Climate-driven invasion and incipient warnings of kelp ecosystem collapse

Domain: earth_science
Published: 2024-01-09
Editorial outcome: accept

Abstract
Climate change is progressively redistributing species toward the Earth’s poles, indicating widespread potential for ecosystem collapse. Detecting early-warning signals and enacting adaptation measures is therefore a key imperative for humanity. However, detecting early-warning signals has remained elusive and has focused on exceptionally high-frequency and/or long-term time-series, which are generally unattainable for most ecosystems that are under-sampled and already impacted by warming. Here, we show that a catastrophic phase-shift in kelp ecosystems, caused by range-extension of an overgrazing sea urchin, also propagates poleward. Critically, we show that incipient spatial-pattern-formations of kelp overgrazing are detectable well-in-advance of collapse along temperate reefs in the ocean warming hotspot of south-eastern Australia. Demonstrating poleward progression of collapse over 15 years, these early-warning ‘incipient barrens’ are now widespread along 500 km of coast with projections indicating that half of all kelp beds within this range-extension region will collapse by ~2030. Overgrazing was positively associated with deep boulder-reefs, yet negatively associated with predatory lobsters and subordinate abalone competitors, which have both been intensively fished. Climate-driven collapse of ecosystems is occurring; however, by looking equatorward, space-for-time substitutions can enable practical detection of early-warning spatial-pattern-formations, allowing local climate adaptation measures to be enacted in advance.

Introduction
Global climate change is causing widespread re-distribution of species and leading to cascading ecological change1. Concerningly, dire predictions of climate change warn of nonlinear “catastrophic” collapse with profound ecological, social and economic consequences2. Therefore, the capacity to learn quickly from early-warning signals of climate-driven collapse3,4 is fundamental if such unwanted and irreversible changes are to be understood and ultimately avoided. The notion of acting ‘before it is too late’ is predicated on detecting warning signals of collapse well in advance, thus much theoretical and practical focus has attempted to define this holy grail2–4.

Detection of early-warning signals has centered on the notion of ‘critical slowing down’ in high-frequency ecological time-series data typically obtained from spatially constrained systems using computationally intensive methods3,4. However, relatively few ecosystems are sampled frequently enough, over long enough, for such metrics to be practically useful5. In contrast, many ecosystems are experiencing accelerating and pervasive signatures of climate change impacts1, which are occurring much faster than high-frequency long-term ecological baselines can be established from which early-warning metrics may be statistically defined4.

For the threat of collapse posed by climate-driven species redistributions, early warnings may be signaled by detecting changes in spatial pattern formation6 as warm-environment species advance their range poleward into historically cooler ecosystems across the globe7. In the marine environment of southeastern Australia, the East Australian Current (EAC) has strengthened over the past 60-years resulting in greater poleward penetration of warm water and an approximate quadrupling of ocean warming rates compared to the global average8. Here, this pronounced change in the physical oceanography corroborates with increasing observations of poleward range-extensions of ~70 marine species from New South Wales (NSW) to eastern Tasmania in recent decades9,10.

Of the species documented to have undergone range-extension to Tasmania, the warmwater Diadematid sea urchin Centrostephanus rodgersii (Agassiz) has extended its range south by ~700 km and is a most conspicuous and ecologically important arrival11–13 due to its ability to destructively overgraze kelp forest habitat (Fig. 1a–d). The cascading impacts of overgrazing by C. rodgersii are profound, with a local loss of over 150 species, including highly lucrative commercial species such as abalone and rock lobster, that live amongst kelp habitat11. Within the central and southern NSW native range of C. rodgersii, this urchin, via its obligate scrapping mode of feeding on macroalgae including consuming holdfasts and juvenile macroalgal recruits, maintains barrens over more than 50% of all shallow reef14 and similar levels of overgrazing are now apparent at some sites in northeast Tasmania. Sites most heavily impacted by overgrazing have warmed beyond the minimal thermal threshold for the urchins’ development15, with proximity of reefs to the EAC driving a steep latitudinal gradient in recruitment and population size dynamics southward along the Tasmanian east coast12 (Fig. 1a). At local scales, field experiments comparing urchin survival inside versus outside Marine Protected Areas showed that urchin abundance is reduced in the presence of large predatory-capable spiny lobsters which have been functionally extirpated across much of the east coast due to intensive harvesting13.

