Chapter 6 Field methods: running a monitoring plot

Skills this lab builds. 4DEE: Ecology Practices → Fieldwork; Natural history; Working collaboratively; Quantitative reasoning and computational thinking. BioSkills: Process of Science → Study Design (“Execute protocols and accurately record measurements and observations”), Data Interpretation & Evaluation (“Describe sources of error and uncertainty in data”); Quantitative Reasoning → “Record, organize, and annotate simple data sets.”

What ecological data do you collect at a sampling site? There are many possibilities! In today’s lab, we will learn several of the most common data collection methods practiced in the Southwest. The protocols presented here are from the Monitoring Manual for Grassland, Shrubland, and Savanna Ecosystems, the method the Bureau of Land Management uses to assess rangeland condition across the western United States under its Assessment, Inventory and Monitoring (AIM) program. Millions of acres are managed using these data to adaptively manage resources. If you take a field job in this region, there is a real chance you will perform this protocols.

6.0.1 Where this lab happens

Sinclair Wash — also called Clay Avenue Wash — a short walk from campus.

This is the same ground you will be designing your own sampling scheme on in the ecological sampling lab, and it is an active restoration site: the Rio de Flag Flood Control Project is reshaping this reach, and the banks you will be measuring are recovering from that work. So the numbers you collect today are not a classroom exercise with a real-world flavour — they are the same measurements a restoration monitoring crew would take here, for the same reason: to find out whether the vegetation is coming back, and how fast.

Keep that in mind in Part 7. When you ask which state on the state-and-transition model your plot best matches, you are asking a live question about a site somebody is actively trying to move from one state to another.

6.0.2 Before class: watch these

The BLM publishes short training videos for each core method. Watch these three before you come — 28 minutes total. They cover what every group does first.

Video Length
Intro to the core methods 3:28
Establishing a transect 6:01
Line-point intercept 18:50

The other three — ecological site identification, photo points and canopy gap — are linked at the top of their own sections below. Watch each one when you reach it.

All of them, plus the manual and blank datasheets, live at https://www.blm.gov/aim/training.

6.0.3 Downloads for this lab

6.0.4 What to print and bring

The forms you fill in outdoors are the official AIM field sheets — the same ones a BLM crew carries. They are built for a clipboard, which a spreadsheet is not, and using the real thing is part of the point.

Print How many What it is
Plot characterization 1 per group Coordinates, slope, aspect, slope shape, landform, hillslope position. Skip the soil horizon table — that is the pit we are not digging
Photo ID card 1 per group This is the board you hold in the photo. Fill it in before each shot
Line-point intercept enough for 150 points per group One sheet per transect, or more — check how many points a sheet holds
Gap intercept 1 per transect per group Note the minimum gap size and perennial only / annual and perennial boxes at the top — fill them in before you start
Unknown plant tracking sheet 1 per group The official version of the placeholder-code log
QA/QC sheet 1 per group For the calibration in Part 5
Herbarium label 1 per specimen Only if you collect
Your species list 1 per group From Part 1 — print it with images if you can

The .csv files in the downloads list are for afterwards, not for the field. Once you are back indoors, type your paper sheets into them. That is how the data gets into a form the analysis script can read, and it is also when transcription errors surface — which is why crews enter data the same day, while they can still remember what a smudged code said.

The two worksheets that are not field sheets — the ecological site worksheet and the specimen quality checklist — you fill in at a computer, in Parts 1 and 7.

Every blank AIM sheet, including the methods we are not running, is at the Monitoring Manual datasheets page.

6.1 Objectives

  1. Establish a monitoring plot and run three AIM core methods on it: photo points, line-point intercept, and canopy gap intercept.
  2. Execute each protocol as written, and record data someone else could use.
  3. Prepare for a field day the way a crew does — identify the ecological site your plot sits on and build a species list for it before going out — and use the site to say whether your cover numbers are good news or bad.
  4. Quantify the disagreement between observers, and decide whether it is small enough to trust your result.
  5. Collect, press and label a voucher specimen for a plant you cannot identify, to the standard set in the tree walk lab.
  6. Say what each method can and cannot tell you — which is what lets you choose among them when you design your own study.

What this lab is for. You are not here to produce a publishable assessment of this site. You are here to run the protocols with your own hands, so that when you design your own sampling scheme in the ecological sampling lab you are choosing between methods you have actually used rather than methods you have read about. That is why the turn-in is mostly datasheets.

