SAGE-GROUSE AND ENERGY DEVELOPMENT: INTEGRATING SCIENCE WITH CONSERVATION PLANNING TO REDUCE IMPACTS

Effective conservation planning in the face of rapid land use change requires knowledge of which habitats are selected at landscape scales, where those habitats are located, and how species ultimately respond to anthropogenic disturbance. I assessed sage-grouse (Centrocercus urophasianus) large scale habitat ecology and response to energy development in the winter and nesting seasons using radio-marked individuals in the Powder River Basin, Montana and Wyoming, USA. Landscape scale percent sagebrush (Artemisia spp.) cover at 4-km2 was the strongest predictor of use by sage-grouse in winter. After controlling for vegetation and topography, the addition the density of coal-bed natural gas wells within 4 km2 improved model fit (AIC -6.66, wi = 0.965) and indicated that sage-grouse avoided energy development. Nesting analyses showed that landscape context must be considered in addition to local scale habitat features (wi = 0.96). Findings provide managers a hierarchical filter in which to manage breeding habitats. Twice the amount of nesting habitat at 3, 5 and 10-km scales surrounded active leks versus random locations. Spatially explicit nesting and wintering models predicted independent sage-grouse locations (validation R2 ≥ 0.98). I incorporated knowledge of energy impacts into a study design that tested for threshold responses at regional scales analyzing 1,344 leks in Wyoming from 1997-2007. Potential impacts were indiscernible at 1-12 wells within 32.2 km2 of a lek (~1 well / 640 ac). At higher wells densities a time-lag showed higher rates of lek inactivity and steeper declines in bird abundance 4 years after than immediately following development. I spatially prioritized core areas for breeding sage-grouse across Wyoming, Montana, Colorado, Utah and the Dakotas and assessed risk of future energy development. Findings showed that bird abundance varies by state, core areas contain a disproportionately large segment of the breeding population and that risk of development within core areas varies regionally. My analyses document behavioral and demographic responses to energy development, offer new insights into large scale ecology of greater sage-grouse and provide resource managers with practical tools to guide conservation

Streaming Audio Using MPEG–7 Audio Spectrum Envelope to Enable Self-similarity within Polyphonic Audio

One method overlooked to date, which can work alongside existing audio compression schemes, is that which takes account of the semantics and natural repetition of music through meta-data tagging. Similarity detection within polyphonic audio has presented problematic challenges within the field of Music Information Retrieval.  This paper presents a method (SoFI) for improving the quality of stored audio being broadcast over any wireless medium through meta-data which has a number of market applications all with market value. Our system works at the content level thus rendering it applicable in existing streaming services. Using the MPEG-7 Audio Spectrum Envelope (ASE) gives features for extraction and combined with k-means clustering enables self-similarity to be performed within polyphonic audio. SoFI uses string matching to identify similarity between large sections of clustered audio. Objective evaluations of SoFI give positive results which show that SoFI is shown to detect high levels of similarity on varying lengths of time within an audio file. In a scale between 0 and 1 with 0 the best, a clear correlation between similarly identified sections of 0.2491 shows successful identification

Occurrence and Ecosystem Effects of Hiking Off-Trail in Michaux State Forest

American public lands provide significant outdoor recreational opportunities that enhance an individual\u27s physical and mental well-being. Hiking is an example of a highly accessible and affordable recreational activity that is popular and easy for people to engage in no matter how experienced they are. While hiking has improved the well-being of many individuals, its impacts on local ecosystems are often disregarded. For our research, we focused on the impacts that hikers deviating off-trail may have on a local ecosystem in Michaux State Forest in Southern Pennsylvania. Through partnering with the foresters at Michaux State Forest and using AllTrails data, we identified heavily trafficked, unmaintained trail areas and conducted numerous field visits to observe the ecological impacts of this continued off-trail use. At each of the sites, we set up trail cameras in order to measure trail traffic, measured trail dimensions at numerous locations, and used quadrats to examine noticeable impacts on ground cover and plant ecology. We found substantial off-trail use at Michaux State Forest, from legal trail “shortcuts” to fully illegal trails. Surprisingly, we found no evidence that off-trail use impacted overall vegetative cover. In all of the study sites, the official trail was wider than the beginning of the illegal trail area and the beginning of the illegal trail was wider than the trail at the placement of the trail camera. For future analysis, we recommend that soil analyses and longer data collection periods potentially through different seasons should be conducted, as our quadrat photos and physical observations were limited due to the leafy ground cover. Our recommendations for future management include increased signage intended to prevent off-trail travel as well as improved hiker education on the principles of Leave No Trace

QuadConv: Quadrature-Based Convolutions with Applications to Non-Uniform PDE Data Compression

We present a new convolution layer for deep learning architectures which we call QuadConv -- an approximation to continuous convolution via quadrature. Our operator is developed explicitly for use on non-uniform, mesh-based data, and accomplishes this by learning a continuous kernel that can be sampled at arbitrary locations. Moreover, the construction of our operator admits an efficient implementation which we detail and construct. In the setting of compressing data arising from partial differential equation (PDE) simulations, we show that QuadConv can match the performance of standard discrete convolutions on uniform grid data by comparing a QuadConv autoencoder (QCAE) to a standard convolutional autoencoder (CAE). Further, we show that the QCAE can maintain this accuracy even on non-uniform data.Comment: 23 pages, 14 figures, 4 table

The effects of springtime mid-latitude storms on trace gas composition determined from the MACC reanalysis

