Feb 27, 2023

Public workspaceTrinity College Botanic Garden long-term monitoring program V.1

DOI
dx.doi.org/10.17504/protocols.io.dm6gpjdedgzp/v1
  • Midori Yajima1,2,
  • Michelle Murray1,2,
  • Jennifer McElwain1,2,
  • Stephen Waldren1,2
  • 1Trinity College Botanic Garden;
  • 2Trinity College Dublin
Midori Yajima
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DOI: dx.doi.org/10.17504/protocols.io.dm6gpjdedgzp/v1
Protocol Citation: Midori Yajima, Michelle Murray, Jennifer McElwain, Stephen Waldren 2023. Trinity College Botanic Garden long-term monitoring program . protocols.io https://dx.doi.org/10.17504/protocols.io.dm6gpjdedgzp/v1
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License,  which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: In development
We are still developing and optimizing this protocol
Created: December 21, 2022
Last Modified: February 27, 2023
Protocol Integer ID: 74313
Keywords: Long-term, monitoring, plant, ecology, stomatal conductance, pollution, PM10, PM2.5, trees, climate change, botanic garden
Funders Acknowledgements:
Sapienza University Postgraduate Scholarship
Grant ID: Decreto Rettorale n. 992/2021 dell’8/04/2021
TERRAFORM ERC Advanced Grant
Grant ID: n. 101020824
Beate Schuler Fund
Disclaimer
The protocol for measuring stomatal conductance, and water use efficiency in the field has been adapted from

Murray M, Soh WK, Yiotis C, Batke S, Parnell AC, Spicer RA, Lawson T, Caballero R, Wright IJ, Purcell C and McElwain JC (2019). Convergence in Maximum Stomatal Conductance of C3Woody Angiosperms in Natural Ecosystems Across Bioclimatic Zones. Front. Plant Sci.10:558. doi: 10.3389/fpls.2019.00558

Soh WK, Yiotis C, Murray M, Parnell A, Wright IJ, Spicer RA, Lawson T, Caballero R, McElwain JC (2019). Rising CO2 drives divergence in water use efficiency of evergreen and deciduous plants. Sci. Adv. 5, eaax7906

The protocol for quantifying PM interception has been adapted from
Baldacchini C, Castanheiro A, Maghakyan N, Sgrigna G, Verhelst J, Alonso R, Amorim JH., Bellan P, Ðunisijević BD, et al. (2017) How does the amount and composition of PM deposited on Platanus acerifolia leaves change across different cities in Europe? Environmental science and technology / American Chemical Society - ISSN 0013-936X - 51:3, p. 1147-1156

Abstract
Botanic gardens hold large, documented, and accessible collections of living plants. These represent unique subsets of taxa from different biogeographical regions growing under common environmental conditions, connecting people to global plant research and conservation efforts while offering a place beneficial for human health and wellbeing. Despite Botanic Gardens being an ideal setting for climate change research, their potential for comparative, long-term studies and outreach in the field is still underutilised. As part of its ten year strategy, Trinity College Botanic Garden (TCBG) aims to tap this potential and establish a programme for long-term (>30 years) monitoring of key physiological performances in its living woody plant collection. The programme will also assess particulate pollution (PM10 and PM2.5) interception by the same trees, pairing climate change and urban green research. Importantly, the project will include the design of a transferable protocol, produce vouchered herbarium specimens as a future historical archive and as a pedagogical tool, and support the garden outreach strategy, so as to nurture its link with both Trinity College Dublin and local communities, ensuring the garden’s legacy into the future.
Guidelines
These are the guidelines for the monitoring currently in place in TCBG. The trees that are being monitored to date are listed here. The code used for data manipulation and herbarium label making in previous rounds of monitoring can be found on GitHub (link to come).

The stomatal conductance (gs), leaf area index (LAI), elemental analysis/ water use efficiency (WUE), particulate matter analysis, herbarium specimens making have to be performed at the end of the growing season, which in Ireland corresponds from July, to not later than mid-August.

