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FAO Bee Survey Design Talk


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A presentation made in March of 2009 in Brazil to the FAO on bee sampling issues.

A presentation made in March of 2009 in Brazil to the FAO on bee sampling issues.

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  • Transcript

    • 1. Purpose of This Presentation
      • To guide the implementation of large scale monitoring surveys of Native Bee populations (e.g., global, national, regional, large protected areas)
      • To present conservative monitoring protocols that can be adjusted to suit local conditions
      • To provide the background and justification for the those guidelines
    • 2. NOT the Purpose of This Presentation
      • To present a one-size-fits-all protocol; goals, objectives, and situations differ and so too must the answer to what is the best set of surveys for a situation
      • To present information about INVENTORIES ; inventories have as their objective an enumeration of the species present, monitoring is designed to look at changes over time; monitoring and inventory can inform each other, but almost always would be approached differently
    • 3. Also NOT the Purpose…
      • Provide a protocol for your RESEARCH project
      • This information can certainly be used to inform how you would sample bees in your research project but it would all most certainly need to be modified to meet your specific analytical needs
    • 4. The World Suspects That Bees are Declining Shrill Carder Bumblebee Distribution Data from NBN, with particular thanks to BWARS .
    • 5. The Problem We do not know the magnitude of the crisis nor have identified how and where to target our conservation measures because until now, there is NO GLOBAL MONITORING PROGRAM
    • 6. Outline of Things to Come in This Presentation
      • Guidelines for monitoring
      • Sampling techniques for bees
      • Number of traps to use
      • Pan trap variables (e.g. color, size)
      • Response variables
      • Number of sites to sample
      • Proposed monitoring plan
    • 7. What Makes a Good Pollinator Monitoring Program?
      • Clearly defined questions
      • Repeatable
      • Low variance
      • Low cost
      • Accurately measures change in most or all of the pollinator community
    • 8. Monitoring - Goals
      • What is the story you want to tell?
      • What species do you want to talk about?
      • What level of trend do you want to detect?
      • Over what time period?
      • Example: We want to be able to detect a 20% change in 15 common species over 10 years (PAY ATTENTION HERE: We didn’t say we would detect these declines, just that we could if they were to occur)
      • How often are you willing to cry wolf?
      • What sort of power to detect a trend do you want?
    • 9. Most Important
      • Clearly Define the Goals and Objectives
      • Define How the Information Will be used
    • 10. 2 Categories of Problems
      • How many samples do I need to track changes?
      • 2. Does my current monitoring program have adequate precision to do the job?
    • 11. Goals: Define What You Want Out of Your Monitoring Program Then We Can Have a Talk About Sample Sizes
      • Biological goals
        • Write down which species you plan to monitor along with a rationale for those choices
      • Statistical goals
        • With how much precision do you want to talk about your animal’s status?
        • What geographic place and scale do you want information for?
        • What do you mean by status?… a list, a map, trends?
    • 12. 3 Factors Affect Your Sample Size
      • Variability of your Sample
      • Your Definition of Precision
      • What you Mean by Trend
    • 13. A Measure of Variability
      • To describe variability in counts of bees we use the CV (Coefficient of Variation)
      • CV = SD/Mean
      • The CV is a standardized way of talking about variability that takes into account the fact that the mean and SD are positively correlated
    • 14. Variance = Variability in Monitoring
      • High CVs mean:
        • Trends are harder to extract from the year to year background noise of the counts
        • More samples needed to detect a trend of a given magnitude
        • Costs will be higher
      • The source of the variance doesn’t matter
      • The CV should be lowered where possible – e.g., standardizing on time of year
    • 15. Defining Precision in Monitoring
      • How often are you willing to cry wolf?
        • i.e., Setting the Alpha Level
      • How powerful do you want your test to be?
        • i.e., Setting the Power Level
      • Are you really only interested in declines?
        • i.e., Setting a 1 or 2-tailed test
    • 16. What do you Mean by Trend? Your Answer Affects the # of Samples you Need
      • Over What Time Period?
        • (2 years, 5, 10, 25?)
      • When is a trend not a trend?
