Fig 1.
An integrated view of reported whale entanglements and ecosystem conditions in the California Current Large Marine Ecosystem (CCLME).
(A) Geographic distribution and seasonal summary (JFM, AMJ, JAS, OND) of reported humpback whale entanglements (red dots) in the CCLME and those found off Mexico with that were confirmed to be entangled in the California Current, 2000-2024 (note reports occur throughout the CCLME, (B) Biogeographic regions showing extent of continental shelf and slope habitat where habitat compression is monitored in the CCLME; orange dots are sampling stations for forage indices. (C) Update of the whale entanglement temporal record for the confirmed number of Humpback whale entanglements reported over 2000 to 2024. The grey line is a long-term trend (trend = 1.11*year-2226.0), with a slope that is approximately 1 whale per year. (D) Standardized relative abundance of northern anchovy (adult and Young-of-the-Year; YOY) and total krill abundance collected from the Rockfish Recruitment and Ecosystem Assessment Survey (stations shown in (B)), which samples forage species during April-June throughout 32°N-42°N, provides a generally reflective index for conditions within the CCLME; dashed boxes indicate heatwave and post anchovy boom.
Fig 2.
Comparison of reported humpback whales whale entanglements and population trends.
(A) Trends in reported entanglements and a representative population abundance of humpback whales within the California Current, 2000–2023; (B) relationship between entanglements and humpback whale abundance; residuals were derived from this relationship to evaluate a density-dependent control of entanglements through changes in habitat compression. Note that the residuals reflect the ‘excess entanglements’.
Fig 3.
Cumulative habitat compression index – a method for tracking annual evolution of thermal habitat in the California Current Large Marine Ecosystem per biogeographic region that highlights years above and below when thermal habitat was enhanced or truncated.
Cumulative HCI (cHCI) curves for all years starting from 1980. The cHCI curve for a given year is calculated by doing the cumulative sum of monthly value over the year starting in January. All cHCI curves are plotted in gray, with the long-term mean plotted with the black-dashed curve. Select years of low (2002, 2013; blue lines) and high (2015, 2016; orange and pink lines) coastwide humpback whale entanglement annual averages are highlighted with colored curves. The most recent year 2024 is shown in red, which is similar to 2015 and 2016 in most regions. See Fig 1 for regional biogeographic boundaries.
Fig 4.
Correlations between reported whale entanglements and habitat compression.
(A) Spearman correlations between monthly cumulative HCI (cHCI) and the annual humpback whale entanglement record (detrended). (B) Spearman correlations between monthly cHCI and residuals derived from the entanglement and population abundance time series (see Fig 2). Negative correlations indicate more entanglements during periods of low cHCI. All correlations are significant, p < 0.001 (see S1 and S2 Tables and S1 Text and S2 Text for bootstrapping results). See Fig 1 for regional biogeographic boundaries.
Fig 5.
Conceptual summary on the utility of the cumulative Habitat Compression Index as an rate tracker of thermal habitat availability pertaining to ecosystem shifts (involving humpback whales and their prey in slope and shelf coastal habitats) to inform whale entanglement mitigation science strategies in the central CCLME (e.g., tactical and strategic ecosystem-based fishery management).
In this example, the cHCI in Region 3 (inset; central California coast) shows the outcomes of years with increased and truncated thermal habitat on whale entanglements. Over 2000-2024, this study found a higher number of whale entanglement reports during years of truncated thermal habitat and highlights the role of the recent anchovy population boom (Fig 1), and potential for increased detection of entanglements when whales are closer to shore. The utilization of short-term seasonal forecasts (at January and July; 6 months out) of habitat compression could improve tactical decisional support for dynamic ocean management (e.g., dynamic versus static fisheries closures).
Fig 6.
Forecasts and observations of habitat compression for 2024 for Region 3 (central California).
(top) The rate of thermal habitat accumulation (cHCI) was forecast below average (dashed line; see Fig 3c) for 2024 and demonstrates skill in forecast at 1-6 months leads. (bottom) Strategic example of how the forecast of cHCI can be implemented to inform changes in spring through applying a forecast from December to March. This is the March cHCI values for every year (2000-2024) for forecasts starting the previous December 14 (i.e., Jan = 0.5, Feb = 1.5, Mar = 2.5 etc…). For example, this strategic short-term forecast of the cHCI can inform the status of habitat compression during a critical time period when humpback whales are migrating back to California waters and when the spring Dungeness Crab fishery is operating and decisions are being made about the length of the season.