6.2 Why point intercept rather than “how much is covered?”

Ask five people to eyeball the percentage of ground covered by grass and you will get five different answers, all of them confident. Ocular cover estimates are fast, and they are unreliable in a way that does not shrink when you get more experienced — it just gets harder to notice.

Point intercept replaces judgment with an event. A pin either hits a plant or it does not. There is no estimating step, so there is nothing for two observers to disagree about except what species they hit and whether the pin was vertical. Cover is then not a guess but a proportion: hits divided by drops.

That is the whole idea, and it is worth stating plainly because it recurs everywhere in this manual. Whenever you can replace an estimate with a count, do it.

6.3 Part 1 — At the computer, before you walk out

A field crew does not start at the plot. It starts at a desk, working out what kind of ground it is about to stand on and what is likely to be growing there — and it does that on work time, because it is part of the job rather than preparation for it.

You have about twenty minutes. Do both of these before anyone puts boots on.

6.3.1 Look up your ecological site

Watch first: Ecological site identification (12:30)

About ten minutes. A field crew never arrives at a plot without completing a pre-site evaluation — they have already pulled the soil map and worked out what kind of ground they expect to be standing on. You are going to do the same thing, for the same reason: it is what makes your field description a test of something rather than a description of nothing in particular.

The whole class looks up the same point — a reference point in the reach of Sinclair Wash we will be working in. Your own plot centre gets assigned when you get out there, and one of the first things you will do on returning is check whether it landed in the map unit you looked up. Sometimes it will not, and that is worth knowing: a wash is exactly where soil map units change, because floodplain, terrace and upland are different ground.

Use the aerial view link above to find the reach. Zoom in until you can see the Rio, which follows the tree line and the path — the path is hard to make out from above, so use the trees. Draw your Area of Interest over that stretch of wash, a few hundred metres of it, centred on the tree line.

  1. Open Web Soil Survey (https://websoilsurvey.nrcs.usda.gov/app/) and click the green Start WSS button.

  2. Define your Area of Interest. Zoom to the plot — searching the coordinates is faster than panning — and draw a small rectangle around it with the AOI tool.

  3. Soil Map tab. Read off the map unit name and symbol the plot falls in. If your rectangle covers more than one map unit, note which one the plot centre is actually in.

  4. Soil Data Explorer tab → Soil Reports → Vegetative Productivity → Link to Ecological Site Descriptions in EDIT, then View Soil Report. The table that opens lists each map unit with a link to its ecological site description in the last column.

  5. Follow the link into EDIT (the Ecosystem Dynamics Interpretive Tool, https://edit.sc.egov.usda.gov/). Record the ecological site name and ID.

  6. Read two sections of the ESD. In General information, find the reference state’s plant community — the species it expects and roughly how much of each. Then find the state-and-transition model, usually drawn as boxes and arrows. Note the slope range, landform and hillslope position the site is described as occupying; you will check those against the ground.

Fill in Part A of the ecological site worksheet — questions 1 and 2 — and take it with you. Part B waits until you are back with your data.

6.3.2 Build a species list

About ten minutes. You used SEINet in the tree walk lab to test one identification. Here you use it for the other thing it is good for: finding out what has been found near a place before you go there.

The ecological site description told you what this kind of ground should support. A SEINet search tells you what people have actually collected here. Those are different questions and the answers rarely match exactly, which is the point.

The practical reason to do this: line-point intercept goes much faster when you already recognise the common species and have their PLANTS codes written down. The scientific reason is better — anything you find that is not on your list is worth a second look. It may be a new record, it may be something invasive, or it may just be a plant nobody bothered to collect. All three are interesting, and you cannot notice any of them without knowing what was expected.

  1. Go to SEINet (https://swbiodiversity.org/seinet/index.php) and choose Search → Search Collections.

  2. Choose collections. Select all of them, or just the Arizona herbaria if you want a tighter list, then click Next.

  3. Find the Point-Radius Search box on the search criteria page. Either type the decimal-degree coordinates for Sinclair Wash straight in, or click the globe icon to open a map and pick the spot, then Submit Coordinates.

  4. Set your radius. Three to five kilometres is about right here — small enough to be about this place, large enough to return a usable number of records.

  5. Run the search, then click the Species List tab. That converts the specimen records into a list of taxa.

  6. Optional but worth it: choose Display as Images to get an illustrated checklist. Printed, that is a field-usable picture key to the species most likely to be under your pin.

