Neubauer, Scott C.; and Raynie, Richard C., "Component greenhouse gas fluxes and radiative balance from two deltaic marshes in Louisiana: Pairing chamber techniques and eddy covariance" (2016 Abstract Coastal marshes take up atmospheric CO 2 while emitting CO 2 , CH 4 , and N 2 O. This ability to sequester carbon (C) is much greater for wetlands on a per area basis than from most ecosystems, facilitating scientific, political, and economic interest in their value as greenhouse gas sinks. However, the greenhouse gas balance of Gulf of Mexico wetlands is particularly understudied. We describe the net ecosystem exchange (NEE c ) of CO 2 and CH 4 using eddy covariance (EC) in comparison with fluxes of CO 2 , CH 4 , and N 2 O using chambers from brackish and freshwater marshes in Louisiana, USA. From EC, we found that 182 g C m À2 yr À1 was lost through NEE c from the brackish marsh. Of this, 11 g C m À2 yr À1 resulted from net CH 4 emissions and the remaining 171 g C m À2 yr À1 resulted from net CO 2 emissions. In contrast, À290 g C m 2 yr À1 was taken up through NEE c by the freshwater marsh, with 47 g C m À2 yr À1 emitted as CH 4 and À337 g C m À2 yr À1 taken up as CO 2 . From chambers, we discovered that neither site had large fluxes of N 2 O. Sustained-flux greenhouse gas accounting metrics indicated that both marshes had a positive (warming) radiative balance, with the brackish marsh having a substantially greater warming effect than the freshwater marsh. That net respiratory emissions of CO 2 and CH 4 as estimated through chamber techniques were 2-4 times different from emissions estimated through EC requires additional understanding of the artifacts created by different spatial and temporal sampling footprints between techniques.

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Seasonal patterns of tree growth are often related to rainfall, temperature, and relative moisture regimes. We asked whether diameter growth of mangrove trees in Micronesia, where seasonal changes are minimal, is continuous throughout a year or conforms to an annual cycle. We installed dendrometer bands on Sonneratia alba and Bruguiera gymnorrhiza trees growing naturally within mangrove swamps on the islands of Kosrae, Federated States of Micronesia (FSM), Pohnpei, FSM, and Butaritari, Republic of Kiribati, in the eastern Caroline Islands of the western Pacific Ocean. Trees were remeasured monthly or quarterly for as long as 6 yr. Annual mean individual tree basal area increments ranged from 7.0 to 79.6 cm 2 /yr for all S. alba trees and from 4.8 to 27.4 cm 2 /yr for all B. gymnorrhiza trees from Micronesian high islands. Diameter increment for S. alba on Butaritari Atoll was lower at 7.8 cm 2 /yr for the one year measured. Growth rates differed significantly by hydrogeomorphic zone. Riverine and interior zones maintained up to seven times the annual diameter growth rate of fringe forests, though not on Pohnpei, where basal area increments for both S. alba and B. gymnorrhiza were approximately 1.5 times greater in the fringe zone than in the interior zone. Time-series modeling indicated that there were no consistent and statistically significant annual diameter growth patterns. Although rainfall has some seasonality in some years on Kosrae and Pohnpei and overall growth of mangroves was sometimes related positively to quarterly rainfall depths, seasonal diameter growth patterns were not distinctive. A reduced chance of moisture-related stress in high-rainfall, wetland environments may serve to buffer growth of Micronesian mangroves from climatic extremes.

Scientists commonly ask questions about the relative importance of processes and then turn to statistical models for answers. Standardized coefficients are typically used in such situations, with the goal being to compare effects on a common scale. Traditional approaches to obtaining standardized coefficients were developed with idealized Gaussian variables in mind. When responses are binary, complications arise that impact standardization methods. In this paper, we review, evaluate, and propose new methods for standardizing coefficients from models that contain binary outcomes. We first consider the interpretability of unstandardized coefficients and then examine two main approaches to standardization. One approach, which we refer to as the latent‐theoretical (LT) method, assumes that underlying binary observations, there exists a latent, continuous propensity linearly related to the coefficients. A second approach, which we refer to as the observed‐empirical (OE) method, assumes responses are purely discrete and estimates error variance empirically via reference to a classical R2 estimator. We also evaluate the standard formula for calculating standardized coefficients based on standard deviations. Criticisms of this practice have been persistent, leading us to propose an alternative formula that is based on user‐defined “relevant ranges.” Finally, we implement all of the above in an open‐source package for the statistical software R. Results from simulation studies show that both the LT and OE methods of standardization support a similarly broad range of coefficient comparisons. The LT method estimates effects that reflect underlying latent‐linear propensities, while the OE method computes a linear approximation for the effects of predictors on binary responses. The contrast between assumptions for the two methods is reflected in persistently weaker standardized effects associated with OE standardization. Reliance on standard deviations for standardization (the traditional approach) is critically examined and shown to introduce substantial biases when predictors are non‐Gaussian. The use of relevant ranges in place of standard deviations has the capacity to place LT and OE standardized coefficients on a more comparable scale. As ecologists address increasingly complex hypotheses, especially those that comparing the influences of different controlling factors (e.g., top‐down vs. bottom‐up or biotic vs. abiotic controls), comparable coefficients become necessary for evaluations.