This range-extending urchin was first detected in Tasmanian waters in 1960 and on the mainland northeast Tasmania at St. Helens in 1978 (Fig. 1a) with early-warning signs of overgrazing first apparent in eastern Tasmania during the early 2000s when small locally grazed patches within otherwise intact kelp forests were observed and termed ‘incipient barrens’16. Incipient barrens represent a transient state progressing from small grazed patches (~1 m2 scale) that become more numerous and coalesce to ultimately collapse kelp and form extensive barrens (10,000–1,000,000 m2 scale) as urchin abundance locally increases (Fig. 1a–d). Based on a priori understanding of the urchin’s destructive habit and the appearance of incipient barren spatial pattern formations8, the range-extending urchin loomed as a major threat to the structure and functioning of Tasmanian reef systems9. Recognizing this threat was of critical importance as urchin overgrazing represents a “catastrophic phase-shift”17, with collapse of productive kelp forests to low-value extensive urchin barren grounds ensured if range-extending urchin abundance exceeds the overgrazing tipping-point (approx. urchin biomass of 700 grams m−2; or ~≥2.2 urchins m−2). Contrastingly, recovery of kelp is very difficult once barrens have formed due to hysteresis, as the tipping-point for kelp recovery is almost a magnitude lower (approx. urchin biomass of 70 grams m−2; or ~≤0.36 urchins m−2)17. Urchin barrens, therefore, represent an alternative stable state that can be practically irreversible as urchins persist by switching diets from large kelps to microscopic and encrusting algae17.

Here, we examine space-time dynamics of nonlinear ecosystem collapse over a 15-year period and examine the presence of incipient barren signals across the chronically warming coastline of eastern Tasmania (Fig. 1b–d). If early-warning signals are ultimately detectable, then knowing how to act, before it is too late, is contingent on understanding mitigating ecological circumstances. Thus, we also explore mechanisms of urchin invasion and overgrazing, respectively for different abiotic (i.e., reef substratum types/depth) and biotic covariates (i.e., predatory spiny lobsters plus competing native urchins and abalone abundances).

Results
Across the region of range-extension (Sites 1–13), dive surveys to 18 m depth revealed the range-extending urchins’ abundance to increase significantly from an average density of 0.10 (±0.05 SE; n=13 sites) to 0.18 (±0.06 SE, n=13 sites) individ m−2 from 2001/02 to 2016/17 (Fig. 2a; Supplementary Table 1a; with site means calculated hierarchically from the mean of 3 subsites per site, with subsite means calculated from mean of 4 transects per subsite within each period). This x1.8 increase over 15 years equated to a compounding rate of population increase of 3.8% per annum. However, abundance of the range-extending urchin was uneven at the ~20 km site-scale (chiefly related to the proximity to the East Australian Current8,12), a feature which persisted through time (i.e., nil site-by-time interaction effect), and increase in abundance varied significantly at the local ~2 km subsite-scale (Supplementary Table 1a). For eastern Tasmania where overgrazing manifested (Sites 1–9), urchin abundance increased significantly from an average of 0.15 (±0.06 SE, n=9 sites) to 0.26 (±0.07 SE, n=9 sites) individ m−2 (Fig. 2a); equating to an increase in abundance of x1.7 over 15 years. Contrastingly, for this section of coast, dive surveys revealed barrens to increase in cover by a factor of x3.9, from 2.3% (±1.6% SE, n=9 sites) to 9.0% (±3.9% SE, n=9 sites) cover (which also varied significantly at the subsite-scale, see Supplementary Table 1b), equating to a compounding rate of barrens increase of 9.5% pa (Fig. 2b).

The disproportionate collapse of kelp to barrens relative to increases in urchin density was revealed by an overall steepening in the negative trend between kelp cover and urchin abundance (Fig. 2c). Notably, the overgrazing collapse of kelp cover was counter to an overall increase in kelp cover outside of reef areas grazed by urchins, with kelp cover on a non-grazed reef in eastern Tasmania increasing from 2001/02 to 2016/17 due to compensatory thickening in cover of lower-lying warm-tolerant stipitate species (i.e., Ecklonia radiata & Phyllospora comosa) in the absence of surface-canopy giant kelp forests (formed by Macrocystis pyrifera) which declined (Supplementary Table 2). Divers also revealed a greater increase in urchin abundance on deeper reefs, particularly on large boulder reef >8 m depth (Fig. 3a–c; Supplementary Table 3a). Similarly, barrens also increased disproportionately in deeper water, with increases also greatest for large boulder reef (Fig. 3d–f; Supplementary Table 3b). Multiple regression showed a significant positive association between the range-extending sea urchin and native urchin (Heliocidaris erythrogramma), while both urchin species were negatively associated with predatory spiny lobsters (Jasus edwardsii) (Supplementary Table 4a). Abalone (Haliotis rubra) was negatively associated with urchin barrens (Supplementary Table 4b).

