LEESBURG, VA – Waterborne Environmental Inc. (Waterborne), a global consulting firm focused on environmental, ecological, and human risk services, today announced Paul Barboza has been named the company’s new Chief Executive Officer (CEO). Prior to joining Waterborne, Barboza, an engineer with a business background, was a highly successful executive within the IT and Government Contracting industries.
“I am thrilled to have this opportunity to lead Waterborne Environmental into the next phase of the company’s growth and expansion. The company’s philosophy of providing novel solutions to complex client challenges ties in with my own leadership style which is to encourage a collaborative, innovative environment that results in higher performing teams and superior work. I am committed to the Waterborne mission and I know that, together with the team, we will achieve great milestones in the near future,” said Barboza.
Barboza brings a wealth of corporate leadership experience to the Waterborne team, including that gained from his most recent role as Chief Operating Officer with Virginia-based technology company, IOMAXIS. His experience includes leading business operations, P&L, business development (BD), corporate IT, Quality, facilities, and Security. He is a graduate of Virginia Tech with a Master’s in Business Administration and a Bachelor’s in Mechanical Engineering.
“In January 2020 Waterborne took on the challenge of tackling some of the most important issues facing the future of our planet. We’ve been steadily assembling the skills, talents, and technologies to achieve this by growing from the inside and from the outside. Bringing on a new CEO was one of the most important goals in that plan. We hit the jackpot with Paul Barboza!,” said outgoing CEO and Waterborne co-founder, W. Martin (Marty) Williams.
According to Patrick Holden, current Board of Directors Chairman and Waterborne co-founder, “It is the beginning of an exciting new era at Waterborne and Paul Barboza is the right man to lead company right now. In 2022 Waterborne will begin its 30th year in business. Up until now the company has been led primarily by its Founders – Marty and myself. Now, for the first time, Waterborne has gone outside the company to hire its next CEO.”
In our newest publication, accepted and published on the Environmental Toxicology and Chemistry website, we assess vulnerabilities to pesticide exposures across multiple bee species. This analysis highlights several uncertainties in the use of the Western honey bee as a surrogate species for pesticide risk assessment based on various bee traits and ecologies.
Aquatic mesocosm studies have long been considered a higher-tier tool for informing risk assessments under European regulations. These simulated pond studies are designed to investigate the impact of a pesticide on an aquatic ecosystem and use the complexities of multiple trophic levels and long-term study duration to observe patterns of impact and recovery.
As presented at this year’s SETAC EU, Waterborne is currently coordinating and providing technical expertise in a collaboration mesocosm project funded by Syngenta, along with Cardno, Inc., EBP and EAWAG, gaiac, Integral Consulting, Inc., and Mesocosm GmbH. The project’s goal is to demonstrate how realistic representations of the food webs and environmental conditions in mesocosms will open the door to running virtual mesocosms while extrapolating available mesocosm data to untested conditions, including time-variable exposure patterns.
To this end, we are working to apply multiple aquatic systems models to mesocosms in a ring study. This will become the foundation for establishing a virtual mesocosm. The development of a virtual mesocosm, through an aquatic systems model, would serve as a risk assessment tool to consider estimated effects under various conditions and will go beyond the experimental limitations of high-tier studies. The work to harmonize model input parameters (efforts to calibrate and validate the models are underway in this long-term project) using control mesocosm data from seven studies spanning across four years.
The ring study approach offers a unique opportunity to compare different models and gain understanding of the mesocosm systems. In this project’s ring study, four aquatic systems models are included: AQUATOX, CASM, Streambugs, and StoLaM+StreamCom. These models were selected since they are capable of simulating aquatic food webs, able to mechanistically represent interactions within the food web, offer different modeling approaches, and are capable of being adapted and parameterized for the unique needs of a mesocosm study.
To learn more about our findings so far, check out our recent presentations from SETAC Europe 2021. We are excited to be part of the team investigating novel ways for ecosystem models to inform the higher-tier risk assessment process.
Population models provide a means for relating individual-level responses to a stressor to changes in population abundance and structure. The models’ value is in their ability to reduce uncertainty in the extrapolation of organism-level ecotoxicological observations and endpoints to ecologically relevant effects. However, there are many challenges incorporating population models into the ecological risk assessment process.