Print it, or keep it on a phone, and write the PLANTS code beside the ten or so species you expect to see most. That list walks out to the wash with you.

Read the list for what it is. It is a record of collecting effort, not a census. Showy plants, roadside plants and anything growing near a parking area are over-represented; grasses, sedges and unglamorous weeds are under-represented, because fewer people stop to press them. You met exactly this problem in the tree walk lab, where the question was whether the dots on the map were the plant or the botanists. It is the same warning here: treat the list as a prior, not a checklist to tick off.

6.4 Part 2 — Establishing the plot

The standard AIM plot uses a spoke design: a permanent stake at plot centre, with three transects radiating out at 120° from one another.

6.4.1 Materials

  1. Three 25 m tapes (or one tape, run three times)
  2. Compass
  3. Pin flag — a thin, straight rod, marked so you can identify it
  4. Stakes for plot centre and transect ends; flagging
  5. Datasheets, clipboard, pencils (pencil, not pen — rain)
  6. Camera or phone, and a photo identification board — a small whiteboard, or paper on a clipboard
  7. Clinometer (or a phone clinometer app) and a GPS unit or phone GPS
  8. Field guide or the key from the tree walk lab
  9. Newspaper and a plant press, or two boards and straps

6.4.2 Procedure

  1. Set plot centre. Drive the centre stake in, leaving less than 30 cm exposed. Your instructor will have assigned the point using a randomisation method — do not move it because the vegetation looks more interesting three metres away. Nudging a plot toward the interesting vegetation is the most common way field data gets biased, and you will take that problem apart properly in the sampling lab in a few weeks. For now, take it on trust: the point is where it is precisely so that nobody’s judgement chose it.

  2. Choose the first azimuth at random, then set the other two at +120° and +240° from it. Record all three bearings on the plot characterization sheet, along with your GPS coordinates, elevation, slope and aspect — you will need the coordinates again in Part 7. (The manual specifies the 120° spacing; how you pick the first bearing is a local convention, so we make it random and we write it down.)

  3. Set transect start stakes 5 m out from centre along each bearing. Run each tape from its start stake outward for 25 m, and stake the far end.

  4. Keep the tape taut, straight, and close to the ground — but not so close that it drags on and disturbs the soil surface. A sagging tape puts your points somewhere other than where you think they are.

  5. Take your photo points — before anyone walks on the plot. This is a core method in its own right, not a snapshot. See below.

6.4.3 Photo points

Watch first: Photo points (6:40)

A photo point is a photograph taken from a recorded position, on a recorded bearing, with the date and plot written in the frame — so that someone standing in the same place in ten years can take the same photograph and lay the two side by side. The whole value is in the repeatability, which is why the position and the board matter more than the photograph does.

  1. Write the board for each transect: date, plot name, transect number, transect bearing.
  2. Stand 5 m back from the transect start stake, in line with the transect bearing, looking out along the tape.
  3. Hold the board at the bottom centre of the frame, with a little space below it, and take the photo. One per transect, three per plot.
  4. Take them before any other measurement. Once your group has walked the transect the vegetation no longer looks the way it did.

A photograph will not tell you percent cover, and it is not trying to. What it does is catch the things your numbers were not designed to catch — a burn, a gully that opened, a shrub that died — and it is the only record on the plot that someone can interpret without knowing your protocol.

The 25 m three-transect spoke plot samples roughly 0.3 ha. The 50 m version in the older edition of the manual samples about 1 ha. Which one a project uses depends on how patchy the vegetation is and how big a change it needs to detect — which is a sample-size question — exactly the kind you will learn to answer for yourself in the sampling lab.

6.4.4 Describing the site

Before you measure any vegetation, describe the ground it is growing on. This takes about ten minutes and it is the part students are most tempted to rush, because it feels like paperwork. It is not. Every field below is one of the things that defines an ecological site, which means this is the only independent evidence you will collect against which to check the map in Part 7.

Put another way: you are not digging a pit, so this description is the only field evidence you have. Take it seriously in proportion.

Fill in the topography and landform block of the plot characterization sheet. Record what you actually see. You looked up a candidate ecological site an hour ago, and it comes with expectations about slope and landform — do not let them fill in the blanks for you. If the ground disagrees with the map, that disagreement is the most useful thing you will collect today.

6.4.4.1 Slope

What it is: how steep the ground is, as a percentage — a 10% slope drops 10 m over 100 m travelled. Percent, not degrees; they are different numbers and mixing them up is a classic error.

