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Max Czapanskiy

· ProfessorVerified

University of California, Santa Barbara · Marine Science

Active 2018–2026

h-index14
Citations1.2k
Papers5243 last 5y
Funding
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About

Max Czapanskiy is affiliated with the College of Creative Studies at the University of California, Santa Barbara. His academic involvement includes teaching courses such as Marine Data Science, Modern Practices in Marine Science, Marine Policy, Bio-Logging, and Data Science. His work focuses on marine science, with an emphasis on data science applications within the field. Contact information for Max Czapanskiy includes his email address, maxczap@ucsb.edu, and his phone number, 805-893-4146. The available information does not provide further details about his research background or key contributions.

Research topics

  • Ecology
  • Environmental science
  • Biology
  • Computer Science
  • Geology
  • Environmental health
  • Mathematics
  • Oceanography
  • Fishery
  • Internal medicine
  • Medicine
  • Paleontology

Selected publications

  • Data from: Dissolved oxygen and metabolic parameters improve species distribution models for a marine predator

    Zenodo (CERN European Organization for Nuclear Research) · 2026-05-20

    otherOpen access

    Species distribute themselves in the environment to maximize fitness, within their physiological and ecological constraints. The influence of dissolved oxygen and temperature on habitat use in marine systems, as well as their interactive effects on metabolic activity, all considerably impact habitat availability. Yet, despite their importance, a species' physiology is rarely directly considered in species distribution models for marine species.

  • Data from: Dissolved oxygen and metabolic parameters improve species distribution models for a marine predator

    DRYAD · 2026-03-30

    datasetOpen access

    Species distribute themselves in the environment to maximize fitness, within their physiological and ecological constraints. The influence of dissolved oxygen and temperature on habitat use in marine systems, as well as their interactive effects on metabolic activity, all considerably impact habitat availability. Yet, despite their importance, a species’ physiology is rarely directly considered in species distribution models for marine species.

  • Effects of carbon dioxide accumulation on post-dive physiological recovery in odontocetes

    Journal of Experimental Biology · 2026-03-03 · 1 citations

    articleOpen access

    Diving performance by marine mammals is associated with marked changes in tissue oxygen (O2) and carbon dioxide (CO2) levels. Yet, the primary metric for diving recovery in most studies has focused exclusively on restoring tissue O2, despite the importance of CO2 offloading as a major determinant for diving homeostasis. To assess the combined role of respiratory and blood gases, we compared post-exercise O2 and CO2 recovery rates in bottlenose dolphins (Tursiops truncatus, n=2) and beluga whales (Delphinapterus leucas, n=4). System-wide recovery mechanisms were also examined, including blood pH, breathing patterns and peripheral vasodilation. Following maximal swim repetitions, respiratory O2 and CO2 rates returned to resting levels within 8 min for belugas (V̇O2: 7.64±1.36 min; V̇CO2: 7.71±1.41 min; mean±s.d.) and 3.5 min for dolphins (V̇O2: 3.41±0.76 min; V̇CO2: 3.41±0.71 min). Blood O2 and CO2 recovery durations also varied by species. Belugas required 12-15 min to reach resting levels, whereas dolphins' blood O2 remained within resting levels and CO2 recovered in ∼4-7 min. Blood pH, driven by changes in PCO2, returned to resting levels between 12 and 15 min for belugas, but remained elevated throughout the recorded recovery period for dolphins. Blood lactate also remained near double the resting values for both species. Overall, we found that the compounding effects of CO2 with blood lactate appear to play a dominant role in odontocete dive recovery, which will dictate the duration of full physiological recovery by wild odontocetes following escape responses from anthropogenic disturbances.

  • Data from: Dissolved oxygen and metabolic parameters improve species distribution models for a marine predator

    Zenodo (CERN European Organization for Nuclear Research) · 2026-05-20

    otherOpen access

    Species distribute themselves in the environment to maximize fitness, within their physiological and ecological constraints. The influence of dissolved oxygen and temperature on habitat use in marine systems, as well as their interactive effects on metabolic activity, all considerably impact habitat availability. Yet, despite their importance, a species' physiology is rarely directly considered in species distribution models for marine species.

  • Collective Science to Inform Global Ocean Protections

    Ecology Letters · 2025-08-01 · 2 citations

    articleOpen access

    In June 2023, the United Nations adopted the High Seas Treaty. Two years later, signatories are poised to ratify this treaty and create a legal instrument to implement marine protected areas (MPAs) in our greatest global commons, ocean areas beyond national jurisdiction. Protection of the open and deep ocean is timely: we stand at the precipice of an industrial revolution in Earth's largest remaining wilderness. Deciding where to strategically implement high seas MPAs under this treaty requires robust biodiversity information, yet publicly accessible data is sparse, particularly at depth. There is now an opportunity for collective science action to support this collective policy action. Realising this opportunity necessitates swift solutions including (1) supporting and incentivising standardised public sharing of existing biodiversity data; (2) broadening the scope of participatory science to process ocean observations into biodiversity data; and (3) equitably implementing new data collection with research partners across our global community.