Extensive underwater towed-video covering 80 km in each survey period from 4 m to 40 m depth, revealed cover of early-warning ‘incipient barrens’ (categorized as three increasing patch-sizes) and fully collapsed ‘continuous barrens’ to all increase significantly through time across eastern Tasmania (Fig. 4a-d; see summary statistics Supplementary Table 5a–d). Greatest increase occurred for the smallest size-class of incipient barrens, i.e., the earliest forewarning of collapse (Fig. 4a). Medium and large incipient barrens, as well as continuous barrens, increased consistently through time across sites (Fig. 4b, c), while small incipient barrens increased significantly at some sites but not at others where barrens had already expanded to larger patch sizes (Fig. 4d; Supplementary Table 5d). At the ~2 km subsite scale, increases in medium-to-large incipient barrens and continuous barrens varied significantly, yet evenness in the increase in small incipient barrens occurred at this scale (Supplementary Table 5a–d). Overall planar cover of barrens more than quadrupled from 3.4% to 15.2% (Fig. 4e), with significant variability in increase among subsites (Supplementary Table 5e). Increase in barrens equated to an expansion rate of 10.5% pa, with a projection of this unmitigated rate indicating barrens cover is poised to increase to ~50% in eastern Tasmania (Sites 1–9) as soon as the year 2029, consistent with that observed locally at St. Helens (Site 2) and as observed in NSW14.

Methods
In 2016/17, scientific divers repeated the same methods used to survey 13 eastern Tasmanian sites (Fig. 1a) as originally surveyed during the 2001/02 ‘first assessment of the threat of C. rodgersii’16. Sampling in both periods involved the consistent survey of a spatially hierarchical arrangement of 4 diver transects (spaced at ~200 m apart) at each of 3 subsites (spaced at ~2 km) within each of the 13 sites (spaced at ~20 km), giving 156 individual diver transects in total spanning 400 km from northeast to southern Tasmania. GPS was used to locate both the start and end positions of transects, which were set perpendicular to the shore, extending from ~4 m depth to a maximum of 18 m depth or a maximum total length of 100 m if the maximum seaward depth was shallower than 18 m. Based on reef topography across all sites, transects were ~50 m in length on average. On each transect line, a pair of buddy divers surveyed a 1 m swath each side of the transect line and for each 5 m section along the transect (giving a base contiguous quadrat size of 5 m2), recorded on slates the depth and abundance of urchins (C. rodgersii and Heliocidaris erythrogramma—noting that H. erythrogramma is not observed to form barrens on the open coast study region of eastern Tasmania31), southern rock lobster and blacklip abalone. Planar cover of substratum types within each contiguous 5 m by 1 m quadrat was estimated to the nearest 5%, i.e., resolved to a 0.5 by 0.5 m area, with substratum classified as either flat rock (>5 m effective diameter), large boulders (>1 m and <5 m diameter), small boulders (>0.2 m and <1 m diameter), cobble (>0.1 m and <0.20 m diameter), pebble (>0.01 m and <0.10 m diameter), gravel (<0.01 m diameter), or sand.

In addition to the temporal survey, a snapshot of barrens patch-sizes across eastern Tasmania (see inset Fig. 1a) was estimated in situ by divers at sites 2, 5, 6, 7, 8, 9 from 2008 to 2011. A total of 76 geo-referenced timed swims (surface GPS towed by a diver for 30–45 min and ranging up to 550 m in length) spanning 5 to 15 m depth were conducted whereby divers searched for and scored barrens patch-sizes using a 1×1 m quadrat for calibration. The sizes of 1297 individual barrens patches were estimated in this way. Note that a barrens patch is an area of reef where all the kelp within the patch has been completely grazed away by urchins, resulting in bare-rock or encrusting/turfing filamentous algal forms (e.g., Fig. 4a, b insets), i.e., the percentage cover of kelp within a barrens patch is 0%, or alternatively 100% barren cover. As barrens patches become larger, urchin abundance within the barren also increases24.

Percentage cover of urchin barrens was assessed by two methods: In situ SCUBA diver assessment along the same transects where urchin and invertebrate counts were recorded in depths from 4–18 m; and towed-underwater-video enabling sampling of barrens in depths >18 m and much greater spatial coverage. Diver-transect estimation of barrens cover, as per in situ assessment of substratum cover, involved each diver estimating the percentage cover of sea urchin barrens to the nearest 5% within 5 m by 1 m quadrats. Reef classified as urchin barrens were characterized as intensively grazed by locally abundant urchins, which was discernible from reef lacking foliose macroalgae for other reasons, e.g., scour, and/or dominance of sessile invertebrates.

Broader kilometer-scale patterns in barrens cover were estimated using a towed-underwater-video camera system. The spatially hierarchical sampling design was as per diver surveys, except that at the subsite level, two video transects were run perpendicular and two transects ran parallel with the shore. Perpendicular transects spanned 4–40 m depth (profiling available reef from the sand edge to shore), while parallel transects focused on the 15 m depth contour where C. rodgersii densities were observed to reach peak levels during original dive surveys. Parallel tows were ~1 km in length in straight-line distance, with the total surveyed distance of perpendicular and parallel video transects across all sites >80 km of reef in each survey period and the same start and end GPS of transects were used in each sampling period.