The data management plan can be found at DMPonline (ID 103451)
Data generated in previous years can be found on Dryad (link to come)
Materials
---------------------------------------------------------------------------------------------------------------
Key: Number of items - where they are kept [What they are used for]
---------------------------------------------------------------------------------------------------------------

  • 1 SC-1 Porometer - TCD Paleobotany lab [Porometry]
  • 1 Thermohygrometer - TCD Paleobotany lab [Porometry]
  • 1 Ceptometer - TCD Paleobotany lab [Porometry]
  • 1 GPS, GARMIN eTrex10 - TCD Paleobotany lab [Porometry, Herbarium]
  • 63 (21 trees x 3 leaves) Leaf tags - Any lightweight ribbon [Porometry]
  • 2 Plant presses, newspapers, cardboards - TCD Botany Dept teaching supplies [Elemental analysis/ Water Use Efficiency, Particulate matter analysis, Herbarium]
  • 189 Leaf tags for pressed plants - TCD Botany Dept [Elemental analysis/ Water Use Efficiency, Particulate matter analysis, Herbarium]
  • 126 Envelopes for preserving leaves - TCD palaeoecology lab [Elemental analysis/ Water Use Efficiency, Particulate matter analysis]
  • 100 (depending on dimension) Lint-free tissues [Particulate matter analysis]
  • 1 Single edged blade [Particulate matter analysis]
  • 63 SEM Stubs [Particulate matter analysis]
  • 63 Conductive tabs [Particulate matter analysis]
  • 1 Carbon paint [Particulate matter analysis]
  • Herbarium materials (sheets, stitching material, glue) [Herbarium]
  • Herbarium printed labels [Herbarium]
Stomatal conductance
Stomatal conductance
When
End of the growing season (July, not later than mid-August)
Leaf selection

1.1.1 Select 3 leaves per tree

Note
Each leaf has to be:
  • Fully expanded (the developmental stage at which many leaf traits are relatively stable)
  • Sun-exposed, or exposed to sun flecks
  • Healthy, pest- and pathogen-free
  • Outermost reachable leaves for tall trees
  • Dry and preferably flat - porometer has to be horizontal



1.1.2 Per each leaf
  • Tag leaf with a ribbon a code that will work as leaf ID (e.g. the first leaf measured on Arbutus unedo will be AU01)
  • Make note of leaf orientation (the N/S/E/W direction the leaf is facing)
  • Make note of GPS position of the tree (if new tree from the ones already used)

Porometry

1.2.1 Take 1 porometry reading x each leaf x each tree
  • Once per day between 08:30 h and 14:00h
  • Over 3-5 consecutive days. Repeat approximately at the same time every day (to account the natural day-to-day variability in gs for each species under ambient conditions) following same order of trees and leaves measured
Note
Equipment-related:
  • Calibrate every day or if temp changes of ca 15 degrees
  • Measure at the prevailing microclimate condition of that day
  • Measure in automatic mode - measures continuously and derive best estimate for leaf

Leaves-related:
  • Measure at the interveinal areolae at mid-lamina of the abaxial surface. In the case of compound leaves, measure the terminal leaflet; for larger leaves clamp the sensor as far onto the leaf as possible, taking care to avoid damage to the leaf margin
  • Measure leaves at the the same position in the crown (e.g. base level, arm reach), to normalise for WUE and gs changes with tree height
  • Measure always at the same position (e.g. right blade of leaf that face me)

During the measuremets:
  • Minimise interfering with the leaves (look away or wear mask to avoid changing CO2 conditions locally, move the leaf as little as possible
  • Name the reading with leaf ID

1.2.2 At each tree measure and take note also of
  • Temp (°C), RH% at each tree with thermo-hygrometer
  • Solar radiation at each leaf with ceptometer's small sensor
  • Any other condition met while taking the measurements (e.g. sudden wind, moving the leaves too much)
Download results

