Towards science-based quantitative conservation management plan add-ons for all Alaskan squirrel species: current and future distributions, conservation management, contaminant exposure, and their role in Alaska Native communities

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Author
Steiner, Moriz
Chair
Huettmann, Falk
Committee
Morton, John M.
Lian, Marianne
Carroll, Jennifer L.
Drown, Devin M.
Keyword
Squirrels
Marmots
Wildlife management
Conservation
Metadata
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URI
http://hdl.handle.net/11122/16311
Abstract
Squirrels are widespread in Alaska, yet a science-based conservation management plan (CMP) is absent at the state level. Squirrels are killed year-round with no bag limits, while population metrics remain unknown and conservation statuses disputed. This thesis proposes modern tools and approaches as addons for long-term, sustainable, holistic CMPs for all Alaskan squirrel species in a changing climate. Chapter 1 provides an overview of squirrels' current roles and uses in Alaska alongside existing management practices and regulations. Chapters 2 and 3 conduct thorough conservation assessments by analyzing and predicting current and future distributions of squirrel species across Alaska and a 600 km buffer region, utilizing Machine Learning (ML) and state-of-the-art predictive Big Data methodologies to forecast climate suitability shifts over time. These chapters demonstrate that Big Data Open-Access ML Ensemble Species Distribution Models can reveal landscape and climate change effects on species populations and distributions, strongly recommending their inclusion in future CMPs. Forecasts indicate two species will face severe habitat fragmentation and potential population declines, requiring additional conservation initiatives to prevent extinctions. Chapters 4 and 5 provide additional considerations for holistic conservation management. Chapter 4 analyzes heavy metal and essential element concentrations in Interior Alaskan red squirrels (Tamiasciurus hudsonicus) and predicts them landscape-wide on a pixel basis, revealing spatial patterns of concentration hotspots and holding the potential for guiding future ground-truthing and community-focused studies. Chapter 5 analyzes squirrel roles and uses in Alaska Native communities using literature reviews, interviews, and ML data mining. Findings indicate that Arctic ground squirrels (Urocitellus parryii) play essential roles in Indigenous traditions. Chapter 6 summarizes all findings in an essay format. This thesis's results and openly shared data can guide longterm, sustainable squirrel management in Alaska. The proposed modern assessment procedures and conservation management approaches can be applied to virtually any vertebrate species worldwide.
Description
Thesis (M.S.) University of Alaska Fairbanks, 2025
Table of Contents
Chapter 1: General introduction -- 1.1 Role of squirrels in Alaska -- 1.2 Conservation management -- 1.2.1 Current conservation management -- 1.2.2 Use of squirrels on ANCSA-assigned Indigenous lands -- 1.2.3 Conservation in times of a human-induced rapidly warming climate -- 1.2.4 Modern conservation management frameworks and approaches -- 1.2.5 Squirrels as indicators and potential sentinels for Anthropogenic impacts and heavy metal contamination -- 1.3 Data chapter citations and affiliation -- 1.4 References. Chapter 2: Using machine learning, the cloud, big data, citizen-science, and 200+ environmental predictors towards proposing modern add-ons to improve conservation management plans for squirrel species in Alaska -- 2.1 Abstract -- 2.2 Introduction -- 2.2.1 Objectives -- 2.3 Methods -- 2.3.1 Study area -- 2.3.2 Species-specific and multi-species composite Super Species Distribution Models (Super SDMs) for all species currently occurring in Alaska and a 600 km buffer region -- 2.3.3 Indigenous land management practices and harvest schemes for a more long-term sustainable management outlook -- 2.4 Results -- 2.4.1 Species-specific Super SDM Ensembles -- 2.4.2 Assemblage Super SDM Ensemble results for all squirrel species currently occurring in Alaska -- 2.4.3 Assemblage Super SDM Ensemble results for all squirrel species currently occurring in Alaska and a 600 km buffer region -- 2.5 Discussion -- 2.5.1 