https://orcid.org/0000-0003-3887-0186
Figures
Abstract
Climate change modifies the abundance and distribution of marine species, which can reshape patterns of species richness. The Northeast US Continental Shelf (NES) is a mid-latitude marine ecosystem experiencing changes in its physical environment and biota; these changes involve both lower and upper trophic level organisms. In this study, change in species richness of fish and macroinvertebrates was examined based on trawl survey data. Using a constrained subset of the survey strata comprising the overall design, we observed some 451 species over the period 1968–2022. Species richness was consistently higher in the autumn survey versus the spring survey. This seasonal difference in richness was mainly due to a contrast in vertebrate taxa as invertebrate species richness was similar between the seasons. Significant trends were found in the species richness when considering all taxa in both spring and autumn surveys. The rate of change in species richness reflected an increase of 10.8 species per decade in spring and an increase of 16.5 species per decade in autumn. The enhanced rate of increase in autumn was reflected in taxonomic and functional groups that we examined, and likely resulted from longer summering phases by migratory vertebrate species and range shifts northward by multiple taxa in response to greater summer temperatures and longer summer duration. Species richness in the NES was positively correlated with temperature over the study period; however, richness was also positively correlated with ecosystem biomass, suggesting the response in species richness is not limited to the redistribution of species alone. We expect richness to continue to increase, especially in autumn, but range contractions and further community restructuring could lead to declines in richness in the northern end of the NES.
Citation: Friedland KD, Scopel LC, Yang X, Gaichas SK, Rokosz KJ (2025) Species richness in the Northeast US Continental Shelf ecosystem: Climate-driven trends and perturbations. PLOS Clim 4(1): e0000557. https://doi.org/10.1371/journal.pclm.0000557
Editor: Jennifer Lee Wilkening, US Fish and Wildlife Service, UNITED STATES OF AMERICA
Received: July 17, 2024; Accepted: December 15, 2024; Published: January 3, 2025
This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Data Availability: All data can be found in the manuscript and supporting information files.
Funding: This work was supported by the Lenfest Ocean Program (Award # 35796 to XY and KR) and New York Sea Grant (NA24OARX417C0158-T1-01 to XY and KR). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
The properties of an ecosystem are highly dependent on its component species [1]; hence, analyses of ecosystems often includes measurements of species richness as part of the characterization of biodiversity [1–3]. Marine ecosystems show high complexity, connectivity, and openness compared to terrestrial ecosystems [4–6], which can complicate interpretations of their community dynamics. Seasonal dynamics can play an important role in marine ecosystems both in terms of physical forcing [7] and biological response [8]. Marine ecosystems can be altered by the overexploitation of harvested species. As such, not only have many marine ecosystems been reshaped, including relative biomass of different trophic levels [9,10], but these ecosystems are also not in an equilibrium state, and are unlikely to return to previous stable states [4,6]. Long-term spatiotemporal analyses are especially important to understand natural and anthropogenic influences on marine ecosystem dynamics [11].
A factor affecting the measurement of species richness, while also conferring stability on ecosystem function, is species abundance and biomass. The detectability of species is related to their abundance across expanding or contracting habitat areas within an ecosystem. This is a distinction that goes beyond the poleward movement of species that can cause a shift in species richness related to newly arriving versus long-established residents. Without any significant change in the distributional center gravity, if a species is more abundant over an expanding area, the chances of its detection will increase. Not only can species richness be related to system biomass, biomass and system stability appear to be dependent on the feedback provided by the level of species richness in the ecosystem [12]. There appears to be a functional aspect to these mechanisms, suggesting that size spectra among ecosystem components may be critical to maintain stability [13]. There is evidence that the generalist species in the upper trophic levels that exploit both the benthic and pelagic energy pathways provide a critical function in the maintenance of the food web and stability in diversity [14]. Hence, robust size spectra and system diversity equip ecosystems with the ability to resist the more deleterious effects of climate change and increased thermal stress [15].
Climate change related shifts in environmental conditions actuate changes in species abundance and distribution, which in turn leads to changes in the patterns of species richness and biodiversity. The changes in species richness and diversity can often be rapid and seen as a regime shift, with marine ecosystems showing faster rates of change compared to terrestrial ecosystems [16–18]. Recent studies demonstrate a strong correlation between ocean temperature and marine species richness [19–21]. Many marine taxa have shifted their distribution poleward and to deeper water in response to warming water temperatures [22–24]. This redistribution of species leads to decreases in equatorial species richness and increases in richness of temperate and polar marine ecosystems [19,20]. Elucidating the changing patterns and possible drivers of species richness under global warming is critical for understanding the intricate link between climate change and marine ecosystems, and provides the scientific basis for ecosystem risk evaluation and mitigation [18].
Climate effects vary in their impact on pelagic versus benthic oriented organisms and by analogy zooplankton versus upper trophic level fish and invertebrates. For example, large mobile pelagic organisms can move to stay within more optimal temperature and salinity conditions, while sessile benthic organisms and plankton must adapt in place to changing conditions, creating potentially novel species interactions in coastal systems [25]. While climate impacts have been studied more comprehensively in commercially exploited fish than in zooplankton, climate driven changes in phenology and body size have been observed for zooplankton, and increased water temperature is predicted to increase zooplankton respiration [26]. Functional diversity of zooplankton is predicted to be relatively stable in some regions [27], while decadal changes in zooplankton species diversity driven by changing hydrography have altered food webs in other regions [28]. As noted above, many vertebrate and invertebrate taxa are shifting poleward, but analysis of fish species richness by feeding guild (planktivore, benthivore, piscivore) showed contrasting rates of change in species richness attributed to contrasting food web interactions in pelagic and benthic habitats at different life stages [29]. Although the full impacts of climate change across primary producers, zooplankton, fish and other apex predators have yet to be disentangled, studying patterns in fish communities can reveal important climate impacts at the ecosystem level.
Many factors shape the global patterns seen in the species richness of marine fish. However, it is relatively easy to discover regionally nuanced patterns that can at times defy expectations. In the Northeast Atlantic, a layered effect of increasing Arctic species with an increase in species originating in southern latitudes produced a near doubling of the number of species in the Norwegian-Barents Sea over a period of approximately two decades [30]. This transformational change in species richness was associated with a bottom temperature change of ≈1° per decade, far exceeding global trends in temperature change. Coastally oriented marine ecosystems can have discontinuities in habitat caused by estuaries and other circulation features that serve as a barrier to species movement and can thus modify regional patterns in species richness [31]. Changes in fishing activity are another possible driver affecting species richness and biodiversity. The effect of fishing can be significant, but is often secondary to environmental change in some ecosystems [20], while under other circumstances, the recovery of overexploited species can cause a shift in species richness despite any consideration of environmental change [32].
