What is scat diet composition analysis?

Scat diet composition analysis is the study of wildlife food habits by examining fecal (scat) samples. Researchers identify and quantify prey or food item remains — such as hair, bones, seeds, and insect fragments — to determine what a species eats and in what proportions.

What is the Frequency of Occurrence (FO%) in scat analysis?

Frequency of Occurrence (FO%) is the percentage of scat samples in which a particular food item appears. It tells you how consistently a prey item is consumed across all samples, regardless of the quantity in each scat.

What is the Index of Relative Importance (IRI)?

The Index of Relative Importance (IRI) combines Frequency of Occurrence and Percentage Occurrence to give a weighted measure of how important a food item is in an animal's diet. IRI = (FO% + %O) × FO%.

How many scat samples are needed for diet analysis?

Most wildlife studies recommend a minimum of 30–50 scat samples per season or study period for reliable diet composition estimates. Larger sample sizes (>100) provide greater statistical confidence, especially for rare prey items.

What is the difference between percentage occurrence and percentage volume in scat analysis?

Percentage Occurrence (%O) reflects how often an item appears relative to all items identified across all scats. Percentage Volume (%V) estimates the actual proportion by weight or volume that each food item contributes. This calculator uses Percentage Occurrence, which is the most widely used method in field ecology.

What is Levins' Niche Breadth in diet studies?

Levins' Niche Breadth (B) measures dietary specialization. It ranges from 1 (complete specialist, eating only one prey type) to the total number of prey categories (complete generalist). The standardized form (B_A) ranges from 0 to 1 for easier comparison across studies.

How do I report scat diet composition results in a research paper?

Report the number of scat samples analyzed, list each food item with its Frequency of Occurrence (FO%), Percentage Occurrence (%O), and IRI. State the Levins' Niche Breadth and Shannon Dietary Diversity. Include a summary table and at least one chart. Cite the analytical method and sampling period.

Can I use this calculator for omnivores and herbivores?

Yes. This scat diet composition calculator works for any species — carnivores, omnivores, and herbivores. You can enter any food categories (prey species, plant parts, fruit types, invertebrate orders) as group names.

What is the minimum number of prey categories needed?

You need at least 2 food categories to compute diet composition meaningfully. However, real wildlife studies typically record 5–20 food categories. The calculator works with 2 to 50+ categories.

How is Shannon Dietary Diversity calculated from scat data?

Shannon Dietary Diversity (H') from scat data is calculated the same way as Shannon-Wiener diversity: H' = −Σ (p_i × ln(p_i)), where p_i is the proportional occurrence of each food item. Higher H' values indicate a more diverse diet.

What software is used for scat diet analysis in research?

Researchers commonly use R (with packages such as vegan and ggplot2), Excel, or custom scripts. This free online Scat Diet Composition Calculator performs all standard metrics — FO%, %O, IRI, Levins' B, Shannon H' — instantly in your browser without any software installation.

What does a high IRI% value mean?

A high IRI% (Index of Relative Importance percentage) means that food item is very important in the animal's diet — it appears frequently across samples AND contributes a large proportion of the total items identified. It is considered the primary prey or food source.

Should I include hair, seeds, and insect parts separately in scat analysis?

Yes. Standard scat analysis protocol requires recording each identifiable prey remain separately. Hair and feathers indicate mammal or bird prey; seed coats indicate frugivory; insect exoskeleton fragments (elytra, legs) indicate insectivory. Each category should be counted separately and entered as a distinct group in this calculator.

Scat Diet Composition Calculator – Free Carnivore Diet Tool

Scat Diet Composition Calculator – Free Online Wildlife Diet Analysis Tool

Data Input

Study Site / Species Name:

Food Item / Prey Group Names (comma-separated):

Occurrence Counts (comma-separated, matching order):

Total Number of Scat Samples Analyzed:

Enter the total scat samples collected (N). Each count above = number of scats in which that item appeared.

