Assessing the Minimum Number of Time Since Last Fire Sample-Points Required to Estimate the Fire Cycle: Influences of Fire Rotation Length and Study Area Scale

Fates of Terrigenous Dissolved Organic Carbon in the Gulf of Maine

A significant amount of organic carbon is transported in dissolved form from soils to coastal oceans via inland water systems, bridging land and ocean carbon reservoirs. However, it has been discovered that the presence of terrigenous dissolved organic carbon (tDOC) in oceans is relatively limited. Therefore, understanding the fates of tDOC in coastal oceans is essential to account for carbon sequestration through land ecosystems and ensure accurate regional carbon budgeting. In this study, we developed a state-of-the-art modeling approach by coupling a land-to-ocean tDOC flux simulation model and a coastal tDOC tracking model to determine the potential fates of tDOC exported from three primary drainage basins in the Gulf of Maine (GoM). According to our findings, over half a year in the GoM, 56.4% of tDOC was mineralized. Biomineralization was responsible for 90% of that amount, with the remainder attributed to photomineralization. Additionally, 37% of the tDOC remained suspended in the GoM, and 6.6% was buried in the marine sediment.

Hurricanes Substantially Reduce the Nutrients in Tropical Forested Watersheds in Puerto Rico

Because nutrients including nitrogen and phosphorus are generally limited in tropical forest ecosystems in Puerto Rico, a quantitative understanding of the nutrient budget at a watershed scale is required to assess vegetation growth and predict forest carbon dynamics. Hurricanes are the most frequent disturbance in Puerto Rico and play an important role in regulating lateral nitrogen and phosphorus exports from the forested watershed. In this study, we selected seven watersheds in Puerto Rico to examine the immediate and lagged effects of hurricanes on nitrogen and phosphorous exports. Our results suggest that immediate surges of heavy precipitation associated with hurricanes accelerate nitrogen and phosphorus exports as much as 297 ± 113 and 306 ± 70 times than the long-term average, respectively. In addition, we estimated that it requires approximately one year for post-hurricane riverine nitrogen and phosphorus concentrations to recover to pre-hurricane levels. During the recovery period, the riverine nitrogen and phosphorus concentrations are 30 ± 6% and 28 ± 5% higher than the pre-hurricane concentrations on average.

Predicting forest fire kernel density at multiple scales with geographically weighted regression in Mexico

Identifying the relative importance of human and environmental drivers on fire occurrence in different regions and scales is critical for a sound fire management. Nevertheless, studies analyzing fire occurrence spatial patterns at multiple scales, covering the regional to national levels at multiple spatial resolutions, both in the fire occurrence drivers and in fire density, are very scarce. Furthermore, there is a scarcity of studies that analyze the spatial stationarity in the relationships of fire occurrence and its drivers at multiple scales. The current study aimed at predicting the spatial patterns of fire occurrence at regional and national levels in Mexico, utilizing geographically weighted regression (GWR) to predict fire density, calculated with two different approaches -regular grid density and kernel density - at spatial resolutions from 5 to 50 km, both in the dependent and in the independent human and environmental candidate variables. A better performance of GWR, both in goodness of fit and residual correlation reduction, was observed for prediction of kernel density as opposed to regular grid density. Our study is, to our best knowledge, the first study utilizing GWR to predict fire kernel density, and the first study to utilize GWR considering multiple scales, both in the dependent and independent variables. GWR models goodness of fit increased with fire kernel density search radius (bandwidths), but saturation in predictive capacity was apparent at 15-20 km for most regions. This suggests that this scale has a good potential for operational use in fire prevention and suppression decision-making as a compromise between predictive capability and spatial detail in fire occurrence predictions. This result might be a consequence of the specific spatial patterns of fire occurrence in Mexico and should be analyzed in future studies replicating this methodology elsewhere.

Methods to Detect Edge Effected Reductions in Fire Frequency in Simulated Forest Landscapes

Reductions in fire frequency (RFF) are known to occur in the area adjacent to the rigid-boundary of simulated forest landscapes. Few studies, however, have removed those edge effected regions (EERs), and many others may, thus, have misinterpreted their simulated forest conditions within those unidentified edges. We developed three methods to detect and remove EERs with RFF and applied them to fire frequency maps of 2900 × 2900 grids developed using between 1000 and 1200 fire-year maps. The three methods employed different approaches: scanning, agglomeration, and division, along with the consensus of two and three of those methods. The detected EERs with RFF ranged in mean width from 5.9 to 17.3 km, and occupied 4.9 to 21.3% of the simulated landscapes. Those values are lower than the 40 km buffer width, which occupied 47.5% of the simulated landscape, used in a previous study in this area that based buffer width on length of the largest fire. The maximum width of the EER covaried with wind predominance, indicating it is not possible to prescribe a standard buffer width for all simulation studies. The three edge detection methods differ in their optimality, with the best results provided by a consensus of the three methods. We suggest that future landscape forest simulation studies should, to ensure their results near the rigid boundary are not misrepresentative, simulate an appropriately enlarged study area and then employ edge detection methods to remove the EERs with RFF.