The video camera was towed ~1–2 m above the seafloor and/or algal canopy, which provided a swath width of ~3–4 m. Recorded video footage was time-stamped using onboard laptop computer dually capturing time, date, GPS position and depth via depth sounder. GPS information related to the boat, while the camera was offset on a towline ~20–30 m behind the boat which varied depending on depth and speed. Video footage was post-processed in the laboratory with barrens types classified for contiguous ~10 m intervals along each transect, which were summed and converted to percentages of the total transect length. Barrens were classified in four types: i.e., ‘continuous’ barrens whereby >85% barrens cover occurred within the camera field of view for 10 m, while the other three categories are different types of ‘patchy’ incipient barrens. ‘Large’ incipient barrens were defined as patchy barren where barrens covered >40% but <85% of the reef; ‘Medium’ incipient barrens defined patchy barren in which barrens occupied between 20–40% cover; while ‘Small’ incipient barrens referred to patchy barren where barren cover was <20% cover. To obtain an overall planar estimate of barrens cover across all barrens categories, the proportion of each barrens type for each transect was multiplied by the mid-point of barrens cover as defined for that barrens type and then summed. That is, the percentage of ‘continuous barrens’ on a transect was multiplied by 0.925 (i.e., the mid-point between 85% and 100% barrens is 92.5%). Likewise, small, medium, and large barren categories were multiplied by their respective mid-points of 0.10 (i.e., mid-point between 1 and 20% cover was nominally 10%), 0.30 (mid-point between 20–40% cover was nominally 30%) and 0.625 (mid-point between >40–85% cover was nominally 62.5%) respectively.

Densities (no. individ. 5 m−2) of sea urchins and cover of barrens and substratum types, plus depth, were averaged across neighboring 5 m by 1 m quadrats on either side of the transect line (i.e., by combining data from each buddy pair as assessed in 5 m by 1 m quadrats on either side of the transect line). To ensure densities and percentage covers were robust estimates per unit area of reef, abundances were converted to densities once the area of any sand in each diver quadrat or interval of video had been removed. To ensure temporal consistency in the depths sampled during each sampling period, diver and video transects were individually matched by depth (4–18 m depth) and transect length (i.e., in terms of the no. of 5 by 1 m quadrats per transect) between 2001/02 and 2016/17 sampling periods. Data were analyzed using analysis of variance (ANOVA) using a nested 2-factor mixed effects model testing the effects of “Time” (i.e., fixed effect, 2001/02 versus 2016/17) and “Site” (i.e., random effect of 13 eastern Tasmanian sites), plus the interactive term of “Time” by “Site”, (i.e., variability in the “Time” effect across “Sites”) and “Subsite” (3 per Site) nested within the “Time” by “Site” interaction term. The analysis of variance in C. rodgersii density and barrens cover at the Subsite-level (for both dive and towed-video estimates of barrens), within each time-period, was based on means of n=4 transects. All statistical analyses were undertaken using R (R Development Core Team 2018), and appropriate transformations of response variables were determined using the boxcox routine available in the MASS package in R.

Distribution of C. rodgersii density and barrens cover across depth, as assessed in situ by divers, was analyzed by defining 2 m depth strata: ranging 4–6 m, 6–8 m, 8–10 m, 10–12 m, 12–14 m, 14–16 m and 16–18 m. The influence of reef substratum type on C. rodgersii density and barrens cover was explored by assigning averaged neighboring quadrats to a dominant substratum type, i.e., the substratum type constituting >50% cover. Where substratum types were equally dominant, the dominant substratum was assigned as the smaller diameter category. Effects of depth and substratum were analyzed through time using a 3-way fixed effects ANOVA on data averaged across eastern Tasmanian sites 1–9 where both urchins and barrens were recorded on diver transects.

