The influence of habitat heterogeneity and disturbance on benthic community structure in deep-sea polymetallic nodule environments and management implications for seabed mining

Habitat heterogeneity is known to influence faunal community structure, but its influence on deep-sea benthic communities remains understudied, particularly for polymetallic nodule environments in abyssal waters. As nodules are currently of interest for mining, understanding the potential impact of this disturbance on habitat heterogeneity, and the subsequent effect on faunal communities, becomes critical for developing environmental management plans. Although some aspects of the influence of habitat heterogeneity on the nodule-associated fauna have been studied, the influence on multiple size components of the benthic community across varying spatial scales has not yet been fully assessed, and the current metrics by which habitat heterogeneity is measured may be insufficient. This review synthesizes existing research regarding habitat heterogeneity, the influence of disturbance on habitat heterogeneity, and the influence of this heterogeneity on metazoan fauna (megafauna, macrofauna, and meiofauna) in polymetallic nodule environments across spatial scales. Current gaps in knowledge and the implications of this knowledge for the management of proposed deep-seabed mining are also discussed.

1 Introduction

Habitat heterogeneity is generally defined as variety in habitat types and has several synonymous terms, including habitat diversity, habitat complexity, and habitat structure (Carvalho and Barros, 2017). Extensive research has examined the influence of habitat heterogeneity on the structure of communities (e.g., Watson, 1964; Bazzaz, 1975; Jumars, 1975a, Jumars, 1975b; Heck and Wetstone, 1977; Abele and Walters, 1979; Rigby and Lawton, 1981; Sardà et al., 1994; Kaiser et al., 1999; Tews et al., 2004; Bulling et al., 2008; McClain and Barry, 2010; Godbold et al., 2011; Zeppilli et al., 2016), including ecological succession (Cordes et al., 2010; Meyer et al., 2016; Aguzzi et al., 2018), and community resilience to disturbance (Kaiser et al., 1999; Boyero, 2003; Rees et al., 2009; Godbold et al., 2011; Clark et al., 2016; Sweetman et al., 2017). However, due to its inaccessibility, much of the deep sea (> 200 m water depth) remains understudied and therefore the influence of habitat heterogeneity on benthic communities in this environment remains poorly understood (Baco et al., 2016; Amon et al., 2022; Radziejewska et al., 2022). This lack of knowledge is particularly true for polymetallic nodule environments, which are commonly located in the most remote parts of the ocean (typically at abyssal depths, 3000–5000 m deep; Simon-Lledó et al., 2019b; Amon et al., 2022; Radziejewska et al., 2022).