How to take it: sight through the clinometer from plot centre in the direction water would run off the plot, at a target the same height as your eye. If two people take it, average them.

Why it matters: slope drives how fast water leaves and how much soil leaves with it.

6.4.4.2 Aspect

What it is: the compass direction the slope faces — again, the direction water runs downhill. Record it in degrees from magnetic north (so 180° is due south).

Why it matters, especially here: in northern Arizona aspect is one of the strongest controls on what grows where. North-facing slopes get less direct sun, stay cooler, hold snow longer into spring and lose less water to evaporation; south-facing slopes are hotter and drier. Two plots a hundred metres apart on opposite aspects can carry genuinely different plant communities on the same soil. If your plot and a neighbouring group’s differ, check your aspects before you conclude anything else.

6.4.4.3 Slope shape

What it is: whether the ground surface curves, and which way. Recorded twice — once looking down the slope, once looking across it.

Shape What you see What it does with water
Concave Curves inward, like the inside of a bowl Collects water, and the fine soil and litter that travel with it
Linear Straight — even, uniform, no curvature Passes water through
Convex Curves outward, like the crest of a hill Sheds water, and loses fines off the surface

Record both directions, e.g. downslope linear, across-slope concave.

Why it matters: two plots at the same slope and aspect can be wet or dry depending only on this. A concave position is a water-gathering position and will usually carry more cover than the convex ground above it.

6.4.4.4 Landform

What it is: the kind of landscape feature the plot sits on. Choose one:

Landform What it is
Hill or mountain Ground that rises above the surrounding land, shaped mainly by erosion
Alluvial fan The fan-shaped apron of sediment where a channel leaves a confined slope and spreads out
Floodplain or basin Low flat ground beside a channel that water spreads across when the channel is full
Terrace A former floodplain, now abandoned above the active channel — flat tread with a steeper riser dropping off it
Flat or plain Extensive level to gently sloping ground with no strong relief
Playa A closed basin floor that ponds water and dries out, usually barren and fine-textured
Dunes Wind-deposited sand with its own relief

If you chose terrace, also record whether you are on the tread (the flat top) or the riser (the slope dropping off its edge).

6.4.4.5 Hillslope position

What it is: where on a hillslope you are, from top to bottom. The standard sequence:

Position Where it is What tends to be true there
Summit The nearly level top Stable, but exposed and often thin-soiled
Shoulder The convex break just below the summit, where the ground starts to fall away Sheds water and soil; usually the most erosional position on the hill
Backslope The main, steepest, straight middle of the slope Material moves through rather than accumulating
Footslope The concave apron at the base, where the slope flattens Collects material coming down the hill
Toeslope The gently sloping ground at the very bottom, grading into the valley floor Wettest and deepest-soiled of the five

Notice the pattern: shoulders lose, footslopes and toeslopes gain. That single fact explains a great deal of why vegetation changes as you walk down a hill, and you should expect your cover numbers to reflect it.

6.4.4.6 Surface observations

Three quick ones, all by eye:

  • Surface rock fragments (%). Roughly what proportion of the ground surface is rock rather than soil or plant. Rock armours the surface against erosion, and it also means less rooting volume.
  • Erosion features. Note what you can actually see: rills (small channels a few centimetres deep), gullies (channels deep enough to step into), pedestals (plants or rocks left standing on little columns as the soil around them washed away), or water flow patterns (fans of deposited litter and sediment showing where water ran).
  • Disturbance. Roads, trails, stumps, fire scars, grazing sign, construction. Write what you see, not what you infer.

6.5 Part 3 — Line-point intercept

Watch first: Line-point intercept (18:50) — required before class.

You will record 50 points per transect, spaced 0.5 m apart, for 150 points on the plot.

So the first point is at 0.5 m, the second at 1.0 m, and the fiftieth at 25.0 m — the far end of the tape.

6.5.1 Dropping the pin

At each 0.5 m mark:

  1. Hold the pin vertical, with its lower end several centimetres above the top of the vegetation, next to the tape.
  2. Release it and let it slide through your hand until it hits the ground. Do not guide it, do not aim it, do not adjust it after it lands.
  3. It matters much more that the pin fell freely than that it landed exactly on the tape mark. Resist the urge to nudge.

Every nudge is a small act of bias, and the direction people nudge is always the same: toward the interesting plant. Two hundred nudges is a systematic error, not noise.