The ecosystem that is the basis of this study, the Northeast US Continental Shelf (NES), is among a number of large marine ecosystems that have experienced increased species richness [33]. The NES is at the junction of major ocean currents, specifically the Labrador Current and the Gulf Stream. Changes in the Atlantic Meridional Overturning Circulation (AMOC) [34], Gulf Stream path [35,36], and Labrador Current [37] impact source water advection into the ecosystem. The AMOC has slowed in recent years [38], while the Gulf Stream has warmed and shifted northward and closer to the coast [36], and concurrently, the Labrador Current flow has diminished [37]. Collectively, the water entering the NES switched from a higher contribution of cold Labrador Slope water to warmer Atlantic Slope water. Hence, the NES has seen significant changes in the distribution of both pelagic and demersal fish species [39], both in terms of biomass and in terms of community structure [40,41]. Most notably, rising temperatures in the NES have been linked to shifts in ecosystem trophic structure and increased species richness [42]. Species with more southern distributions in the NES are experiencing northward shifts of their thermal habitat, expanding their distributions, whereas for species with northern distributions, increasing temperatures are reducing their distribution via loss of suitable thermal habitat [22]. What has not been addressed concerning species richness in the NES is the seasonal contrast in patterns of change in richness over time, within-ecosystem spatial variation in the change in richness, nor the application of rarefaction methods to estimate species richness.
To demonstrate the changing patterns of species richness in the NES and explore the possible mechanistic drivers behind these changes, we require comparable information on temporal and spatial dynamics of species numbers. A long-term monitoring program has been carried out on the NES since 1963 to measure fish and macroinvertebrate populations, which provides a basis for species richness estimates. The overall objective of this study is to describe the temporal and spatial dynamics of species richness in the NES on a seasonal basis and from these estimates explore the possible drivers of change in NES species richness. Richness calculations were allocated between taxonomic and functional groups reflective of their position within the ecosystem. Finally, we consider the correlation between richness and surface and bottom temperature and biomass to understand the role of climate change in influencing change in species richness in the NES. These analyses should have relevance to the management of biodiversity and the utilization of resource species as they reflect change to the ecology and energy flows within the ecosystem.
Methods
Study system and trawl survey
This study was based on the results of a fisheries-independent monitoring program conducted on the Northeast US Continental Shelf (NES). The survey characterizes fish and macroinvertebrate populations using bottom trawl fishing gear while also collecting environmental data. The program is part of the assessment activities of Northeast Fisheries Science Center [43] and has been conducted annually with separate seasonal surveys in the spring since 1968 and autumn since 1963. Each seasonal survey consists of approximately 300 stations (Table 1) distributed in a random stratified design off the coast from south of Cape Hatteras (south of 35°N) to Nova Scotia; the full spatial extent of all survey strata are shown in S1 Fig. The survey was conducted over all strata in only some years; in most years, a core set of strata were sampled, the distribution of which is also shown in S1 Fig and shown as specific tow locations in Fig 1. The core strata have been used by researchers to provide catch and distribution information considered to be comparable over time [23,44]. We constrained most of the analysis of the trawl data to catch made in core strata and to a matching set of years (1968–2022) for both the spring and autumn surveys. Technical issues in the autumn of 2017 and the COVID-19 epidemic in both seasons in 2020 disrupted survey activities making these years missing values. During the survey time series, changes were made to the trawl gear and survey vessels. These changes were accompanied by experiments to determine inter-calibrations to adjust new data to the historical time series [43]. The effects of these shifts were fully calibrated as described in Miller et al. [45]; the conversion factors used to address the issue of catch rate do not explicitly address the issue of species detectability. Finally, the bottom trawl survey is based on a trawl gear designed primarily to capture fish species. Great discipline has been taken to identify fish taxa captured in the survey. Invertebrate taxa are also taken in the survey despite the gear design that targets fish species. Invertebrate species were also identified; however, survey logistics have at times required some invertebrate groups to be handled as a common pool and thus not all species were fully enumerated in some years. Hence, counts of all species and of only invertebrate species must be considered conservative estimates and subject to time series variations.
NES study system with the location of stations from the bottom trawl survey core strata shown in red. Blue lines denote divisions of the core area into a northern band above 41.75°N, a southern band located below 40°N, and a middle band in between. Dashed line marks the 100m depth contour.
Mean longitude and latitude (Lon and Lat) with respective standard deviations (SD) for trawl stations (n, number of stations) within core survey strata during spring and autumn. Longitude and latitude outside mean ±SD are highlighted; also highlighted are years with fewer than 200 trawl stations.
Species observed in the ecosystem
The number of species encountered in the NES was estimated by simply counting the extant number of species. Observed species counts over the entire survey, including all strata, yielded a taxon list of 559 taxa, noting that this is likely an underestimate because the survey recorded catch with unknown identity (unidentified specimens <1% of the catch by weight). The taxon count for the core strata of the survey totaled 451 taxa (see species list in S1 Table). The time series of observed species counts underscores the variability in the survey strata visited each seasonal survey (see S2 Fig); the species numbers in all strata were usually much higher than the core strata, reflecting the variable number of additional strata. On average, the species richness in all strata was 31% higher than in the core strata.
Estimated species richness partitioned by taxonomic and functional groups
NES species richness was estimated seasonally for all species and by taxonomic and functional groups. Richness of all species was estimated over all survey strata and within the core strata only. Richness estimates by taxonomic and functional groupings were done over core strata only. The taxonomic comparisons were between vertebrate and invertebrate taxa (88% vertebrate, see S1 Table for designations), and between taxa in the superclasses Osteichthyes and Chondrichthyes (90% Osteichthyes). Richness was also estimated by functional groups, which were taken to reflect different feeding strategies and positions in the ecosystem food web; the functional types included benthivores, piscivores, and planktivores (50%, 26% and 24%, respectively). Species richness was estimated using the “specpool” command from the “vegan” package (version 2.6–4) in R. This routine provided a series of extrapolated richness estimates; we chose the first order jackknife estimate simply owing to its tendency to provide a midrange value among the estimates provided [46]. Time series trend in extrapolated species richness was tested with a two-tailed Mann-Kendall non-parametric trend test [47]. To reduce the effect of inflated significance caused by autocorrelated time series data, we used the Yue and Pilon correction method [48]; a Theil-Sen slope was estimated for each time series, which indicates whether there are significant trends. All trend statistics were calculated using the “zyp.trend.vector” command from the “zyp” package (version 0.10–1.1) in R. In graphic presentations, trends were represented with the absence or presence of a regression line.
Species richness within the ecosystem
Change in the number of species was estimated for sub-regions of the NES using latitudinal cutoffs. The latitude of all core strata tows were analyzed to determine one third quantiles; the cutoffs were 40.00°N and 41.75°N (Fig 1). These cutoffs tend to divide the data into similar numbers of tows in each latitudinal band by year and season. Species richness for all taxa was then calculated for each latitudinal band.
System drivers and species richness
We considered temperature and biomass trends from external studies to frame potential drivers of species richness in the NES. Water temperature estimates were extracted from Friedland et al. [49] based on a gridded interpolation of survey-derived and other sources of in situ temperature measurements that match the temporal samples of the bottom trawl survey. Ecosystem biomass from Friedland et al. [50] represents swept area estimates of biomass for each season conditioned on machine learning species distribution models. The models provide dynamically defined strata matched with appropriate tow densities for the swept area calculation, which were then summed over the ecosystem. We examined the correlative relationships within the data using Pearson product-moment correlation. The species richness of all species and by taxonomic and functional groups were correlated with biomass and temperature for the years 1976–2019 (limited to the duration of the biomass and temperature data).
