Community Ecology Notes Community ecology explores biodiversity by examining species interactions and environmental factors. A community is composed of interacting species within a specific space and time. Community ecology studies the patterns of diversity, abundance, and composition of species. Community ecologists formulate theories and test them by comparing predictions to data. Measuring Biodiversity Biodiversity refers to the variety of life at all levels of organization. Metrics for characterizing communities include:Species richness (number of species) Abundance (number of individuals) Evenness (homogeneity of abundances) Diversity indices (e.g., Shannon's index H = − ∑ < e m > i = 1 S p < / e m > i ln p i H = -\sum<em>{i=1}^{S} p</em>i \ln p_i H = − ∑ < e m > i = 1 S p < / e m > i ln p i Species composition (identity and relative abundance) Turnover (changes in composition over space or time) Fundamental Patterns of Biodiversity Species-area relationships (SARs) describe the relationship between habitat area and the number of species.S = c A z S = cA^z S = c A z S S S A A A z z z c c c More area generally correlates with more species. Species abundance distributions (SADs) describe the abundance of each species in a community.They can be represented graphically or as histograms. SADs capture information about richness, evenness, and community structure. Organizes community ecology around four main processes:Selection/niches: Species differences regarding resource use, environment responses, and interactions. Dispersal: Movement of species through space. Drift/demographic stochasticity: Randomness in birth and death events. Speciation: Origination of new species. Two Species Lotka-Volterra Competition Model Describes the interaction between two species competing for the same resource d N < e m > 1 d t = r < / e m > 1 N < e m > 1 K < / e m > 1 − N < e m > 1 − α < / e m > 12 N < e m > 2 K < / e m > 1 \frac{dN<em>1}{dt} = r</em>1N<em>1\frac{K</em>1 - N<em>1 - \alpha</em>{12}N<em>2}{K</em>1} d t d N < e m > 1 = r < / e m > 1 N < e m > 1 K < / e m > 1 K < / e m > 1 − N < e m > 1 − α < / e m > 12 N < e m > 2 d N < e m > 2 d t = r < / e m > 2 N < e m > 2 K < / e m > 2 − N < e m > 2 − α < / e m > 21 N < e m > 1 K < / e m > 2 \frac{dN<em>2}{dt} = r</em>2N<em>2\frac{K</em>2 - N<em>2 - \alpha</em>{21}N<em>1}{K</em>2} d t d N < e m > 2 = r < / e m > 2 N < e m > 2 K < / e m > 2 K < / e m > 2 − N < e m > 2 − α < / e m > 21 N < e m > 1 Where:N i N_i N i r i r_i r i K i K_i K i α i j \alpha_{ij} α ij Equilibria are found when d N i d t = 0 \frac{dN_i}{dt} = 0 d t d N i = 0 Four possible equilibria:( 0 , 0 ) (0,0) ( 0 , 0 ) ( K 1 , 0 ) (K_1, 0) ( K 1 , 0 ) ( 0 , K 2 ) (0, K_2) ( 0 , K 2 ) ( N < e m > 1 ^ , N < / e m > 2 ^ ) (\hat{N<em>1}, \hat{N</em>2}) ( N < e m > 1 ^ , N < / e m > 2 ^ ) N < e m > 1 ^ = K < / e m > 1 − α < e m > 12 N < / e m > 2 \hat{N<em>1} = K</em>1 - \alpha<em>{12}N</em>2 N < e m > 1 ^ = K < / e m > 1 − α < e m > 12 N < / e m > 2 N < e m > 2 ^ = K < / e m > 2 − α < e m > 21 N < / e m > 1 \hat{N<em>2} = K</em>2 - \alpha<em>{21}N</em>1 N < e m > 2 ^ = K < / e m > 2 − α < e m > 21 N < / e m > 1 For coexistence equilibrium to be biologically sensible(positive abundances), either: \frac{K1}{K 2} > \alpha{12} and K < / e m > 2 K < e m > 1 > α < / e m > 21 \frac{K</em>2}{K<em>1} > \alpha</em>{21} K < e m > 1 K < / e m > 2 > α < / e m > 21 1}{K 2} < \alpha{12} and K < / e m > 2 K < e m > 1 < α < / e m > 21 \frac{K</em>2}{K<em>1} < \alpha</em>{21} K < e m > 1 K < / e m > 2 < α < / e m > 21 Knowt Play Call Kai