Tag: Research

  • What Have We Learned From 6 Years of Monitoring Wild Bees?

    What Have We Learned From 6 Years of Monitoring Wild Bees?

    There are around 4,000 bee species in the US and over 400 in Pennsylvania (Figure 1). With so many species it’s very difficult to know what’s going on with each species and any collection of species that co-occur at any given location. There’s growing concern that bees are declining because of a variety of stressors such as habitat loss, pesticides, invasive species, and climate change. While there is good evidence that some bumble bee species in the US are declining, the status and trends for most other species are largely unknown due to a lack of data. This is why there’s an ongoing effort to establish a US nationwide bee monitoring program. In our recently published paper we looked at changes in populations of many bee species using data from 6 years of intensive bee monitoring.

     

    A grid of 12 bee photos sitting on flowers. The bees vary in size, shape, and color.
    Figure 1. A variety of bees found in Pennsylvania, photos by Nash Turley CC BY-NC-SA 4.0

    We’ve been working to understand how populations of bees in-and-around several apple orchards in Southern Pennsylvania are changing over time. To do this we’ve been monitoring bees for the last 6 years using Blue Vane Traps (Figure 2), a type of trap that attracts and captures a wide variety of bees. With these we’ve collected data on what bees are active every single week between April and October for 6 years in a row. So far we’ve collected 144 species! This is 33% of the species found in the whole state. As is the case in all collections of species in nature, most species were rare, for half of the species we collected 5 or fewer individuals. However, we did have 40 species with enough observations to be able to look at population trends over time.

     

    A photo of a blue vane trap hanging from a pole with green vegetation in the background. The trap is about 1 foot tall with bright blue top with vanes and a funnel leading into a yellow tub at the bottom
    Figure 2. Blue Vane Trap, a type of insect trap that attracts and captures a wide variety of bees and other pollinating insects. Photo by Nash Turley CC BY-NC-SA 4.0.

    We found that 26 species were stable over time, that is, no detectable change in abundance between 2014-2019 (Figure 3). However, 13 species, or about ⅓ of the species we could measure, declined in abundance over time. Many of the declining species were bumble bees and sweat bees. By contrast, only 1 species increased in abundance over time. In addition to changes in species’ abundances, we also saw declines in the number of species observed. At the peak year we found an average of 46 species at each collection site which dropped to an average of 30 species per site at the end of our study.

     

    Three graphs with bee abundance on the y axis and years on the x axis with points and trend lines. These show the abundance of bees between 2014 and 2019. The first graph there is no trend, no change over time, which is the pattern for 26 species in the study. The second graph shows straight line declining over time, these declines were seen in 13 species. The last graph shows a curvy line that increases sharply in the last two years, only one species (Melissodes bimaculata) increased in this way.
    Figure 3. Changes in abundance of three bee species between 2014 and 2016. These three species are representative of categories of species that were stable, declining, and increasing.

    Our collections were at 4 orchards all within a few miles of each other, so we don’t know if the patterns of declines we saw are happening in other areas. Also, 6 years of data are probably not enough to provide strong evidence of longer-term trends. Rather our patterns could be a product of year-to-year fluctuations that by random chance happened to show declines during our 6-year snapshot. Others have suggested at least 10 years of data are needed to detect long-term patterns of declines in insect populations. We are continuing our collections of hopes that we can provide more concrete evidence of population trends in the future.   

    In addition to studying changes in abundance over time (across years), we also looked at seasonal changes (within years). We wanted to understand how bee communities (the combination of species active at any given time) change from month to month. We found that bee communities in April, May, June, and July are all distinct. That means that each month you go out and look at bees between April and July you will see new species and unique combinations of species flying around. We also looked at seasonal patterns of abundance for our 40 focal species and that there were 3 types of life history strategies which are shown in Figure 4: 1) species are are active for just a short time in the spring such as mason bees and mining bees (pink), 2) those that are active for a short time just in the summer such as squash bees and long-horned bees (purple), and 3) species with a broad period of activity that are likely to be flying about from May all the way to September like bumble bees and most sweat bees (blue). Non-native honey bees had the widest period of activity, they are always around. 

     

    A grid with months April to October on the top and seven types of bees on the side. For each bee the squares are filled in for the month that most of the bees were captured. On the right are photos of each type of bee, high detailed photos of specimens with black backgrounds.
    Figure 4. Seasonal patterns of activity for seven types of bees in Pennsylvania. Filled in squares represent months in which the majority of bees were captured. See main text for further explanation of the patterns.

    Our analysis of bee monitoring data over 6 years helped us learn a great deal about the natural history of bee communities and species-level insight for 40 co-occurring species. Our results are concerning because they suggest there could be declines in species’ abundances and community-wide biodiversity in recent years, but further study is needed to know if this is part of an ongoing pattern. We hope that data like this will be helpful in identifying species of conservation concern, or species that could be good indicators for detecting threats to other bees or insects more generally. We also hope that basic natural history data on many species will be useful for guiding conservation and habitat restoration efforts focused on helping bees and other pollinators. You can read more about this research in our open access paper published in Ecology and Evolution: 

    Turley NE, Biddinger DJ, Joshi NK, López-Uribe MM. Six years of wild bee monitoring shows changes in biodiversity within and across years and declines in abundance. Ecology and Evolution.  

