Modeling and Forecasting the Influence of Current and Future Climate on Eastern North American Spruce-Fir (Picea-Abies) Forests

The spruce-fir (Picea-Abies) forest type of the Acadian Region is at risk of disappearing from the United States and parts of Canada due to climate change and associated impacts. Managing for the ecosystem services provided by this forest type requires accurate forecasting of forest metrics across this broad international region in the face of the expected redistribution of tree species. This analysis linked species specific data with climate and topographic variables using the nonparametric random forest algorithm, to generate models that accurately predicted changes in species distribution due to climate change. A comprehensive dataset, consisting of 10,493,619 observations from twenty-two agencies, including historical inventories, assured accurate assignation of species distribution at a finer resolution (1 km2) than previous analyses. Different dependent variables were utilized, including presence/absence, a likelihood value, abundance variables (i.e. basal area, stem density, and importance value), and predicted maximum stand density index (SDImax), in order to inspect the difference in results in regards to their conservation management utility, as well as the effects of inherent species life history traits on outcomes. Using linear quantile mixed models, predictions of SDImax were estimated for spruce or fir-dominated plots across the Acadian Region. Model performance was strong and estimates of SDImax from these models were similar to previous regional studies. The establishment of an individual constant slope of self-thinning for plots dominated by each spruce or fir species reinforces previous research that Reineke’s slope is not universal for all species, and that the differences in slope are telling of different species’ life history patterns. Individual plot estimates of SDImax, achieved through a varying intercept, allowed for the assessment of each stand’s potential and limitations in regards to the impact that climate, nutrient availability, site quality, and other factors might have on SDI. A high association with environmental variables was exhibited for all dependent variables. Area under receiver operator curve values for presence/absence models averaged 0.99 ± 0.01 (mean ± SD) well above the accepted standard for excellent model performance. The addition of historical tree data revealed supplementary suitable habitat along the southern edge of species’ ranges, due to marginal dynamics potentially overlooked by approaches relying solely on current inventories. The likelihood models provided an adequate surrogate to abundance models, reflecting gradients of suitable habitat. The SDImax variables performed the best of the continuous variables inspected in regards to climate associations, likely because of the selection of spruce or fir-dominated plots and the ability to capture core ranges. Black spruce (Picea mariana (Miller) B.S.P.) responded the best to abundance modeling, due to this species’ uniform range. White spruce (Picea glauca (Moench) Voss) consistently performed the worst among all species for each model, due to this species’ wide distribution at low abundances. Presence/absence models assist in understanding the full range of climatically suitable habitats, abundance values provide the ability to prioritize suitable habitat based upon higher abundance, and SDImax models can be utilized for the construction of Density Management Diagrams and the active management of future landscapes based on size-density relationships

Homogeneous nucleation of dislocations as a pattern formation phenomenon

Dislocation nucleation in homogeneous crystals initially unfolds as a linear symmetry-breaking elastic instability. In the absence of explicit nucleation centers, such instability develops simultaneously all over the crystal and due to the dominance of long range elastic interactions it advances into the nonlinear stage as a collective phenomenon through pattern formation. In this paper we use a novel mesoscopic tensorial model (MTM) of crystal plasticity to study the delicate role of crystallographic symmetry in the development of the dislocation nucleation patterns in defect free crystals loaded in a hard device. The model is formulated in 2D and we systematically compare lattices with square and triangular symmetry. To avoid the prevalence of the conventional plastic mechanisms, we consider the loading paths represented by pure shears applied on the boundary of the otherwise unloaded body. These loading protocols can be qualified as exploiting the 'softest' and the 'hardest' directions and we show that the associated dislocation patterns are strikingly different

Acclimation and migration potential of a boreal forest tree, balsam poplar (Populus balsamifera L.) in a changing climate

