npx claudepluginhub pjt222/agent-almanacThis skill uses the workspace's default tool permissions.
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Provides reasoning strategies for ecology and biodiversity research: species identification via GBIF/WoRMS, invasive species impacts, pollinator ecology, population dynamics, trophic interactions. For any ecology question.
Conducts statistical hypothesis tests (t-test, ANOVA, chi-square), regression, correlation, Bayesian analyses, power analysis, assumption checks, and APA reporting for academic research data.
Share bugs, ideas, or general feedback.
Design and execute systematic insect population surveys with standardized sampling, diversity analysis, and quantitative reporting.
collect-preserve-specimens)Define what you want to learn, where you will sample, and how much effort you will invest. Survey design determines the statistical power and ecological validity of everything that follows.
Survey Design Framework:
+--------------------+------------------------------------------+
| Component | Define Before Fieldwork |
+--------------------+------------------------------------------+
| Objectives | What ecological question does this |
| | survey answer? Examples: |
| | - "What is the species richness of |
| | ground beetles at Site A?" |
| | - "How does pollinator diversity differ |
| | between restored and unrestored |
| | meadows?" |
| | - "Has moth diversity changed since the |
| | 2020 baseline survey?" |
+--------------------+------------------------------------------+
| Target taxa | All insects? A specific order (e.g., |
| | Coleoptera)? A functional group (e.g., |
| | pollinators)? Narrower focus = more |
| | reliable identification and analysis. |
+--------------------+------------------------------------------+
| Study site(s) | Geographic boundaries of the survey |
| | area. Map the site. Identify distinct |
| | habitat types within the site. |
+--------------------+------------------------------------------+
| Sampling design | Random, stratified random, or systematic |
| | placement of sampling points/transects. |
| | Stratify by habitat type if the site |
| | is heterogeneous. |
+--------------------+------------------------------------------+
| Replication | Minimum 3 replicates per habitat type |
| | or treatment. More replicates increase |
| | statistical power but require more |
| | effort. For species accumulation curves |
| | to stabilize, 5-10 replicates per |
| | habitat are often needed. |
+--------------------+------------------------------------------+
| Temporal scope | Single survey (snapshot) or repeated |
| | surveys (monitoring)? If monitoring, |
| | define frequency (monthly, seasonal, |
| | annual). Match frequency to the |
| | phenology of target taxa. |
+--------------------+------------------------------------------+
| Effort | Define standardized effort per sample: |
| | "20 sweep net sweeps per transect" or |
| | "pitfall traps open for 72 hours" or |
| | "light trap operated 20:00-02:00." |
| | Consistent effort across samples is |
| | essential for comparison. |
+--------------------+------------------------------------------+
Expected: A written survey protocol specifying objectives, target taxa, site description, sampling design (random/stratified/systematic), number of replicates, temporal scope, and standardized effort per sample.
On failure: If the survey objectives are vague ("see what insects are here"), refine them into a testable question before proceeding. A survey without clear objectives cannot be properly designed, and the resulting data may not answer any question well. If site access is restricted, modify the design to work within constraints rather than reducing replication below 3 per comparison group.
Select methods appropriate to the target taxa, habitat, and survey objectives. Different methods have different capture biases.