Results
Species richness of all species
The time series of species richness among all species suggests an increase in richness in both spring and autumn seasons. The number of species across all survey strata averaged 186 species in spring and 244 in autumn (Fig 2A). Since the number and distribution of survey strata used in the analysis varied over time, trends in these data were not estimated. When the number of species is estimated within the core strata only, distinct trends emerged, with both spring and autumn richness increasing significantly (Fig 2B). The number of species in core strata averaged 137 in spring and increased at a rate of 10.8 species per decade (Table 2). The number of species averaged 187 in autumn and increased by 16.5 species per decade. We repeat here that the estimate of all species are conservative because some invertebrate taxa were inconsistently identified due to logistical issues.
Estimated species richness as number of species for all taxa over the full extent of the survey in a given year (a). Estimated species richness for all species within the core strata of the survey only (b). No trend tests were conducted on the data in panel (a) since there is no standardizing criteria applied. Data in panel b were tested for trend, solid lines indicate trends found significant at p<0.01. Error bars for estimated number of species are standard errors.
Theil–Sen estimators of trend (expressed as decadal rates) by species group and season with associated p-value of Mann-Kendall Test For Monotonic Trend.
Species richness by taxonomic groups
The time series of species richness among vertebrate and invertebrate taxa suggest both taxonomic groups have increased in richness, with the caveat of identification issues with the invertebrates. The number of species among vertebrates increased significantly in both spring and autumn within core survey strata (Fig 3A). Spring vertebrates averaged 117 species and increased at a rate of 5.3 species per decade, whereas autumn vertebrates averaged 164 species and increased at a rate of 11.0 species per decade. Invertebrate species richness was similar across seasons, with number of species in spring averaging 19 compared to the autumn average of 22. Their rates of increase were also similar at 5.1 and 6.0 species per decade in spring and autumn, respectively. Logistical issues with invertebrate identification were more frequent in the beginning of the time series, suggesting the trend values are likely overestimates.
Estimated species richness as number of species for vertebrate (a) and invertebrate (b) taxa over the core strata of the survey by season. Solid lines indicate trends found significant at p<0.01. Error bars for estimated number of species are standard errors.
The time series of species richness among vertebrate fishes within the superclasses of Osteichthyes and Chondrichthyes had different seasonal responses. Species richness among Osteichthyes fish increased significantly in both spring and autumn (Fig 4A). However, the number of Chondrichthyes fishes only increased during the autumn season and did not trend during spring (Fig 4B). The number of bony fish species averaged 102 and 143 species in spring and autumn, respectively; and increased 4.6 and 10.3 species per decade, respectively. In cartilaginous fishes, the number of species averaged 15 and 22 species in spring and autumn, respectively; the increase in cartilaginous fishes was only 0.5 fish per decade in spring and 0.9 fish per decade in autumn, again noting the spring rate was not significant.
Estimated species richness as number of species for Osteichthyes (a) and Chondrichthyes (b) taxa over the core strata of the survey by season. Solid lines indicate trends found significant at p<0.01, the absence of a line indicates a non-significant trend. Error bars for estimated number of species are standard errors.
Species richness by functional groups
The seasonal contrasts in species richness seen in taxonomic groupings was preserved in the richness of functional groups benthivores, piscivores, and planktivores. The number of benthivore species averaged 58 in spring and 81 in autumn (Fig 5A); however, the autumn time series increased significantly at a rate of 6.1 species per decade over the study period whereas the spring benthivore species richness did not trend significantly. Piscivore species richness averaged 34 and 47 in spring and autumn, respectively; they increased significantly in both seasons at 2.0 and 3.2 species per decade, respectively (Fig 5B). Similarly, planktivores species richness averaged 24 and 36 in spring and autumn, respectively; they increased significantly at rates of 1.3 and 1.9 species per decade, respectively (Fig 5C).
Estimated species richness as number of species for Benthivores (a), Piscivores (b), and Planktivores (c) taxa over the core strata of the survey by season. Solid lines indicate trends found significant at p<0.01, the absence of a line indicates a non-significant trend. Error bars for estimated number of species are standard errors.
Species richness by latitudinal bands
Analysis of species richness by latitudinal band revealed gradients of richness and of the rate of change in richness. In both spring and autumn, the northern latitude band tended to have the lowest species richness, averaging 75 and 85 species, respectively (Fig 6A). The middle latitude band had species richness values that were slightly higher at 88 and 115 species in spring and autumn, respectively (Fig 6B). The southern band had substantially higher species richness of 151 and 201 species in spring and autumn, respectively (Fig 6C). A reverse pattern emerged in the trend data, where northern and middle bands had significantly increasing trends in both seasons, whereas the southern band trends were non-significant in both seasons (Table 3).
Estimated species richness as number of species for the northern (a), middle (b), and southern (c) latitude band over the core strata of the survey by season. Solid lines indicate trends found significant at p<0.01, the absence of a line indicates a non-significant trend. Error bars for estimated number of species are standard errors.contour.
Theil–Sen estimators of trend (expressed as decadal rates) by latitude band and season with associated p-value of Mann-Kendall Test For Monotonic Trend.
Relationship between species richness and biomass and temperature
Species richness was positively correlated with both biomass and temperature, though there were differences in the seasonal correlations and the correlations partitioned by taxonomic and functional groups. Species richness of all species was positively correlated with system biomass, surface temperature, and bottom temperature in spring (Fig 7A–7C) and in autumn (Fig 8A–8C), noting the correlations in autumn were significant at p<0.01. Species richness of vertebrates was positively correlated with all three of the system driver variables in both spring (Fig 7D–7F) and autumn (Fig 8D–8F). However, invertebrate species richness was not significantly correlated with the temperature drivers in spring (Fig 7G–7I), whereas these correlations were significant in autumn (Fig 8G–8I). Species richness of superclass Osteichthyes and Chondrichthyes fishes were significantly correlated with system driver variables in spring (Fig 7J–7O) and in all but the Chondrichthyes and bottom temperature correlation in autumn (Fig 8J–8O). In spring, species richness of all three functional groups was significantly correlated with bottom temperature and benthivore richness was significantly correlated with biomass (Fig 7P–7X). In autumn, the same set of functional group correlates were also significant, with additional significant correlations between surface temperature with benthivores and piscivores (Fig 8P–8X).
Scatterplots of species richness as number of species by taxonomic and functional groups versus NES Biomass, mean annual surface temperature (ST), and mean annual bottom temperature (BT). Species groups include: All species (ALL, a,b,c); vertebrates (VER, d,e,f); invertebrates (INV, g,h,i); Osteichthyes (OST, j,k,l); Chondrichthyes (CHO, m,n,o); Benthivores (BEN, p,q,r); Piscivores (PIS, s,t,u); and, Planktivores (PLA, v,w,x). In each scatterplot, the absence of line indicate a non- significant correlation with a p>0.05, dashed line indicates a significant correlation of p≤0.05, and a solid line indicates a significant correlation of p≤0.01.
Scatterplots of species richness as number of species by taxonomic and functional groups versus NES Biomass, mean annual surface temperature (ST), and mean annual bottom temperature (BT). Species groups include: All species (ALL, a,b,c); vertebrates (VER, d,e,f); invertebrates (INV, g,h,i); Osteichthyes (OST, j,k,l); Chondrichthyes (CHO, m,n,o); Benthivores (BEN, p,q,r); Piscivores (PIS, s,t,u); and, Planktivores (PLA, v,w,x). In each scatterplot, the absence of line indicate a non- significant correlation with a p>0.05, dashed line indicates a significant correlation of p≤0.05, and a solid line indicates a significant correlation of p≤0.01.