Thesis (Ph.D.) University of Alaska Fairbanks, 2012In the North American boreal forest, 21st century climate change is projected to result in longer growing seasons, increased forest productivity, and northward expansions or shifts in species ranges. These projected impacts are largely based on observations across natural temperature gradients, e.g., latitude or altitude, or correlations between current species' distributions and modern climate envelopes. These approaches, although valuable, do not consider biological capacities important in a species' ability to cope with novel environments through physiological or phenological acclimation. Within a single species, adaptation to local environments may cause some populations to respond differently to climate change than others. Acclimation (phenotypic plasticity) is often treated as a separate phenomenon from local adaptation, but the latter may determine the range of acclimation responses or thresholds. To more accurately predict how boreal tree species will respond to a directionally changing climate, it is necessary to experimentally examine the effects of warming on the growth and physiology of individual species and how those effects differ across a species' range. This research investigated how tree growth responses to increasing temperature are influenced by differences in adaptation and acclimation across the latitudinal range of the North American boreal forest tree, Populus balsamifera L. (balsam poplar). Warming experiments, both in the greenhouse and in the field, indicated that growth of balsam poplar trees from a broad latitudinal gradient responds positively to increased growing temperatures, with increases in height growth ranging from 27-69 % in response to 3-8 °C average warming. Genotypes from southern populations grew consistently taller in both field and greenhouse experiments. The field experiment enabled investigation into the effects of warming and source latitude on balsam poplar phenology; both experimentally warmed and southern individuals grew larger and exhibited longer growing seasons (more days of active growth). Lastly, I describe a theoretical/methodological framework for exploring the role of epigenetics in acclimation (plasticity) and adaptation to changing environments. The results from these experiments are integrated with information on adaptive gradients in balsam poplar to predict both the in situ responses of balsam poplar to increased temperatures, and the potential for northward range shifts in the species.General Introduction -- Latitudinal variation in growth responses to experimental warming in the boreal forest tree, balsam poplar (Populus balsamifera L.) -- Acclimation and adaptation potential of balsam poplar, Populus balsamifera L., in a changing climate -- The role of epigenetics in plant adaptation -- General conclusions -- Appendix

Self-concatenated coding for wireless communication systems

In this thesis, we have explored self-concatenated coding schemes that are designed for transmission over Additive White Gaussian Noise (AWGN) and uncorrelated Rayleigh fading channels. We designed both the symbol-based Self-ConcatenatedCodes considered using Trellis Coded Modulation (SECTCM) and bit-based Self- Concatenated Convolutional Codes (SECCC) using a Recursive Systematic Convolutional (RSC) encoder as constituent codes, respectively. The design of these codes was carried out with the aid of Extrinsic Information Transfer (EXIT) charts. The EXIT chart based design has been found an efficient tool in finding the decoding convergence threshold of the constituent codes. Additionally, in order to recover the information loss imposed by employing binary rather than non-binary schemes, a soft decision demapper was introduced in order to exchange extrinsic information withthe SECCC decoder. To analyse this information exchange 3D-EXIT chart analysis was invoked for visualizing the extrinsic information exchange between the proposed Iteratively Decoding aided SECCC and soft-decision demapper (SECCC-ID). Some of the proposed SECTCM, SECCC and SECCC-ID schemes perform within about 1 dB from the AWGN and Rayleigh fading channels’ capacity. A union bound analysis of SECCC codes was carried out to find the corresponding Bit Error Ratio (BER) floors. The union bound of SECCCs was derived for communications over both AWGN and uncorrelated Rayleigh fading channels, based on a novel interleaver concept.Application of SECCCs in both UltraWideBand (UWB) and state-of-the-art video-telephone schemes demonstrated its practical benefits.In order to further exploit the benefits of the low complexity design offered by SECCCs we explored their application in a distributed coding scheme designed for cooperative communications, where iterative detection is employed by exchanging extrinsic information between the decoders of SECCC and RSC at the destination. In the first transmission period of cooperation, the relay receives the potentially erroneous data and attempts to recover the information. The recovered information is then re-encoded at the relay using an RSC encoder. In the second transmission period this information is then retransmitted to the destination. The resultant symbols transmitted from the source and relay nodes can be viewed as the coded symbols of a three-component parallel-concatenated encoder. At the destination a Distributed Binary Self-Concatenated Coding scheme using Iterative Decoding (DSECCC-ID) was employed, where the two decoders (SECCC and RSC) exchange their extrinsic information. It was shown that the DSECCC-ID is a low-complexity scheme, yet capable of approaching the Discrete-input Continuous-output Memoryless Channels’s (DCMC) capacity.Finally, we considered coding schemes designed for two nodes communicating with each other with the aid of a relay node, where the relay receives information from the two nodes in the first transmission period. At the relay node we combine a powerful Superposition Coding (SPC) scheme with SECCC. It is assumed that decoding errors may be encountered at the relay node. The relay node then broadcasts this information in the second transmission period after re-encoding it, again, using a SECCC encoder. At the destination, the amalgamated block of Successive Interference Cancellation (SIC) scheme combined with SECCC then detects and decodes the signal either with or without the aid of a priori information. Our simulation results demonstrate that the proposed scheme is capable of reliably operating at a low BER for transmission over both AWGN and uncorrelated Rayleigh fading channels. We compare the proposed scheme’s performance to a direct transmission link between the two sources having the same throughput

Optimization Modeling and Machine Learning Techniques Towards Smarter Systems and Processes