6.5.2 What you record at each point

Three groups of columns:

Top layer (first hit). The uppermost or first stem, leaf or plant base the pin intercepts. Record the species code. If the pin touches nothing on the way down, record N.

Lower layers. Everything else the pin passes through on its way down, in vertical order, plus these non-plant codes:

Code Meaning
HL Herbaceous litter
WL Woody or succulent litter, > 5 mm
NL Non-vegetative litter
VL Vagrant lichen
DS Deposited soil

Soil surface. What is at the very bottom — the base of a plant (record its species code), or:

Code Meaning
S Bare mineral soil
LC Lichen crust
CY Cyanobacterial crust
M Moss
D Duff
R Rock, ≥ 5 mm
BR Bedrock
W Water

The one rule people break: record each plant species only once per pin drop, the first time the pin intercepts it — even if the pin passes through the same plant three times on the way down. A species that got hit is a species that got hit; the number of times is not data here.

What this method cannot see. A pin records a species only if it lands on one. A plant occupying 1% of the plot has roughly a 1% chance per drop, so across 150 points you will miss most of the uncommon species entirely — and uncommon is often exactly what a manager is required to know about. Line-point intercept is a good way to measure abundance and a poor way to establish presence. Keep an eye out as you walk for species that never turn up under the pin; you do not have to record them today, but noticing them is the point.

6.5.3 Species codes

Use USDA PLANTS codes (https://plants.usda.gov) — generally the first two letters of the genus plus the first two of the species: Pinus ponderosa → PIPO, Bouteloua gracilis → BOGR.

When you do not know the plant, do not guess and do not leave it blank. Give it a placeholder:

Code Meaning
AF1, AF2 … Annual forb, unknown 1, 2 …
PF1, PF2 … Perennial forb
AG1, AG2 … Annual graminoid
PG1, PG2 … Perennial graminoid
SH1, SH2 … Shrub
TR1, TR2 … Tree

A consistently-applied placeholder is real data — the same convention you used for UNK-1 in the tree walk lab, with the growth form built into the code. You can go back and resolve PF1 to a name later, and every point where you recorded it updates at once. “Some kind of daisy?” cannot be resolved by anyone, ever.

6.6 Part 4 — Canopy gap intercept

Watch first: Canopy gap intercept (15:35)

Line-point intercept tells you how much plant cover there is. It cannot tell you how that cover is arranged, and those are different things. Two plots can both come in at 40% foliar cover — one as an even scatter of small plants, the other as dense clumps separated by three metres of open ground. Wind and water do not treat those two plots the same. Neither do seeds, and neither does fire.

Gap intercept measures the arrangement. You run it on the same three tapes, so it costs you a walk rather than a setup.

6.6.1 Procedure

  1. Walk the tape from 0 m outward, watching the line rather than the ground beside it.
  2. A gap begins where plant canopy ends, and continues until plant canopy begins again. Only canopy that is over the line counts — a plant 10 cm to the side of the tape is not closing your gap.
  3. Record the start and end position of each gap, in centimetres. The gap length is the difference.
  4. Gaps shorter than 25 cm are not recorded. That is the manual’s minimum: below it you are measuring the space between grass blades, not the structure of the plant community.
  5. Repeat for all three transects.

6.6.2 The decision you have to make before you start

The official datasheet carries a line that says circle one: perennial vegetation only, or annual and perennial vegetation. That is not a formality. In a wet year, annuals can close most of the gaps on a site whose perennial structure has not changed at all — so the two choices can give you very different numbers off the same tape on the same afternoon.

Decide as a group, say it out loud, write it on the sheet. Then, when you compare with another group, check that they made the same call before you conclude anything about the two plots.

This is the same problem as the “did it touch?” rule in the calibration section, arriving from a different direction: a protocol is only repeatable to the extent that its judgment calls have been written down.

6.6.3 What you calculate

Gap lengths are summed within size classes and expressed as a proportion of the line:

\[\%\ \text{of line in gaps of a given class} = \frac{\text{sum of gap lengths in that class}}{\text{line length}} \times 100\]

The standard classes are 25–50 cm, 51–100 cm, 101–200 cm, and greater than 200 cm. Report all four. The largest class is usually the one managers care about, because a two-metre gap is where erosion starts and where an invasive seedling lands without competition.

6.7 Part 5 — Observer calibration

This is the part of the lab that most resembles a real field job and least resembles a normal class exercise. Before a crew’s data is used, the crew has to demonstrate that its members produce the same numbers on the same ground.