Discussion
As seen in other temperate marine ecosystems, species richness in the NES has changed in recent decades concomitantly with changes in climate conditions [33]. We observed major changes in species richness as a function of season, latitude, taxon, and functional group, which we explore in more detail below.
Interpretations of seasonal and geographic changes in the NES
The Gulf of Maine, at the northern end of the NES, is one of the most rapidly warming marine ecosystems in the global ocean [34], further enhanced by the appearance of marine heatwaves since 2012. One of the features of warming in the Gulf of Maine is the lengthening of summer and the delay in the breakdown of stratification in the autumn, which has been more pronounced and consistent than changes in spring phenology [51,52]. While the spring is typically distinguished by a major phytoplankton bloom with high species richness [51,53], followed by the emergence of large copepod Calanus finmarchicus [54,55], autumn dynamics are more variable. In autumn, the phytoplankton blooms can last longer and be associated with greater richness in the zooplankton community [51,56]. Our estimates of richness from core strata in the bottom trawl survey revealed a notable increase of approximately 10.8 species per decade in the spring and 16.5 species per decade in the autumn. The differences in changes to seasonal species richness appear to reflect the asymmetry in seasonal temperature change in the NES. Throughout the NES, sea surface temperature increased significantly in the warm portion of the year over summer into autumn and has resisted change in the cool portion during winter and spring [8,52,57], which has likely contributed to the smaller observed changes in richness in the spring. We found that species richness in autumn was consistently higher than spring for all examined taxa, and changes in richness were statistically significant for every group we examined. Our results indicate that the increases in autumn temperatures, slower stratification breakdown, and delayed autumn cooling are likely driving major changes to species richness for both vertebrate and invertebrate taxa, and more comprehensively than in spring.
Geographically, we found that species richness increased significantly in the northern and middle latitude bands in our study area, including the Gulf of Maine, whereas there was no significant change in richness in the southern band (Table 3). The magnitude of warming was weakest in the southern band, where major warming occurred primarily during summer only [52]. The Gulf Stream Index is associated with warming in all bands, driving an earlier summer start in the southern band and later summer end in the central and northern bands [52,58]. The position of the Gulf Stream is in turn driven by the AMOC [52], which has been weakening because of climate change, resulting in faster warming rates, especially in the northern band [35].
The consequences of these geographic differences in warming rates emerge when examining the abundance and distribution of specific taxa. Major shifts have occurred in multiple trophic levels in the NES, including declines in cold-water species and increases in warm-water species [58]. Arctic copepods have been less abundant since 2012, whereas warm-water copepods have increased over the same time period [59,60]. Other changes in the zooplankton assemblage include elevated counts of thaliaceans, larvaceans, and gastropods [59]. Changes in Labrador Current transport as well as temperatures drive zooplankton community composition in the Gulf of Maine and Georges Bank [61]. These changes in zooplankton communities may alter the timing, quality, and quantity of prey available for fish, marine mammals, and seabirds [26]. Among fishes, trawl surveys have found elevated counts of uncommon warm-water species like butterfish (Peprilus triacanthus), mackerel (Scomber scombrus), shortfin squid (Illex illecebrosus), and black-belly rosefish (Helicolenus dactylopertus) in the last 15 years [62], and these species have also become abundant in seabird chick diets over the same period [63,64]. Since 2014, rare species also began appearing consistently in trawl surveys and commercial catches with increasing biomass, necessitating new focal species in the annual summer research survey on the Bay of Fundy [62,65]. Meanwhile, cold-water species have increased their depths or moved northward to escape warming temperatures [23,52]. Thus far, the expansion and increased biomass of warm-water species into the central and northern bands appear to be the primary drivers of increasing richness in the NES; cold-water species are abundant enough to be regularly detected in bottom-trawl surveys throughout the NES, and a loss of richness has not yet occurred. However, patterns in the movements and biomass of cold-water species indicate that their ranges are shifting northward, and hint at their future replacement by warm-water species in the NES.
Temperature actuated cold edge movement of species would be more active during the warm portion of the year [66], resulting in expansion in species ranges and more species using the NES. This calls into question what the change in spring species richness reflects since species may redefine their range and habitat use based on autumn conditions and are only present in the spring survey because of changes in the warm portion of the year. We also need to be mindful of some limitations of our approach. Since only core strata were used to derive species richness trends, the change rates of species richness may be underestimated owing to the limitations of the sampling program. Conversely, in years with more sampling beyond the core strata, extant species richness numbers of all strata were higher than those of the core strata only; we can confidently predict that the NES will continue to see change in species richness with continued change in climate conditions. It is also important to keep in perspective that what we see in changes to regional-scale species richness is part of a global pattern where extinction rates are probably outpacing speciation rates [67]. Moreover, the loss of species at the ends of the global climate continuum may at some point affect the temperate range of the continuum [68].
Patterns of species richness among taxonomic and functional groupings
Although the species richness of both vertebrate and invertebrate taxa has increased in the NES, the seasonal contrast in richness change in this study was driven mostly by vertebrate species. We believe that this contrast can be attributed to life history-specific movement and dispersal patterns, which tend to be stronger among invertebrate early life history stages and among vertebrate adult stages [69]. Furthermore, the subset of invertebrates sampled in the bottom trawl survey was primarily limited to non-migratory crustaceans (crabs and shrimps) and shellfish, unlike many vertebrates that showed strong seasonal migratory patterns [70]. Whereas seasonal migration creates species richness differences among vertebrates, the absence of seasonal migration minimizes the difference in seasonal richness among invertebrates in our sample. This would also explain the similarity in the pattern and rate of change of invertebrates between spring and autumn. We therefore focus on patterns in vertebrate taxa.
Migratory patterns of vertebrate species tend to follow temperature patterns. In the past, many migratory vertebrates would move northward during the spring and summer months and depart before major temperature changes in the autumn [70]. However, owing to increases in summer duration that are primarily linked to delayed cooling in autumn, not earlier warming in spring [52,71], many migratory species may delay their return to warmer southern waters in the autumn [58], increasing the likelihood of them being detected in the bottom trawl survey [70]. Northward distributional shifts are most pronounced for species in shallow waters, including both bony and cartilaginous fish, and especially in the autumn [70,71], reflecting the strong statistical support for the increases in autumn richness that we observed across multiple vertebrate taxa. Because the magnitudes of changes to winter and spring temperatures are less [70,71], and migratory species are already likely to be detected in the spring, the increase in spring richness is comparatively much less than in autumn, especially in the southern latitude band. Differences in the magnitude of change in richness between Osteichthyes and Condrichthyes likely reflects the number of species in each taxon. There are far more species in Osteichthyes than Condrichthyes in the NES, so despite seeing major shifts northwards in species of both taxa, there are simply more teleosts that can undergo change, leading to their greater rate of increase in richness.
For non-migratory or less mobile species, temperature changes influence their productivity and survival, leading to gradual changes in abundance [39,58,70]. Warming waters at the northern end of their range can lead to some species expanding their thermal habitat and achieve higher growth rates [70]. At the southern end of their range, growth may be inhibited by high temperatures [70], and for areas with complex bathymetry, habitat fragmentation can occur as waters warm, where previously appropriate thermal habitat is no longer contiguous, forcing these species to move to cooler waters [58]. For species occupying deeper water, they may also be able to adjust their depths and find appropriate thermal habitat vertically, rather than necessitating northward movements to the same extent as shallow-water species [71,72], limiting the rate of their northward shifts. The result for these species is that range shifts are more gradual, slowly proliferating through population processes instead of rapid latitudinal movements to suitable thermal habitat [58]. Regardless of mobility, however, there are strong signs that thermal habitat is shrinking for many species in the NES [39,58,71], leading primarily to movements northward.
