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Cat Population Simulator Documentation

Complete guide to parameters, algorithms, and scientific foundations

Legacy model and Hawaiʻi scenarios

This documentation describes the existing educational engine. Its archived audit identifies demographic defects that remain unresolved by the location explorer. Population outputs are not validated Hawaiʻi forecasts.

Every preset is a hypothetical Hawaiʻi scenario with explicit assumptions, including the closed-population case. Presets are not calibrated local colonies. Selecting one resets the complete parameter set.

Mapped environmental evidence, model estimates, management choices and official health advice are separate. The explorer does not infer infection probability or pregnancy-safe areas.

Explore Hawaiʻi watershed and stream context

Overview & Scientific Basis

This simulator uses an individual-based stochastic population model to project feral cat population dynamics under different management scenarios. The model is based on peer-reviewed research, primarily:

  • Miller et al. (2014) - Core methodology for open population modeling
  • Boone et al. (2019) - Long-term mortality tracking framework
  • Nutter et al. (2004) - Baseline demographic parameters
  • Gunther et al. (2022) - Compensatory mechanisms in managed populations

Key Model Features

  • 6-month timesteps - Aligned with feline breeding cycles
  • 1,000 Monte Carlo iterations - Provides confidence intervals
  • Individual tracking - Each cat has age, sex, and sterilization status
  • Open population dynamics - Immigration, emigration, and abandonment
  • Density dependence - Realistic population regulation

Why 6-Month Timesteps?

Cats can reach sexual maturity at 4-6 months and have a gestation period of ~63 days. A 6-month timestep captures one complete breeding cycle while being computationally efficient. This approach is standard in peer-reviewed cat population models.

Why 1,000 Iterations?

Population dynamics are inherently stochastic—random events affect outcomes. Running 1,000 simulations and averaging results provides stable estimates with 95% confidence intervals, showing the range of likely outcomes rather than a single prediction.

Core Parameters

Initial Population

initialPopulation
Default: 50 catsRange: 1-1,000

The starting number of cats in your focal area. This represents the colony or population you want to model.

Scientific basis: Miller et al. (2014) used 50 cats as a typical focal population representing approximately 0.5 km² of urban habitat.

For a single colony, use actual count if known

For an area, estimate based on sightings or surveys

Larger populations take longer to simulate but give more stable results

Simulation Length

simulationYears
Default: 10 yearsRange: 1-30 years

How many years to project the population forward. Longer simulations show long-term trends but have more uncertainty.

Scientific basis: Boone et al. (2019) used 10-year simulations as standard, noting that management effects often take 5+ years to manifest.

5 years: Short-term planning

10 years: Standard for comparing strategies

20+ years: Long-term population trajectory

Management Strategy

strategy
Default: NoneRange: None, TNR, Removal, Hybrid

The intervention approach applied to the population.

Scientific basis: Based on strategies modeled in Miller et al. (2014) and Boone et al. (2019).

None: Baseline—what happens without intervention

TNR: Trap-Neuter-Return—cats are sterilized and returned

Removal: Cats are permanently removed from population

Hybrid: Kittens/juveniles removed, adults sterilized

Intervention Intensity

intensity
Default: 50%Range: 0-100%

The proportion of targetable cats that your program attempts to treat each 6-month period.

Scientific basis: Miller et al. (2014) found 15-20% intensity needed for decline in isolated populations, 30%+ in connected populations.

25%: Low-intensity, volunteer-based effort

50%: Moderate, consistent program

75%+: High-intensity, well-funded program

Actual cats treated = intensity × trappability (70%)

Carrying Capacity

carryingCapacity
Default: 100 catsRange: 10-10,000

The maximum population the environment can sustain. Population growth slows as this limit is approached.

Scientific basis: Carrying capacity is determined by food availability, shelter, and territory. Urban areas with feeding stations have higher capacity.

Set to 2x initial population for typical scenarios

Higher values allow more population growth

Lower values create more density-dependent effects

Demographic Parameters

These parameters control birth and death rates. They are based on field studies of feral cat populations and have the greatest impact on population dynamics.

Kitten Survival (0-6 months)

kittenSurvival
HIGH - Small changes significantly affect population growth
Default: 25%Range: 5-50%

The probability that a kitten survives to 6 months of age. This is the most critical demographic parameter.

Scientific basis: Nutter et al. (2004) documented 75% kitten mortality in feral populations. Levy et al. (2003) found similar rates.

25%: Typical feral conditions

35-40%: Managed colony with feeding

45-50%: Exceptional care, low predation

This parameter is heavily affected by density

Juvenile Survival (6-12 months)

juvenileSurvival
MODERATE
Default: 70%Range: 50-90%

The probability that a juvenile (6-12 months old) survives to adulthood.