  • Convert in .csv format
  • Clean data (variable names lowercase, no spaces, keep only relevant info, add meatadata taken in the field i.e. temp, rh, notes). Final dataset should look like "Expected results" below


Expected result


ABCDEFGHIJKLMNOPQRS
specimen_specieleaf_idlatlondatetimegstempsensor_serial_numbersensor_cal_numberleaf_sensor_rhfilter_sensor_rhenvironment_rhenvironment_templeaf_orientationleaf_parleaf_sun_exposureleaf_appearancenotes
Magnolia grandifloraMG0153.3125-6.2596666672022-08-129:18:03172.522.1LPS2225230360445.1217021W40Full sunHealthyMoved leaf horizontally,PAR retaken at 10:15 due to technical difficulties. The conditions had changed to shady during this time lapse.
Magnolia grandifloraMG0153.3125-6.2596666672022-08-139:06:07195.522.2LPS2225220360447.121.870.522.7W45Sun flecksHealthyMoved leaf horizontally



Download metadata

  • Take weather data from the garden MET station, readings from the 30 days before the monitoring (monitoring days included)
  • Clean data. Final dataset should look like "Expected result" below


Expected result

ABCDEFGHIJK
doydatetimerhtemppressurenet_radparwind_speedwind_directionprecipitation
1522022-06-011:00:0094.29.291012NA0.0320.079233.4NA
1522022-06-011:30:0094.79.261012NA0.0230.129176.1NA



Leaf Area Index
Leaf Area Index
When

During porometry, after taking stomatal conductance readings. It may not be possible to take LAI for each tree, depending on their local conditions (e.g. for trees that are shaded by other trees)
LAI readings

TBD
Elemental analysis/ Water Use Efficiency
Elemental analysis/ Water Use Efficiency
When
Immediately after the last day of porometry

Collection needs to be after a period of 5 to 10 days of no rain and low winds, to avoid particulates to being washed away
Leaf selection

Same 3 leaves x tree used for porometry
Leaf collection and dehydration

2.2.1 Pick leaves and tag them with the same code used previously
2.2.2 Press in plant press for approx. 2 weeks, changing newspapers regularly or Oven dry at 50-60 °C for 2 days
2.2.3 Sort dried leaves in separate envelopes reporting leaf ID
Elemental analysis in the lab

TBD
Water Use Efficiency

TBD

Particulate Matter analysis
Particulate Matter analysis
When
Collection must be immediately after the last day of porometry, or soon after. It has to be after a period of 5 to 10 days of no rain and low winds, to avoid particulates to be washed away
Leaf selection

  • 3 leaves x tree, choosing leaves close to the ones used for porometry/ elemental analysis (same branch, similar dimension and orientation if possible)

Note
Each leaf has to be
  • Healthy, pest- and pathogen-free
  • Collected at basal exterior canopy

Leaf collection and dehydration

3.2.1 Pick leaves and tag them with the same code used previously + progressive numbering (i.e. sample ID that will be used in Scanning Electron Microscopy (SEM) later)
3.2.2 Wrap leaves in lint-free tissue to avoid contamination from paper fibers or other sources while pressing
3.2.3 Press in plant press for approx. 2 weeks, changing newspapers regularly or leave the press in oven at 50-60 °C for 2 days. Leaves need to be pressed so that can be imaged correctly under the SEM later
3.2.4 Sort dried leaves in separate envelopes reporting leaf ID and sample ID, keeping them wrapped in lint free tissue
Samples preparation in the Centre for Microscopy and Analysis lab

3.3.1 Cut 1 sample of 0.5 x 0.5 cm ca from each leaf with single edged blade

Note
Each sample has to be
  • Cut from the central portion of the leaf, close to midvein, halfway from the bottom to the top of the leaves, right blade (positioning the leaf tip downwards) as in the section where porometry was done on the other leaves