Relative contributions of time, latitude, substratum, depth plus other mobile benthic invertebrates including predatory lobsters, locally native sea urchins and abalone on C. rodgersii density and barrens was examined with multiple linear regression using n=3200 quadrat-level estimates. Effects were partitioned using the “Relaimpo” package available in R (https://cran.r-roject.org/web/ packages/relaimpo/relaimpo.pdf) using Lindeman, Merenda and Gold (LMG) estimation to determine the contribution of each explanatory variable to the overall R2 of linear model fits. Correlations between explanatory variables of ≥0.70 or ≤−0.70 resulted in only one of the variables being retained, e.g., substratum types were highly correlated given their sum to 100% within quadrats, therefore only the “large boulder” substratum variable was retained.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This is a very important paper with significance that extends well beyond SE Australia. Collapses of complex ecosystems often surprise managers and the scientists studying them. Ling and Keane effectively apply contemporary theories on ecosystem forecasting to document conditions leading to, and foretelling, the collapse of Tasmanian kelp forest ecosystems. The authors describe a trophic cascade, in which fisheries induced declines of large rock lobster predators and warming ocean temperatures facilitate the expansion of sea urchins that graze down kelp forests. The resulting \"barren\" state has low productivity, is species depauperate and has reduced commercial value.\n\nThe Ling and Keane study illustrates well some of the warning signs of collapse for complex marine ecosystems. This is the first study I've seen that documents changes in in kelp-deforested \"barren\" patches in both space and time. While our changing climate is unmanageable at decadal time scales, some of the human-induced changes to local marine food webs can be reversed relatively rapidly and thus prevent incipient barren patches from becoming sea urchin barren stable states.\n\nThe authors describe a viable plan for identifying and reversing the kelp forest ecosystem from becoming a barren state. Sea urchin gonads (roe) are a highly valued food so harvesting sea urchins would be a practical solution. However, this is most viable where barren patches are surrounded by kelp which they define as \"incipient barrens\" (e.g., Fig. 1C). The importance of taking management actions during this early warning phase is that once kelp forests are entirely overgrazed, sea urchins do not die but they reabsorb their gonads and thus lose their economic value for sea urchin harvesting.\n\nThis study is relevant globally as kelp forests are declining world-wide (Filbee-Dexter and Scheibling 2014). Such declines often result from the loss of sea urchin predators (Steneck et al 2004, Norderhaug et al 2014). Ling and Keane suggest that fisheries management can improve kelp forest ecosystems and maintain a desirable stable state. There is evidence for this thesis in the Northern Hemisphere where the combination of sea urchin harvesting and invertebrate predators released from fishing pressure maintained the preferred kelp forest alternative stable state (Steneck et al 2013).\n\nThe authors point out that warming seas not only improve conditions for sea urchin larvae, but also facilitate changes in the species composition of algal communities. This too has been observed globally with species of foliose macroalgae replacing kelp species. This creates ecosystems with greater carrying capacity and ecosystem services than the crustose coralline dominated \"sea urchin barren\" state.\n\nReaders should understand that the authors do not think the climate-driven aspect of this paper can be managed directly. This study is on the indirect effects of climate change. So, it differs from the well documented decline of coral reefs following acute warming events. There is no way to manage or mitigate ocean warming impacts on coral reefs. However, kelp forest ecosystems are different because it is possible to identify \"incipient states\" of change for management actions to be applied at an ecosystem scale with relatively rapid results.\n\nLiterature cited\nFilbee-Dexter, K. and Scheibling, R.E., 2014. Sea urchin barrens as alternative stable states of collapsed kelp ecosystems. Marine ecology progress series, 495, pp.1-25.\nNorderhaug, K.M., Christie, H., Pedersen, M.F. and Fredriksen, S., 2014. Predators of the destructive sea urchin Strongylocentrotus droebachiensis on the Norwegian coast. Marine Ecology Progress Series, 502, pp.207-218.\nSteneck, R.S., Graham, M.H., Bourque, B.J., Corbett, D., Erlandson, J.M., Estes, J.A. and Tegner, M.J., 2002. Kelp forest ecosystems: biodiversity, stability, resilience and future. Environmental conservation, 29(4), pp.436-459.\nSteneck, R.S., Leland, A., McNaught, D.C. and Vavrinec, J., 2013. Ecosystem flips, locks, and feedbacks: the lasting effects of fisheries on Maine's kelp forest ecosystem. Bulletin of Marine Science, 89(1), pp.31-55.", "reviewer_2": "This is well-written and interesting manuscript that explores the poleward extension of a sea urchin grazer and resulting incipient barrens as an early warning sign of climate change-driven ecosystem collapse. I found the manuscript technically sound and the results compelling, although I provide a few considerations for the authors below. Overall, I believe this research will be of interest to the field, but its broader significance may be limited only in the sense that urchin barrens are well-documented as a driver of ecosystem collapse, and they have been repeatedly linked to climate change-driven perturbations such as marine heatwaves, declines in macroalgae, and loss of predators. However, it is particularly interesting that the incipient barrens described in this study are the result of the range extension of a dominant reef grazer. My main comments are therefore to consider the generality of incipient barrens as early warning signs and whether the warning is specific to the extension of a grazer into novel habitats. I provide several thoughts on this below.