The continued penetration of technology in our daily lives has led to the emergence of the concept of Internet-of-Things (IoT) systems and networks. An increasing number of enterprises and businesses are adopting IoT-based initiatives expecting that it will result in higher return on investment (ROI) [1]. However, adopting such technologies poses many challenges. One challenge is improving the performance and efficiency of such systems by properly allocating the available and scarce resources [2, 3]. A second challenge is making use of the massive amount of data generated to help make smarter and more informed decisions [4]. A third challenge is protecting such devices and systems given the surge in security breaches and attacks in recent times [5]. To that end, this thesis proposes the use of various optimization modeling and machine learning techniques in three different systems; namely wireless communication systems, learning management systems (LMSs), and computer network systems. In par- ticular, the first part of the thesis posits optimization modeling techniques to improve the aggregate throughput and power efficiency of a wireless communication network. On the other hand, the second part of the thesis proposes the use of unsupervised machine learning clustering techniques to be integrated into LMSs to identify unengaged students based on their engagement with material in an e-learning environment. Lastly, the third part of the thesis suggests the use of exploratory data analytics, unsupervised machine learning clustering, and supervised machine learning classification techniques to identify malicious/suspicious domain names in a computer network setting. The main contributions of this thesis can be divided into three broad parts. The first is developing optimal and heuristic scheduling algorithms that improve the performance of wireless systems in terms of throughput and power by combining wireless resource virtualization with device-to-device and machine-to-machine communications. The second is using unsupervised machine learning clustering and association algorithms to determine an appropriate engagement level model for blended e-learning environments and study the relationship between engagement and academic performance in such environments. The third is developing a supervised ensemble learning classifier to detect malicious/suspicious domain names that achieves high accuracy and precision

The potential economic implications of black locust (Robinia pseudoacacia l.) on agricultural production in South Africa

Black Locust (Robinia pseudoacacia L.) is an invasive deciduous, strongly suckering, broad- leaved tree that has the potential to be widely distributed across a large portion of South Africa. Robinia pseudoacacia has invaded all nine of South African provinces, with large infestations found in the Eastern Cape, Kwa Zulu-Natal, Free State and Gauteng provinces. The invasive tree has the potential to spread into livestock grazing lands in South Africa. Because R. pseudoacacia has the ability to spread and thrive in a variety of habitats and resists control, the distribution of the invasive tree into grazing land poses a problem for landowners. The potential economic impacts of R. pseudoacacia on agricultural production stem from the trees ability to reduce the carrying capacity of livestock. This study estimated the potential economic implications of R. pseudoacacia on agricultural production in South Africa, specifically looking at the livestock sector. The prevalence of R. pseudoacacia potential distribution was calculated by using a maximum-entropy predictive habitat model, MAXENT. The distribution of livestock, based on grazing capacity (ha/LSU), in South Africa was then determined. The potential direct economic impacts were estimated by assessing the impact of the potential distribution of R. pseudoacacia on the carrying capacity of livestock. The results showed that an infestation of R. pseudoacacia has the potential to reduce the gross margin in the livestock sector by between approximately R130 million and R961 million, dependent on the probability of invasion. Therefore, the potential invasion of R. pseudoacacia can have detrimental effects on the livestock sector in South Africa. The potential high levels of foregone income and business activity found in this study reaffirm the need to devote resources to develop a viable, economical and effective control method, such as biological control

SOFT POWER OF INTERNATIONAL NEWS MEDIA: AMERICAN AUDIENCES’ PERCEPTIONS OF CHINA’S COUNTRY IMAGE MEDIATED BY TRUST IN NEWS

This experimental study explores the concept of “soft power” in the context of international news management and concepts that may influence soft power, such as trust in news. Specifically, this study investigated how a news source (Chinese versus American) and the valence of a news story (positive versus negative news) affect an audience’s perception of a country’s image along with several dimensions. Theories on social categorization from psychology and image management theory from public relations were synthesized with branding and international politics in a cross-cultural communication context. Hypotheses predicted that positive images or “soft power” for a foreign country would be mediated by the audience’s perceived trust in news coverage. Results suggested that regardless of the source or valence of a news story, the aspects of China’s image in the contexts of responsibility and leadership - were enhanced significantly by mere exposure to news about China. However, positive news about China did not always work in favor of the country’s image. When comparing effects of source, negative news about China from a Chinese source enhanced Americans’ perceived image of China as a socially responsible country while the identical news story presented with a U.S. news source had little effect. American participants also perceived negative news stories to be more objective (regardless of its source). Finally, American participants perceived the American news source as more accurate and objective as compared to when the identical news story was presented with a Chinese media source

Causes and Consequences of Species Diversity in Forest Ecosystems

What are the causes and consequences of species diversity in forested ecosystems, and how is this species diversity being affected by rapid environmental and climatic change, movement of invertebrate and vertebrate herbivores into new biogeographic regions, and expanding human populations and associated shifts in land-use patterns? In this book, we explore these questions for assemblages of forest trees, shrubs, and understory herbs at spatial scales ranging from small plots to large forest dynamics plots, at temporal scales ranging from seasons to centuries, in both temperate and tropical regions, and across rural-to-urban gradients in land use