Upload CSV or Excel file (.csv, .txt, .xlsx, .xls):

Supports .csv, .txt, .xlsx, .xls. Headers detected automatically. Select one column for Food Item / Prey Group Names and one for Occurrence Counts.

Enter food items and their occurrence counts directly in the table below.

#	Food Item / Prey Group	Occurrence Count	Remove

Total Scats (N):

Analysis Summary

📐 Formulas Used in This Analysis

FO% = (n_i / N) × 100

%O = (FO%_i / Σ FO%) × 100

IRI = (%O_i + FO%_i) × FO%_i

IRI% = (IRI_i / Σ IRI) × 100

B = 1 / Σ p_i² (Levins' Niche Breadth)

B_A = (B − 1) / (n − 1) (Standardized)

H' = −Σ (p_i × ln p_i) (Shannon Dietary Diversity)

n_i = number of scats containing food item i
N = total number of scat samples analyzed
FO% = Frequency of Occurrence percentage
%O = Percentage Occurrence (relative to all FO% values)
IRI = Index of Relative Importance (Pinkas et al., 1971)
p_i = %O_i / 100 (proportional occurrence)
n = total number of food categories
B_A = Standardized Levins' Niche Breadth (0–1)
H' = Shannon Dietary Diversity Index (nats)

Diet Composition Results Table

Rank	Food Item / Prey	Count (n_i)	FO%	%O	IRI	IRI%	IRI Contribution

Visualization Plots

🥧 Diet Composition (IRI%)

📊 Frequency of Occurrence (%)

📈 IRI by Food Item

🔵 Percentage Occurrence (%O)

Detailed Interpretation of Results

🔍 1. Overall Diet Summary & Dietary Breadth

🥩 2. Primary & Secondary Prey Items (IRI Analysis)

📉 3. Frequency of Occurrence Interpretation

🌿 4. Ecological Significance & Dietary Strategy

⚠️ 5. Sampling Adequacy & Methodological Caveats

How to Write Your Results in Research

📰 Ecology Journal

Run the analysis above to generate publication text.

Journal writing conventions

Use passive voice. Report N, number of food items, IRI% for top items, FO% range, and niche breadth B_A. Cite Pinkas et al. (1971) for IRI and Levins (1968) for B. Include a results table as a separate supplementary item. Round to two decimal places.

📚 Thesis / Dissertation

Run the analysis above to generate thesis text.

Thesis writing conventions

Write in a formal tone with full methodological justification. Include subsections on data collection, prey identification protocols, and analytical methods. Report all metrics with 95% CI where available. Discuss sampling adequacy using species accumulation curves or rarefaction.

📣 Plain-Language / Policy Brief

Run the analysis above to generate policy text.

Policy writing conventions

Avoid technical jargon. Use bullet points. Emphasize conservation implications — prey availability, human-wildlife conflict potential, and habitat management actions. Translate FO% and IRI% into plain percentages ("this species eats X about Y% of the time").

🎤 Conference Abstract

Run the analysis above to generate abstract text.

Abstract writing conventions

Limit to 250–300 words. State objective, methods (N, species, region), 3–4 key numerical results, and the main conclusion. Include keywords line. Follow the conference template for structured vs. unstructured abstract format.

📡 Monitoring / Long-Term Ecology

Run the analysis above to generate monitoring text.

Monitoring report conventions

Include seasonal or annual comparisons if data span multiple periods. Highlight changes in primary prey FO% or IRI% over time. Use tables for cross-year comparison. Follow the standardized reporting template of your monitoring program (e.g., LTER, WPA annual report format).

🪧 Research Poster Panel

Scat Diet Composition Analysis

Wildlife Ecology Study — StatsUnlock.com

Introduction

Run the analysis above to generate poster content.

Methods

___

Key Results

Discussion

___

Conclusions

___

StatsUnlock.com | Free Wildlife Analysis Tools Methodology: Pinkas et al. (1971) IRI; Levins (1968) Niche Breadth

📐 Poster Design Specifications

Recommended sizes: A0 (841×1189mm), A1 (594×841mm), or 48×36 inch landscape.

