in Krakow
Janowiak, Franciszek
Institute of Plant Physiology
Duncan, David H.
University of Melbourne
Vesk, Peter A.
University of Melbourne
Possingham, Hugh P.
University of Queensland
Knops, Johannes M. H.
Xi’an Jiaotong-Liverpool University
Misinformation, internet honey trading, and beekeepers drive a plant invasion
Dryad
dataset
2020
Honeybee
beekeepers
internet trade
pollinators
invasive wildlife trade
FOS: Biological sciences
Polish Ministry of Science and Higher Education*
Mobilność Plus, 1324/1/MOB/IV/15/2016/0
Polish Ministry of Science and Higher Education*
Iuventus Plus, IP2012 029472
ARC Centre of Excellence for Environmental Decisions
https://ror.org/01k8nkc73
CE11001000104
Australian Government
https://ror.org/0314h5y94
Polish Ministry of Science and Higher Education
Mobilność Plus, 1324/1/MOB/IV/15/2016/0
2021-10-22T00:00:00Z
2021-10-22T00:00:00Z
en
244438 bytes
3
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Biological invasions are a major human induced global change that is
threatening global biodiversity by homogenizing the world’s fauna and
flora. Species spread because humans have moved species across geographic
boundaries and have changed ecological factors that structure ecosystems,
such as nitrogen deposition, disturbance, etc. Many biological invasions
are caused accidentally, as a byproduct of human travel and commerce
driven product shipping. However, humans also have spread many species
intentionally because of perceived benefits. Of interest is the role of
the recent exponential growth in information exchange via internet social
media in driving biological invasions. To date, this has not been
examined. Here we show that for one such invasive species, goldenrod,
social networks spread misleading and incomplete information that is
enhancing the spread of goldenrod invasions into new environments. We show
that the notion of goldenrod honey as a “superfood” with unsupported
healing properties is driving a demand that leads beekeepers to produce
goldenrod honey. Social networks provide a forum for such information
exchange and this is leading to further spread of goldenrod in many
countries where goldenrod is not native, such as Poland. However, this
informal social information exchange ignores laws that focus on preventing
the further spread of invasive species and the strong negative effects
that goldenrod has on native ecosystems, including floral resources that
negatively impact honeybee performance. Thus, scientifically unsupported
information on “superfoods” such as goldenrod honey that is disseminated
through social internet networks has real world consequences such as
increased goldenrod invasions into novel geographical regions which
decreases native biodiversity.
Global presence of invasive goldenrod Data on goldenrod invasiveness
(file: Global_data_Goldenrod_status_and planting.xlsx) were collected from
literature cited in the Center for Agriculture and Bioscience
International website (https://www.cabi.org/isc/datasheet/50599) and our
extensive search of literature on goldenrods. We illustrated the results
on a map using QGIS open source software. Global interest in goldenrod
plants for apiculture We used Google Search to collect data on the number
of internet records containing information about honey produced from
goldenrod nectar in countries where the plant is not native, and added
these results to the map (file: "Global_data_Goldenrod_status_and
planting.xlsx, Fig. 1 in the manuscript). The Google Search tool allowed
us to estimate the internet supply of information about this topic (file:
International_interest_in_goldenrod.xlsx). The key phrase was ‘goldenrod
honey’ and the language was adjusted for each region search; for example,
for the UK we used English, for Germany German, for Hungary Hungarian,
etc. The words were checked by native speakers or translated using the
Google Translate tool, and the relevance of all translations was validated
using Google Graphics. In addition, we checked all search results from the
first five pages (50 items in total) in the Google Browser to locate all
relevant records. We also checked the occurrence of the phrase ‘how to
plant goldenrod for bees’ using the Google Search browser. The sentence is
more complicated to translate and validate than just ‘goldenrod honey’.
Thus, we used only English, German, Russian, and similar languages in
relevant countries such as Ukraine and Belarus, and Hungarian, Romanian,
and Polish, as native speakers. We checked the first 50 pages (if
available) to find all relevant listings. For Europe, we excluded all
results about native goldenrods, which are not used in apiculture because
they occur at much lower abundances than introduced alien goldenrod
species. There are no native goldenrod species in Africa, Australia, or
Oceania. All internet searches were performed on 15–17 October 2017.
Global availability of goldenrods in ecommerce in invaded countries
We checked the availability and purchase of goldenrod seeds,
seedlings, and roots on international and local internet platforms in
countries where goldenrod has an ‘invasive’ status according to the Centre
for Agriculture and Bioscience International (file:
International_Goldenrod_ecommerce.xlsx). We used the following platforms:
Amazon, eBay, Etsy, Allegro, and OLX. Search was performed on 27 May 2020.