6.7.1 Procedure

  1. Your TA will lay one extra transect in a piece of ground with a good mix of vegetation, litter and bare soil.
  2. Each person in the group runs that same transect independently, recording their own datasheet. Do not talk. Do not look at anyone else’s sheet. This is the whole point.
  3. Everyone calculates foliar cover, bare ground and litter cover from their own numbers.
  4. Assemble the group’s results into calibration_datasheet.csv and look at the spread.

6.7.2 The thresholds

The monitoring manual sets these explicitly:

Method Standard
Line-point intercept All observers within 10 percentage points (absolute) of one another, for each indicator
Vegetation height Counts in each height category differ by no more than 2
Species inventory Number of species recorded differs by no more than 2

Only the first row applies to what you ran today. The other two are in the table because calibration is not something done once for one method — every method a crew runs has a standard it has to meet, and a crew that passes on line-point intercept and fails on height is not a calibrated crew.

Crews recalibrate once a month, or whenever they move into a new ecosystem type, whichever comes first.

6.7.3 What to do with the answer

If your group is inside 10 points: say so, and say which indicator was closest to failing.

If your group is outside 10 points — and some groups will be — that is a finding, not a failure, and the useful move is to work out where the disagreement came from. Almost always it is one of three things:

  • Species identification. Two people hit the same plant and called it different things. Fixable with a key and a voucher.
  • The “did it touch?” judgment. One person counts a leaf that brushes the pin; another does not. Fixable with an agreed rule, stated out loud, before you start.
  • Pin verticality. Someone is unconsciously tilting the pin. Fixable by watching each other drop it.

Notice that all three are fixable, and none of them are fixed by trying harder. The fix for observer error is a clearer protocol, not more effort — and that is the transferable lesson of this entire lab.

6.8 Part 6 — Unknown plants and voucher specimens

The placeholder codes only help if someone can eventually resolve them. That is what a voucher specimen is for: a physical, permanent record of exactly which plant you meant.

The tree walk lab covered why a specimen works and what makes one worth keeping — reproductive material, both leaf surfaces, a relocatable locality, the determiner field. This part is the protocol for doing it on a plot you are in the middle of measuring, where the order of operations matters and the collecting is not free.

  1. Check permission first. Collecting is allowed here because your instructor arranged it for this site. On public land it usually requires a permit, and on private land it requires the landowner. This is not a formality — it is the first question a professional asks.

  2. Finish all measurements on the plot before you collect anything. Collecting first means walking on and disturbing the thing you are about to measure.

  3. Collect from outside the plot if you possibly can. Only take a specimen from inside the plot if more than ten individuals of that species are present on it.

  4. Take a whole plant if you can — roots, leaves, and any flowers or fruit. The reproductive parts are what most keys run on, and a specimen without them often cannot be identified at all.

  5. Press it. Lay the plant flat between several sheets of newspaper, spread the leaves so they do not overlap, and put it under weight or in a press. The newspaper draws the moisture out; change it if it gets damp.

  6. Label it. The monitoring manual requires, at minimum: plot name, unknown plant ID number, and date. That is what ties the pressed specimen back to the code in your dataset.

    A herbarium label carries more than that — collector, precise locality, elevation, habitat, associated species — and the extra information is what makes a specimen useful to anyone beyond your project decades later. Use the printed herbarium label from the tree walk lab, fill in every field even though the minimum label does not demand it, and affix it to the mounted sheet. Every specimen in the Deaver Herbarium on this campus is useful today because someone wrote down more than the minimum.

  7. Once dry, mount the specimen to the standard from the tree walk lab: reproductive material easily viewed, one leaf turned over so the underside shows, a fragment packet on the sheet, and the plant filling the sheet without reaching the edges. Score it against the same checklist you used there, in the OWN rows, before you hand it in — a specimen that would not survive that scoring is not going to survive a curator.

6.9 Part 7 — Ecological site: does the map match the ground?

Back indoors, at a computer. Bring your plot characterization sheet, your LPI and gap results, and Part A of the worksheet you filled in at the start of the period.

You have a foliar cover number. Here is the problem with it: 40% cover is good news on one site and a symptom on another, and nothing in your data can tell you which. A dry, shallow-soiled site may never have supported more than 30%. A deep-soiled meadow at 40% has lost most of what it had.