But first, what makes population models so useful? In a nutshell: population-level ecological effects can be extrapolated without the need for costly field studies with high numbers of test organisms and challenges due to novel study designs. Applying a population model allows for many different scenarios to be observed, beyond what is feasible to test through experiments with test organisms alone. What about the challenges? To begin with, modeling must be focused to address specific risk assessment objectives. Once a focus has been identified, scientists then must contend with the data availability, complexity, uncertainty of the model and the resources needed for its development.
To address these challenges, Waterborne’s team collaborated with population modelers across industry, academia, and the US EPA to develop a tool: Pop-GUIDE. Pop-GUIDE (Population modeling Guidance, Use, Interpretation, and Development for Ecological risk Assessment) serves as a stepwise decision guide and modeling framework. This tool has been designed to guide risk assessors and modelers through the following five phases to develop a conceptual model in line with the level of complexity and uncertainty appropriate for the available data and risk assessment goals:
Phase I. Model Objectives
Phase II. Data Compilation
Phase III. Decision Steps
Phase IV. Conceptual Model
Phase V. Model Implementation and Evaluation
We are excited to introduce Pop-GUIDE as the most comprehensive guidance for population model development to date! This guidance now allows us to overcome some of the challenges of assimilating population modeling into regulatory decision-making and will truly bring us into the future of ecological risk assessment! Our recent publication provides a deeper dive into the structure and layout of the guidance as well as case studies under multiple regulatory statutes.
In our June newsletter, we mentioned the recent release of a 2-part publication series in Environmental Toxicology and Chemistry presenting 1) a model validation of BEEHAVE and 2) an application of BEEHAVE. This month, we’re taking a deeper dive into these two publications and, through a case study, will show both how the BEEHAVE model can potentially be used for large-scale colony feeding studies (LSCFSs) and how it could inform future study designs in order to improve overwintering success in control hives as well as guide consistency across studies.
Part 1 of this series presents the validation of the BEEHAVE model with control data from large-scale colony feeding studies (LSCFSs). LSCFSs are studies used to assess the potential risks of pesticide exposure at the colony level and are typically conducted in higher-tier honey bee risk assessments. These studies are very costly and time intensive and carry significant resource concerns should unexpected issues arise. They also carry challenges such as potential high overwintering losses in untreated controls (observed in some studies). In addition, study designs can vary with respect to bee keeping activities and study schedules.
BEEHAVE is a mechanistic model of a honey bee colony and its interactions with the landscape. It provides a tool to systematically assess multiple factors (e.g., weather, landscape composition, and beekeeping activities) that influence colony outcomes and can inform study design. To use it properly, the model should be validated to demonstrate that it can appropriately reproduce patterns observed in the field prior to use.
In our study, we used untreated control data from seven LSCFSs that were conducted in North Carolina between 2014 and 2017 in BEEHAVE’s validation. Initial conditions of the colonies, the spatial and temporal bee resource composition of the landscape surrounding the study apiaries, the weather, and feeding of the untreated control colonies were used to parameterize the model. Two of the seven studies were used for the calibration of the model and the remaining five were used for validation of the model. The validation results suggested that the calibrated BEEHAVE model provided good agreement with apiary-specific data for the first study year. However, conditions in the springtime following overwintering presented a challenge for the model outputs since they did not match the observed colony conditions.
Based on the above observations, the calibrated BEEHAVE model is recommended to be useful in predicting a colony’s dynamics in LSCFSs prior to overwintering. Additionally, the results from the model are typically less variable than observations from colonies in the field. In other words, predictions from BEEHAVE should not be used as precise predictions of individual colony properties but rather applied to compare impacts of different environmental and beekeeping scenarios applied to colonies kept similar conditions. Our in-depth analysis informs the usability of BEEHAVE in applications related to higher tiered risk assessments and a path to model validation using multiple study data sets.
