Conservation genetics for endangered species is crucial in long-term conservation actions.Inbreeding depression and genetic diversity are main genetic parameters with relevance toconservation. The Iberian lynx was by 2002 the most endangered felid in the world. Manyconservation programs have been carried out during the last 20 years, greatly improving theoutlook of the species. There is a paucity of information on the genetic consequences of thereintroduction program thus far. In the following research study, the most endangered Iberianlynx population, the Doñana population, is assessed to determine its actual genetic status andevaluate the genetic consequences of translocations initiated in 2007. This was achieved by thereconstruction of the pedigree of the wild population, and molecular analysis based on genotypedata with the use of Single Nucleotide Polymorphisms (SNPs). The molecular parameterscalculated were inbreeding coefficients, ancestry and genetic diversity. Results show an increase ingenetic diversity and a decrease in inbreeding following translocations. Post translocationinbreeding was found and explained by ancestral classes the individuals belonged to. These resultslay foundation for the importance of the ongoing translocations within the population andemphasize the need in the coming years for the conservation efforts carried out so far.

Across the central and eastern United States, upland oaks are experiencing regeneration complications. This thesis comprises two studies evaluating challenges in regenerating upland oaks. One study evaluates upland Quercus spp., Carya spp., and Acer rubrum L. response to prescribed fire and impacts on seedling growth and mortality. This study found prescribed fire promoted oak growth when canopy cover was < 77%. Oaks displayed lower percent mortality and higher resprout capacity after fire compared to red maple. The second study investigates impacts of Microstegium vimineum presence on Quercus alba L., Liriodendron tulipifera L., and Acer rubrum L. seedlings under different light and moisture environments. Microstegium vimineum presence decreased growth of both sweetgum and red maple; white oak was less impacted, likely because of its conservative growth strategy and high-water use efficiency. Oaks’ conservative growth strategy may offer more resiliency compared to its competitors in response to prescribed fire and Microstegium vimineum.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

Unmanned aerial vehicles (UAVs) with high-resolution cameras are common in today’s society. Industries, such as the forestry industry, use drones to get a fast overview of tree populations. More advanced sensors, such as near-infrared light or depth data, can increase the amount of information that UAV images provide, providing information about the forest, such as; tree quantity or forest health. However, the fast-expanding field of deep learning could help expand the information acquired using only RGB cameras. Three deep learning models, FasterR-CNN, RetinaNet, and YOLOR were compared to investigate this. It was also investigated if initializing the models using transfer learning from the MS COCO dataset could increase the performance of the models. The dataset used was Swedish Forest Agency (2021): Forest Damages-Spruce Bark Beetle 1.0 National Forest Data Lab and drone images provided by IT-Bolaget Per &amp; Per. The deep learning models were to detect five different tree species; spruce, pine, birch, aspen, and others. The results show potential for the usage of deep learning to detect tree species in images from UAVs. / Obemannade drönare med högupplösta kameror är vanliga i dagens samhälle. Branscher, så som skogsindustrin, kan använda sig av sådana drönare för att få en snabb översikt över ett skogsområde.Mer avancerade sensorer, som använder nära-infrarött ljus eller djupdata, kan öka mängden information som drönarna kan samla in, information såsom; trädmängd eller data om skogens hälsa. Det snabbt växande området djup-maskinlärning kan dock hjälpa till att utöka informationen som kan extraheras vid användning av endast RGB-kameror. Tre modeller för djupinlärning, Faster R-CNN, RetinaNet och YOLOR, jämfördes för att undersöka detta. Det undersöktes också om initiering med för-tränade vikter, med överföringsinlärning från datasetet MS COCO, skulle kunna öka modellernas prestanda. Datasetet som användes var Skogsstyrelsen (2021): Skogsskador-Granbarkborre1.0 Nationell Forest Data Lab samt drönarbilder tillhandahållna av IT-Bolaget Per &amp; Per. Det tredjupinlärnings-modellerna skulle detektera fem olika trädarter: gran, tall, björk, asp, och övrigt.Resultaten visar potential för användning av djupinlärning för att upptäcka trädarter i bilder från drönare.

For this dissertation, I measured how plant communities in Appalachian forests responded to disturbances caused by forest management activities. I had two primary objectives including (1) testing theories of biological diversity and invasions by nonnative species; and (2) providing empirical data that will help guide the sustainable use of forest resources. This work is part of the Southern Appalachian Silviculture and Biodiversity (SASAB) experiment that was established in the early 1990s to investigate ecosystem responses to a gradient of timber harvesting disturbances. Ranging from undisturbed controls to silvicultural clearcuts, the disturbance gradient is replicated at sites located throughout the Appalachian mountains of Virginia and West Virginia. The plant community was sampled across a wide range of spatial scales (2 hectares to 1 m2) using a nested sampling design and was also sampled at three times including pre-disturbance, one year post-disturbance, and ten year post-disturbance. For one element of the study I tested modern theories of biological invasions and investigated how the forest disturbance gradient interacted with species diversity to influence invasion by nonnative species (Chapter 2). Contrary to popular ecological theories of biotic resistance, the most diverse sites tended to be more easily invaded following intense canopy disturbance. Interestingly, none of the sites in this study were dominated by invasive plants, which led me to ask whether dominant tree species in forests provided resistance to nonnative plant establishment and growth through the quality of the litter they produce. I also asked how might animals that are known to alter litter layers interact with dominant tree species to influence plant invasions. Therefore, I conducted an experiment investigating how changes in litter from dominant tree species and invasions by nonnative earthworms might influence invasibility of forests using forest floor mesocosms (Chapter 3). I found that plant invasion was inhibited by native oak litter even when earthworms were present, suggesting that oak forests may resist plant invasions via oak tree litter. In contrast, plant invasion was greater under invasive tree litter and earthworm activity tended to facilitate invasive plant success only under invasive tree litter. I was also interested in understanding how disturbance might alter relationships between local and regional diversity. The long-term data of the forest disturbance experiment allowed me to investigate how local species richness is mediated by regional species richness after disturbance and during forest community development (Chapter 4). Local richness depended strongly on regional richness only after disturbance via colonization of species, but this relationship changed during forest aggradation. These results suggest that regional species pools are important to maintain local diversity following disturbance, but that local interactions (through canopy closure of dominant trees) exert control over species diversity during community reorganization. Lastly, I tested current theories on how diversity influences compositional stability after disturbance (Chapter 5). Disturbance consistently resulted in decreased compositional stability, but diversity was associated with stability in complex ways, which depended on how stability was measured and at what scale. Species-rich areas were in some instances less stable; in other instances areas with intermediate levels of diversity were more stable. These results suggest that disturbance causes shifts in species composition via colonization, but the ways in which diversity of sites influences compositional stability is complex and depends on methods used and the scales of observation. Taken together, these results suggest that disturbance influences invasibility, species saturation, and compositional stability of ecological communities. These properties change immediately following disturbance, and during forest development and canopy closure. Data from this project were useful in testing existing theories of community ecology, and may ultimately prove useful for forest managers as they decide how to protect biodiversity while planning for other uses of forest resources. Overall, these results suggest that colonization of species is the primary process driving plant community patterns in Appalachian forests following disturbance. / Ph. D.