Cover is not interpretable on its own. It is only interpretable against what this particular piece of ground is capable of — and that is what an ecological site is.

An ecological site is a kind of land defined by the soil, climate and landform it has, grouped so that all the land in one ecological site produces the same kind of plant community and responds to disturbance the same way. Each one has a published Ecological Site Description (ESD): a reference plant community with expected species and cover, and a state-and-transition model showing the other states that site can be in and what pushes it between them.

At the computer this morning you found the site the map says you were standing on. You have now spent an afternoon on the actual ground. This part is where those two meet.

6.9.1 What we are not doing, and why it matters

The full AIM protocol confirms the ecological site by digging a soil pit 50 cm across and at least 70 cm deep, describing every horizon, texturing the soil by hand, and photographing the profile. We are not doing that — it needs permission, a shovel, and an hour we do not have.

So the map’s claim stands or falls on your surface description alone. That is a real limitation and you should name it in your answer. Soil maps are drawn at a scale where a single mapped polygon routinely contains more than one soil, so the ecological site you looked up is a hypothesis about your plot, not a fact about it. The pit is how a crew tests that hypothesis properly; your slope, aspect, landform and hillslope position are how you test it partially.

You have met this shape before. In the tree walk lab an identification was a hypothesis you could defend and someone could later re-test. This is the same thing one level up: the map proposes, the ground disposes.

6.9.2 First: were you where we thought you were?

Before anything else, check the assumption the whole lookup rested on. Take your plot’s GPS coordinates off your plot characterization sheet, go back into Web Soil Survey, and draw a small Area of Interest around your actual plot centre.

Did it fall in the map unit the class looked up this morning?

  • If yes, the reference community you read is the right one to compare against. Carry on.
  • If no, you have a more interesting afternoon than everyone else. Record your actual map unit and its ecological site, and use that one for the questions below. Then say, in a sentence, what is different about where your plot sits — bank, terrace, upland — that would explain two units meeting there.

A wash is precisely the kind of place where this happens. It is not an error; it is the map doing its job at a boundary, and noticing it is the whole skill.

6.9.3 Part B of the worksheet

Questions 1 and 2 you answered at the computer this morning. These are the rest.

  1. How does your plot compare? Put your LPI foliar cover and your three most abundant species next to the reference community’s. Do not smooth over the differences — the interesting result is a mismatch.

  2. Which state on the state-and-transition model does your plot best match? Name the state and give your evidence from your own data. If you cannot tell from what you collected, say that instead — and say what you would have needed to measure.

  3. Does your own site description agree with the ecological site? The ESD gives a slope range, a landform and a hillslope position for its site. Put yours beside them. If they disagree, that is a real result and worth more than agreement — say which is more likely to be wrong, the map or your reading of the ground, and why.

  4. What would the soil pit have let you check that your surface description could not? One or two sentences, in your own words.

  5. Does your gap data fit the story? Look at the largest gap class and ask whether it is consistent with the state you chose in question 4.

6.10 The rest of the core methods

You ran three field methods and identified your ecological site. A real AIM crew runs the whole core set on the same plot, and the ones you did not run are not harder — they are just more time than one lab period has.

These are here to practice if you want to. Nothing below is assigned and none of it is graded. But if you are thinking about a field job in this region, or you want a method for your own study at Sinclair Wash that measures something the three you ran cannot, this is where to look. Each video is short, and every protocol is written out in the manual.

Method What it measures that today’s three don’t Time on a 3-transect plot Video
Plant species inventory Which species are present, including the uncommon ones the pins miss. Gives richness, and invasive and rare-plant presence/absence 0.25 h 4:02
Vegetation height Vertical structure — 30 points on the transects you have already laid out 0.25–0.5 h 8:06
Basal gap intercept Gaps between plant bases rather than canopies. Far less seasonal than canopy gap, and it is what erosion models actually want 0.1–1.0 h covered in the canopy gap video
Soil stability test Whether the soil itself holds together when it gets wet — the only measurement in the set that is about soil rather than plants 0.4–0.6 h, 18 samples run in parallel 16:18
Soil hand texturing Soil texture by feel — sand, silt and clay fractions, without a lab 10:50 of video, then practice 10:50

The one worth a second look is soil stability. It pairs directly with the canopy gap data you collected. Large gaps tell you where water and wind get a run at bare ground; aggregate stability tells you whether that ground comes apart when they do. Either number alone understates the risk; together they are the erosion story. The test runs 18 samples at once in a well kit, so the elapsed time is mostly waiting.