Limitations -- 2.5.2 Conclusion and management implications -- 2.6 References. Chapter 3: Holistic species conservation assessment in a changing climate: a shifting paradigm from conserving biodiversity to minimizing species extinction in squirrels -- 3.1 Abstract -- 3.2 Introduction -- 3.3 Methods -- 3.3.1 Study -- 3.3.3 Future climate data (environmental variables/predictors) -- 3.3.4 Maxent biodiversity distribution models -- 3.3.5 Multi-species composite Species Distribution Model and Forecast (SDM & SDF) for all included species -- 3.3.6 Species-specific case study assessment -- 3.3.7 Resist-Accept-Direct (RAD) conservation for the squirrel species assemblage -- 3.4 Result -- 3.4.1 Overlapping predicted Species Distribution Forecast (SDF) hotspots -- 3.4.2 Case studies -- 3.4.2.1 Columbian ground squirrel -- 3.4.2.2 Alaska marmot -- 3.4.2.3 North American red squirrel -- 3.4.2.4 Assemblage-wide current and future distribution assessment and management approach -- 3.5 Discussion -- 3.5.1 Main research question: what insights provide the species distribution models and forecast? A) Sub-question: which predicted squirrel species hotspots are likely to move into Alaska by 2100 because of the changing climate? -- 3.5.2 Case studies and RAD considerations -- 3.5.3 Future model considerations and next steps -- 3.5.4 Rules of thumb -- 3.5.5 Limitations of this study -- 3.5.6 Conclusion -- 3.6 References. Chapter 4: Heavy metal and essential elements analyses of North American red squirrels in Interior Alaska: first data mining implications in squirrels as sentinel specie with a One-Health outlook -- 4.1 Abstract -- 4.2 Introduction -- 4.2.1 Heavy metal analyses -- 4.2.2 Spatial predictions of essential elements and heavy metals for Alaska -- 4.3 Methods -- 4.3.1 Study area -- 4.3.2 Study species -- 4.3.3 Review of previous studies on trace elements and heavy metals in squirrels -- 4.3.4 Crowd-sourcing and necropsies of deceased squirrels for tissue samples -- 4.3.5 Squirrel tissue analyses of composite samples -- 4.3.6 Spatial data mining analysis of the heavy metal & essential element results -- 4.3.7 Quantitative assessment of the TreeNet prediction accuracy -- 4.4 Results -- 4.4.1 Literature review results of previous studies on squirrel trace element and heavy metal analyses -- 4.4.2 Raw lab results and a side-by-side comparison with the literature review -- 4.4.3 Spatial predictions of heavy metals and essential elements in red squirrels in Alaska -- 4.5 Discussion -- 4.5.1 Perspectives of the wider Anthropocene, One Health, and squirrels as sentinel animals -- 4.5.2 Limitations of the study -- 4.5.3 Conclusion -- 4.6 References. Chapter 5: What are the various roles and perceptions of squirrels in Alaska Native cultures? A proof-of-concept using Machine Learning with insights from interviews with Alaska Native communities -- 5.1 Abstract -- 5.2 Introduction -- 5.3 Methods -- 5.3.1 Literature review -- 5.3.2 Interview survey of the role of squirrels in Alaska Native communities -- 5.3.3 Coding of interview responses and questions -- 5.3.4 Classification and Regression Tree (CART) and TreeNet Machine Learning analysis -- 5.3.5 Contextualization of the interview data using squirrel subsistence harvest data -- 5.4 Results -- 5.4.1 Literature review on squirrels in northern North American Indigenous and non-Indigenous literature -- 5.4.2 Interviews -- 5.4.3 Machine Learning interview response analysis -- 5.4.4 Machine Learning interview response analysis; a simplified summary -- 5.4.5 Squirrel subsistence harvest data -- 5.5 Discussion -- 5.5.1 Study's limitations and lessons learned -- 5.5.1.1 Suggested improvements for accommodative interviewing approaches specifically for Alaska Native communities -- 5.5.1.2 Misalignment and tensions between Alaska Native knowledge and relationship building with Western academic timelines -- 5.5.1.3 Westernization of Indigenous and Alaska Native stories and potential issues in how they were recorded -- 5.5.1.4 What Machine Learning approaches can and cannot do -- 5.5.2 Conclusion -- 5.6 References. Chapter 6: General conclusions -- 6.1 Thinking like a red squirrel: conservation as preparation in climate-changing Alaska -- 6.2 References.
Date
2025-12
Type
Thesis
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