        • Yes! 0% is Not a Trend
        • But is 1%? How about 20%?
        • You have to decide what the smallest trend is you want to detect
    • 17. Our Favorite Monitoring Objectives
        • Trend = 50% decline over a set period of time
        • Precision = Alpha 0.2, Power 0.9, 2-tailed
        • Look at 10 and 25 year scenarios
    • 18. Time Conquers All Some Broad Results of our Simulations
      • The Number of Sites You Need to Sample will be High When you are Looking to Detect Trends over <10 Years
      • For Surveys Run for at Least 20 Years the Maximum Number of Plots Needed (Under Reasonable Scenarios) is only 13
    • 19. Those Nasty Zeros
      • Sample sizes must be INCREASED by the proportion of zero counts or places where the species does not occur
        • For example, if you want to track a species and you calculate that you need 20 plots, but that species only shows up on about 50% of the plots then you would need 40 not 20 plots
      • Hint: Keep Counts High by collecting a lot of bees at each sampling location
    • 20. Some Examples of How Counts of Animals and Plants Vary: Mean Percent CV’s Taken from the Literature
      • Large Mammals 14
      • Grasses/Sedges 21
      • Herbs 21
      • Turtles 33
      • Large Birds 36
      • Lizards 42
      • Salmonids 47
      • Caddisflies 50
      • Snakes 54
      • Dragonflies 57
      • Small Birds 57
      • Beetles 58
      • Small Mammals 60
      • Spiders 64
      • Medium Mammals 65
      • Non-Salmonids 71
      • Moths 90
      • Bats 93
      • Butterflies 111
      • Drosophilid Flies 131
      • Bees? You will see how they fit in later in the slide show.
    • 21. CV’s are Very Predictable (at least if you are an amphibian). Correlation between CV of amphibian counts during first and last 5 years of long-term count series
    • 22. Some Background on Bee Sampling: How have Bees been Sampled in the Past?
      • Pan/Bowl/Moericke/Funnel traps
      • Netting
      • Malaise traps
      • Counts at flowers
      • Trap nests
      • Bait Stations
    • 23. A Bit More about Pan Type of Traps
      • Pan, Bowl, Funnel, and Moericke traps – All have the same basic idea: Attract bees using the color of the trap and then drown them in the trap’s liquids
        • Inexpensive
        • No “observer” bias
        • Easily standardized
        • Captures a broad spectrum of bee species (but some groups not well represented)
      • Downside
        • No host plant data
        • Some bee species very poorly sampled
    • 24. Monitoring – General Bee Issues to Consider
      • Year-to-Year Variance HIGH, HIGH, HIGH
      • Something to think about: What is your measure of a bee population?
        • Traditional Measure: Numbers of INDIVIDUALS caught
        • Better: Number of PLACES caught
    • 25. So, Back to Bees and Calculating What Should be Sampled and How
      • We used data from previous studies to compare coefficients of variation across techniques and situations
      • And…explore what the relationship is between Species Richness, Abundance and their CVs
      • And… look at if there is a benefit to getting more samples
    • 26. We Thank These Generous People who Shared their Published and Unpublished Data
      • Jim Cane – Georgia
      • Gordon Frankie - California
      • Terry Griswold – California
      • Rob Jean - Indiana
      • Emanuel Kula – Czech Republic
      • Gretchen LeBuhn – California
      • Bob Minckley - Mexico, Arizona
      • D.F. Owen – Great Britain
      • Frank Parker – Utah
      • Dave Roubik - Panama
      • Karen Wetherill – New Mexico
    • 27. Definitions: How we Calculated the summary CVs Used in the Next Set of Slides for an Individual Site
      • Species Richness – We counted all the species found each year, calculated the SD across those years, and then divided by the mean species richness
      • Bee Abundance – We counted all the bees for all the bee species found within a year, calculated the SD across those year, and then divided by the mean bee abundance
      • More on next slide
    • 28. More Definitions
      • Individual Species Abundance – In this case FOR EACH SPECIES we calculate a yearly total, then, also for each species, we estimate calculate a SD across the years, and divide that by the mean… THEN we take the MEAN OF THOSE INDIVIDUAL CVs
      • Top 5 Species – In this case FOR JUST THE TOP 5 MOST ABUNDANT SPECIES we do the same thing we just talked about above
    • 29. Relationship Bee Abundance and CV of Species Richness at a Site – A Nice, Highly Significant, Negative Relationship Log Total Numbers CV of Richness
    • 30. Relationship Between Species Richness and CV of Species Richness – Basically the Same Relationship, Just a Bit Noisier Mean Species Richness CV of Richness
    • 31. Relationship Between Species Richness and CV of Bee Abundance – Similar relationship, but looser still Mean Species Richness CV of Abundance
    • 32. Relationship Between Mean Bee Abundance and CV of Abundance - Ditto Log Total Numbers CV Abundance
    • 33. Possible Take Home Messages of The Last 4 Graphs
      • Possible Interpretation #1: Where bees are abundant, bee populations are more stable
      • Possible Interpretation #2: If you catch more bees you will lower your CV and consequently your monitoring program will be better able to detect trends
      • Possible Interpretation #3: Easy to catch bees have low sampling variability
    • 34. Which Bee Survey Technique Minimizes Variance of Bee Counts?