Among functional groups, mean benthivore richness was greatest, and the rate of their increase in autumn was largest compared to piscivores and planktivores. To some extent, the magnitude of these trends can be explained by the number of species in each functional group, where the number of benthivores was greatest (50%), followed by piscivores (26%) and planktivores (24%). The greater rate of richness increase in autumn also reflects the phenology of warming in the NES and vertebrate migratory strategies (see above). Benthivores–which include coastal fish, elasmobranchs, groundfish, and benthic invertebrates–are vulnerable to temperature shifts in the NES [39]. Invertebrates and groundfish were projected to be the most negatively affected by future warming, leading to future range contractions and declines in abundance and biomass [39,73]. Groundfish in many cases are at the southern edge of their ranges, and so further warming is likely to shift their distributions northward [73]. Benthic invertebrates usually have limited or no mobility, strict habitat specificity, and may also have calcareous shells susceptible to ocean acidification, which may also depress their populations in warming zones and shift their populations northward [74]. Meanwhile, coastal fishes are one of the few taxa projected to increase in range and in biomass with future warming [73]. Temperature shifts, especially by longer summers and greater autumn temperatures, are likely to drive benthivores north, and likely reflect the strong patterns we observed.
Piscivores include groundfish, pelagic fish, and elasmobranchs, and planktivores are primarily pelagic fish [39]. Zooplankton dynamics in the NES are dictated strongly by advective processes, which have changed notably over recent decades [75]. Furthermore, increases in bottom temperatures have reduced the abundance, condition, and emergence timing of Calanus, and appear to be influenced by the Gulf Stream Index and AMOC [51]. These changes to the zooplankton community may inhibit the growth and movement of planktivore species, reflected in future warming projections [73], but the high mobility of pelagic planktivores may permit them to track changes in their prey by shifting their distributions [39].
Shifts of functional groups northward can have interacting effects on future marine communities, and in the NES, changes in piscivore abundance forebode future reorganization. Range contraction and habitat fragmentation can force species into proximity, increasing competition between species [71]. The susceptibility of groundfish like cod to warming may shift the NES ecosystem from a groundfish-based predator regime to one of dogfish and silver hake [58]. Some taxa, like squids, are highly mobile and track temperature changes quickly, and change their foraging strategy based on their body size, increasing piscivory [58]. Increasing numbers of piscivores may exacerbate declines in groundfish with further warming [73].
Drivers of species richness
The close attention given to the role of temperature in defining marine fish habitats provides a natural connection between trends in species richness and temperature change. Marine fish are highly sensitive to temperature change and respond to these changes with great rapidity [76]. The positive correlation between all species and vertebrate taxa with both surface and bottom water temperatures were in concordance with similar findings elsewhere [77]. The inconsistent correlations between invertebrate species richness and temperature needs to be couched in reference to the issues with species identification of some invertebrate species and the relatively small numbers of invertebrates captured in the survey. A sample size issue may also be at work with the contrast between Osteichthyes and Chondrichthyes species richness and correlations with temperature. Most vertebrates will also be bony fish, so naturally thermal correlations with these fishes will reflect the correlations seen with vertebrate fishes. There is an absence of correlation between cartilaginous fishes and autumn bottom temperature, which we may attribute to a sample size issue as well. However, cartilaginous fishes have varying ability to thermoregulate distributionally [78], which may affect latitudinal movements of some species making them less responsive to temperature change than bony fish species. The species richness of all three functional groups, benthivores, piscivores, and planktivores, consistently correlated with bottom temperature, but are not consistently correlated with surface temperature. Since the dataset used in the study is based on a bottom tending gear, perhaps this contrast should have been more pervasive among the correlations. Though temperature has increased throughout the water column, there are nuanced differences in the progression of change in temperature at the surface and bottom [49], which may account for the contrast in the correlations.
Total species biomass is frequently utilized as an indicator of ecosystem productivity and health. Increased species biomass may enhance species’ detectability, dispersal, and connectivity, potentially contributing to a higher observed species richness. Even without significant changes in species’ distribution, an increase in abundance or biomass increases the likelihood of its detection during surveys. Increasing temperature in the NES has led to expansion of species occurrence along with increase of biomass for many taxa, with benthivores showing the fastest habitat expansion in both seasons and the highest CPUE increase rate in autumn [40]. Our results indicate that only benthivore richness exhibited a significant correlation with the system’s total biomass across both seasons, suggesting that the biomass of certain rare benthivorous species may have increased, potentially enhancing their detectability. The response of top predators to warming temperatures is primarily mediated by the impact of warming on prey availability [79]. Therefore, the increases in the biomass of top predators such as benthivores may be attributed to enhanced prey availability as they expand their habitat [80]. Species richness plays a critical role in maintaining biomass and ecosystem stability [12]. Previous studies have identified species richness as a key predictor of reef fish biomass [15]. However, comparative research in the Northeast Atlantic revealed no significant relationship between species richness and total fish biomass [14]. The relationship between biomass and species richness can differ in its interpretation depending on whether it is examined through temporal variation or across habitats with differing productivity patterns.
Species richness in context
Increased species richness presents both challenges and opportunities for fisheries and fishery management. These can include new exploitable resources and economic opportunity, competition with iconic species for habitat, trophic cascades or ecosystem re-engineering, and introduction of invasive or undesirable species. Potential impacts are illustrated by the introduction, spread, and establishment of non-indigenous species in the Mediterranean Sea [81,82]. In that ecosystem, a new shrimp species provided economic opportunity for nearshore fisheries, but it replaced the native prawn which previously supported a fishery [83]. The introduction of rabbitfish, a schooling herbivore, altered food web energy flows in rocky habitats where this niche was previously unfilled [83]. In addition, invasive jellyfish blooms have posed localized issues for communities both in terms of tourism and power generation [81]. While increased richness on the NES is not due to non-indigenous species at present, shifts in the ecological community can nevertheless alter the landscape of opportunities for fishers. For example, fisheries and markets may be set up for a certain species mix, while adaptation to a new mix may require changes in permits, equipment, and machinery. In the North and Celtic Seas, increased species richness was attributed to the increase in warmer water Lusitanian species, while Boreal species were retained in the ecosystems as well [84]. Overall, Lusitanian species tended toward smaller body sizes [84], such that fisheries could face potential market challenges due to both changing species and size distributions of the catch, with traditional species “diluted” by those species shifting in. As species richness increases, a flexible fishery management system that allows fishers to sustainably exploit novel species compositions could contribute to sustainability of fishing communities adapting to climate change [85].
Conclusions
We examined the seasonal trends in species richness of a temperate marine ecosystem finding high rates of species accretion, noting that these rates were conservatively estimated. Our intention was to construct time series estimates with greater confidence and allow for the analysis of time series properties including trends. Furthermore, we allocate these changes in richness among taxonomic and functional groups of species, finding that more mobile vertebrate taxa, especially benthivores and piscivores, account for most the pattern of richness change observed. Our estimates of change in species richness exceed other reported data [33], which heightens our concerns over how changing species composition may be affecting the assessment procedures and the application of management advice in the NES [86,87]. Our assessments need to track the changing interactions between species, including taxa newly added to the ecosystem, and how these interactions may affect assessment results. We feel that by doing so, we may be able to minimize the impacts on communities and their associated economies [88].