It is also the method that would let you answer question 6 on the ecological site worksheet properly, rather than by inference.

Blank datasheets and the full protocol for every method are at https://www.blm.gov/aim/training. If you want to run one of these on your own time, ask your instructor — the plot stakes stay in the ground.

6.11 Analysis — optional

You do not have to do this, and none of it is graded. Today was about running the protocols. But you collected real data, and if you want to see what it says, the script is there.

Open FieldMethods_LPI.R. It calculates, from your 150 points:

\[\%\ \text{foliar cover} = \frac{\text{points with any plant in the top layer}}{\text{total pin drops}} \times 100\]

\[\%\ \text{bare ground} = \frac{\text{points with top layer} = \texttt{N},\ \text{no lower layers, and soil surface} = \texttt{S}}{\text{total pin drops}} \times 100\]

\[\%\ \text{basal cover} = \frac{\text{points with a species code in the soil surface column}}{\text{total pin drops}} \times 100\]

\[\%\ \text{composition of species A} = \frac{\text{points where A occurs in any layer}}{\text{points with any rooted vegetation}} \times 100\]

Two things to notice before you run it.

Foliar cover and basal cover are different numbers and they answer different questions. Foliar cover is how much of the ground is shaded from above — it governs interception of rain, soil temperature, and how much light reaches a seedling. Basal cover is how much ground the plants actually occupy at the soil surface — it is far less variable between seasons and is what erosion models care about. A grassland can lose most of its foliar cover in a dry August and lose almost none of its basal cover.

Percentages of different things do not add to 100. Foliar cover, basal cover and bare ground are all computed over the same 150 points but count different events. If your numbers sum to 130, you have not made an arithmetic mistake.

6.12 Assignment

Most of what you turn in is the raw record. That is deliberate: a field crew is judged on whether its datasheets are usable, not on whether it did the arithmetic.

1. Your datasheets, complete and legible, for every method you ran:

Sheet What makes it complete
Plot characterization Coordinates, elevation, and the full site description — slope, aspect, both slope shapes, landform, hillslope position, surface observations — plus all three bearings and your gap vegetation rule
Photo point log Three rows, three photographs attached, board readable in each
Line-point intercept All 150 points
Canopy gap All three transects
Unknown plant log One row per placeholder code, with location notes and photo numbers
Ecological site worksheet Part A, the map unit check, and all of Part B

A datasheet with blanks in it is not finished. If a cell is genuinely empty, write why.

2. Your calibration result — the spread among observers for each indicator, whether you met the 10-point standard, and for whichever indicator was worst, your best explanation of what caused the disagreement.

3. One paragraph — the method-selection question. This is the part that matters.

You ran three methods today, on one plot, and there are seven more in the AIM core set you did not run. In a few weeks you will design your own sampling scheme at Sinclair Wash. Pick the method you would build that study around, name the question it answers, and say what it will fail to tell you — then name one method you did not run today that you would add to cover the gap.

Answer it from what happened to you today — how long each method took, where your group disagreed, what you could see standing on the plot that none of the three methods wrote down, and what the ecological site description told you that your own numbers could not — not from the descriptions in this chapter. The honest version of this paragraph is worth more than a correct one.

One thing to carry forward. Your calibration numbers say how much two people disagree about the same ground. Any change you later claim to detect — between years, between treatments, between sites — has to be bigger than that disagreement before it means anything. A number with no error estimate attached cannot be compared to anything, and a great deal of monitoring money is spent on data that turns out not to be able to answer the question it was collected for.

6.13 Sources

BLM Assessment, Inventory and Monitoring (AIM) training materials — the core-method videos, the manual and blank datasheets: https://www.blm.gov/aim/training

Herrick, J.E., J.W. Van Zee, S.E. McCord, E.M. Courtright, J.W. Karl, and L.M. Burkett. Monitoring Manual for Grassland, Shrubland, and Savanna Ecosystems, 2nd ed., Volume I: Core Methods. USDA-ARS Jornada Experimental Range, Las Cruces, New Mexico.

A note on these sources: confirm the edition year on the printed title page before citing. The 2nd edition is widely cited as 2017; the PDF linked above is a February 2020 revision of it. The AIM training videos are unlisted Vimeo videos published by DOI-BLM Media Services; the links here work for anyone with them, but if one stops resolving, the training page above is the stable route to all of them.