      • We compared yearly CVs across techniques for the following measures of a bee population:
        • Bee Abundance
        • Species Richness
        • Individual Species Abundance
        • Top 5 Species
    • 35. Comparison of Techniques: Bee Abundance – No Real Difference Between Techniques Bait Bowl Funnel Malaise Moericke Netting Trap Visual CV
    • 36. Comparison of Techniques: Individual Species Abundance – Note low CVs for Bait and High for Funnel and Moericke Bait Bowl Funnel Malaise Moericke Netting Trap Visual CV
    • 37. Comparison of Techniques: Species Richness – About the same, except for bait, which is quite low Bait Bowl Funnel Malaise Moericke Netting Trap Visual CV
    • 38. Comparison of Techniques: Top 5 Species: Same interpretation as the last one Bait Bowl Funnel Malaise Moericke Netting Trap Visual CV
    • 39. OK, Now Something a Little Different
      • The next slides show results for individual sites
        • 16 sites were available for analysis for bowls
        • 13 sites for netting
      • Take a look at how the CV’s varied among these sites
    • 40. Bowl CVs: Individual Species Abundance – Super High!
    • 41. Netting CVs: Individual Species Abundance – Whoa, Nellie ! Also Super High!
    • 42. Bowl CVs: Top 5 Species – Better, Much Lower
    • 43. Netting CVs: Top 5 Species – Similar, Better, Much Lower
    • 44. Bowl CVs: Bee Abundance – Oh My, Quite Nice!
    • 45. Netting CVs: Bee Abundance – Sweet!
    • 46. Summary- Which Technique?
      • Relatively little difference in CV across techniques – With the exception of very low fluctuations of bees coming into bait traps, but unfortunately bait traps work only for some Euglossine species in the New World tropics
      • Our recommendation: Pan Traps or Moericke traps
        • Inexpensive,
        • No observer bias
        • Easy
    • 47. What Measure of a Population to Use?
      • Note that species that occur at low numbers in surveys have high CVs and are unlikely to be monitored well
      • Note that species that occur commonly have (on average) much better CVs and are thus trends in their populations are much more likely to be detected
      • If you pool all the individuals caught regardless of species into one grand category, you have wonderful CVs and can detect quite small changes in the number of “bees”
      • Ditto on simply tracking changes in the number of species detected
    • 48. To Sum Up the Previous Slide
      • Bee monitoring programs will have excellent abilities to detect changes in the total number of individuals and species and moderate abilities to detect changes in the common species
      • If you want to detect changes in rare species , you need to increase your probability of detecting them by altering your sampling techniques and strategies and not depend on a generic monitoring program to track everything
    • 49. How many bowl traps in a transect should we use?
      • What follows was taken from Leo Shapiro’s and Collaborators Unpublished Work (being readied for publication)
      • Used 4 data sets with large numbers of bowls and where bee captures were recorded for each individual bowl
      • Randomly sampled from data to create accumulation curves
      • Where curve saturates (flattens), there is little gain in the number of species estimated
    • 50. Accumulation curves for pan traps Examples of
    • 51. Summary- How many traps?