  • Integrating animal tracking and trait data to facilitate global ecological discoveries

    Journal of Experimental Biology · 2025-02-15 · 11 citations

    articleOpen access

    Understanding animal movement is at the core of ecology, evolution and conservation science. Big data approaches for animal tracking have facilitated impactful synthesis research on spatial biology and behavior in ecologically important and human-impacted regions. Similarly, databases of animal traits (e.g. body size, limb length, locomotion method, lifespan) have been used for a wide range of comparative questions, with emerging data being shared at the level of individuals and populations. Here, we argue that the proliferation of both types of publicly available data creates exciting opportunities to unlock new avenues of research, such as spatial planning and ecological forecasting. We assessed the feasibility of combining animal tracking and trait databases to develop and test hypotheses across geographic, temporal and biological allometric scales. We identified multiple research questions addressing performance and distribution constraints that could be answered by integrating trait and tracking data. For example, how do physiological (e.g. metabolic rates) and biomechanical traits (e.g. limb length, locomotion form) influence migration distances? We illustrate the potential of our framework with three case studies that effectively integrate trait and tracking data for comparative research. An important challenge ahead is the lack of taxonomic and spatial overlap in trait and tracking databases. We identify critical next steps for future integration of tracking and trait databases, with the most impactful being open and interlinked individual-level data. Coordinated efforts to combine trait and tracking databases will accelerate global ecological and evolutionary insights and inform conservation and management decisions in our changing world.

  • Collective science to inform global ocean protections

    2025-03-24 · 1 citations

    preprint

    In June 2023, the United Nations adopted the High Seas Treaty. Two years later, signatories are poised to ratify this treaty and create a legal instrument to implement marine protected areas (MPAs) in our greatest global commons, ocean areas beyond national jurisdiction. Protection of the open and deep ocean is timely: we stand at the precipice of an industrial revolution in Earth’s largest remaining wilderness. Deciding where to strategically implement high seas MPAs under this treaty requires robust biodiversity information, yet publicly accessible data is sparse, particularly at depth. There is now an opportunity for collective science action to support this collective policy action. Realizing this opportunity necessitates swift solutions to 1) support and incentivize standardized public sharing of existing biodiversity data; 2) broaden the scope of participatory science to process ocean observations into biodiversity data; and 3) equitably implement new data collection with research partners across our global community.

  • Author response for "Collective Science to Inform Global Ocean Protections"

    2025-06-10

    peer-review
  • Dissolved oxygen and metabolic parameters improve species distribution models for a marine predator

    2025-03-03

    preprintOpen access

    Species distribute themselves in the environment to maximize fitness, within their physiological and ecological constraints. The influence of dissolved oxygen and temperature on habitat use in marine systems, as well as their interactive effects on metabolic activity, all considerably impact habitat availability. Yet, despite their importance, a species’ physiology is rarely directly considered in species distribution models for marine species. We used species distribution models following boosted regression tree frameworks to evaluate the inclusion of dissolved oxygen and the Aerobic Growth Index (AGI; a metric for metabolic demands) for predicting habitat suitability of immature shortfin mako sharks ( Isurus oxyrinchus ) in the California Current System and adjacent waters using tracking data from 2003-2015. Model performance was assessed using the True Skill Statistic (TSS), Area Under the receiver operating Curve (AUC), and Percent Deviance Explained. Relative to distribution models solely considering traditional environmental predictor variables, we found that dissolved oxygen and the AGI considerably improved immature mako shark species distribution model predictive performance (ΔTSS dissolved oxygen = 0.099; ΔTSS AGI = 0.09; ΔAUC dissolved oxygen = 0.053 ; ΔAUC AGI = 0.050) and explanatory power of the distribution of shortfin mako sharks (Δ% Deviance Explained dissolved oxygen = 10.8; Δ% Deviance Explained AGI = 10.2). While the AGI had similar performance to models considering dissolved oxygen, species habitat predictions including the AGI uniquely predicted low habitat suitability in regions known to be metabolically stressful for the species, the Pacific North Equatorial Current. Ocean warming and deoxygenation are inextricably linked, which will have direct impacts on metabolic habitat viability, thus appropriately accounting for these changes together will result in improved understanding of current habitat availability, climate-ready management tools, and robust conservation planning.

  • Author response for "Collective Science to Inform Global Ocean Protections"

    2025-04-28

    peer-review

Frequent coauthors

  • Jeremy A. Goldbogen

    Pacific University

    64 shared
  • David E. Cade

    University of California, Santa Cruz

    47 shared
  • Matthew S. Savoca

    Pacific University

    46 shared
  • William T. Gough

    University of Hawaiʻi at Mānoa

    33 shared
  • James A. Fahlbusch

    Stanford University

    33 shared
  • Shirel R. Kahane‐Rapport

    California State University, Fullerton

    30 shared
  • Elliott L. Hazen

    NOAA National Marine Fisheries Service Southwest Fisheries Science Center

    25 shared
  • Paolo S. Segre

    University of Wisconsin–Green Bay

    21 shared

Education

  • PhD, Hopkins Marine Station

    Stanford University

    2022
  • M.S. GIS, Geography

    San Francisco State University

    2018
  • B.S., Computer Science

    Columbia University

    2014
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