In Part 2, we present the application of BEEHAVE to simulate untreated control colonies in LSCFSs under a range of beekeeping and feeding scenarios. The goal was to identify the most important factors that impact control colony conditions in the fall, and inform study design aspects that increase the likelihood of overwintering success in control colonies. The composition of the landscape, feedings patterns, initial control colony conditions, and weather conditions were derived from the seven LSCFS. The following four aspects were examined for potential impact on fall colony conditions using the calibrated BEEHAVE: 1) colony conditions reported at the time of study initiation, 2) feeding timing and amount, 3) landscape composition around apiaries reflecting spatial and temporal bee resource availability, and 4) weather impacting daily foraging hours available to simulated foraging bees. Different inputs were used for each of the four aspects to represent the ranges of variability that across the available LSCFSs. Feeding schedules and initial conditions were most impactful to colony conditions in the fall and were targeted in more detailed simulation scenarios. Further analysis suggests the importance of colony conditions at study initiation and sugar feeding amounts and timing for colony fall conditions and subsequent overwintering success. The results can be used to inform a more standardized study design with increased likelihood of overwintering survival of controls.
This case study for applying a colony-level validated model to simulate a large-scale feeding study is a demonstration of how ecological modeling tools can be used to inform study designs for field-based, resource intensive studies.
Some species listed under the Endangered Species Act (ESA) occur in agricultural landscapes where their habitats have the potential to be exposed to pesticides. Aquatic species, in particular, may be at risk to pesticides applied to nearby agricultural fields, even though applications are not made directly to the aquatic habitat. Population modeling has emerged as a useful tool in predicting exposure risk and the impacts pesticides have on their populations.
A recent article we published in the Journal of Environmental Toxicology and Chemistry, takes an in-depth look at how a hybrid model—combining an aquatic ecosystem model (CASM) and a species-specific population model for the Topeka shiner (TS-IBM)—can be used to estimate the potential impacts on populations. Through these models, we are able to consider realistic assumptions about the species ecology, ecosystem factors, and potential exposures within the habitat. Additionally, Toxicokinetic/Toxicodynamic (TKTD) models were incorporated into the TS-IBM to capture direct lethal and sublethal effects on individual fish from the time-variable exposures.
In this endangered Topeka shiner (Notropis topeka) study, a hybrid model was applied to compare the effects from potential exposure to a fungicide in oxbow habitats on the shiner population. Hybrid modeling approaches that combine species-specific models with an ecosystem-level model can be advantageous as this type of hybrid model sets population dynamics in the context of species interaction which can further address indirect effects mediated by the food web. We chose the example pesticide due to its known toxicity to fish in standard laboratory studies. The variable exposure scenarios were based on conservative assumptions and made it possible to test the outcomes for the populations of applying a 15-foot vegetative filter strip (VFS) between the treatment area and the waterbody compared to no exposure mitigation measure.
Furthermore, exposure multiplication factors (EMFs) were applied to the exposure scenarios with and without VFS to assess the simulated population-level effects. We found that direct effects on the simulated shiners governed the observed population-level effects, while effects mediated by the food web did not play an important role in the case of the fungicide.
Our conclusions demonstrated that such modeling approaches can help to measure the effectiveness of various mitigation strategies for endangered species protection. We found that the VFS between the treated area and the oxbow habitat resulted in a two to three times reduction in simulated population-level effects compared with the exposure scenario without a VFS, suggesting the effectiveness of the mitigation strategy for Topeka shiner populations in oxbow habitats.
Pollinator-plant relationships represent some of the most striking examples of mutualism and coevolution in all of nature. We’ve discussed in our pollinator protection article how native bees can be generalists, often thriving on a diverse availability of flowering plants. This diversity is a benefit to both bee and plant alike. From a bee’s perspective, diverse food sources can supply a well-rounded diet and from a plant’s perspective, diversity in pollinators helps to assure successful reproduction. However, these symbiotic interactions can be driven by specific pollinator preferences, sometimes to the point of becoming a completely obligate relationship.
Plants are pollinated by different types of animals, the most common of which include bees, flies, butterflies, beetles, moths, bats, and birds. Each of these animal pollinators displays specific preferences, such as color, scent, flower shape, presence or absence of nectar guides, and characteristics of nectar and pollen. For example, without a sense of smell, birds are attracted to bright red or orange flowers. In return, plants relying on avian pollination have evolved to be typically odorless, bright in color, with funnel or cup-shaped flowers and sometimes a strong base for perching. Plants that have evolved for pollination by bats or moths emit scents at night to account for nocturnal activity patterns: musty scents for bats and strong sweet scents for moths. (Next time you’re admiring a beautiful flower, challenge yourself to consider what traits may have evolved in response to pollinator preferences! Information from the U.S. Forest Service provides some great details to get you started.)