      • Curve saturates on average at 15-20 pan traps
      • Previously we showed that CV decreased with more species
      • Recommendation: 24 pan traps per transect, or 3 Moericke traps, this satisfies both having sufficient number of traps per transect and capturing enough specimens
    • 52. What type of pan traps should we use?
      • Size
      • Color
      • Number
      • Distance apart
      • Sampling time
    • 53. Size of pan traps df=6,147, F-value=0.20, p-value=0.977 12 oz 6 oz 1oz 2 oz 3.25 oz 4 oz 0.7 oz No significant difference
    • 54. Is pan trap color really important? Compare how many individuals are caught in different colored bowls for key species
    • 55. Color of Pan Trap - Numerous trials on East Coast of U.S. Blue UV Yellow UV Pale Blue UV Pale Blue White White UV Blue Yellow
    • 56. Data for The Following Slides
      • Were taken from a large month-long USDA ARS study of bowl color run by the Smithsonian Parasitic Hymenoptera group in Calvert County, Maryland
      • Note how each species has its own preferences
      • Note the large sample sizes
      • Also note how the florescent colors performed about equally well as the non-florescent ones
    • 57. Augochlorella aurata
    • 58. Andrena nasonii
    • 59. Andrena violae
    • 60. Calliopsis andreniformis
    • 61. Are bees more attracted to fluorescent or non-fluorescent colored pan traps? Data from Sam Droege Note, that bowls were placed adjacent to one another Genus   non-uv uv Agapostemon 0 1 Andrena 0 1 Apis 0 1 Augochlora 1 1 Augochorella 1 3 Bombus 0 3 Calliopsis 2 6 Ceratina 4 11 Anthididum 0 3 Halictus 2 11 Heriades 0 1 Hylaeus 2 2 Lasioglossum 13 77 Melissodes 1 4 Osmia 1 0 Perdita 1 1 Sphecodes 0 2 Total 28 128
    • 62. Color is important
      • Using multiple colors catch more species
      • Fluorescence dramatically increases catch, at least under some circumstances
      • Recommendation: Use 3 colors UV-blue, UV-yellow and white
    • 63. Does Adding Scents or Sweets in the Water in the Bowl Boost Catch? Nope – Data from 10 trials with 5 replicates of each category – Maryland data
    • 64. Does Adding Salt Increase the Number of Bees Captured? Not in Maryland it doesn’t - Same set up as last time, but note that salt in the New World tropics will attract bees but this has not been tried in traps Treatments are different concentrations of salt in bowl traps
    • 65. Scent is not important
      • None of the scents or salt increased catch in Eastern North America
      • Recommend: dishwasing liquid (Blue Dawn is our favorite)
      • Note that several detergents and laundry soaps were trialed all worked the same but CITRUS based detergents DECREASED captures
    • 66. How far apart should bowls be?
      • Trapping web and paired studies suggests bowls should be 3-5 m apart
      Colored dots indicate trap locations and colors indicate the number of bees captured, from these data traps were determined to not compete with each other when spaced >3m apart
    • 67. When should we sample? Significant effect of time of year From Russell et al. powerline study, note that colors denote significant treatments yet samples fell into date groups in CCA ordination space
    • 68. Change in Captures in May 2-Day Time Intervals Sampling period Data from previously mentioned USDA study
    • 69. What should we be measuring? The upcoming slides tell the story
      • Do we decrease variability by focusing on subsets of our bees? Remember how we calculated the CVs for the previous graphs? Well they are the same except we added two new ones (1. and 2. below) calculated the same way as the others.