     

  • 2021 iRES Virtual Program – Student Projects Results

    2021 iRES Virtual Program – Student Projects Results

     

    With funding from the National Science Foundation (NSF), a group of biologists, engineers and climate scientists from Penn State (USA), University of Kansas (USA), Universidad Militar Nueva Granada (Colombia), and Pontificia Universidad Católica del Perú (Peru) launched a summer research program for undergraduate students to help shed light on how pollinators and pollination are responding to our changing world. In 2021, the program was offered virtually to 12 students from the USA, Colombia, and Peru. One of the unique characteristics of this program is that it brings together teams from biological sciences and engineering to find answers to these questions. Why is this an advantage? A major challenge for biologists to understand how pollinator populations are responding to changing climates is that we don’t have instruments that allow us to understand the behavior and physiology of small organisms that move very fast like bees.

    Our team of students and mentors in 2021 was set up to answer the following questions:

    1. How will increasing temperatures affect pollinator foraging?

    2. How do air pollutants affect floral scents and pollinator foraging behavior?

    3. How will heat stress on pollinator-dependent crops impact food supply in cities where the largest concentrations of human populations are found?

     

    To investigate question 1, Maren Appert and Abigail Jiménez from California (USA), Alonso Delgado from Texas (USA), and Andrés Herrera and Ruben Martín from Cajicá (Colombia) collected foraging data of pollinators along with the varying temperatures of the day and set up bioassays to quantify the critical thermal maxima (CTmax) of pollinators that were foraging during the coolest and hottest parts of the day. The hypothesis they had was that pollinators foraging during the hottest parts of the day would tolerate higher temperatures during the CTmax bioassay. Because these students were working from home, some of them had to set up experiments in their kitchens or get very creative to have the experimental set up working in their backyards. Some students even had their kids as their field assistants. In collecting the empirical data to test their hypothesis, they collected CTmax data from several types of pollinators (bees and flies), and from females and males. The preliminary results of their experiments have reached some interesting findings: (1) some bee species (like honey bees) have significantly higher CTmax than most other bees and flies; (2) males tend to have higher CTmax than female bees, and (3) bees that exhibit higher CTmax generally forage during hotter times of the day. To learn more about their projects and findings, please visit and watch this video.

    https://www.youtube.com/watch?v=C_ArmNt8RYw

    For question 2, students aimed to understand how air pollutants affect pollinator foraging patterns. This project had two parts. Part 1 focused on developing numerical models to understand how floral scents degrade with environmental pollutants. Part 2 focused on developing radars that could be used to study how changes in floral scents can impact pollinator foraging. In this project, Renata Proano and Tatiana Terranova from Pennsylvania (USA), and Luis Ocupa and Juan Tello from Lima (Peru) worked together. Renata, Luis, and Juan studied the rate of destruction of the most abundantly floral scents (linalool, limonene, β-myrcene, and geraniol) of Geranium Graveolens in urban and rural regions of Pennsylvania. Results from their project indicate that air pollutants modify the quantity and the quality of floral scents leading to floral scents not traveling the necessary distance needed for insect pollinators to locate flowers. However, to appropriately study how air pollutants change pollinator foraging patterns, it is necessary to develop devices that will allow us to characterize foraging behavior. To achieve this goal, Tatiana worked on analyzing radar data to characterize the foraging patterns of bees. Using the programming language python, she was able to develop a program to interpret radar data into realistic foraging flights of bees. To learn more about the projects developed for question 2, check out the two videos below.

    https://youtu.be/gMC2VgdXyoohttps://www.youtube.com/watch?v=bfxn5VATLAM

    Students Alonso Zevallos and Rocio Beneito from Florida (USA) and Yannet Quispes from Lima (Peru) worked on questions 3. Their project aimed to quantify the pollination footprint of populated regions throughout the United States under the scenario of future rising temperatures (i.e., heat stress/waves) to determine how these regions would be impacted by a shortage of pollination dependent crops. For this project, students chose cabbage, soybean, sweetpotato, squash, and cucumber as model crops, and regions of the United States associated with the consumption of these commodities under the probability of increased ambient temperature. Students used publicly available production data and existing pollination field studies and quantified pollinator-dependence of these model crops on insect-mediated pollination services in several U.S. regions. Overall, their results indicate that as temperature rises, the pollination footprint for both consumption and production decreases. In addition, their data suggests that as temperatures begin to rise, pollination footprint will drop, decreasing the supply of pollinator-dependent commodities as demand for these in many U.S. regions increase due to increasing population pressure. These findings imply that there is an urgency to take action to stop these rising temperatures.

    Despite the pandemic, our 2021 iRES virtual program facilitated the collaborative work of students and mentors from 9 institutions in 3 countries. All students’ projects generated novel scientific findings and benefited from the interdisciplinary interactions of scientists in different fields. Our results indicate that our changing world is impacting pollinators in multiple ways and that changes in pollinator foraging behavior, their ability to fly under high temperature and to respond to changes in the plants may significantly disrupt plant-pollinator interactions and our food systems. We are hoping the next 2 years of this project will continue to generate valuable data to understand how pollinators are responding to all of these ongoing environmental changes linked to human activities.




    Project funded by NSF 

    (OISE-1952470)

    and is administered by the López-Uribe Lab in the Department of Entomology at Penn State University.

    Contributed post by

    Margarita M. López-Uribe

    Assistant Professor in Pollinator Health

    Pennsylvania State University