Global availability of information about goldenrod honey as a superfood
and its healing properties We checked the abundance of information on the
internet about the healing properties of goldenrod honey using the Google
Search browser and various phrases about healing different ailments (file:
Goldenrod_honey_properties.xlsx). Search performed on 26 May 2020. Local
interest in goldenrod plants for apiculture To increase data
precision and completeness, we focussed on one specific country, Poland,
where we used data from the biggest internet platforms, Allegro
(www.allegro.pl) and OLX (www.olx.pl). We searched both platforms for
goldenrod honey availability, price, and purchase from 2008 to 2018 (file:
Ecommerce_goldenrod_honey_Poland.xlsx). We also used internet tools such
as Google Trends and the Google Search browser to closely examine
beekeeper and customer interest in goldenrods (file:
Google_Trends_goldenrod_honey_Poland.xlsx). Google Trends
(https://trends.google.com/trends/) is a public web facility provided by
Google Inc. that measures how often a particular search item is entered
into Google Search browsers, relative to the total search volume. The
trends provided by this tool estimate changes in searches for an item or
phrase and are often used to examine temporal changes in socio-economic
studies. To avoid biases, we set the ‘food’ filter, allowing searches to
only find food-related items when searching for goldenrod honey, thereby
avoiding searches for gardening plants. For Poland, we checked the Google
Search browser for trends in available information on goldenrod honey as a
healing superfood (file: Goldenrod_honey_properties.xlsx). We checked
these trends for general healing properties and for kidney problems as an
example. Using the Google Search browser, we also checked internet forums
where beekeepers exchanging advice and knowledge, to check where they
plant goldenrod for bees and if they have noted deteriorating influences
on their honeybee colonies (file:
Advices_where_to_plant_goldenrod_Poland.xlsx). Specifically, in forums for
beekeepers, we searched for the number of posts per year and the number of
people offering advice about planting goldenrod for bees. We noted the
typical habitat most often recommended for planting this species. The
forums were active from 2008 to 2018. Avoiding bias in collecting
sociological data from the internet To collect sociological data on the
interest of beekeepers in goldenrod, we used triangulation as the best
advised method for collecting non-experimental data in social science. The
method suggests using at least three different sources of data or to
address at least three different questions about each researched topic.
For this reason, we conducted our study globally and locally, using Google
Search, Google Trends, and ecommerce portals, with several research
questions. Our research was conducted according to the methods advised by
Google Inc. to deal with the inaccuracy of Google Search results. We
followed the official instructions provided by Google to improve the
results. We used two filters officially advised by Google IT. The first
was the “rc = 1” request parameter to request an accurate result count for
up to 1 M documents (source of the advice:
https://support.google.com/gsa/answer/2672285?hl=en). The second was r =
0, allowing for directory filtering (filtering documents coming from the
same folder) and duplicate sniper filtering (if two documents have the
same generated snippet, they will be filtered). Both filters were
officially advised by Google:
https://stackoverflow.com/questions/33426045/how-to-get-an-accurate-m-value-from-the-google-search-appliance-api-with-php, and checked by programmers from the University of Queensland. However, neither of these two filters changed the results. Seasonal changes in native food availability for honeybees We used data from field surveys conducted in 2014 and 2015 to examine the abundance dynamics of flowering species in grasslands invaded by goldenrod and in two types of control grassland (file: Bee_abundance_and_resource_dynamics.xlsx). We chose 10 grasslands invaded by goldenrods, 10 control grasslands that had recently been set aside, and 10 control grasslands that were managed (cut twice a year in June/July and late August). In each grassland, five 16 m2 quadrants were randomly placed. Plant species richness and flower abundance were estimated within these quadrants. Plant species were counted every two weeks starting in early April and ending at the beginning of November in both 2014 and 2015. During each survey, the flower abundance of each plant species was estimated as a categorical variable: 0, 1–10, 11–50, 51–100, 101–150, 151–200, 201–250, 251–300, 301–350, 351–400, and >400 flowers/inflorescences per 16 m2. We compared flowering species dynamics from early spring to late summer in the goldenrod invaded grasslands and the abandoned and mown control grasslands within these quadrants. We also counted all honeybees that foraged in each plot during each plant survey. Experiment on the lifespan of bees fed on goldenrod honey We experimentally measured the lifespans of honeybee workers fed on fresh goldenrod nectar (honey) and compared them with two control groups: workers fed on fresh honey from a mixture of native flowers and workers fed on sugar dissolved in water, which is typically used in honeybee experiments (file: Bee_survival_experiment.xlsx). The three treatments were stored under the same conditions for the same period. Both honey types and the control had 80% sugar content. We diluted them with water to 70% so that the treatments could be changed twice daily; otherwise, harmful pathogens such as fungus may have developed and influenced the results. All bees also had access to clean water. The water and honey were placed in Eppendorf tubes. We used five independent colonies that were not genetically related. We collected 150 bees from each colony. For each treatment, we assigned 50 random, just-hatched workers and kept them in small cages (a wood-frame cage, 13 × 9 cm and 5 cm high, with glass and steel mesh sides) and provided a small piece of bee comb. We noted the number of dead bees every day, over a 33-day period. We kept all the bees in the same conditions in climate chambers. The conditions resembled those in hives (34 °C, darkness, humidity 50–60%). The placement of the cages was changed randomly every day.
All data are in Excel files. Each file contains the
"Description" sheet, where detailed explanation of variables is
given.