Tetra Tech, Inc. is an American Pasadena, California-based consulting and engineering services firm. The company provides consulting, engineering, program management, and construction management services in the areas of water, environment, infrastructure, resource management, energy, and international development. Specific services for consulting and engineering projects include applied science, information technology, engineering, design, construction management, and operations and maintenance.
Aim Climate change is causing distributional shifts in many species globally. identifying and anticipating these shifts is critical to understanding ecosystem impacts and implementing successful management strategies. species distribution models (SDMs) are useful tools often employed to describe current and changing habitat use, particularly for marine predators. However, most SDMs assume the statistical relationships between species and their environment are temporally static, which may not be true. We examined how incorporating temporal variability improved SDM performance and estimated range shifts for six Odontocete species. We used a high performing model to quantify changes in Odontocete distribution over a 24-year period.Location Waters of the United States, east coast, from Florida to Nova Scotia.Methods We utilised nearly 1.4 million kilometres of line transect survey data collected from 1997 to 2020 along the East Coast of the United States to evaluate changes in the distribution of six Odontocete species. We assessed six model specifications of generalise additive models that varied in the extent of temporal and spatial variability incorporated.Results We found that the best performing model specifications included temporally dynamic species-environment relationships and temporally dynamic spatial terms. These model specifications identified significant poleward range shifts in all species for which we had sufficient data across their range. In contrast, model specifications which only included static terms performed poorly and identified limited or no spatial shifts.Main Conclusions These results advance our predictive capabilities from static species-environment relationships for marine predators and demonstrate the importance of carefully considering assumptions and model specifications when modelling changes to distributions. The odontocete range shifts we identified are likely to have substantial ecosystem impacts, and the framework we present offers a diagnostic approach for modelling and identifying range shifts in other wide-ranging species.
Underground coal fires (UCFs) pose a persistent environmental and economic threat to both the built and natural worlds. In Colorado, 38 known coal fires are currently monitored by the Colorado Division of Reclamation, Mining, and Safety, many of which are in the immediate vicinity of communities and transportation infrastructure. The Axial underground coal mine fire in northwestern Colorado has been active for over 70 years and has a documented history of surface impacts, including wildfire ignition and UCF-induced slope instability near a major highway corridor. Subsurface investigations indicate active combustion in multiple coal seams, contributing to complex and evolving surface deformation. Unmanned Aerial System (UAS)-based optical surveys acquired between 2018 and 2025 were used to assess terrain changes and slope instability at the Axial site. Structure-from-motion photogrammetry was used to generate three-dimensional point clouds and orthomosaics, and surface deformation was quantified using the Multiscale Model-to-Model Cloud Comparison (M3C2) algorithm. Orthomosaic products were additionally evaluated to characterize the development of geomorphic features and cross-validate the interpretation of M3C2-derived deformation patterns. Repeat UAS surveys effectively identified changes in unstable and hazardous terrain caused by UCFs. Results reveal progressive subsidence, fracture development, and localized slope instability associated with ongoing subsurface combustion. The findings provide critical information for risk mitigation and illustrate both the capabilities and challenges of using UAS photogrammetry for long-term monitoring of geohazards associated with legacy coal mine fires. The study further emphasizes the importance of georeferencing strategies, including ground control points and real-time kinematic positioning, to ensure consistent and reliable multi-temporal change detection.
Quaternary lavas (ankaramite, basalt, basaltic andesite, andesite, dacite) from the Kamchatka, Kurile, Ecuador and Cascade volcanic arcs contain Cl-bearing mineral microinclusions in rock-forming minerals and groundmass volcanic glass. They are represented by chlorargyrite (with a variable amount of native Ag), Cu, Ag, Sn, and Zn compounds with Cl and S, Sn- and Pb-Sb oxychlorides compositionally similar to abhurite and nadorite, as well as bismoclite and Cl-F-apatite. The Cl-bearing compounds with chalcophile metals are best approximated by mixtures of chlorargyrite with Cu sulfides, malachite, or azurite. Some Cl-bearing solid microinclusions in magmatic rock-forming minerals could have formed from Cl-rich melts exsolved from arc magmas during differentiation. Alternatively, specific magmatic microinclusions may record the decomposition of primary sulfides in the presence of Cl-bearing magmatic volatiles. Post-magmatic Cl microminerals found in fractures, pores, grain contacts, and groundmass glass are most probably precipitated from hydrothermal fluids accompanying their emplacement at the surface and post-eruption transformations in active fumarole fields. Assemblages of Cl-bearing microminerals with native metal, alloy, sulfide, oxide, and sulfate microinclusions in arc lavas potentially record late-magmatic to post-magmatic stages of formation of the epithermal and possibly porphyry mineralization beneath arc volcanoes.
Abstract Nature-based solutions (NbS) are increasingly recognized as effective tools for climate adaptation, yet their implementation remains limited by the perception that engineering guidance is lacking. This paper examines the existing spectrum of available guidance, ranging from informal case studies to peer-reviewed literature and state-level manuals, highlighting the need to clarify which types of standards are most useful across project types and contexts. Drawing on historical precedents, current practices, and recent advances in evaluating performance, we argue that a body of data and design knowledge exists but is decentralized and underutilized. We propose the creation of a Natural Infrastructure Engineering Hub (HUB) to centralize NbS resources, support adaptive learning, and promote the development of NbS-specific guidance that can evolve as more projects are designed, built, and monitored. Through cross-sector collaboration and phased implementation, the HUB offers a pathway to scale NbS with confidence, rigor, and transparency.