Scientific basis: Juveniles have passed the high-mortality kitten stage but haven't fully developed adult survival skills.

60%: Harsh conditions, high predation

70%: Typical feral conditions

80%: Managed colony

Adult Survival (per 6 months)

adultSurvival
HIGHEST - Most influential parameter on population growth
Default: 80%Range: 60-95%

The probability that an adult cat survives each 6-month period. Adults are the most resilient age class.

Scientific basis: Miller et al. (2014) found adult survival has the highest elasticity (0.573)—changes in adult survival have 3x more impact than changes in reproduction.

70%: High-risk environment (traffic, predators)

80%: Typical feral conditions

90%: Protected colony, low threats

Litters Per Year

littersPerYear
MODERATE
Default: 1.4Range: 0.5-3.0

Average number of litters a breeding female produces per year.

Scientific basis: Nutter et al. (2004) documented 1.4 litters/year in feral populations. Cats can theoretically have 3 litters/year but rarely achieve this.

1.0: Poor conditions, seasonal breeding

1.4: Typical feral population

2.0+: Excellent conditions, year-round breeding

Kittens Per Litter

kittensPerLitter
LOW-MODERATE - High kitten mortality buffers litter size effects
Default: 3Range: 1-6

Average number of kittens born per litter.

Scientific basis: Median litter size is 3-4 kittens (Nutter et al. 2004). Range is typically 1-8.

2-3: Young or older mothers

3-4: Prime breeding age

5+: Exceptional fertility

Female Ratio

femaleRatio
MODERATE - Directly affects breeding population
Default: 50%Range: 40-60%

Proportion of the population that is female. Only females can reproduce.

Scientific basis: Sex ratio at birth is approximately 1:1. Adult populations may skew slightly due to differential mortality or dispersal.

50%: Natural sex ratio

55%: Slight female bias (males disperse more)

45%: Male-biased (some colonies)

Population Connectivity

Why Connectivity Matters

Miller et al. (2014) showed that immigration from surrounding areas is the primary reason TNR programs fail to reduce populations. Even high-intensity TNR cannot overcome continuous influx of unsterilized cats from neighboring areas.

Population Type

populationType
CRITICAL - Determines if local management can succeed
Default: OpenRange: Open, Closed

Whether cats can enter or leave the focal population.

Scientific basis: Most real populations are 'open'—cats move between areas. Truly closed populations (islands, fenced areas) are rare.

Open: Realistic for most mainland populations

Closed: Islands, fenced sanctuaries, or isolated areas

Open populations are much harder to manage

Neighborhood Size

neighborhoodSize
HIGH - Larger neighborhoods = more immigration pressure
Default: 200 catsRange: 0-10,000

The estimated cat population in surrounding areas that could send immigrants to your focal area.

Scientific basis: Miller et al. (2014) used 4x the focal population as neighborhood size, representing the surrounding 2 km².

Set to 0 for closed populations

4x focal population is a reasonable default

Urban areas may have much larger neighborhoods

Immigration Rate

immigrationRate
HIGH - Even 2% can undermine local management
Default: 2%Range: 0-10%

Percentage of the neighborhood population that immigrates to the focal area each 6-month period.

Scientific basis: Boone et al. (2019) used 2% as default. Young males are primary dispersers (75% male bias in immigrants).

0%: Closed population

1%: Low connectivity

2%: Moderate connectivity (default)

5%+: High connectivity, urban areas

Emigration Rate

emigrationRate
MODERATE
Default: 2%Range: 0-10%

Percentage of the focal population that leaves each 6-month period.

Scientific basis: Emigration partially offsets immigration but sterilized cats are less likely to leave established territories.

Usually set equal to immigration rate

Lower emigration = population accumulates

Sterilized cats tend to stay in territory

Abandonment Rate

abandonmentRate
MODERATE - Continuous source of unsterilized cats
Default: 4 cats/periodRange: 0-20

Number of pet cats abandoned into the feral population each 6-month period.

Scientific basis: Miller et al. (2014) used 4 kittens/timestep (2 male, 2 female) as default abandonment rate.

0: No abandonment (rare)

2-4: Typical urban/suburban

8+: High abandonment areas

~30% of abandoned cats may already be sterilized

Density Dependence

As population density increases, competition for resources intensifies. This creates natural population regulation—and also explains why populations can rebound after management reduces numbers.

How Density Affects Population

0-50%
Low Density

Abundant resources. Kitten survival and breeding rates at maximum. Population grows rapidly.

50-80%
Moderate Density

Competition increasing. Kitten mortality rises, breeding rate decreases. Population growth slows.

80-100%
High Density

Severe competition. High kitten mortality, reduced breeding, slight adult mortality increase. Population stabilizes near carrying capacity.