Supporting information
S1 Table. Scientific names of species from core strata areas of the NES used in the study.
Listing of species names used in the study.
https://doi.org/10.1371/journal.pclm.0000557.s001
(DOCX)
S1 Fig. Map of bottom trawl survey strata.
All strata shown with shading and core strata differentially shaded in red.
https://doi.org/10.1371/journal.pclm.0000557.s002
(DOCX)
S2 Fig. Total number of observed species.
Extant species counts found in all strata and only in core strata in spring (a) and autumn (b).
https://doi.org/10.1371/journal.pclm.0000557.s003
(DOCX)
Acknowledgments
We gratefully acknowledge the staff and crew of the NOAA NEFSC bottom trawl survey. We also thank the anonymous reviewers for their constructive feedback.
References
- 1. Hooper DU, Chapin FS III, Ewel JJ, Hector A, Inchausti P, Lavorel S, et al. Effects of Biodiversity on Ecosystem Functioning: A Consensus of Current Knowledge. Ecological Monographs. 2005;75: 3–35.
- 2. Peet RK. The Measurement of Species Diversity. Annual Review of Ecology and Systematics. 1974;5: 285–307.
- 3. DeJong TM. A Comparison of Three Diversity Indices Based on Their Components of Richness and Evenness. Oikos. 1975;26: 222–227.
- 4. Link J. Does food web theory work for marine ecosystems? Marine Ecology Progress Series. 2002;230: 1–9.
- 5. Carr MH, Neigel JE, Estes JA, Andelman S, Warner RR, Largier JL. Comparing Marine and Terrestrial Ecosystems: Implications for the Design of Coastal Marine Reserves. Ecological Applications. 2003;13: 90–107.
- 6. Crowder L, Norse E. Essential ecological insights for marine ecosystem-based management and marine spatial planning. Marine Policy. 2008;32: 772–778.
- 7. Thoral F, Montie S, Thomsen MS, Tait LW, Pinkerton MH, Schiel DR. Unravelling seasonal trends in coastal marine heatwave metrics across global biogeographical realms. Sci Rep. 2022;12: 7740. pmid:35545696
- 8. Friedland KD, Record NR, Pendleton DE, Balch WM, Stamieszkin K, Moisan JR, et al. Asymmetry in the rate of warming and the phenology of seasonal blooms in the Northeast US Shelf Ecosystem. ICES Journal of Marine Science. 2023;80: 775–786.
- 9. Lotze HK, Milewski I. Two Centuries of Multiple Human Impacts and Successive Changes in a North Atlantic Food Web. Ecological Applications. 2004;14: 1428–1447.
- 10.
Nisbet ICT, Nisbet ICT, Veit RR, Auer SA, White TP. Marine birds of the Eastern United States and the Bay of Fundy: distribution, numbers, trends, threats, and management. Cambridge, Massachusetts: Nuttall Ornithological Club; 2013. Available: https://www.biodiversitylibrary.org/bibliography/192850
- 11. Fukami T, Wardle DA. Long-term ecological dynamics: reciprocal insights from natural and anthropogenic gradients. Proceedings of the Royal Society B: Biological Sciences. 2005;272: 2105–2115. pmid:16191623
- 12. Danet A, Mouchet M, Bonnaffé W, Thébault E, Fontaine C. Species richness and food-web structure jointly drive community biomass and its temporal stability in fish communities. Ecology Letters. 2021;24: 2364–2377. pmid:34423526
- 13. Lefcheck JS, Edgar GJ, Stuart-Smith RD, Bates AE, Waldock C, Brandl SJ, et al. Species richness and identity both determine the biomass of global reef fish communities. Nat Commun. 2021;12: 6875. pmid:34824244
- 14. Maureaud A, Hodapp D, van Denderen PD, Hillebrand H, Gislason H, Spaanheden Dencker T, et al. Biodiversity–ecosystem functioning relationships in fish communities: biomass is related to evenness and the environment, not to species richness. Proceedings of the Royal Society B: Biological Sciences. 2019;286: 20191189. pmid:31288699
- 15. Duffy JE, Lefcheck JS, Stuart-Smith RD, Navarrete SA, Edgar GJ. Biodiversity enhances reef fish biomass and resistance to climate change. PNAS. 2016;113: 6230–6235. pmid:27185921
- 16. Blowes S, Supp S, Antão L, Bates A, Bruelheide H, Chase J, et al. Biodiversity trends are stronger in marine than terrestrial assemblages. bioRxiv; 2018. p. 457424.
- 17. Blowes SA, Supp SR, Antão LH, Bates A, Bruelheide H, Chase JM, et al. The geography of biodiversity change in marine and terrestrial assemblages. Science. 2019;366: 339–345. pmid:31624208
- 18. Hodapp D, Roca IT, Fiorentino D, Garilao C, Kaschner K, Kesner-Reyes K, et al. Climate change disrupts core habitats of marine species. Global Change Biology. 2023;29: 3304–3317. pmid:36789726
- 19. Chaudhary C, Richardson AJ, Schoeman DS, Costello MJ. Global warming is causing a more pronounced dip in marine species richness around the equator. Proceedings of the National Academy of Sciences. 2021;118: e2015094118. pmid:33876750
- 20. Jones DI, Miethe T, Clarke ED, Marshall CT. Disentangling the effects of fishing and temperature to explain increasing fish species richness in the North Sea. Biodivers Conserv. 2023;32: 3133–3155.
- 21. Kitchel ZJ, Pinsky ML. Regional species gains outpace losses across North American continental shelf regions. Global Ecology and Biogeography. 2023;32: 1205–1217.
- 22. Kleisner KM, Fogarty MJ, McGee S, Hare JA, Moret S, Perretti CT, et al. Marine species distribution shifts on the US Northeast Continental Shelf under continued ocean warming. Prog Oceanogr. 2017;153: 24–36.
- 23. Nye JA, Link JS, Hare JA, Overholtz WJ. Changing spatial distribution of fish stocks in relation to climate and population size on the Northeast United States continental shelf. Mar Ecol-Prog Ser. 2009;393: 111–129.
- 24. Richardson AJ. In hot water: zooplankton and climate change. ICES Journal of Marine Science. 2008;65: 279–295.
- 25. Staudinger MD, Lynch AJ, Gaichas SK, Fox MG, Gibson-Reinemer D, Langan JA, et al. How Does Climate Change Affect Emergent Properties of Aquatic Ecosystems? Fisheries. 2021;46: 423–441.
- 26. Ratnarajah L, Abu-Alhaija R, Atkinson A, Batten S, Bax NJ, Bernard KS, et al. Monitoring and modelling marine zooplankton in a changing climate. Nat Commun. 2023;14: 564. pmid:36732509
- 27. Benedetti F, Ayata S-D, Irisson J-O, Adloff F, Guilhaumon F. Climate change may have minor impact on zooplankton functional diversity in the Mediterranean Sea. Diversity and Distributions. 2019;25: 568–581.
