Big Cat Ecology Course

Lesson 1 • Physiology and Metabolic Processes

Explains digestive, reproductive, and thermoregulatory physiology unique to felids. Provides biological context for understanding energy budgets and habitat needs.

Lesson 2 • Taxonomy and Evolutionary History

Covers Felidae family classification, phylogenetic relationships, and speciation events. Establishes the taxonomic framework used throughout the course.

Lesson 3 • Species Diversity and Global Distribution

Surveys the 37 recognised wild cat species across continents and biomes. Prepares students to connect species identity with habitat and behaviour chapters.

Lesson 1 • Ecological Niche and Guild Interactions

Analyses niche partitioning among sympatric felids and interactions with other carnivores. Prepares students for multi-species monitoring frameworks.

Lesson 2 • Microhabitat Use and Shelter Selection

Examines den site selection, resting cover, and microhabitat preferences. Informs field survey placement and camera trap positioning techniques.

Lesson 3 • Habitat Types and Structural Requirements

Identifies forest, grassland, arid, and montane habitats used by wild cats. Connects structural features like cover density to predator ambush strategies.

Lesson 4 • Home Range and Territory Dynamics

Explains how cats establish, defend, and adjust territories relative to resources. Builds spatial reasoning needed for field survey design.

Lesson 1 • Parental Care and Cub Development

Traces developmental stages from birth through independence in wild cats. Supports age-class identification used in population surveys.

Lesson 2 • Hunting Strategies and Predatory Behaviour

Details stalking, ambush, coursing, and cooperative hunting techniques. Connects predatory behaviour to habitat structure and prey type.

Lesson 3 • Activity Patterns and Diel Rhythms

Examines nocturnal, crepuscular, and diurnal activity cycles across species. Informs optimal timing for field surveys and camera trap deployment.

Lesson 4 • Communication and Scent Marking

Covers vocal, visual, and chemical communication channels used by felids. Provides interpretive tools for sign surveys and behavioural observation.

Lesson 1 • Field Data Recording and Quality Control

Establishes standardised data sheets, GPS waypoint logging, and field QC protocols. Ensures data integrity for statistical analysis in subsequent chapters.

Lesson 2 • Individual Identification Techniques

Explains coat pattern matching, ear notch cataloguing, and whisker spot mapping. Enables mark-recapture population estimates covered in the next chapter.

Lesson 3 • Sign Surveys and Track Identification

Teaches identification of tracks, scat, scrapes, and kills as species-presence indicators. Grounds students in low-tech detection before electronic methods.

Lesson 4 • Acoustic and Olfactory Detection Methods

Introduces passive acoustic monitoring and lure-based detection for elusive species. Expands detection toolkit beyond visual and photographic methods.

Lesson 1 • Occupancy Modelling Fundamentals

Introduces detection probability, site covariates, and single-season occupancy models. Provides the statistical foundation for all monitoring frameworks in this chapter.

Lesson 2 • Population Trend Analysis

Applies index-based and model-based methods to detect population change over time. Connects monitoring outputs to conservation decision thresholds.

Lesson 3 • Spatially Explicit Capture-Recapture

Extends mark-recapture to estimate density using spatial detection data. Addresses movement and home range overlap in camera trap arrays.

Lesson 4 • Demographic Parameter Estimation

Estimates survival, recruitment, and sex ratios from field data. Provides inputs for population viability analysis introduced in later chapters.

Lesson 1 • Compensation and Incentive Schemes

Reviews livestock compensation programmes, insurance models, and payment for coexistence. Links economic incentives to long-term tolerance of wild cats.

Lesson 2 • Habitat Loss and Fragmentation

Quantifies deforestation, land conversion, and edge effects on wild cat populations. Establishes threat context for conservation planning chapters.

Lesson 3 • Livestock Depredation and Conflict Dynamics

Examines predation on livestock, conflict hotspot mapping, and socioeconomic drivers. Grounds coexistence strategy design in empirical conflict data.

Lesson 4 • Coexistence Tools and Mitigation Measures

Evaluates predator-proof enclosures, livestock guardian animals, and early warning systems. Provides practical intervention options for field practitioners.

Lesson 1 • Protected Area Design and Evaluation

Covers reserve size, shape, buffer zones, and management effectiveness evaluation. Connects spatial planning principles to wild cat home range requirements.

Lesson 2 • Landscape Connectivity and Corridor Planning

Designs wildlife corridors using least-cost path modelling and resistance surfaces. Addresses fragmentation threats identified in the previous chapter.

Lesson 3 • Monitoring, Adaptive Management, and Reporting

Establishes feedback loops between monitoring data and management decisions. Produces structured reporting outputs required by conservation programmes.

Lesson 4 • Conservation Status Assessment

Applies threat category criteria and population viability analysis to assess species status. Provides the evaluative framework for prioritising conservation actions.

Lesson 1 • Research Communication and Publication

Structures findings into peer-reviewed manuscripts, technical reports, and stakeholder briefs. Completes the research cycle from data collection to knowledge dissemination.

Lesson 2 • Research Question and Hypothesis Design

Formulates testable hypotheses grounded in ecological theory and conservation need. Anchors all subsequent methodological choices to a clear research objective.

Lesson 3 • Telemetry and GPS Collar Data Analysis

Processes GPS fix data to derive movement paths, kernel density home ranges, and step selection functions. Integrates movement ecology into conservation planning outputs.

Lesson 4 • Advanced Statistical Analysis

Applies mixed-effects models, Bayesian inference, and multivariate techniques to felid data. Elevates analytical rigour beyond introductory population estimation methods.