3.3.2 Prepare SEM stubs with conductive tabs
3.3.3 Using tweezers, mount 1 sample x stub and press firmly with lint-free tissue
3.3.4 Paint the edges of the sample with carbon paint (pure graphene) to prevent curling while in the SEM
3.3.5 Mark the bottom of the stub with the sample ID


Note
Tip
Keep track of leaf ID, corresponding sample ID, and any note on samples throughout the analyses (e.g. sample charging under the SEM, sample damaged)

3.3.6 Leave samples mounted on the stubs to dry out for 1-2 days
3.3.7 Carbon coat samples at 20 nm thickness
Analyses using TESCAN MIRA3 TIGER SEM

3.4.1 Set microscope settings

Note
On the TIGER set
  • HV 15
  • speed 3
  • WD 15

On the AZtec software, set Energy Dispersive X-Ray Spectroscopy (EDS) with
  • Resolution 512
  • Acquisition time fixed duration, frame count 1
  • Number of channels 1024
  • Process time 2
  • Pixel dwell time 500 microsec



3.4.2 Map samples
For each sample, pick 3 sub-sample areas at random at low magnification and increase resolution at 800 X

For each sub-sample
  • Take micrographs using Secondary Electron light (SE) (optional)
  • Map samples with Energy Dispersive X-Ray Spectroscopy (EDS) using Back Scattered Electron light. Map will be performed using the integrated AZtec software
  • Label sub-samples as A, B, C (so e.g. sample 1, will have 1A, 1B, 1C)

3.4.3 Save project in double copy
Analyses using offline computer

3.5.1 Download saved project and open with AZtec
3.5.2 Set feature analysis settings

Note
On "Detect feature settings" window
  • Image scan size
  • Dwell time 25 microsec
  • Input signal BSE
  • Number of frames 1
  • Smallest feature size 1 pixel (2.58 micron from settings, 0.38 micron for current image)
  • Normalise results

On "detection refinement" window
  • gray levels filter: smooth filer, gaussian smooth filter
  • Binary image filter: erosion filter, close filter (regulate intensity base on the image), hole fill

On "Acquire site settings" window
  • classification scheme: Midori (TCBG monitoring)
  • classification filter pm10, pm2.5
  • quant setup: normalise results, element list: fixed list and current spectrum

For each sub-sample

3.5.2 Select PM on the sample surface by tresholding image to select features by their appearance (PM will be distinguishable from the background, can be selected highlighting lighter part of the spectrum for heavy metals, darker for carbon-based particulates)
3.5.3 Adjust filter settings to better select PM (e.g. use erosion filer if feature is bigger than actual PM when observed in the background). If filter settings still highlight features not corresponding to any actual PM, manually delete the features that do not match
3.5.4 Extract data on highlighted features, showing morphological and chemical information as in "Expected result" below
3.5.5 Copy-paste data on spreadsheet


Download results

  • Convert in .csv format
  • Clean data. See "Expected results" below

Expected result

ABCDEFGHIJKLMNOPQRST
specimen_specieleaf_idsample_idnoteslatlonpm_idpm_classpm_areapm_ecdpm_perimeterpm_shapepm_countonamgalsikca
Magnolia grandifloraMG011ANA53.3125-6.2596666671PM2.50.34147224690.6593754382.339323571.275308684NANANANANANANANA
Magnolia grandifloraMG011ANA53.3125-6.2596666676PM2.50.45529632920.76138117322.1841040730.8337630498NANANANANANANANA


Herbarium sheets
Herbarium sheets
When
Collection must happen immediately after the last day of porometry, or soon after. It must be in dry weather to avoid molds in specimens
Selection of the specimen

4.1.1 Select and pick 1 specimen x tree for the actual herbarium sheet + 2/3 extra leaves (or leaflets) to preserve for any future analysis