          • Bees represented by an average of at least 1 individual
          • Bees represented by an average of at least 5 individuals
          • The Top 5 Species
          • All Individual Bee Species
          • Bee Abundance
          • Bee Richness
    • 70. Impact of Category and Pooling on the CV Note that pooling across sites had relatively little impact on CV
    • 71. Impact of Category and Pooling on the CV Note that pooling across replicates and sites had little impact on CV
    • 72. Impact of Category and Combining Netting and Bowling on the CV Note that pooling netting and bowl trapping data has a slight but positive impact on CV
    • 73. Impact of Category and Pooling across Sites Note that pooling has a consistent slight positive impact on CV
    • 74. Impact of Measuring Number of Occupied Cells vs Stems on CV Note that using the number of occupied stems rather than the total number of occupied cells has a slight but consistent positive impact on CV
    • 75. Impact of Pooling across sites on CV Very Interesting! In this case pooling across sites has a large positive impact on CV
    • 76. Impact of Pooling From Individual Month to All Year Pooling across all the months of data Roubic’s site has a relatively large positive impact on CV
    • 77. Impact of Category on CV
    • 78. Impact of Category on CV
    • 79. Impact of Category and Pooling across Sites on CV Note the slight but relatively consistent positive impact on CV by pooling sites
    • 80. CV Lessons
      • Pooling across species – large gain
      • Pooling across time – large gain
      • Pooling across sites – only a small gain
        • Due to high site differences?
    • 81. There are quite a few other taxa that end up in bowls that could be sampled. Taiwan Bowl Captures
    • 82. How many sites do we need to sample and for how long?
      • Key parameters are:
        • Degree of variability
        • Number of times (years) that you will sample
        • Effect size that you wish to detect (e.g. 5% decline per year)
      • Measures – How You Will Analyze the Data
        • Sign test: Number of sites that declined
        • Paired T-test: Magnitude of decline
        • Regression: Slope of decline
    • 83. Warning – Statistics Ahead
      • Hold on to your seats, we are going to get into some statistical issues now. You don’t have to worry about the details (unless you want to) but there are some important take home messages to, indeed, take home
      • For most of you, you can skip through the following slides and get to the meat at the end
    • 84. Sample Size Calculations
      • We can estimate sample sizes if we plug in the various factors affecting samples sizes such as:
        • The time span you want to detect trends
        • The percent change in population you want to detect
        • The alpha level you choose
        • The power level you choose
        • The type of analysis technique
        • The species’ CVs
    • 85. We use Simulations to Estimate Samples Sizes (Really we are estimating statistical power here, but that’s a detail – Statistical power is the ability to statistically detect a change if one were occurring)
      • These simulations create mathematical populations with known declines (effect sizes)
      • We choose how variable to make the simulated populations based on the CVs from real bee surveys
      • Next we simulate sampling from these populations
      • Then we score the simulated sites for having declined or not
    • 86. Analytical Technique
      • In this slide show we simulate surveys that use the Sign Test to detect changes
      • If you are more of a regression kind of person you can check out similar analyses using regression at:
      • The results are quite similar
    • 87. Created populations with known declines
    • 88. We Varied CVs, Effect sizes and Sampling Intervals
      • CVs= Low (0.4-0.5), Medium (0.8-1.1) and High (1.6-1.8)
      • Annual Declines = 2%, 5%, 7% and 10%
      • Sampling interval = every 2nd year or every 5th year
    • 90. No surprise here, its easier to detect a large decline than a small one, note that this is just a 2-year study
    • 91. EFFECT SIZE Small decline Big decline
    • 92. Low CV – 2 years
    • 93. Low CV – 5 years
    • 94. Med CV - 2
    • 95. Med CV - 5
    • 96. High CV - 2 No surprise here, if you have high variability in your CVs you need tons of samples to detect a change
    • 97. High CV - 5
    • 98. Effect of Study Length on Power for Low CV No surprise here….its easy to detect a trend over a longer period of time than a shorter one
    • 99. Power results Using the sign test, we have good power to detect even a 2% decline within 5 years across a range of CVs with only 100-300 sample sites. We have slightly more power if we use a paired t-test.
    • 100. More Lessons from Power Analyses
      • If… you are interested in trends in only the common species, species richness, or total number of bees
      • And… you are interested only in detecting large changes over long periods of time
      • See next slide for more on this thought
    • 101. More Thinking
      • So, if you take the long view and set up monitoring programs for bees with a goal of detecting change over 10+ years then all of a sudden you need only a few samples
      • Check the graph out on the next slide showing numbers needed for different year scenarios for different levels of CV
      • CV makes a huge difference in the short run, but as you increase the number of years you monitor then it all converges on a lucky 13 sites (in this simulation using a regression analysis rather than sign test)
    • 102.  