Evolutionary pressure can also yield extreme examples of pollinator-plant relationships, some of which represent complete species-to-species dependence. For example, the death camas (Anticlea elegans) is a beautiful flowering plant that is deathly toxic to most pollinators and animals. Yet even this plant has developed a single pollinator relationship with the solitary andrenid bee (Andrena astragali). Curiously, the adult andrenid bee is also unable to consume the pollen or nectar of the death camas, but its kids love it! Once hatched, the bee larva consumes the pollen ball. It is not completely understood if the larvae are immune to the plant toxins or if the toxic chemicals degrade prior to consumption.
The intricate relationships between pollinators and plants has become a focal point for toxicological consideration in Endangered Species Assessments for US EPA. During these assessments, we conduct a three-step consultation process to evaluate the potential risk to Federally-listed threatened or endangered species. While direct effects of chemicals are characterized, we also examine indirect effects during Step 1 of an Endangered Species Assessment (ESA). Indirect effects refers to impacts on other species for prey, habitat, or symbiotic interactions upon which a listed species relies and is the last step in the decision tree for Step 1 of the ESA. For example, a chemical may not be directly toxic to an endangered pollinator, but an indirect effect could occur if the chemical affects the plant(s) that the pollinator relies upon for a food source. It is the last step in the decision tree for Step 1 of the ESA. Up until this point, an individual species has not been determined as a “no effect” species. In the case of “indirect effects”, a species may have an obligate or a generalist relationship to another species that is directly affected by the chemical being assessed. An obligate relationship infers that one or both of the listed species depends on the other for its survival. A generalist relationship means that a species is able to survive on a variety of other species and is not solely dependent on one for survival.
An example is the endangered species, Dicerandra immaculata (Lakela’s mint), a small fragrant shrub. This species occurs in six isolated sites in the southern Indian River and northern St. Lucie counties in Florida. Lakela’s mint has a generalist relationship, relying solely on pollinating insects for survival. Another example is the Karner blue butterfly (Lycaeides Melissa samuelis), an endangered species located mainly in Wisconsin but also found in Indiana, Michigan, Minnesota, New Hampshire, New York, and Ohio. This species has an obligate relationship to the wild lupine (Lupis perennis) because the butterfly’s caterpillars only feeds on wild lupine leaves, making this species dependent on the wild lupine for its survival.
Understanding the precise species interactions is critical for an in-depth look at potential exposure and risk of a chemical to a listed species. The beautifully intricate pollinator-plant relationships, which are the result of millions of years of coevolution, serve as a prime example of these interactions!
Much of the most recent research in pollinator protection, and in fact a lot of new ecological research in general, is focused on computer model simulations, such as the BEEHAVE model. In particular, recent honeybee-specific projects have incorporated BEEHAVE to simulate the development of a honeybee colony and its nectar and pollen foraging behavior in different landscapes. BEEHAVE additionally allows for representation of multiple stressors to honeybee colonies and predicts the potential impact on colony development and survival.
Our Effects Team has used the BEEHAVE model for various projects and found it invaluable in honeybee colony predications. For example, in collaboration with the Pollinator Research Task Force, we recently released a 2-part publication series in Environmental Toxicology & Chemistry presenting, 1) a model validation of BEEHAVE using large-scale colony feeding studies, which can be used to inform the use of BEEHAVE to higher-tier ecological risk assessments, and 2) an application of BEEHAVE to analyze overwintering outcomes from simulated large-scale colony feeding studies. The findings from this work can be used to inform study designs for a large-scale colony feeding study in order to improve overwintering success in control hives and drive consistency within and across studies.
