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DEMOGRAPHIC MONITORING: FIELD SAMPLING AND DATA TREATMENT F. Xavier Picó

DEMOGRAPHIC MONITORING: FIELD SAMPLING AND DATA TREATMENT F. Xavier Picó Centro Nacional de Biotecnología (CSIC) Madrid, Spain. Field sampling. Demographic plots as sampling units. Hypericum cumulicola (Hypericaceae). Photo: P. Quintana-Ascencio. Field sampling.

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DEMOGRAPHIC MONITORING: FIELD SAMPLING AND DATA TREATMENT F. Xavier Picó

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  1. DEMOGRAPHIC MONITORING: FIELD SAMPLING AND DATA TREATMENT F. Xavier Picó Centro Nacional de Biotecnología (CSIC) Madrid, Spain

  2. Field sampling Demographic plots as sampling units Hypericum cumulicola (Hypericaceae). Photo: P. Quintana-Ascencio.

  3. Field sampling Accurate estimates of life-cycle traits Lobularia maritima (Cruciferae). Photo: F.X. Picó.

  4. Demographic monitoring is determined by life-history type Life histories: 1. Annuals with and without seed bank. 2. Short-lived (with and without seed bank) and long-lived pluricarpic perennials. 3. Monocarpic perennials. Key life-cycle traits that require specific experiments: 1. Seed survival in the soil seed bank. 2. Recruitment rates (i.e., No. of recruits at t per flowering plant at t – 1).

  5. F13 F14 F15 S11 S22 S33 S44 S55 G21 G32 G43 G54 sdlg juv sm md lrg K12 K23 K34 K45 G53 K24 K35 K25 Data treatment 1. Analysis of spatio-temporal variation in life-cycle traits. 2. Assessment of the dynamics of plant populations. Ramonda myconi (Gesneriaceae). Photo: F.X. Picó. Source: Picó & Riba (2002) Plant Ecology.

  6. Analyses to examine the spatio-temporal variation in life-cycle traits 0. Identification of outliers and graphical representation of variability in life-cycle traits. 1. Continuous variables (e.g., fecundity). ANOVA, Simple main effects test. 2. Binomial variables (e.g., flowering probability). Logistic regression. 3. Demographic transitions (e.g., survivorship, growth, stasis). Log-linear analysis.

  7. Log-linear analysis Null model: YHM, F Young ramets Vegetative ramets Model Effect df df Chi-Square Chi-Square YHM, YF Year (Y) 1 0.00 ns 2 28.11 *** YHM, HF Habitat (H) 2 1.64 ns 4 22.51 *** YHM, MF Microhabitat (M) 3 16.73 *** 6 22.63 *** YHM, YF, HF Y x H 3 1.64 ns 6 50.73 *** YHM, YF, MF Y x M 4 16.74 ** 8 50.58 *** YHM, HF, MF H x M 5 18.38 ** 10 45.31 *** YHM, YF, HF, MF Y x H x M 6 18.39 ** 12 73.63 *** Aechmea nudicaulis (Bromeliaceae). Photo: D. Berg. Source: Sampaio, Picó & Scarano (submitted).

  8. sdlg lrg md sd sm Population dynamics of plants: a modeling approach t t + 1 sd sdlg sm md lrg sd 0.12– 12.7 38.3 177.7 sdlg 0.01 0.880.3 0.9 4.5 sm – 0.09 0.69 0.40 0.17 md – – 0.16 0.26 0.12 lrg – – 0.15 0.34 0.70 Lobularia maritima (Cruciferae). Photo: F.X. Picó. Source: Picó, de Kroon & Retana (2002) Ecology.

  9. Matrix analyses 1. Population growth rate. Change in the number of individuals over time. Confidence intervals using probability density functions. 2. Sensitivity and elasticity analyses. Contributions of vital rates to population growth rate. 3. Variance decomposition analyses. Contributions from the variance (covariance) in vital rates to the variance in population growth rate. 4. Current gap of knowledge: statistical treatment of results.

  10. 1800 1500 Urús 1200 Population size 900 600 300 Ingla 1 & 2 0 0 100 200 300 400 500 Time (yr) Stochastic simulations 1. Stochastic projections using the observed set of matrices. Ecological and management scenarios. 2. Bootstrapping and re-sampling methods. Ramonda myconi (Gesneriaceae). Photo: F.X. Picó. Source: Picó & Riba (2002) Plant Ecology.

  11. Large population 100 Small population 80 60 Time to extinction (yr) 40 20 0 No Low High Inbreeding level The more information we have the better our knowledge will be Inbreeding depression, density dependence, spatial structure, etc. Succisa pratensis (Dipsacaceae). Photo: C. Farmer. Source: Picó, Jongejans, Quintana-Ascencio & de Kroon (in preparation).

  12. Final remark Long-term demographic monitoring is needed to: 1. fully assess the demographic behavior of plants, 2. validate demographic models, and 3. perform experiments with artificial populations.

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