- 28. Möllmann C, Müller-Karulis B, Kornilovs G, St John MA. Effects of climate and overfishing on zooplankton dynamics and ecosystem structure: regime shifts, trophic cascade, and feedback loops in a simple ecosystem. ICES Journal of Marine Science. 2008;65: 302–310.
- 29. Thompson MSA, Couce E, Schratzberger M, Lynam CP. Climate change affects the distribution of diversity across marine food webs. Global Change Biology. 2023;29: 6606–6619. pmid:37814904
- 30. Gordó-Vilaseca C, Stephenson F, Coll M, Lavin C, Costello MJ. Three decades of increasing fish biodiversity across the northeast Atlantic and the Arctic Ocean. Proceedings of the National Academy of Sciences. 2023;120: e2120869120. pmid:36656855
- 31. Hu W, Du J, Su S, Tan H, Yang W, Ding L, et al. Effects of climate change in the seas of China: Predicted changes in the distribution of fish species and diversity. Ecological Indicators. 2022;134: 108489.
- 32. Thompson PL, Anderson SC, Nephin J, Haggarty DR, Peña MA, English PA, et al. Disentangling the impacts of environmental change and commercial fishing on demersal fish biodiversity in a northeast Pacific ecosystem. Marine Ecology Progress Series. 2022;689: 137–154.
- 33. Batt RD, Morley JW, Selden RL, Tingley MW, Pinsky ML. Gradual changes in range size accompany long-term trends in species richness. Ecol Lett. 2017;20: 1148–1157. pmid:28699209
- 34. Pershing AJ, Alexander MA, Hernandez CM, Kerr LA, Le Bris A, Mills KE, et al. Slow adaptation in the face of rapid warming leads to collapse of the Gulf of Maine cod fishery. Science. 2015;350: 809–812. pmid:26516197
- 35. Saba VS, Griffies SM, Anderson WG, Winton M, Alexander MA, Delworth TL, et al. Enhanced warming of the Northwest Atlantic Ocean under climate change. J Geophys Res-Oceans. 2016;121: 118–132.
- 36. Todd RE, Ren AS. Warming and lateral shift of the Gulf Stream from in situ observations since 2001. Nat Clim Chang. 2023;13: 1348–1352.
- 37. Gonçalves Neto A, Palter JB, Xu X, Fratantoni P. Temporal Variability of the Labrador Current Pathways Around the Tail of the Grand Banks at Intermediate Depths in a High-Resolution Ocean Circulation Model. Journal of Geophysical Research: Oceans. 2023;128: e2022JC018756.
- 38. Jackson LC, Biastoch A, Buckley MW, Desbruyères DG, Frajka-Williams E, Moat B, et al. The evolution of the North Atlantic Meridional Overturning Circulation since 1980. Nat Rev Earth Environ. 2022;3: 241–254.
- 39. Hare JA, Morrison WE, Nelson MW, Stachura MM, Teeters EJ, Griffis RB, et al. A Vulnerability Assessment of Fish and Invertebrates to Climate Change on the Northeast US Continental Shelf. Plos One. 2016;11. pmid:26839967
- 40. Friedland KD, Langan JA, Large SI, Selden RL, Link JS, Watson RA, et al. Changes in higher trophic level productivity, diversity and niche space in a rapidly warming continental shelf ecosystem. Science of the Total Environment. 2020;704: 135270. pmid:31818590
- 41. Friedland KD, Ganley LC, Dimarchopoulou D, Gaichas S, Morse RE, Jordaan A. Change in body size in a rapidly warming marine ecosystem: Consequences of tropicalization. Science of The Total Environment. 2023;903: 166117. pmid:37572904
- 42. Collie JS, Wood AD, Jeffries HP. Long-term shifts in the species composition of a coastal fish community. Can J Fish Aquat Sci. 2008;65: 1352–1365.
- 43. Desprespatanjo LI, Azarovitz TR, Byrne CJ. 25 Years of Fish Surveys in the Northwest Atlantic—the NMFS Northeast Fisheries Centers Bottom Trawl Survey Program. Mar Fish Rev. 1988;50: 69–71.
- 44. Bell RJ, Richardson DE, Hare JA, Lynch PD, Fratantoni PS. Disentangling the effects of climate, abundance, and size on the distribution of marine fish: an example based on four stocks from the Northeast US shelf. Ices J Mar Sci. 2015;72: 1311–1322.
- 45. Miller TJ, Das C, Politis PJ, Miller AS, Lucey SM, Legault CM, et al. Estimation of Albatross IV to Henry B. Bigelow calibration factors. NEFSC Ref Doc 10–05. 2010; 238.
- 46. Smith EP, van Belle G. Nonparametric Estimation of Species Richness. Biometrics. 1984;40: 119–129.
- 47. Mann HB. Nonparametric tests against trend. Econometrica. 1945;13: 245–259.
- 48. Yue S, Pilon P, Phinney B, Cavadias G. The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrol Process. 2002;16: 1807–1829.
- 49. Friedland KD, Morse RE, Manning JP, Melrose DC, Miles T, Goode AG, et al. Trends and change points in surface and bottom thermal environments of the US Northeast Continental Shelf Ecosystem. Fisheries Oceanography. 2020;29: 396–414.
- 50. Friedland KD, Tanaka KR, Smoliński S, Wang Y, Hodgdon C, Mazur M, et al. Trends in Area of Occurrence and Biomass of Fish and Macroinvertebrates on the Northeast U.S. Shelf Ecosystem. Marine and Coastal Fisheries. 2023;15: e10235.
- 51. Record NR, Balch WM, Stamieszkin K. Century-scale changes in phytoplankton phenology in the Gulf of Maine. PeerJ. 2019;7: e6735. pmid:31106049
- 52. Thomas AC, Pershing AJ, Friedland KD, Nye JA, Mills KE, Alexander MA, et al. Seasonal trends and phenology shifts in sea surface temperature on the North American northeastern continental shelf. Elem Sci Anth. 2017;5: 1–17.
- 53. Kane J. Multiyear variability of phytoplankton abundance in the Gulf of Maine. ICES J Mar Sci. 2011;68: 1833–1841.
- 54.
Jossi JW, Kane JM. An atlas of the dominant zooplankton collected along a continuous plankton recorder transect between Massachusetts USA and Cape Sable NS, 1961–2008. Northeast Fisheries Science Center (U.S.), editor. 2013. Available: https://repository.library.noaa.gov/view/noaa/4563
- 55. Staudinger MD, Mills KE, Stamieszkin K, Record NR, Hudak CA, Allyn A, et al. It’s about time: A synthesis of changing phenology in the Gulf of Maine ecosystem. Fisheries Oceanography. 2019;28: 532–566. pmid:31598058
- 56. Johnson CL, Runge JA, Curtis KA, Durbin EG, Hare JA, Incze LS, et al. Biodiversity and Ecosystem Function in the Gulf of Maine: Pattern and Role of Zooplankton and Pelagic Nekton. Plos One. 2011;6. pmid:21304990
- 57. Friedland KD, Hare JA. Long-term trends and regime shifts in sea surface temperature on the continental shelf of the northeast United States. Cont Shelf Res. 2007;27: 2313–2328.
- 58. Pershing AJ, Alexander MA, Brady DC, Brickman D, Curchitser EN, Diamond AW, et al. Climate impacts on the Gulf of Maine ecosystem: A review of observed and expected changes in 2050 from rising temperatures. Elementa: Science of the Anthropocene. 2021;9: 00076.