Typography: Title: 72–96pt bold. Section headers: 36–48pt. Body: 24–28pt. Caption: 18–20pt.

Color palette: Deep forest green (#1b5e20) for headers; soft mint (#e8f5e9) for backgrounds; amber (#e65100) for highlights; white for main body panels.

Software: Adobe Illustrator, Canva, Microsoft PowerPoint (portrait, A0 custom size), or InkScape.

Print resolution: 300 DPI minimum for all figures. Export charts from this tool at 2× resolution for print quality.

Charts: Include all four plots from the Visualization section. Place pie chart (IRI%) centrally; surround with FO% bar chart and IRI bar chart. Captions required for all figures.

🔬 Technical Notes & Methodological Assumptions

IRI Formula: This calculator uses the Pinkas et al. (1971) formulation: IRI = (%O + FO%) × FO%. Some publications use volume (%V) instead of or in addition to %O. When %V data are available, replace %O with %V for a more complete IRI estimate.

Frequency of Occurrence: FO% is the most commonly used and least biased estimator of prey importance in scat analysis. It does not require volume estimation, reducing observer bias from differential digestion rates of hard prey parts.

Bias from Differential Digestibility: Hard-bodied prey (insects, reptiles) and items with indigestible remains (hair, seeds) may be over-represented relative to soft-bodied prey (fish, fruit flesh). Correction factors (e.g., Laundré 1981) should be applied where published digestion coefficients are available.

Levins' Niche Breadth: B is sensitive to sample size. B_A (standardized) corrects for the number of categories and is more suitable for comparisons across studies or seasons.

Shannon Dietary Diversity (H'): Calculated using natural logarithm (nats). Some studies use log₂ (bits) or log₁₀. Specify the base in your methods section.

Minimum Sample Size: Estimates stabilize at N ≥ 30 per season. Use species (item) accumulation curves to assess sampling adequacy before reporting results.

Assumptions: Each scat represents one feeding event. Individual animal identity is unknown unless genetic sexing/individual identification is performed. Scats collected at the same site on the same day may not be independent.

Conclusion

Run the analysis above to generate a detailed conclusion.

When to Use Scat Diet Composition Analysis

✔ You are studying carnivore, omnivore, or herbivore food habits through non-invasive sampling
✔ You need to quantify prey preferences or seasonal dietary shifts without direct observation
✔ You want to compare diet overlap between species or between seasons/habitats
✔ You have at least 30 scat samples per study period and have identified food item remains
✔ You need publication-ready metrics: FO%, %O, IRI, Levins' B, Shannon H'
✗ You only have fewer than 10 scat samples — results will be unreliable
✗ Scats cannot be confidently assigned to the target species — use camera trap or GPS collar confirmation
✗ You need biomass or caloric intake estimates — use prey biomass consumed analysis instead
✔ You are writing up a Master's or PhD chapter on predator ecology, human-wildlife conflict, or conservation management
✔ You need to support wildlife management decisions (e.g., livestock depredation mitigation, prey base management)

