## Probabilistic Risk Assessments for Listed Species Potentially Exposed to Pesticides Dwayne R.J. Moore – Intrinsik Environmental Sciences Inc., New Gloucester , ME October 6 th , 2014

# Common Concerns With **Quantitative Uncertainty Analysis**

• Lack of available expertise • Hard to do • Resource intensive • Need lots of data • Decisions less obvious than with risk quotients

• Goal of this presentation: Demonstrate that above concerns can be overcome ... and can be done so rather easily

# General Approach

• Consider generic receptor groups and scenarios at the outset

– If risk negligible for all fish species in a standard pond, then no need for PRAs for most, if not all, listed fish species

– If some species at risk, move to species - specific analyses 

### • Approach QUAs for listed species in a tiered fashion

– Simple, conservative scenarios may be sufficient for decision making

– Highly refined analyses only when necessary 

### • Decision criteria required in this process **# Species**

# QUAs for General Receptor Groups

**0 20**  **40 60**  **80 100** 

**0 0.5**  **1 1.5**  **Conce ntration (μ**  **g/L) R** **e v** **e r** **s e** **C u** **m u** **l a** **t i** **v e** **P r** **o b** **a b** **i l** **i t** **y (** **% )** 
Ty pical Application R at e Maximum Application R ate 

## • Consider a simple example: Chemibears • Only a few major use patterns • Focus on worst - case use pattern • Concern is for acute risk to fish from SLERA • PRA conducted using PRZM/EXAMS standard pond model • Peak EECs estimated for 30 years

# Fish SSD for **Chemibears**

**0 20**  **40 60**  **80 10**  **0**

**1 10**  **10 0**  **10 00**  **10 000**  **10 000**  **0 Co**  **nce ntr**  **ation (μ**  **g/ L)** **P e** **r c** **e n** **t A** **f f** **e c** **t e** **d** Fit te d SSD ( LC /E C5 0s ) Co nf id enc e Li mi ts

o n th e Fit

te d SSD LC /E C5 0 Dat a Lo w To xi city

S SD

# Risk Curve for Fish Exposed to **Chemibears**

• Near zero probability of exceeding low LCx of even most sensitive species • De minimis risk • Although probabilistic, still a conservative RA

– Max application rate

– Standard pond adjacent to treated field

– Exposure duration of acute tests = 96 hrs • Little need to assess each listed fish species **Fr es**  **hw ate**  **r Fis**  **h, M**  **axi mu**  **m App**  **li ca**  **ti on**  **R at**  **e ( Sc**  **en ar** 

**io 1)** 

0 20 40 60 80 10 0

0 20 40 60 80 10 0 **% SSD**  **Sp ec**  **ie s**  **Af**

**fe ct**  **ed E** **x c** **e e** **d e** **n c** **e P** **r o** **b a** **b i** **l i** **t y** **( %** **)** Ris k Cu rve De M in im

is -L ow R is k Bo unda ry Lo w-In te rm

edi ate Ris k Bo un da ry In ter me di ate-H ig h Ris k Bo un dar y

**Fish**

# A Simple Species **- specific Example** 

• FIFRA QUA for chemibears indicated risk to mammals • Louisville bat forages in proximity to treated areas • SLERA indicates potential risk • Simple Monte Carlo analysis

– Distributions for insect residues, bat body weight and foraging behavior

– Include residue decline over time

– Calculate daily oral exposure

– Compare to reproduction threshold 

## • Output indicates that reproduction threshold never exceeded for >100,000 bats for even a single day

# A Higher Tier, Species **- specific QUA:**  **California Red -**  **legged Frog**
• CRLF listed as threatened in 1996 • SLERA indicated potential risk to aquatic - phase CRLF • Refined exposure estimates derived for three scenarios in Watsonville Slough watershed in CA

– Worst - case scenarios

– Ponds, flowing waters, ditch

– CRLF core areas, critical habitat, elemental occurrences and/or use patterns co - exist in this watershed