The relationship between springtime air pollution transport of ozone (O3) and carbon monoxide (CO) and mid-latitude cyclones is explored for the first time using the Monitoring Atmospheric Composition and Climate (MACC) reanalysis for the period 2003–2012. In this study, the most intense spring storms (95th percentile) are selected for two regions, the North Pacific (NP) and the North Atlantic (NA). These storms (∼60 storms over each region) often track over the major emission sources of East Asia and eastern North America. By compositing the storms, the distributions of O3 and CO within a "typical" intense storm are examined. We compare the storm-centered composite to background composites of "average conditions" created by sampling the reanalysis data of the previous year to the storm locations. Mid-latitude storms are found to redistribute concentrations of O3 and CO horizontally and vertically throughout the storm. This is clearly shown to occur through two main mechanisms: (1) vertical lifting of CO-rich and O3-poor air isentropically, from near the surface to the mid- to upper-troposphere in the region of the warm conveyor belt; and (2) descent of O3-rich and CO-poor air isentropically in the vicinity of the dry intrusion, from the stratosphere toward the mid-troposphere. This can be seen in the composite storm's life cycle as the storm intensifies, with area-averaged O3 (CO) increasing (decreasing) between 200 and 500 hPa. The influence of the storm dynamics compared to the background environment on the composition within an area around the storm center at the time of maximum intensity is as follows. Area-averaged O3 at 300 hPa is enhanced by 50 and 36% and by 11 and 7.6% at 500 hPa for the NP and NA regions, respectively. In contrast, area-averaged CO at 300 hPa decreases by 12% for NP and 5.5% for NA, and area-averaged CO at 500 hPa decreases by 2.4% for NP while there is little change over the NA region. From the mid-troposphere, O3-rich air is clearly seen to be transported toward the surface, but the downward transport of CO-poor air is not discernible due to the high levels of CO in the lower troposphere. Area-averaged O3 is slightly higher at 1000 hPa (3.5 and 1.8% for the NP and NA regions, respectively). There is an increase of CO at 1000 hPa for the NP region (3.3%) relative to the background composite and a~slight decrease in area-averaged CO for the NA region at 1000 hPa (-2.7%)

Robust non-Gaussian semantic simultaneous localization and mapping

Submitted in partial fulfillment of the requirements for the degree of Master of Science in Aeronautics and Astronautics at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2019.The recent success of object detection systems motivates object-based representations for robot navigation; i.e. semantic simultaneous localization and mapping (SLAM), in which we aim to jointly estimate the pose of the robot over time as well as the location and semantic class of observed objects. A solution to the semantic SLAM problem necessarily addresses the continuous inference problems where am I? and where are the objects?, but also the discrete inference problem what are the objects?. We consider the problem of semantic SLAM under non-Gaussian uncertainty. The most prominent case in which this arises is from data association uncertainty, where we do not know with certainty what objects in the environment caused the measurement made by our sensor. The semantic class of an object can help to inform data association; a detection classified as a door is unlikely to be associated to a chair object. However, detectors are imperfect, and incorrect classification of objects can be detrimental to data association. While previous approaches seek to eliminate such measurements, we instead model the robot and landmark state uncertainty induced by data association in the hopes that new measurements may disambiguate state estimates, and that we may provide representations useful for developing decisionmaking strategies where a robot can take actions to mitigate multimodal uncertainty. The key insight we leverage is that the semantic SLAM problem with unknown data association can be reframed as a non-Gaussian inference problem. We present two solutions to the resulting problem: we first assume Gaussian measurement models, and non-Gaussianity only due to data association uncertainty. We then relax this assumption and provide a method that can cope with arbitrary non-Gaussian measurement models. We show quantitatively on both simulated and real data that both proposed methods have robustness advantages as compared to traditional solutions when data associations are uncertain.This work was partially supported by the Office of Naval Research under grants N00014-18-1-2832 and N00014-16-2628, as well as the National Science Foundation (NSF) Graduate Research Fellowship

A Currency for Offsetting Energy Development Impacts: Horse-Trading Sage-Grouse on the Open Market

Background: Biodiversity offsets provide a mechanism to compensate for unavoidable damages from new energy development as the U. S. increases its domestic production. Proponents argue that offsets provide a partial solution for funding conservation while opponents contend the practice is flawed because offsets are negotiated without the science necessary to backup resulting decisions. Missing in negotiations is a biologically-based currency for estimating sufficiency of offsets and a framework for applying proceeds to maximize conservation benefits. Methodology/Principal Findings: Here we quantify a common currency for offsets for greater sage-grouse (Centrocercus urophasianus) by estimating number of impacted birds at 4 levels of development commonly permitted. Impacts were indiscernible at 1-12 wells per 32.2 km(2). Above this threshold lek losses were 2-5 times greater inside than outside of development and bird abundance at remaining leks declined by -32 to -77%. Findings reiterated the importance of time-lags as evidenced by greater impacts 4 years after initial development. Clustering well locations enabled a few small leks to remain active inside of developments. Conclusions/Significance: Documented impacts relative to development intensity can be used to forecast biological tradeoffs of newly proposed or ongoing developments, and when drilling is approved, anticipated bird declines form the biological currency for negotiating offsets. Monetary costs for offsets will be determined by true conservation cost to mitigate risks such as sagebrush tillage to other populations of equal or greater number. If this information is blended with landscape level conservation planning, the mitigation hierarchy can be improved by steering planned developments away from conservation priorities, ensuring compensatory mitigation projects deliver a higher return for conservation that equate to an equal number of birds in the highest priority areas, provide on-site mitigation recommendations, and provide a biologically based cost for mitigating unavoidable impacts