\n\nMajor comments:\n-The ms suggests that incipient barrens have the potential to deforest half of eastern Tasmanian reefs (like 182) within coming decades. While this is certainly a possibility, sea urchin barrens have been documented around the world at the spatial magnitude of meters to hundreds of kilometers (reviewed in Filbee-Dexter and Scheibling 2014). Some persist for only a season and others have persisted for many decades. In my opinion, understanding the environmental and ecological contexts that explain the likelihood of incipient barrens persisting and expanding is the fundamental link needed to explain when and why incipient barrens are an early warning sign.\n\n-It is interesting that in this system ecosystem collapse was due to the poleward expansion of a particular grazer species (C. rodgersii) into novel habitat. Perhaps the early warning sign is not just the emergence of incipient barrens, but specifically incipient barrens formed by a particular species in novel habitat. If this is correct, please emphasize this in the manuscript. It is not just range extensions or redistribution of grazers with specific thermal affinities, but barrens have been documented globally and attributed to native grazers as well. The authors mention the inclusion of the native sea urchin as a covariate, but if it is indeed the case that these barrens are driven by the extension of C. rodgersii and not the native species, then this should be emphasized. This could be supported with the addition of density of the native species in Figure 2C or as a supplementary figure.\n\n-Unless I am missing something, why not consider the total absolute density of both the native urchin and also C. rodgersii? It looks like they are treated independent in Table SI5. It would be interesting to see a plot of the baseline and temporal densities of both species over time.\n\nLine 122 – I recommend removing ‘resistance and resilience’ unless the authors provide some specific definitions for these terms as context, along with carefully defined statistical tests. Briefly, I interpret resistance and resilience as ecosystem-level responses where resistance is the capacity of a system to maintain community structure (or functioning, depending on goals) despite a perturbation, and resilience is both resistance to- and recovery from-perturbation (sensu Bates et al. 2019). Perhaps there is a different interpretation in this system, but please provide clear definitions of these terms if they are retained.\n\nThe ms uses the terms ‘phase-shift’ and ‘stable state’ in a few different places. It seems that ‘phase-shift’ is used to describe the changes here, which I think is correct, but as a reader it would be helpful to see this defined. Dudgeon et al. 2010 define a stable state as a novel configuration that persists after the environmental conditions return to what they were before a perturbation, which is not the same of a phase shift. I think the terms are used correctly here, but line 109 uses “phase shift” and 115 uses “alternative states.”\n\nPerhaps I missed this, but I don’t see how the critical ‘tipping points’ were derived other than an approximation from Figure 2C. I looked up reference 17 but I don’t see a mention of the tipping points included here. The authors have the data to quantitatively derive these tipping points. The way I have seen this done (and recommend) is that a discriminant analysis is first used to assign each replicate (quadrat or site) a binary value (1 = barren, 0 = forest) based on several predictors (substrate type, algal cover, depth, etc.) and this becomes the response for a logistic regression. The logistic regression is then performed using urchin density as the predictor and the tipping point thresholds are the density values at which it becomes likely (50%, 80%, 95%, whatever probability you choose) that the system with shift to barren or return to forest. The challenge with the recovery arrow is it depends on replicates where barrens were observed transitioning to forests. Without that, it is just a single tipping point based on correlative observations between kelp density and urchin density. Please consider this type of a model to identify the tipping points and whether there are sufficient ‘reverse-shift’ replicates to identify the reverse-shift threshold.\n\nMinor comments:\nI am curious about kelp cover over time. Without a plot of the time series of kelp cover it is difficult to assess whether increases in urchin density proceed kelp loss or just amplify macroalgae declines that are the result of already poor environmental conditions. I am not sure whether these data are available since the study used two discrete time periods, but in order to really attribute barren expansion as a driver of kelp loss (which completely makes sense), it requires a temporal component. Otherwise it is correlative and kelp loss could have preceded increases in urchin density, or led to emergence from refuge.\n\nLine 69-72 – this is really interesting that C. rodgersii are so prevalent!\nLine 77 – do lobsters prey on C. rodgersii specifically, or would this be a novel species interaction?\nLine 127 – It is not just the effect of absolute abundance but also change in grazer behavior. Some highly forested areas can maintain high densities of cryptic passively-grazing sea urchins, so it is the behavioral emergence from refuge resulting from resource availability (decline in macroalgae due to warming) that can feedback to influence declines (Smith & Tinker 2022, Karatayev et al. 2021). In Figure 2A it looks like the mid latitude sites had historically high densities relative to the north and south (with the exception of St. Helens) and also the relatively highest densities after 2016. Were these deep sites with large boulders? It looks here that the pattern is the same, just amplified. I.e., sites with historically high densities of urchins continued to have the relatively highest densities.