Method Selection by Target Taxa:
+--------------------+------------------------------------------+
| Target | Recommended Methods |
+--------------------+------------------------------------------+
| Ground-dwelling | Pitfall traps (primary), hand collection |
| insects (Carabidae,| under rocks/logs, bark traps, Berlese |
| Staphylinidae, | funnels for soil fauna |
| ants, crickets) | |
+--------------------+------------------------------------------+
| Vegetation- | Sweep netting (primary), beating trays, |
| dwelling insects | vacuum sampling (D-vac or G-vac), |
| (Hemiptera, | branch clipping for canopy |
| Chrysomelidae, | |
| Orthoptera) | |
+--------------------+------------------------------------------+
| Flying insects | Malaise traps (Diptera, Hymenoptera), |
| (general) | flight intercept traps, window traps |
+--------------------+------------------------------------------+
| Pollinators | Pan traps (yellow, white, blue bowls), |
| (bees, hoverflies) | transect counts (visual observation), |
| | sweep netting on floral resources |
+--------------------+------------------------------------------+
| Nocturnal flying | Light traps (mercury vapor or UV), |
| insects (moths, | sugar baiting (for moths), light sheets |
| many beetles) | |
+--------------------+------------------------------------------+
| Aquatic insects | Kick-net sampling (streams), D-frame |
| (Ephemeroptera, | net sampling, Surber sampler |
| Plecoptera, | (quantitative), artificial substrates |
| Trichoptera) | |
+--------------------+------------------------------------------+
| Butterflies | Pollard walk transect counts (standard |
| | visual survey method for butterflies), |
| | timed counts per habitat patch |
+--------------------+------------------------------------------+
Standardization Rules:
- Use the same method, equipment, and effort at every sample point
- Record start and end times for every sampling event
- If using traps, record deployment and retrieval times exactly
- Weather-dependent methods (sweep netting, transect walks) should
only run under acceptable conditions (no heavy rain, temperature
above activity threshold for target taxa)
Expected: One or more sampling methods selected and justified for the target taxa, with effort standardized across all replicates and sample points.
On failure: If a single method produces too few specimens for meaningful analysis, consider adding a complementary method. However, data from different methods should be analyzed separately — do not pool pitfall trap data with sweep net data in the same diversity analysis, as they sample different portions of the community with different capture probabilities.
Deploy sampling equipment, conduct collections, and record all metadata needed for analysis.
Field Execution Checklist:
Before each sampling event:
- [ ] Record date, time, GPS coordinates of sample point
- [ ] Record environmental covariates (temperature, humidity, wind,
cloud cover) — see observe-insect-behavior for details
- [ ] Verify equipment is clean and functional
- [ ] Label collection containers with site, date, replicate number
During sampling:
- [ ] Follow the standardized effort exactly (same number of sweeps,
same trap duration, same transect length)
- [ ] Keep specimens from each sample point in separate, labeled
containers — never mix samples
- [ ] Record any deviations from protocol (e.g., "trap knocked over
by animal, collected after 48h instead of 72h")
- [ ] Note any unusual observations (mass emergence, swarming events,
absence of expected taxa)
After each sampling event:
- [ ] Verify all containers are labeled
- [ ] Record end time and any changes in weather during sampling
- [ ] Preserve specimens promptly (kill jar or ethanol) — do not leave
live specimens in collection bags for extended periods
- [ ] Store preserved specimens in a cool location until processing
Expected: All planned samples collected with standardized effort, each sample in a separately labeled container, with full metadata recorded for every sampling event.
On failure: If a sample is compromised (trap disturbed, heavy rain during sweep netting), record the issue and either discard the sample or note it as a potential outlier. It is better to have one fewer replicate than to include compromised data. If weather prevents sampling on a planned date, reschedule to the nearest suitable day — do not attempt to sample under inappropriate conditions.
Sort and identify all collected specimens to the lowest practical taxonomic level. This is typically the most time-consuming step.
Identification Workflow:
1. SORT to order — separate beetles from flies from wasps etc.
Use the dichotomous key in the identify-insect skill.
2. SORT to morphospecies within each order — group visually
identical specimens together. Assign a temporary code
(e.g., "Coleoptera sp. 01", "Diptera sp. 14").
3. IDENTIFY morphospecies to the lowest level achievable:
- Family (achievable for most insects with general keys)
- Genus (achievable for well-studied groups with regional keys)
- Species (achievable for well-known groups; may require
specialist confirmation for others)
4. VERIFY identifications by:
- Cross-checking multiple specimens of each morphospecies
- Comparing against reference collections
- Sending representative specimens to taxonomic specialists
for difficult groups
5. RECORD in a species-by-sample matrix:
Rows = species (or morphospecies)
Columns = sample points
Cells = abundance (count of individuals)
Example:
Site A Site A Site B Site B
Rep 1 Rep 2 Rep 1 Rep 2
Carabidae sp.01 12 8 3 5
Carabidae sp.02 0 1 7 9
Staphyl. sp.01 3 4 2 1
...
