Disturbance events affect forest composition and structure across a range of spatial and temporal scales, and forest development may differ after natural, anthropogenic, or compound disturbances. Following large, natural disturbances, salvage logging is a common yet controversial management practice around the globe. While the short-term impacts of salvage logging have been studied in many systems, the long-term effects remain unclear. Further, while natural disturbances create many persistent and unique microsite conditions, little is known about the long-term influence of microsites on forest development. We capitalized on over eighty years of data on stand development following the 1938 hurricane in New England to provide the longest known evaluation of salvage logging impacts, as well as to highlight developmental trajectories for eastern hemlock (Tsuga canadensis)-white pine (Pinus strobus) forests under a variety of disturbance histories. Eight decades following disturbance, there were no differences in current overstory composition between areas that were logged, hurricane disturbed, or hurricane disturbed and salvage logged, but white pine declined across most sites. In contrast, structural characteristics remain distinct between the three management histories. In the unsalvaged area, the diversity of microsites and the coverage of uprootings and pits influenced overstory tree composition, diversity, and structural characteristics. These findings underscore the long-term influence of salvage logging on forest development and the importance of natural disturbance-mediated microsite conditions on tree species growth and survival. Future salvage logging efforts should consider these impacts and provide a greater range of unsalvaged areas across the landscape to maintain these important structural legacies over the long term.

Some climate models predict that, within the next 30-50 years, sea surface temperatures (SSTs) will frequently exceed the current thermal tolerance of corals (Fitt et al. 2001; Hughes et al. 2003; Hoegh-Guldberg et al. 2007). A potential consequence is that mass coral bleaching may take place (i) during warm El Niño-Southern Oscillation (ENSO) events which are predicted to occur in some regions more frequently than the current 3-7 year periodicity (Hoegh-Guldberg 1999; Sheppard 2003) or (ii) perhaps as often as annually or biannually if corals and their symbionts are unable to acclimate to the higher SSTs (Donner et al. 2005, 2007). Global data also indicate an upward trend toward increasing frequencies, intensities, and durations of tropical hurricanes and cyclones (Emanual 2005; Webster et al. 2005). As coral communities have been shown to require at least 10-30 years to recover after a major disturbance (e.g. Connell 1997; Ninio et al. 2000; Bruno & Selig 2007; Burt et al. 2008), it is possible that future coral communities may be in a constant state of recovery, with regeneration times exceeding the periods between disturbances. Life history traits (e.g. reproduction, recruitment, growth and mortality) vary among species of hard corals; thus, gradients in community structures may have a strong influence on susceptibilities to disturbance and rates of recovery (Connell 1997; Ninio & Meekan 2002). Taxa which are more susceptible to bleaching and mechanical disturbance (e.g. tabular and branching acroporids and pocilloporids) may experience continual changes in population structure due to persistent cycles of regeneration or local extirpation, while the more resistant taxa (e.g. massive poritids and faviids) may display relatively stable population structures (Woodley et al. 1981; Hughes & Connell 1999; Baird & Hughes 2000; Marshall & Baird 2000; Loya et al. 2001; McClanahan & Maina 2003). Determining whether resistant coral taxa have predictable responses to disturbances, with consistent patterns over wide spatial scales, may improve predictions for the future affects of climate change and the composition of reefs (Done 1999; Hoegh-Guldberg 1999; McClanahan et al. 2004). The work presented in this dissertation describes the spatial and temporal patterns in community structures for high latitude coral assemblages that have experienced the types of natural disturbances which are predicted to occur in tropical reef systems with increasing frequency as a result of climate change. The primary area of focus is the southeastern Arabian Gulf, where the coral communities are exposed to natural conditions that exceed threshold limits of corals elsewhere in the world, with annual temperature ranges between 14-36°C (Kinzie 1973; Shinn 1976) and salinities above 40 ppt. Two additional regions are included in this study for comparisons of high latitude coral community structures. The northwestern Gulf of Oman is adjacent to the southeastern Arabian Gulf (i.e. the two bodies of water are connected by the Strait of Hormuz); however, the environmental conditions are milder in the Gulf of Oman such that the number of coral