Effects of hurricanes and climate oscillations on annual variation in reproduction in wet forest, Puerto Rico.

Interannual changes in global climate and weather disturbances may influence reproduction in tropical forests. Phenomena such as the El Niño Southern Oscillation (ENSO) are known to produce interannual variation in reproduction, as do severe storms such as hurricanes. Using stationary trap-based phenology data collected fortnightly from 1993 to 2014 from a hurricane-affected (1989 Hugo, 1998 Georges) subtropical wet forest in northeastern Puerto Rico, we conducted a time series analysis of flowering and seed production. We addressed (1) the degree to which interannual variation in flower and seed production was influenced by global climate drivers and time since hurricane disturbance, and (2) how long-term trends in reproduction varied with plant lifeform. The seasonally de-trended number of species in flower fluctuated over time while the number of species producing seed exhibited a declining trend, one that was particularly evident during the second half of the study period. Lagged El Niño indices and time series hurricane disturbance jointly influenced the trends in numbers of flowering and fruiting species, suggesting complex global influences on tropical forest reproduction with variable periodicities. Lag times affecting flowering tended to be longer than those affecting fruiting. Long-term patterns of reproduction in individual lifeforms paralleled the community-wide patterns, with most groups of lifeform exhibiting a long-term decline in seed but not flower production. Exceptions were found for hemiepiphytes, small trees, and lianas whose seed reproduction increased and then declined over time. There was no long-term increase in flower production as reported in other Neotropical sites.

Spatial analysis of undernutrition of children in léogâne Commune, Haiti.

BACKGROUND: Over a fifth (21.9%) of children under 5 years of age in Haiti suffer from chronic malnutrition, 11.4% are underweight, and 5.1% suffer from acute malnutrition. Léogâne Commune has one of the highest under-five mortality rates in the country. Ordinary least squares regression conducted using data from household surveys to assess the impact of causal factors on child undernutrition may mask important local variations. OBJECTIVE: To characterize the nutrition and health situation of children 6 to 35 months of age in LLogdne Commune, Haiti, using geographically weighted regression. METHODS: In July 2008, the Children's Nutrition Program of Haiti conducted a representative cross-sectional household survey (N = 150) using a modified 33 x 6 alternative sampling design. Household questionnaires were administered to caregivers of children 6 to 35 months of age and anthropometric measurements were collected. Geographically weighted regression was employed to evaluate how undernutrition (weight-forage) and its household determinants vary across the region. Geographically weighted regression and ordinary least squares regression models were compared. RESULTS: The residuals of the ordinary least squares regression model were spatially autocorrelated (Moran's I = 0.08, z = 1.90, p = .058), indicating that undernutrition occurs in pockets rather than being evenly distributed throughout the population. There was no improvement in performance from the ordinary least squares regression model to the geographically weighted regression model. CONCLUSIONS: Despite some limitations, this study illustrates a promising approach for using geospatial data to improve the understanding of how a nutrition situation varies across a region and provide deeper insight into its underlying causes.