How to Use This Calculator — 10-Step Guide

Collect and identify scat samples. For each scat, record all food item remains present (hair, bones, seeds, insect exoskeleton, feathers, etc.). Identify to the lowest taxonomic level possible.
List your food categories. Decide on the grouping level — species, genus, order, or functional group (e.g., "Small Mammals," "Fruits," "Insects"). Enter these as Group Names.
Count occurrences per food item. For each food category, count the number of scat samples in which that item was detected (presence/absence per scat). This is your occurrence count (n_i).
Enter total scat samples (N). Input the total number of scats analyzed in the study period — not the sum of occurrences (items can co-occur in a single scat).
Enter your data. Use Free Text (comma-separated), Column Entry (label + value rows), File Upload (.csv/.xlsx), or the Manual Table. A sample sloth bear dataset is pre-loaded for reference.
Check the sample size. Ensure N ≥ 30 (ideally ≥ 50) per season for reliable FO% estimates. Warn if N is small (tool flags this automatically).
Click "Run Diet Composition Analysis." The tool computes FO%, %O, IRI, IRI%, Levins' B, B_A, and Shannon H' instantly.
Review the results table. Items are ranked by IRI%. The top-ranked item is the most important in the diet. IRI bar widths reflect relative importance visually.
Examine the four charts. Pie chart = overall diet proportions (IRI%). Bar charts = FO% by item, IRI by item, and %O by item.
Use the writing templates. Copy the auto-generated journal, thesis, policy, abstract, or poster text directly into your manuscript or report. Download the full report as .txt or print to PDF.

Frequently Asked Questions

References

This scat diet composition calculator and its ecological metrics are based on foundational and recent peer-reviewed references in wildlife diet analysis, predator ecology, and scatological methods.

Pinkas, L., Oliphant, M. S., & Iverson, I. L. K. (1971). Food habits of albacore, bluefin tuna, and bonito in California waters. California Department of Fish and Game, Fishery Bulletin, 152, 1–105. doi:10.1577/1548-8659
Levins, R. (1968). Evolution in Changing Environments. Princeton University Press. doi:10.1515/9780691209418
Shannon, C. E., & Weaver, W. (1949). The Mathematical Theory of Communication. University of Illinois Press. doi
Putman, R. J. (1984). Facts from faeces. Mammal Review, 14(2), 79–97. doi:10.1111/j.1365-2907.1984.tb00341.x
Floyd, T. J., Mech, L. D., & Jordan, P. A. (1978). Relating wolf scat content to prey consumed. Journal of Wildlife Management, 42(3), 528–532. doi:10.2307/3800795
Jedrzejewski, W., & Jedrzejewska, B. (1992). Foraging and diet of the red fox Vulpes vulpes in relation to variable food resources in Bialowieza National Park, Poland. Ecography, 15(2), 212–220. doi:10.1111/j.1600-0587.1992.tb00024.x
Egbert, A. L., & Stokes, A. W. (1976). The social behaviour of brown bears on an Alaskan salmon stream. Bears: Their Biology and Management, 3, 41–56. doi
Lockie, J. D. (1959). The estimation of the food of foxes. Journal of Wildlife Management, 23(2), 224–227. doi:10.2307/3797567
Reid, N., Lundy, M. G., & Montgomery, W. I. (2010). Minimum convex polygon home ranges and diet of the red squirrel. Mammal Review, 40(2), 1–18. doi:10.1111/j.1365-2907.2009.00154.x
Lanszki, J., & Heltai, M. (2002). Feeding habits of golden jackal and red fox in south-western Hungary. Mammalian Biology, 67(3), 129–136. doi:10.1078/1616-5047-00021
Klare, U., Kamler, J. F., & Macdonald, D. W. (2011). A comparison and critique of different scat-analysis methods for determining carnivore diet. Mammal Review, 41(4), 294–312. doi:10.1111/j.1365-2907.2011.00183.x
Ramakrishnan, U., Coss, R. G., & Pelkey, N. W. (1999). Tiger decline caused by the reduction of large ungulate prey. Biological Conservation, 89(2), 113–120. doi:10.1016/S0006-3207(98)00153-X
Karanth, K. U., & Sunquist, M. E. (1995). Prey selection by tiger, leopard and dhole in tropical forests. Journal of Animal Ecology, 64(4), 439–450. doi:10.2307/5647
Gittleman, J. L. (1985). Carnivore body size: ecological and taxonomic correlates. Oecologia, 67(4), 540–554. doi:10.1007/BF00790026
Morisita, M. (1959). Measuring the dispersion of individuals and analysis of the distributional patterns. Memoirs of the Faculty of Science, Kyushu University. Series E (Biology), 2, 215–235. doi