Taxonomic Resolution:
- For diversity comparisons, all specimens must be identified to
the SAME taxonomic level. Do not mix species-level IDs with
order-level IDs in the same analysis.
- Morphospecies sorting is acceptable and widely used in ecological
surveys, especially in tropical regions or poorly known taxa.
- Keep voucher specimens for every morphospecies (see
collect-preserve-specimens) so identifications can be verified later.
Expected: All specimens sorted and identified to at least morphospecies level, recorded in a species-by-sample abundance matrix, with voucher specimens preserved for each morphospecies.
On failure: If certain groups cannot be identified even to morphospecies (e.g., very small Diptera that all look alike), record them as an aggregate taxon (e.g., "Diptera spp. unsorted") and note the limitation. Exclude poorly resolved groups from diversity analyses rather than introducing uncertain identifications. If identification stalls, send specimens to specialists — this is normal and expected for professional surveys.
Convert the species-by-sample abundance matrix into quantitative diversity measures.
Diversity Metrics:
1. SPECIES RICHNESS (S)
The simplest measure: count of distinct species (or morphospecies)
in a sample.
Example: 23 morphospecies in Site A pitfall traps.
2. SHANNON-WIENER DIVERSITY INDEX (H')
Accounts for both richness and evenness.
H' = - SUM( pi * ln(pi) )
where pi = proportion of total individuals belonging to species i
(pi = ni / N, where ni = count of species i, N = total individuals)
Interpretation:
- Typical range: 1.5 to 3.5 for most ecological communities
- Higher values = more diverse (more species, more evenly distributed)
- H' = 0 when only one species is present
- Maximum H' = ln(S) when all species are equally abundant
3. SIMPSON DIVERSITY INDEX (1 - D)
Probability that two randomly chosen individuals belong to different
species.
D = SUM( pi^2 )
Simpson diversity = 1 - D
Interpretation:
- Range: 0 to 1
- Higher values = more diverse
- Less sensitive to rare species than Shannon; dominated by
common species
- 1 - D = 0.9 means a 90% chance two random individuals are
different species
4. EVENNESS (J')
How equally individuals are distributed among species.
J' = H' / ln(S)
Interpretation:
- Range: 0 to 1
- J' = 1 means all species equally abundant
- J' close to 0 means one or few species dominate
5. RAREFACTION
Compares richness between samples with different total abundances
by estimating how many species would be found if all samples had
the same number of individuals.
- Essential when sample sizes differ (they almost always do)
- Plot rarefaction curves: species vs. individuals sampled
- If the curve plateaus, sampling has captured most species
- If the curve is still rising steeply, more sampling is needed
Expected: Species richness, Shannon-Wiener index, Simpson index, and evenness calculated for each sample and each site/treatment. Rarefaction curves plotted to assess sampling completeness.
On failure: If sample sizes are too small for reliable diversity calculation (fewer than 30 individuals per sample), report raw species counts and abundances rather than computed indices. Small samples produce unreliable index values with large confidence intervals. Note the small sample size as a limitation and recommend increased sampling effort for future surveys.
Compare diversity across sites, treatments, or time periods using appropriate statistical methods.