Density-Dependent Kitten Mortality

densityKittenMortality
HIGH - Primary mechanism of population regulation
Default: 0.5Range: 0-1.0

How strongly kitten survival decreases as population approaches carrying capacity.

Scientific basis: Miller et al. (2014) documented increased kitten mortality at high densities due to resource competition and disease.

0: No density effect (unrealistic)

0.5: Moderate effect (default)

1.0: Strong effect—kitten survival drops sharply at high density

Density-Dependent Breeding Reduction

densityBreedingReduction
MODERATE
Default: 0.3Range: 0-1.0

How strongly breeding rate decreases as population approaches carrying capacity.

Scientific basis: Gunther et al. (2022) documented reduced breeding in high-density populations due to stress and resource scarcity.

0: No effect on breeding

0.3: Moderate reduction (default)

0.6+: Strong reduction—fewer litters at high density

Compensatory Effects

When population is reduced (by any management strategy), remaining cats have more resources. This leads to improved kitten survival andincreased breeding—partially offsetting management efforts. This is why sustained, high-intensity intervention is required for population reduction.

Management Strategies

No Action

Baseline scenario showing natural population dynamics without intervention.

  • • Population regulated by natural mortality
  • • High kitten mortality (75%)
  • • Population stabilizes at carrying capacity
  • • Useful for comparison with management scenarios

TNR (Trap-Neuter-Return)

Cats are trapped, sterilized, and returned to their territory.

  • • Sterilized cats remain in population
  • • Occupy territory, reducing immigration
  • • Requires 70%+ sterilization rate for decline
  • • Less effective in open populations

Removal

Cats are permanently removed from the population.

  • • Immediate population reduction
  • • Opens territory for immigrants
  • • Triggers compensatory reproduction
  • • Requires sustained effort

Hybrid

Kittens and juveniles removed; adults sterilized and returned.

  • • Combines benefits of both approaches
  • • Adults maintain territory
  • • Removes high-mortality age classes
  • • May be more resource-efficient

Strategy Effectiveness (from Miller et al. 2014)

StrategyIntensity for Decline (Isolated)Intensity for Decline (Connected)
TNR15-20%30%+
Removal15-20%25-30%
Hybrid~15%~25%

Cost Calculations

Sterilization Cost

sterilizationCost
Default: $75Range: $25-$200

Cost per cat for spay/neuter surgery, including anesthesia and basic care.

Scientific basis: Costs vary by location. Hawaii costs are typically higher ($100-150) due to limited veterinary resources.

$25-50: Low-cost clinic, mainland

$75: Typical subsidized program

$100-150: Hawaii, full-service

$150+: Private veterinary clinic

Trapping Cost

trappingCost
Default: $25Range: $0-$100

Cost per trapping event, including equipment, bait, and labor.

Scientific basis: Includes trap depreciation, bait, transport, and volunteer/staff time.

$0: Volunteer-only programs

$25: Typical with some paid staff

$50+: Professional trappers

Feeding Cost

feedingCostPerMonth
Default: $15/cat/monthRange: $0-$50

Monthly cost to feed each cat in a managed colony.

Scientific basis: Feeding is often part of TNR programs to monitor colonies and maintain cat health.

$0: No managed feeding

$10-15: Basic feeding program

$25+: Premium food, supplements

Removal Cost

removalCost
Default: $100Range: $50-$300

Cost per cat for permanent removal, including trapping, transport, and processing.

Scientific basis: Includes all costs associated with removing a cat from the population.

$50-100: Shelter intake

$100-150: Professional removal

$200+: Remote area removal

Total Cost Calculation

Total Cost =

(Cats Sterilized × Sterilization Cost) +

(Trapping Events × Trapping Cost) +

(Population × Feeding Cost × Months) +

(Cats Removed × Removal Cost)

Cost per Cat Reduced = Total Cost ÷ (Initial Population - Final Population)

Simulation Algorithm

Each simulation runs for the specified number of years, with events processed in a specific order each 6-month timestep. This order is based on the Vortex population modeling software used in peer-reviewed studies.

1

Reproduction

Intact adult females may produce litters. Litter size is drawn from a Poisson distribution. Breeding probability is affected by density and seasonality.

2

Mortality

Each cat faces age-specific mortality. Kittens have highest mortality (75%), affected by density. Adults have lowest mortality (~20% per 6 months).

3

Aging

All surviving cats age by 6 months. Kittens become juveniles, juveniles become adults.

4

Movement

For open populations: immigrants arrive (Poisson-distributed), emigrants leave, abandoned cats are added.

5

Intervention

Management actions are applied. Cats are selected for treatment based on intensity and trappability (70%).

6

Recording

Population counts, costs, and mortality are recorded for this timestep.

Why This Order?

Processing reproduction before mortality means newborn kittens experience mortality in the same timestep they are born. This is biologically appropriate—kittens born at the start of a 6-month period face mortality throughout that period.

