Can community structure track sea-level rise? Stress and competitive controls in tidal wetlands.

Climate change impacts, such as accelerated sea-level rise, will affect stress gradients, yet impacts on competition/stress tolerance trade-offs and shifts in distributions are unclear. Ecosystems with strong stress gradients, such as estuaries, allow for space-for-time substitutions of stress factors and can give insight into future climate-related shifts in both resource and nonresource stresses. We tested the stress gradient hypothesis and examined the effect of increased inundation stress and biotic interactions on growth and survival of two congeneric wetland sedges, Schoenoplectus acutus and Schoenoplectus americanus. We simulated sea-level rise across existing marsh elevations and those not currently found to reflect potential future sea-level rise conditions in two tidal wetlands differing in salinity. Plants were grown individually and together at five tidal elevations, the lowest simulating an 80-cm increase in sea level, and harvested to assess differences in biomass after one growing season. Inundation time, salinity, sulfides, and redox potential were measured concurrently. As predicted, increasing inundation reduced biomass of the species commonly found at higher marsh elevations, with little effect on the species found along channel margins. The presence of neighbors reduced total biomass of both species, particularly at the highest elevation; facilitation did not occur at any elevation. Contrary to predictions, we documented the competitive superiority of the stress tolerator under increased inundation, which was not predicted by the stress gradient hypothesis. Multifactor manipulation experiments addressing plant response to accelerated climate change are integral to creating a more realistic, valuable, and needed assessment of potential ecosystem response. Our results point to the important and unpredicted synergies between physical stressors, which are predicted to increase in intensity with climate change, and competitive forces on biomass as stresses increase.

Does food vendor density mediate the association between neighborhood deprivation and BMI?: a G-computation mediation analysis.

BACKGROUND: In previous research, neighborhood deprivation was positively associated with body mass index (BMI) among adults with diabetes. We assessed whether the association between neighborhood deprivation and BMI is attributable, in part, to geographic variation in the availability of healthful and unhealthful food vendors. METHODS: Subjects were 16,634 participants of the Diabetes Study of Northern California, a multiethnic cohort of adults living with diabetes. Neighborhood deprivation and healthful (supermarket and produce) and unhealthful (fast food outlets and convenience stores) food vendor kernel density were calculated at each participant's residential block centroid. We estimated the total effect, controlled direct effect, natural direct effect, and natural indirect effect of neighborhood deprivation on BMI. Mediation effects were estimated using G-computation, a maximum likelihood substitution estimator of the G-formula that allows for complex data relations such as multiple mediators and sequential causal pathways. RESULTS: We estimated that if neighborhood deprivation was reduced from the most deprived to the least deprived quartile, average BMI would change by -0.73 units (95% confidence interval: -1.05, -0.32); however, we did not detect evidence of mediation by food vendor density. In contrast to previous findings, a simulated reduction in neighborhood deprivation from the most deprived to the least deprived quartile was associated with dramatic declines in both healthful and unhealthful food vendor density. CONCLUSIONS: Availability of food vendors, both healthful and unhealthful, did not appear to explain the association between neighborhood deprivation and BMI in this population of adults with diabetes.

Understanding large-scale deforestation in southern Jinotega, Nicaragua from 1978 to 1999 through the examination of changes in land use and land cover.

Nicaragua, home to the largest remaining extent of rainforest in Central America (total surface area) and to a significant indigenous population, has lost approximately half of its forest cover since 1950. This major and rapid loss of forest cover has been explained as the consequence of an eastward moving agricultural frontier that cuts through the region of Jinotega. If the current deforestation rate continues, the country could lose its remaining forest cover over the course of the next two decades; therefore, it is essential that the dynamics and relationships of land-use and land-cover change (LUCC) in this region are understood. To examine LUCC in Nicaragua over time, Landsat imagery from the southern portion of the region of Jinotega, taken in 1978, 1987, and 1999 was utilized. A remote-sensing method, supervised classification, which allows for the grouping of spectrally similar values for each year, followed by an image change detection analysis (postclassification comparison) was conducted. Groundtruthing (field validation) was conducted in 2006 to validate the data, which yielded increasing overall accuracy rates of 71.68% for 1978, 82.35% for 1987, and 84.38% for 1999. The classification and change detection results showed that if the agricultural cultivation overtook this region, it happened before 1978. Therefore, the possibility that either deforestation did not actually occur along an agricultural frontier or that it was located further east exists; this would be an interesting subject for future studies. There was, however, clear evidence of increased forest cover from 1987 to 1999 near the urban center, correlating with the enforced reforestation law in the city of Jinotega.

Temporal and spatial relationships between watershed land use and salt marsh disturbance in a pacific estuary.

Historical and recent remote sensing data can be used to address temporal and spatial relationships between upland land cover and downstream vegetation response at the watershed scale. This is demonstrated for sub-watersheds draining into Elkhorn Slough, California, where salt marsh habitat has diminished because of the formation of sediment fans that support woody riparian vegetation. Multiple regression models were used to examine which land cover variables and physical properties of the watershed most influenced sediment fan size within 23 sub-watersheds (1.4 ha to 200 ha). Model explanatory power increased (adjusted R(2) = 0.94 vs. 0.75) among large sub-watersheds (>10 ha) and historical watershed variables, such as average farmland slope, flowpath slope, and flowpath distance between farmland and marsh, were significant. It was also possible to explain the increase in riparian vegetation by historical watershed variables for the larger sub-watersheds. Sub-watershed area is the overriding physical characteristic influencing the extent of sedimentation in a salt marsh, while percent cover of agricultural land use is the most influential land cover variable. The results also reveal that salt marsh recovery depends on relative cover of different land use classes in the watershed, with greater chances of recovery associated with less intensive agriculture. This research reveals a potential delay between watershed impacts and wetland response that can be best revealed when conducting multi-temporal analyses on larger watersheds.