\n\nLines 140-142 – the difference in slopes seems to be heavily influenced by two or three quadrats in the 01/02 period with high kelp cover despite high urchin densities (blue points, Figure 2C), but there is clearly less kelp at lower urchin densities in the 2016/17 period. It would be worthwhile to at least compare the slopes after remove those two or three extreme quadrats.\n\nLine 289-129 – please parenthetically include the error associated with these means.\n\nFigures:\nFigure 1. Love this figure! However “Barrens patch size” is difficult to read. Please make the text black.\nFigure 2. In a) there was clearly an increase in the mean density between periods, but there was an even more pronounced increase in the range across replicate quadrats with a skewness towards a wider density range above the mean. This is an interesting result that could suggest underlying patch-level dynamics. In a and b) please increase the transparency of the filled area and show the datapoints. c) the reverse shift arrow is difficult to see. Please change the color or make it darker. Also, I know that the tipping point arrows are approximate, but where these approximated by visual inspection or using a quantitative approach? Unless I am missing something, I don’t see how the 2.2 and 0.36 thresholds were determined. Please see my comment about the discriminant analysis and consider whether the recovery arrow is appropriate depending on the number of replicates where true recovery was observed. If recovery was not observed, then hysteresis is speculative and the relationship between kelp cover and urchin density should be represented by a single line or curve (single tipping point for forward and reverse shifts).\n\nFigure 3. Please add the datapoints and make the filled area more transparent so that we can see them. I would reorder from bottom to top: flat rock, small boulders, large boulders.\nFigure 4. Please add text indicating the patch size to each facet to remind us the extent of ‘small’ ‘medium’ and ‘large’.\n\nReferences in response:\nFilbee-Dexter, K., & Scheibling, R. E. (2014). Sea urchin barrens as alternative stable states of collapsed kelp ecosystems. Marine ecology progress series, 495, 1-25.\nKaratayev, V. A., Baskett, M. L., Kushner, D. J., Shears, N. T., Caselle, J. E., & Boettiger, C. (2021).Grazerbehaviourcanregulatelarge‐scalepatterningofcommunitystates.Ecology Letters, 24(9), 1917-1929.\nSmith, J. G., & Tinker, M. T. (2022). Alternations in the foraging behaviour of a primary consumer drive patch transition dynamics in a temperate rocky reef ecosystem. Ecology Letters, 25(8), 1827-1838.\nBates, A. E., Cooke, R. S., Duncan, M. I., Edgar, G. J., Bruno, J. F., Benedetti-Cecchi, L., ... & Stuart-Smith, R. D. (2019). Climate resilience in marine protected areas and the ‘Protection Paradox’. Biological Conservation, 236, 305-314.", "reviewer_3": "Summary:\nShifting environmental conditions are redistributing species across the globe. This study focuses on a range expansion of a sea urchin native to Australia to kelp forests off the coast of eastern Tasmania. Replicate surveys conducted across 13 sites and 15 years apart are described. These include diver surveys of urchin, lobster, and abalone abundance, and percent cover of substrate, including barren. Additionally, the authors conducted similar video surveys of planar cover of total urchin barrens and of different barren sizes in order to show the evolution of small incipient barrens (a starting condition) to large and continuous barrens that represent a state shift in the system. The authors found that incipient barrens increased through time, especially in northeastern and eastern Tasmania (southeastern Tasmania showed few urchins and barrens). The authors also showed how increases in the abundance in urchins was associated with disproportionally increased barren area. Deeper areas of reef with large boulders were associated with greater urchin abundance and there were negative associations between urchin abundance and the predatory lobster. The authors conclude with a discussion of using these early warning signals to initiate further research, partnerships, and ecosystem defense strategies.\n\nGeneral comments:\nOverall, I thought this was a well written and timely study worthy of publication. The two most important results from the study, in my opinion, are the data showing the temporal progression of urchin abundance and barren cover/size across space and the clear change in slope between barren area and urchin density between the two time points, implying a non-linear relationship. I did have some comments on how to improve the manuscript and reproducibility.\n\nFirst, I have some trouble with the authors stating that barren cover may increase to 50% by 2029. I understand that this is an extrapolation on the measured barren expansion rate between the two survey dates. I also feel that the authors intuition is likely correct, especially considering that there are multiple stressors that are all trending towards a more hostile environment for kelp. However, I am not sure the data support this conclusion when viewed in a different way. First, we start with looking at sites 1 – 9, defined as eastern Tasmania by the authors. From the planar barren data in Supp Data 3, the site with a highest urchin barren area in the 2001-2002 surveys (Site 2; St Helens) had a mean urchin barren area of ~23%. In the later surveys in 2016-2017, it had a mean urchin barren area of ~42.5%, representing an increase of just under 20% in 15 years. All of the other sites had vastly lower barren areas in the 2001-2002 surveys, and sites 1, 3, 4, 8, and 9 all has less than 10% barren area in the 2016-2017 surveys (with site 5 having just over 10% and site 6 and 7 having about 17.5%). It could be that there are non-linearities in the rate of barren expansion that are not being considered when observing the early stages of barren formation (i.e., is there a greater rate of barren expansion when moving from 0% to 10% than from 20% to 50%) at sites using only two time points. While I personally believe the authors may be correct (due to both increases in urchin abundance and temperature in this system, along with personal experience observing urchin barrens in other areas of the world), I would caution the authors to word these statements carefully. Additionally, while the authors do state that eastern Tasmania only covers sites 1 – 9 (and not the southern sites 10 – 13 where little barren cover has been observed in the data presented), there is a chance that people will interpret these findings as the entire eastern coast of Tasmania. Another reason to be as clear as possible when stating these predictions in the manuscript.