- 59. Government of Canada. Optical, chemical, and biological oceanographic conditions on the Scotian Shelf and in the eastern Gulf of Maine in 2016. 2018 [cited 14 May 2024]. Available: https://publications.gc.ca/site/eng/9.860959/publication.html
- 60. Government of Canada. Chemical and biological oceanographic conditions on the Scotian Shelf and in the eastern Gulf of Maine during 2022. 2024 [cited 14 May 2024]. Available: https://publications.gc.ca/site/eng/9.933052/publication.html
- 61. Batchelder HP, Daly KL, Davis CS, Ji R, Ohman MD. Climate Impacts on Zooplankton Population Dynamics in Coastal Marine Ecosystems | Oceanography. Oceanography. 2013;26: 34–51.
- 62. Government of Canada. Maritimes research vessel survey trends on the Scotian Shelf and Bay of Fundy. 2018 [cited 14 May 2024]. Available: https://publications.gc.ca/site/eng/9.866582/publication.html
- 63. Scopel L, Diamond A, Kress S, Shannon P. Varied breeding responses of seabirds to a regime shift in prey base in the Gulf of Maine. Marine Ecology Progress Series. 2019;626: 177–196.
- 64. Scopel LC. Developing seabird bioindicators for the Gulf of Maine: a demographic study of an Arctic Tern (Sterna paradisaea) metapopulation. 2022 [cited 14 May 2024]. Available: https://unbscholar.lib.unb.ca/handle/1882/37435
- 65. Government of Canada. Maritimes research vessel survey trends on the Scotian Shelf and Bay of Fundy. 2024;Science Response 2024/010. Available: https://publications.gc.ca/site/eng/9.866582/publication.html
- 66. Fredston-Hermann A, Selden R, Pinsky M, Gaines SD, Halpern BS. Cold range edges of marine fishes track climate change better than warm edges. Global Change Biology. 2020;26: 2908–2922. pmid:32037696
- 67. Dornelas M, Chase JM, Gotelli NJ, Magurran AE, McGill BJ, Antão LH, et al. Looking back on biodiversity change: lessons for the road ahead. Philosophical Transactions of the Royal Society B: Biological Sciences. 2023;378: 20220199. pmid:37246380
- 68. Brandl SJ, Johansen JL, Casey JM, Tornabene L, Morais RA, Burt JA. Extreme environmental conditions reduce coral reef fish biodiversity and productivity. Nat Commun. 2020;11: 3832. pmid:32737315
- 69. Allen RM, Metaxas A, Snelgrove PVR. Applying Movement Ecology to Marine Animals with Complex Life Cycles. Annual Review of Marine Science. 2018;10: 19–42. pmid:28813201
- 70. Henderson ME, Mills KE, Thomas AC, Pershing AJ, Nye JA. Effects of spring onset and summer duration on fish species distribution and biomass along the Northeast United States continental shelf. Rev Fish Biol Fisher. 2017;27: 411–424.
- 71. Kleisner KM, Fogarty MJ, McGee S, Barnette A, Fratantoni P, Greene J, et al. The Effects of Sub-Regional Climate Velocity on the Distribution and Spatial Extent of Marine Species Assemblages. Plos One. 2016;11. pmid:26901435
- 72. Walsh HJ, Richardson DE, Marancik KE, Hare JA. Long-Term Changes in the Distributions of Larval and Adult Fish in the Northeast U.S. Shelf Ecosystem. PLOS ONE. 2015;10: e0137382. pmid:26398900
- 73. Allyn AJ, Alexander MA, Franklin BS, Massiot-Granier F, Pershing AJ, Scott JD, et al. Comparing and synthesizing quantitative distribution models and qualitative vulnerability assessments to project marine species distributions under climate change. PLOS ONE. 2020;15: e0231595. pmid:32298349
- 74. Gaichas SK, Link JS, Hare JA. A risk-based approach to evaluating northeast US fish community vulnerability to climate change. ICES Journal of Marine Science. 2014;71: 2323–2342.
- 75. Record N, Kenney R, Balch W, Davies K, Pershing A, Johnson C, et al. Rapid Climate-Driven Circulation Changes Threaten Conservation of Endangered North Atlantic Right Whales. Oceanog. 2019;32.
- 76. Pinsky ML, Fenichel E, Fogarty M, Levin S, McCay B, St. Martin K, et al. Fish and fisheries in hot water: What is happening and how do we adapt? Population Ecology. 2021;63: 17–26.
- 77. Antão LH, Bates AE, Blowes SA, Waldock C, Supp SR, Magurran AE, et al. Temperature-related biodiversity change across temperate marine and terrestrial systems. Nat Ecol Evol. 2020;4: 927–933. pmid:32367031
- 78. Osgood GJ, White ER, Baum JK. Effects of climate-change-driven gradual and acute temperature changes on shark and ray species. Journal of Animal Ecology. 2021;90: 2547–2559. pmid:34145907
- 79. Robinson B, Coletti HA, Ballachey B, Bodkin JL, Kloecker K, Traiger SB, et al. Lack of strong responses to the Pacific marine heatwave by benthivorous marine birds indicates importance of trophic drivers. Marine Ecology Progress Series. 2024;737: 215–226.
- 80. Engelhard GH, Ellis JR, Payne MR, ter Hofstede R, Pinnegar JK. Ecotypes as a concept for exploring responses to climate change in fish assemblages. ICES Journal of Marine Science. 2011;68: 580–591.
- 81. Galil BS, Marchini A, Occhipinti-Ambrogi A. East is east and West is west? Management of marine bioinvasions in the Mediterranean Sea. Estuarine, Coastal and Shelf Science. 2018;201: 7–16.
- 82. Galil BS, Boero F, Campbell ML, Carlton JT, Cook E, Fraschetti S, et al. ‘Double trouble’: the expansion of the Suez Canal and marine bioinvasions in the Mediterranean Sea. Biol Invasions. 2015;17: 973–976.
- 83. Galil BS. Loss or gain? Invasive aliens and biodiversity in the Mediterranean Sea. Marine Pollution Bulletin. 2007;55: 314–322. pmid:17222869
- 84. Hofstede R ter Hiddink JG, Rijnsdorp AD. Regional warming changes fish species richness in the eastern North Atlantic Ocean. Marine Ecology Progress Series. 2010;414: 1–9.
- 85. Golden AS, Baskett ML, Holland D, Levine A, Mills K, Essington T. Climate adaptation depends on rebalancing flexibility and rigidity in US fisheries management. ICES Journal of Marine Science. 2024;81: 252–259.
- 86. Wiedenmann J, Legault CM. Something strange in the neighborhood: Diverging signals in stock assessment data for Northeast U.S. fish stocks. Fisheries Management and Ecology. 2022;29: 269–285.
- 87. Mills KE, Kemberling A, Kerr LA, Lucey SM, McBride RS, Nye JA, et al. Multispecies population-scale emergence of climate change signals in an ocean warming hotspot. ICES Journal of Marine Science. 2024;81: 375–389.
- 88. Cheung WWL, Frölicher TL, Lam VWY, Oyinlola MA, Reygondeau G, Sumaila UR, et al. Marine high temperature extremes amplify the impacts of climate change on fish and fisheries. Science Advances. 2021;7: eabh0895. pmid:34597142