BEEHAVE was a star at May’s 2021 SETAC Europe conference where a new mechanistic effect model (BEEHAVE-Ecotox) was demonstrated to link realistic exposures of bees in the field with subsequent effects on different levels of the colony. We’re excited to review this work once published, as this model has significant risk assessment implications, including the capacity to extrapolate from laboratory to semi-field and field studies as well as the option to study effects in different crops and regions and to test various mitigation strategies.
Beyond BEEHAVE… Waterborne’s scientists will soon be presenting and publishing a slew of recent work in the field of pollinator protection, including:
Evaluating vulnerability assessments across non-Apis bees: applying robust methodologies to examine individual and population level vulnerability across species!
Evaluating the utility of endpoints used in guideline laboratory studies for honeybees: what parameters are really driving the hazard?
Considering how we can approach screening-level type risk assessments for surfactants and inert ingredients.
Keep an eye on our upcoming newsletters for more details on our recent pollinator work.
Also, Waterborne’s Lead Ecotoxicologist, Jenn Collins will be co-chairing and presenting during the upcoming pollinator session of the American Chemical Society National Meeting in August. Other co-chairs for this session include environmental scientist John Purdy, Tom Steeger and Katrina White from the US EPA, and Annie Krueger from the University of Nebraska-Lincoln. This session is gearing up to be full of great presentations and new considerations for pollinator risk assessment.
There is something mesmerizing about watching bees at work! These little workers have been agriculturally critical to humans for thousands of years, and over this extended time, we have accumulated a wealth of research about their physiology and behavior. Here, we focus on honey bee foraging behavior, which provides us with a fascinating example of how the honey bee colony functions more as a superorganism than a population of individuals.
Honey bee foragers collect all of the nutritional elements for their colony, including nectar, pollen, and water. Water is sourced close to the colony and used to hydrate and cool the colony during hot weather. Research has shown that pollen foraging, a colony’s main source of protein, minerals, and vitamins, is directed by the colony’s current state. Pollen stores are vital for brood production and healthy development of young within the hive, and pollen foraging has been shown to be regulated by the presence of brood pheromone and young larvae in the colony, as well as the quantity of stored pollen. Nectar, on the other hand, is the primary source of carbohydrates and provides the necessary energy for foragers and the colony as a whole. Honey bees store nectar as honey and securing healthy supplies allows for strong colony maintenance and overwintering.
Contrary to pollen foraging, bees continue to forage for nectar regardless of the honey stores in the colony. However, plans in the colony are subject to change! Larval pheromones have been shown to transition the behavior of nectar-foraging bees to pollen foraging for a duration of time to meet a growing need of pollen in the colony.
It is also important to note that not all nectar and pollen sources are equivalent. Just as flowers physically differ, flowers provide varying types and levels of nutritional elements. Forager bees will often visit a buffet of different flower types to bring well-rounded sustainment back to the colony. Interestingly, bees base foraging decisions on the nutritional value of certain flowers and their own colony’s requirements.
Foraging preference studies have demonstrated that the highest criteria for foraging was nutritional content of protein and relative availability of resources, especially when the colony need was high (indicated by number of larvae). In one study, white clover (Trifolium repens) and then daisy fleabanes (Erigeron annus) were visited most frequently and accounted for the most collected pollen when colonies were given a diverse landscape of floral resources. The same study showed observations of peak foraging rates in the early afternoon and that foraging was highly dependent on temperature outside the hives. The high energy demand for flight muscle movements means that honey bees very rarely forage below 55 °F (13 °C) or above 100 °F (38 °C).
Honey bees are experts at efficiency determination, measuring their own spent energy to required work ratios in real time and relaying the best foraging locations to the colony on their return. They do this through the “waggle dance,” which is exactly what it sounds like! When worker bees return from optimal locations, they wiggle their bodies in a way that the other bees understand as both directions and distance to the best foraging location. What looks like an adorable dance is in reality a very precise method of communication. Angles and duration of these “dances” relay the direction and distance. Bees are showing us that dancing isnt’ just for after-work fun…it IS work!
While there are many factors that impact honey bee foraging behavior, it’s clear to see that honey bees are never blindly working. It’s been several centuries since Chaucer introduced the saying “busy as a bee,“ but, given all we know about bees, we should take this idiom on face value. Bees pursue directed work with decision-based efficiency rather than aimlessly buzzing around.