Parameter Relationships

Parameters don't act in isolation—they interact in complex ways. Understanding these relationships helps interpret simulation results.

Density → Kitten Survival

NegativeStrong

As population approaches carrying capacity, kitten survival decreases due to resource competition. At 90% capacity, kitten survival may drop from 25% to 15%.

Density → Breeding Rate

NegativeModerate

High density causes stress and resource scarcity, reducing breeding frequency. Females may skip breeding cycles or resorb litters.

Low Density → Survival (Compensatory)

PositiveModerate

When population is reduced, remaining cats have more resources. Kitten survival can increase by up to 30%, partially offsetting management efforts.

Sterilization Rate → Population Growth

NegativeStrong

Sterilized cats can't reproduce but still occupy territory. At 70%+ sterilization, population typically declines.

Sterilization Rate → Immigration Effect

NegativeModerate

Sterilized cats maintain territory, reducing space for immigrants. This 'buffer effect' is a key benefit of TNR.

Immigration Rate × Neighborhood Size → Immigrants

MultiplicativeHigh

Actual immigrants = neighborhood size × immigration rate. A 200-cat neighborhood with 2% immigration = 4 immigrants per timestep.

Adult Survival → Population Growth

PositiveHighest

Adult survival has 3x more impact on population growth than reproduction (elasticity = 0.573). This is because adults breed multiple times over their lifespan.

Understanding Outputs

Population Statistics

Final Population (Mean)
Average population at end of simulation across all 1,000 iterations.
95% Confidence Interval
Range containing 95% of simulation outcomes. Wider intervals indicate more uncertainty.
Probability of Decline
Percentage of iterations where final population was lower than initial. Higher is better for management.
Sterilization Rate
Proportion of final population that is sterilized. 70%+ typically needed for decline.

Mortality Breakdown

Total Deaths
All cat deaths during the simulation period.
Kitten Deaths
Deaths of cats 0-6 months old. Typically the largest category.
Natural Deaths
Deaths from age, disease, environment, and density effects.
Intervention Deaths
Cats removed through management (removal strategy only).

Interpreting Mortality Data

High mortality is not necessarily "bad"—it's a natural part of population dynamics. Without intervention, populations are regulated by high kitten mortality. TNR reduces births, which reduces kitten deaths. Removal shifts mortality from natural to intervention. The simulator presents this data neutrally for users to interpret based on their own values and goals.

Limitations & Caveats

Simplified Age Structure

The model uses 4 age classes (kitten, juvenile, adult, senior) rather than continuous aging. This is sufficient for population-level predictions but doesn't capture individual variation.

No Spatial Structure

The model assumes a well-mixed population. It doesn't account for territory boundaries, movement patterns, or spatial clustering. Use for single colonies or defined areas.

Constant Immigration

Immigration rate is constant throughout the simulation. In reality, immigration may vary seasonally or in response to local population changes.

No Disease Dynamics

Disease is modeled as a constant mortality risk, not as epidemics that spread through populations. This is adequate for most scenarios but may underestimate mortality during disease outbreaks.

Stochastic Uncertainty

Even with 1,000 iterations, results have uncertainty. Use confidence intervals and probability of decline rather than focusing on exact numbers.

When NOT to Use This Model

  • Individual cat outcomes - Model predicts population trends, not individual fates
  • Very small colonies (<10 cats) - Stochastic effects dominate, high uncertainty
  • Short timeframes (<1 year) - Seasonal variation may dominate
  • Precise predictions - Use for relative comparisons, not exact numbers

Scientific References

Miller PS, Boone JD, Briggs JR, et al. (2014). Simulating Free-Roaming Cat Population Management Options in Open Demographic Environments. PLOS ONE.DOI

Boone JD, Miller PS, Briggs JR, et al. (2019). A Long-Term Lens: Cumulative Impacts of Free-Roaming Cat Management Strategy and Intensity on Preventable Cat Mortalities. Frontiers in Veterinary Science.DOI

Nutter FB, Levine JF, Stoskopf MK (2004). Reproductive capacity of free-roaming domestic cats and kitten survival rate. Journal of the American Veterinary Medical Association.DOI

Gunther I, Hawlena H, Azriel L, et al. (2022). Reduction of free-roaming cat population requires high-intensity neutering in spatial contiguity to mitigate compensatory effects. Proceedings of the National Academy of Sciences.DOI

Lohr CA, Lepczyk CA (2014). Desires and Management Preferences of Stakeholders Regarding Feral Cats in the Hawaiian Islands. Conservation Biology.DOI

Levy JK, Gale DW, Gale LA (2003). Evaluation of the effect of a long-term trap-neuter-return and adoption program on a free-roaming cat population. Journal of the American Veterinary Medical Association.