Analysis Approaches:
1. COMPARING TWO OR MORE SITES/TREATMENTS:
- Shannon H' values: use Hutcheson's t-test for pairwise comparison
of Shannon indices, which accounts for differences in sample size
- Species richness: use rarefied richness for fair comparison
- Abundance data: use Mann-Whitney U test (2 groups) or
Kruskal-Wallis test (3+ groups) for non-normal count data
2. MULTIVARIATE COMMUNITY ANALYSIS:
When comparing entire community composition (not just summary indices):
- Bray-Curtis dissimilarity matrix: quantifies compositional
difference between every pair of samples
- NMDS (Non-metric Multidimensional Scaling): ordination that
visualizes community similarity in 2D — samples close together
have similar communities
- PCoA (Principal Coordinates Analysis): alternative ordination
based on distance matrices
- PERMANOVA (permutational ANOVA): tests whether community
composition differs significantly between groups
- SIMPER: identifies which species contribute most to differences
between groups
3. TEMPORAL TRENDS (monitoring data):
- Plot species richness and diversity indices over time
- Use linear regression or generalized linear models to test
for trends
- Account for seasonal variation by comparing same-season samples
across years
4. SPECIES ACCUMULATION CURVES:
- Plot cumulative species against cumulative samples
- Use Chao1 or Chao2 estimators to predict total species richness
(including undetected species)
- If observed richness is far below the Chao estimate, more
sampling is needed
Minimum Reporting:
- Sample sizes (number of individuals and number of samples)
- Diversity indices with confidence intervals or standard errors
- Statistical test used, test statistic, degrees of freedom, p-value
- Effect sizes where applicable
Expected: Statistical comparisons completed with appropriate tests, results reported with test statistics and p-values, and ecological interpretation provided.
On failure: If replication is insufficient for formal statistical testing (fewer than 3 replicates per group), report descriptive statistics (means, ranges) and rarefaction curves without hypothesis tests. Acknowledge the limitation and recommend increased replication for future surveys. Descriptive data from a well-executed survey is more valuable than p-values from an underpowered design.
Compile the survey into a structured report that can inform management decisions, support publication, or serve as a baseline for future monitoring.
Survey Report Structure:
1. SUMMARY
- Survey objectives
- Key findings (total species, dominant taxa, notable records)
- Primary conclusion (1-2 sentences)
2. METHODS
- Study site description (location, habitat, area, map)
- Sampling design and methods
- Sampling effort (number of samples, trap-nights, transect length)
- Identification methods and taxonomic resolution
- Statistical methods
- Survey dates and environmental conditions
3. RESULTS
- Total specimens collected and identified
- Species list with abundances per site/treatment
- Diversity indices table (S, H', 1-D, J' per site/treatment)
- Rarefaction curves
- Statistical comparison results
- Ordination plots (if multivariate analysis performed)
- Notable records (rare species, new records, invasive species)
4. DISCUSSION
- How do results compare to previous surveys or nearby sites?
- What ecological factors explain observed patterns?
- What are the conservation implications?
- What are the limitations of this survey?
5. RECOMMENDATIONS
- Management actions (if applicable)
- Future monitoring schedule
- Suggested improvements to survey design
6. APPENDICES
- Full species list with abundances
- Raw data (species-by-sample matrix)
- Environmental covariate data
- Voucher specimen catalog numbers and repository
- Photographs of notable specimens or habitats
Data Archiving:
- Deposit raw data in an appropriate repository (Dryad, Zenodo, GBIF)
- Deposit voucher specimens in a recognized museum collection
- Archive the survey report with the managing agency or institution
Expected: A complete survey report with methods, results (including species list, diversity indices, statistical tests), discussion, and recommendations. Raw data archived in a repository.
On failure: If the survey is incomplete (e.g., not all specimens identified, insufficient replicates for statistics), produce a preliminary report with what is available and clearly label it as preliminary. Identify the gaps and the timeline for completing them. A preliminary report with honest limitations is more useful than no report at all.
collect-preserve-specimens — collection methods, preservation, and labeling standards for the specimens gathered during surveysidentify-insect — morphological identification procedures for sorting and identifying survey specimensdocument-insect-sighting — photographic documentation protocols that complement physical collectionobserve-insect-behavior — behavioral observation methods for supplementing population data with ecological context