Did you know that there are over 20,000 recognized species of bees around the world, 4,000 of which are native to the United States? Although pollinator protection efforts have been a core focus in ecological stewardship, most of us tend to focus on the European honey bee (Apis mellifera) and miss out on the bulk of the wonderfully diverse pollinator populations found across the globe.
The European honey bee has long been used as the surrogate species for both Apis and non-Apis bees and other insect pollinators in risk assessments. The focus on A. mellifera makes sense for a few reasons: (1) we have a strong understanding of its behavior and ecology, (2) A. mellifera have a long history of management for honey production and, more recently, crop pollination, and (3) this species is commercially available and relatively easy to keep under laboratory conditions.
Focusing on the European honey bee has its drawbacks. For example, the protection goals set forth in the 2014 Guidance for Assessing Pesticide Risk to Bees by the USEPA, Health Canada and the California Department of Pesticide Regulation, including maintenance of pollination services, hive production, and biodiversity, do not uniformly apply to both Apis and non-Apis bees. In other words, thousands of non-Apis bee species may not benefit from protective efforts set forth by these guidelines and could be at a potential risk from pesticides. Bee species are diverse in life cycle, sociality, nesting and foraging behavior, overwintering, and size and their diverse ecology and behavior should be accounted for when considering risk from chemical exposure and toxic effects.
While the European honey bee receives most of the credit, many species are very important for crop pollination—and few of them are managed for this purpose. In many cases, non-Apis bees turn out to be more effective pollinators than the honey bee, such as:
Bumble bees (Bombus ssp.) are relatively large in size as well as furry in comparison to many other bees, allowing them to pick up and carry more pollen from plant to plant. They are social bees, but with only a few hundred worker bees, their colonies are much smaller than European honey bee colonies. Bumble bee colonies do not overwinter. Instead, mated queens overwinter and start a new colony on their own in the spring. Bumble bee species are commercially available for crop pollination in North America, Europe, and Asia.
Not all bees live in colonies! Solitary bees comprise a vast variety of bee species that, in turn, employ various nesting strategies. A few of these solitary bee species can be managed for crop pollination, most prominently species in the genus Osmia: blue orchard bees and the red mason bees are used in orchard pollination, and the leaf-cutting bee, Megachile rotundata, is managed for alfalfa pollination. These three species nest in above-ground, existing cavities, making it relatively easy to provide artificial nesting sites and collect the overwintering bees that have not emerged from their cocoons yet.
However, the majority of bee species nest underground, usually digging their own nests. Examples include the following bees: the squash bee (Eucera pruinosa) which exclusively forages for the pollen of plants in the cucurbit family and the alkalibee (Nomia melanderi), an avid pollinator of alfalfa. The alkali bee is found in the Western United States and nests in soils with high salt content. It can form large nest aggregations in suitable locations and farmers may set aside and manage areas close to their alfalfa fields to create the right nesting conditions for the bees.
In tropical regions, including for instance Brazil, stingless bees (Meliponini) are considered key pollinators. Like the honey bee, they are highly social and live in large colonies. They comprise a variety of species across the globe with a large diversity in ecology, nest architecture, and substrates used for nest building.
In order to consider the potential impacts of chemicals to the wide variety of bees, we must acknowledge the different routes of exposure. Dependent on the species and its ecology, bees can come into direct contact with chemicals through dust or spray, mud and soil, nesting materials (e.g., wax or leaf pieces), plant surfaces and plant resins. In addition, bees can also be exposed orally to residues in nectar and pollen. Exposure will also vary depending on life-stage and, in social bees, castes. Beyond the exposure routes, bee physiology can result in different sensitivities to toxic compounds across bee species. As you can see, bees can vary greatly in biological and behavioral characteristics and research is needed to better understand the interaction between these characteristics and the potential pesticide exposure and effects at the level of a colony or population. Recently, we have been working to apply a trait-based vulnerability assessment across 10 different bee species with individual and population-level implications. We’re looking forward to publishing our findings soon. Stay tuned to our upcoming newsletters for more on this important work. In the meantime, we encourage you to explore the various bee species native to your area. The Xerces Society has a multitude of educational resources if you’d like to learn more about the diverse pollinators in your region.