taxa therein is threefold that found in the southeastern Arabian Gulf (i.e. 107 coral species in the Gulf of Oman compared to 34 species in this region of the Arabian Gulf (Riegl 1999; Coles 2003; Rezai et al. 2004)). Broward County, Florida is geographically remote from the Gulfs and, therefore, serves as a benchmark for testing whether consistent patterns in community structures exist despite different climatic and anthropogenic influences. The coral communities within the southeastern Arabian Gulf, the northwestern Gulf of Oman, and Broward County, Florida have been exposed to recurrent elevated sea surface temperature (SST) anomalies, sequential cyclone and red tide disturbances, and frequent hurricanes and tropical storms, respectively. These disturbances and other impacts (e.g. bleaching episodes, disease outbreaks, anthropogenic stresses) have affected the more susceptible acroporids and pocilloporids, resulting in significant losses of coral cover by these families and shifts towards massive corals as the dominant taxa. During the post-disturbance scarcity or absence of branching and tabular corals, the resistant massive taxa have become the crux of the essential hard coral habitat for fish, invertebrates and other marine organisms. Because recovery to pre-disturbance community structures may take decades or may not occur at all, it is vital that scientists and resource managers have a better understanding of the spatial and temporal ecology patterns of the corals that survive and fill in the functional gaps that are created by such disturbances. To aid in this understanding, this dissertation presents spatial and temporal patterns for the coral assemblages which have developed after the respective disturbances. Spatial ecology patterns are analyzed using graphical descriptions (e.g. taxa inventories, area cover, densities, size frequency distributions), univariate techniques (e.g. diversity indices), distributional techniques (e.g. k-dominance curves) and multivariate techniques (e.g. hierarchical clustering, multidimensional scaling). Temporal comparisons at monitoring sites within the southeastern Arabian Gulf and northwestern Gulf of Oman describe the coral population dynamics and are used to create size class transition models that project future population structures of massive corals in the recovering habitats.

<p>Three prescribed burn sites and seven selective timber harvest sites were surveyed using a UAS equipped with a PPK-triggered RGB sensor to determine optimal image collection parameters surrounding each type of disturbance and land cover. The image coordinates were corrected with a third-party base station network (CORS) after the flight, and photogrammetrically processed to produce high-resolution georeferenced orthomosaics. This addressed the first objective of this study, which was to <i>establish effective data procurement methods from both before and after planned </i>disturbances. <br></p><p>Orthomosaic datasets surrounding both a prescribed burn and a selective timber harvest, were used to classify land covers through geographic image-based analysis (GEOBIA). The orthomosaic datasets were segmented into image objects, before classification with a machine-learning algorithm. Land covers for the prescribed prairie burn were 1) bare ground, 2) litter, 3) green vegetation, and 4) burned vegetation. Land covers for the selective timber harvest were 1) mature canopy, 2) understory vegetation, and 3) bare ground. 65 samples per class were collected for prairie burn datasets, and 80 samples per class were collected for timber harvest datasets to train the classifier. A supported vector machines (SVM) algorithm was used to produce four land cover classifications for each site surrounding their respective planned disturbance. Pixel counts for each class were multiplied by the ground sampled distance (GSD) to obtain area calculations for land covers. Accuracy assessments were conducted by projecting 250 equalized stratified random (ESR) reference points onto the georeferenced orthomosaic datasets to compare the classification to the imagery through visual interpretation. This addressed the second objective of this study, which was to <i>establish effective data classification methods from both before and after planned </i>disturbances.<br></p><p>Finally, a two-tailed t-Test was conducted with the overall accuracies for each disturbance type and land cover. Results showed no significant difference in the overall accuracy between land covers. This was done to address the third objective of this study which was to <i>determine if a significant difference exists between the classification accuracies between planned disturbance types</i>. Overall, effective data procurement and classification parameters were established for both <i>before </i>and <i>after </i>two common types of <i>planned </i>disturbances within the CHF region, with slightly better results for prescribed burns than for selective timber harvests.<br></p>