\n\nMy other concern is with the data files that accompany the manuscript. I found a few discrepancies (or edits) that need to be addressed before publication. First, in Figure 2, n is defined as 1730 for the 2001-2002 surveys and 1727 for the 2016-2017 surveys, but the data file contains 1600 for both. I see the data files says (in the sheet name) that ‘no sand’ has been truncated. This may lead to the discrepancy and must be addressed. I found the stated statistics in the figure to be nearly identical. Second, using the planar urchin barren cover I found sites 1 – 9 to have 3.22% barren cover in the 2001-2002 surveys and 12.72% in the 2016-2017 surveys. Similar to what is stated in the paper but different (it may also lead to a slightly different rate of change for your extrapolation). Maybe I am looking at the wrong data, but others may do the same. Third, I was a bit confused on the proportion of barren sizes in the planar barren area data sheet. I think these data need more explanation in the manuscript so that readers can analyze these data correctly. These are the three that were most apparent in my analysis of the data and there may be others, so I think a careful reanalysis of the data provided is warranted.\n\nSpecific comments:\nDefine the abbreviation for New South Wales (NSW) in paragraph three of the introduction.\nMisspelling of ‘survey’ in the acknowledgments.", "reviewer_4": "This paper shows an extensive amount of kelp and sea urchin data collected in Tasmania, comparing 2001/2002 and 2016/2017. The authors stress the current increases in urchin barren cover in warming coastal zones (poleward). Besides, they focus on the potential for early-warnings of a catastrophic shift towards complete urchin barrens, by monitoring incipient spatial patterns.\n\nAs a theoretical ecologist, I’m not familiar with the field methods used, so I won’t be able to comment on these. I will focus on the link to the theory made by the authors, and the interpretation on the data in the context of alternative stable states and early warning.\n\nFirst of all, I’m impressed by the richness of the data. I’m not completely convinced of the entire line of reasoning, and the support by the data. I would like to share my thoughts on this, and some suggestions below.\n\nFirstly, I miss a discussion on the scale of the theoretical dynamics and the data. Are the observed patterns assumed to be stable, or unstable transient states where small incipient patches with high numbers of urchins slowly expand into the kelp? In the last case, is the early warning not actually the start of the (maybe slow) collapse? Or in the first case, how catastrophic is the collapse then? A reference is made to Rietkerk et al, but any discussion on the scale of the described feedbacks, the scale of the tipping points, and the scale of the data is lacking.\n\nOne of the first points made in the paper, is that the kelp-sea urchin system has alternative stable states, and shows catastrophic shifts at a certain level of urchin cover. This data seems to support this, although it is not completely clear to me at what scale (see first point) (if I understand correctly 50m). To illustrate the hypothesized existence of alternative stable states, it would be insightful to illustrate the frequency distribution vertically next to Fig. 2c, to show bimodality in the data.\n\nThe authors draw two arrows in Figure 2c indicating tipping points. I understand that these levels are based on earlier research, but since they have no relation to the data studied itself, the drawn trajectories give the reader a bit of a false idea of a directional change. I would suggest to draw actual observed trajectories by drawing arrows for each of the sites between the two observation periods.\n\nIt is unclear to me how Figure 3 relates to the main point of the paper. Maybe I miss something, and could it just be stressed a bit more.\n\nHow the data is presented at the moment, I don’t see that mapping patches and patch sizes would help for early warning. How do the patch sizes compare to urchin barren cover? Can results from Figure 2 and patch sizes as measured in Figure 4 be compared? Can actually urchin barren cover be used as an early warning sign, where simply the occurrence of patches is the first warning (so from 0 to >0% cover), or is there more information in the patch sizes measured? For instance, does cover stay the same, but patches become larger at sites where there are more urchins? This could easily be shown in a plot, and helps the reader to convince the usefulness of looking at patches and patch sizes in particular.\n\nOverall, I think the link between theory and data can be strengthened more to convince the reader. Also, the bridge to actual early warning signs (cover? patches?) needs some consideration. Furthermore, I think with some adaptions, it can become a rich paper, discussing an important question, whether (the increase of / occurrence of) incipient patches can be used as warning signs of systemic kelp collapse."}, "author_response": "Reviewer #1 recognises the importance of this research and strongly endorses the manuscript. IKQE=@K9IM9O9DO9MEL>;LJJ=KQP"}]

Decision letter