Note
  • Each specimen has to include any flower or fruit found, if possible. Specimens can be branches or separate leaflets in case of trees that whose growth could be damaged by annual cuttings (e.g. palm tree)
  • Close to the leaves used for porometry/ elemental analysis and PM analysis
  • Healthy looking



4.1.2 Label each specimen annotating species name
4.1.3 Separately, make note of
  • Species name
  • Specimen ID, as "TCBG sample-number" e.g. "TBCG1". Each specimen ID must be unique, so latest specimens have to continue the numbering of the herbarium sheets made in previous years
  • Date
  • Collectors
  • Coordinates (can be taken from previous specimens)
  • Location in the garden (e.g. walled garden, west arboretum etc. can be taken from previous specimens)
  • Notes, including branch height when on the tree, ecological notes

4.1.3 Place specimen in plastic bag for transport (ideally one bag per specimen)
Preparation of specimens

4.2.1 Dehydrate plants in plant press within 12 hours from collection. Store the plant press in a dry place for approx. 2 weeks, changing newspapers regularly

Note
For each specimen
  • Arrange it as flat as possible
  • Arrange any flower of fruit in a way that they do not overlap
  • Arrange so that specimen shows both sides of leaves e.g. turning one leaf to show the back
  • If the specimen is too big for the press, bend it

4.2.2 Once ready, drop the press with all the specimen in the Herbarium freezer inside the Botany Department for at least 72 hours, to kill any residual mold that could contaminate the specimen that are already in the Herbarium.

Making of herbarium labels

Print labels with information noted in the field

Note
Tip

Copy information in a spreadsheet as it follows:

ABCDEFGHIJKLMNOPQRSTUVWXYZAAABACADAEAFAGAHAIAJAKALAMAN
GLOBAL_UNIQUE_IDENTIFIER HERBARIUM TITLE COLLECTOR ADDITIONAL_COLLECTOR COLLECTOR_NUMBER DATE_COLLECTED LOCAL_NAME FAMILY GENUS SPECIES AUTHOR_OF_SPECIES INFRASPECIFIC_RANK INFRASPECIFIC_EPITHET AUTHOR_OF_INFRASPECIFIC_RANK COUNTRY STATE_PROVINCE COUNTY LOCALITY IMAGE_URL RELATED_INFORMATION LAT_DEGREE LAT_MINUTE LAT_SECOND LAT_FLAG LON_DEGREE LON_MINUTE LON_SECOND LON_FLAG ELEVATION ATTRIBUTES REMARKS GEOREFERENCE_SOURCES PROJECT IDENTIFIED_BY DATE_IDENTIFIED TYPE_STATUS PROCESSED_BY DATE_LASTMODIFIED SPECIMEN_LOCATION
Trinity College Botanic Garden long term monitoring program Midori Yajima, Anne Dubearnes TCBG1 23-Aug-22 Azara microphylla Ireland Dublin Trinity College Botanic Garden, entrance 53 18 45.2 N 6 15 35.4 W Branch heigh 225 cm, cultivated in planted beds, surrounded by gravel and asphalt, partly shaded by building
Trinity College Botanic Garden long term monitoring program Midori Yajima, Anne Dubearnes TCBG2 23-Aug-22 Magnolia grandiflora Ireland Dublin Trinity College Botanic Garden, walled garden 53 18 45 N 6 15 34.8 W Branch height 111 cm, cultivated, partly shaded by wall

And use the herblabel R package (using "KUN") to print labels instead of creating them one by one. Final result should look like



Making of herbarium sheets

4.3.1 Mount specimens on herbarium sheets, making sure to
  • Stitching them instead of using glue. Use glue only if necessary (e.g. specimen is too heavy, there are too many leaves) so that each specimen can be removed and used for future analyses
  • Storing the extra leaves in a separate paper bag attached to the sheet
  • Printing and attaching herbarium labels reporting the information noted on the field

4.3.2 Store herbarium sheet in dedicated box in Trinity Herbarium

Expected result



Upload data on Dryad
Upload data on Dryad
TBD