# Exposure Assessment **for Ponds**

• Strawberries and lettuce most important crops • M aximum rates assumed • 3 ponds connected, surrounded by agriculture (83.2% of total crop land ) • PRZM , EXAMS and VFSMOD used to simulate hydrology and pesticide transport in multiple fields surrounding the ponds • Parameterized to reflect site - specific soil characteristics, topography, size of each pond • Distributions for

– Spatial and temporal distribution of applications

– Hydrologic characteristics

– Spray drift

# Exposure Output: Pond 1

0 0% 20% 40% 60% 80% 100%

0.001 0.01 0.1 1 10**C u** **m u** **l a** **t i** **v e** **P r** **o b** **a b** **i l** **i t** **y**



## Concentration **(μg/L)**

# Exposure Assessment: **River**

• Largest remaining freshwater riparian habitat for CRLF • Historically high chemibears , > 99% of average upstream use in CRLF core areas • Surrounding soils have high runoff potential • Watershed divided into 10 sub - basins, each sub - basin parameterized based on site specific characteristics • SWAT used to estimate EECs by simulating the transport via moving water within the watershed • Distributions for water body characteristics and pesticide application in watershed

# Exposure Assessment: **Ditch**

• Drainage ditch to Watsonville Slough, one of four with recorded CRLF occurrences • Ditch catchment consists of almost 100% agriculture • Ditch within 6 m of agricultural land prone to runoff (50% clay ) • SWAT model and Monte Carlo simulation used to derive EEC distributions

# Concentration **- response Curve for**  **Xenopus laevis** 

0 0.2 0.4 0.6 0.8 1

0 5000 10000 15000 20000**P r** **o p** **o r** **t i** **o n** **M o** **r t** **a l** **i t** **y**

**Concentration (μg/L)** Data from Palmer (2011) Probit Model 95% Confidence Limits

# Risk Characterization

• No direct risk to aquatic - phase CRLFs in ponds and the river and little risk in ditch (<1% probability of 1% mortality) • Other analyses indicated low risk to prey species • Weight - of evidence assessment

– Probabilistic modeling indicates little to no risk

– Monitoring data indicate low er levels than model predictions

– Field study: “no adverse acute or long - term effects w ere obvious in either fish or aquatic invertebrate communities ”. Over 13 applications to cotton had been made to the adjacent field over a three - year study

– Mesocosm studies: Only transient effects to sensitive, aquatic invertebrates at modeled concentrations

# Case Studies: Lessons Learned

• FIFRA SLERA and co - occurrence analysis may result in many listed species needing further assessment • Higher tier, species - specific analyses useful and doable, but resource - intensive • Need intermediate options

– QUAs for generic receptor groups and conservative standard scenarios are useful following FIFRA SLERA

– Lower tier, species - specific QUAs may be sufficient to alleviate risk concerns 

# • Decision criteria are required to guide assessors through the tiered assessment

# Decision Making With Quantitative **Uncertainty Analysis**

• “Bright lines” lacking for the outputs of QUA • Probabilistic bright lines can assist communication and decision making • Bright lines will likely differ between receptor groups

‒ Indirect vs direct effects

‒ Low v s high fecundity listed species

‒ Threatened vs endangered 0 20 40 60 80 100

0 20 40 60 80 100**E x** **c e** **e d** **e n** **c e** **P r** **o b** **a b** **i l** **i t** **y (** **% )** 

**% Species or Individuals**  **Affected**



### Low **r isk?**  **Intermediate risk? High risk?**  **Mitigation required?**

# Those Pesky Concerns ...

• Lack of available expertise, hard to do

– Intermediate QUA options are easy and require little expertise beyond that required to run standard models

– Modest training and proper guidance can deal with this issue

– EPA has developed excellent guidance on QUA 

## • Resource intensive

– Intermediate options require little effort beyond screening - level analyses

– Higher - tier, species - specific analyses are resource intensive

– Need effective filters in endangered species assessment process 

## • Need lots of data

– For intermediate options, little additional data required

– Absolutely critical to assess data and use only acceptable and relevant data 

## • Decisions less obvious than with risk quotients

– Not if probabilistic bright lines are developed to guide assessors