    • 103. So to Summarize our Summaries
      • To detect short-term changes (5 years) in bee populations you can detect global or regional changes with a network of 100-300 sampling locations
      • To detect 10 year changes you can use networks of around 25
      • To detect 25 year changes you can use 13 sites
    • 104. The Difference Between Global, Regional, and Local Bee Sampling
      • Scale doesn’t matter for the sample size estimates we just presented
      • Thus the basic results would be the same for the Globe, Africa, Germany, or the U.S. State of Maryland (the nicest of all the states, by the way)
      • What does differ is that the distribution of species varies and thus if you want to detect changes at the species level you will have to increase your numbers of samples regionally to make up for plots where the species doesn’t occur
      • See next slide
    • 105. More on That Thought
      • So if you have a global network of bee surveys
      • You can, no problem at all, easily estimate changes globally in the total number of bees and species richness
      • But what if you wanted to estimate changes in the collective members of the genus Melitoma?
      • It only occurs in the New World, hmmm
    • 106. Distribution of Various Melitoma Species from Photo from University of Georgia
    • 107. Ah….
      • Then you need to proportionally increase your samples in the New World to account for the fact that Melitoma does not be occur on all of your survey sites throughout the world
      • So, your decision as to what species, genera, or groupings of bees you want to survey will also influence how many samples you need simply based on their distributions and abundance
      • Its your call, but just don’t forget that you can’t estimate a trend for something that isn’t there
    • 108. Our Basic Sampling Plan for any Large Area (e.g., park, county, state, small country)– This will detect a high percentage of species, detect modest declines in trends in total number of bees, species richness, and common bee species over 10 year or greater intervals
      • 25 transects
      • 24 pan traps per transect (8 of each color) (can be replaced with 3 continuously run Moericke traps)
      • Sample every 2 weeks
      • Sample every year
    • 109. A Global or Continental Sampling Plan
      • If changes in bee populations over 2-year intervals is important
      • Large changes in total bee numbers or species richness could be detected with only 50-100 sampling locations
      • Increasing this to 300 locations will allow greater regional assessments and more power to detect changes at the genus and species level
      • If detecting short-term changes are less important then you can go for few sites
    • 110. Where to Sample – Things to Consider in Terms of What you want to Talk About
      • Do you want to talk about the entire globe, state, or park?
      • Or do you want to talk about just some portion of it (agricultural areas, cotton plantings, natural areas, national parks, roadsides)?
      • Where you sample determines what kinds of statements you can make
    • 111. Sampling: Random, Systematic, Chosen
      • Random sampling – Classical way to choose where to sample
      • Systematic – For natural communities usually a better way to place samples due to non-randomness of habitats and populations
      • Chosen – You can pick and choose where to sample but if you do that then you can ONLY talk about those sites and not extrapolate to ANYWHERE else
    • 112. What to count
      • Minimum: Numbers of bees, wasps, flies without respect to species
      • Or…You can ID bees to genus, morpho-species, species, sex
      • A lot will depends on time, resources, availability of identification expertise
    • 113. Specimen Processing
      • Batch processing
      • Dry specimens
      • Store in bulk containers (e.g., petri dishes) by sample location/date
      • Pin representative collection
        • Rest remain unpinned
      • Store in climate controlled environment – humidity is a problem, check for bugs
    • 114. You can Analyze Monitoring Data in Many Ways
      • Non-parametric sign test or Binomial test
      • Paired t-test
      • Simple Regression
      • Route Regression
      • Estimating Equations
      • Site Occupancy Models
      • Bayesian Approaches
      • Etc.
    • 115. What You Will Get
      • With 100 or more sites sampled, in 5 years (preferably 10), you will have the ability to detect 5% declines in some individual species, species richness and abundance
      • With 25 sites sampled, you will be able to detect 5% declines in 10-25 years