In the deep sea, habitat heterogeneity comes in many forms, and varies considerably across spatial and temporal scales (Figure 1). On large (i.e., regional) scales, habitat heterogeneity generally takes the form of broad-scale environmental variability. For example, depth gradients and proximity to shore influence the presence of physiological stressors (e.g., pressure, salinity) and critical resources (e.g., oxygen, food, calcium carbonate, etc.), which together exert a considerable influence on the diversity, composition, and abundance of deep-sea faunal communities over large spatial scales (Sanders and Hessler, 1969; Thiel, 1979; Etter and Grassle, 1992; Rex et al., 2006; Rex and Etter, 2010; Priede et al., 2013). Temporal scales may also influence deep-sea habitat heterogeneity through seasonal (Billett et al., 2001; Ruhl and Smith, 2004; Moran et al., 2005; Sun et al., 2006) or climatic cycles (e.g., climate oscillations; Billett et al., 2001; Levin et al., 2001; Ruhl and Smith, 2004; Arntz et al., 2006; Hooff and Peterson, 2006) that influence the flux of surface-derived carbon to the seafloor. However, the extent of the relationship between temporal cycles and benthic community structure remains ambiguous (Thurston et al., 1998; Radziejewska, 2002; Gambi et al., 2014; Woolley et al., 2016), particularly in remote and understudied abyssal environments (Lutz et al., 2007; Kahn et al., 2012). At intermediate scales, habitat heterogeneity in the form of habitat type (e.g., methane seep, seamounts) and substrate type (e.g., soft or hard substrate, biogenic structures) remains a significant factor influencing community structure (Levin et al., 1986; Cordes et al., 2010; Danovaro et al., 2014; Meyer et al., 2016; Gooday et al., 2021; Kazanidis et al., 2021), with higher heterogeneity generally correlated with higher diversity and higher abundance of fauna (Samadi et al., 2006; Levin et al., 2010; Huvenne et al., 2011; Zeppilli et al., 2011, Zeppilli et al., 2012; Robert et al., 2015; Lacharité and Metaxas, 2017). However, variation in environmental variables (e.g., currents/flows, hypoxic conditions) can overshadow these effects at certain locations (Gooday et al., 2010; Pereira et al., 2022). At intermediate to small scales, food flux can enhance habitat heterogeneity through the creation of food patches, which can be characterized by low (e.g., diffuse patches of POC flux or marine snow; McClain et al., 2011; Danovaro et al., 2013; Gambi et al., 2014; Lacharité and Metaxas, 2017) or high organic carbon enrichment (e.g., an organic fall; Lundsten et al., 2010; Laurent et al., 2013; Smith et al., 2015; Silva et al., 2021). Low-enrichment food patches often support higher faunal diversity (McClain et al., 2011; Danovaro et al., 2013; Lacharité and Metaxas, 2017), while high-enrichment food patches (i.e., organic falls) consistently increase faunal abundance (Smith et al., 2015; Webb et al., 2017; Young et al., 2022). Although these high-enrichment patches often also support higher species richness, dominance by organic fall specialists generally results in lower evenness than background communities (Lundsten et al., 2010; Cunha et al., 2013; Young et al., 2022). At smaller spatial scales, the influence of substrate heterogeneity tends to be stronger than the influence of broader scale environmental heterogeneity. For example, across ocean basins, environmental conditions, and broader habitat type, high sediment grain size diversity consistently correlates with higher infauna species diversity in the deep sea (Etter and Grassle, 1992; Parry et al., 2003; Rex and Etter, 2010). Habitat heterogeneity can also be influenced by geological factors in the deep sea, which can operate at a variety of scales, including mineral composition (e.g., heavy metals or minerals grains decrease faunal diversity, as in Cerrano et al., 1999), seafloor bathymetry (e.g., heterogenous seafloor morphology supports higher faunal abundance or diversity as in Durden et al., 2015 and Zeppilli et al., 2016, respectively), and hydrodynamics (e.g., structures that alter hydrodynamics influence community composition, as in Levin et al., 1986; Zajac et al., 2000; Alt et al., 2013).

Figure 1

Figure 1. Summary of factors influencing habitat heterogeneity in the deep sea, according to the spatial scale of focus. Arrows indicate direction of increasing scale and delineate different types of factors. Dotted line indicates interaction or overlap between types of factors. Modified from Rosli et al., 2017.

Habitat heterogeneity is also frequently influenced by disturbance, which creates habitat patches that may increase or decrease local habitat heterogeneity depending on the size and scale of the disturbance and the spatial scale of focus (Grassle and Morse-Porteous, 1987; Gallucci et al., 2008; Willig and Presley, 2018). The kinds of natural disturbance influencing habitat heterogeneity in the deep ocean can range from small disturbances created by burrowing fauna or biogenic structures (e.g., burrows, tests, etc.; Kukert and Smith, 1992; Levin et al., 2003; Jones et al., 2007) to strong bottom currents (Levin et al., 1994; Harris, 2014; Liao et al., 2017; Tung et al., 2023) to underwater landslides and turbidity currents (Glover et al., 2010; Harris, 2014; Heijnen et al., 2022; Bigham et al., 2023) to episodic influxes of food from the surface (e.g., organic falls, strong seasonal pulses of phytodetritus; Thurston et al., 1998; Smith et al., 2008, Smith et al., 2015). Often, one of these disturbances (e.g., turbidity currents) can lead to another (e.g., food flux; Harris, 2014; Heijnen et al., 2022). The smallest of these disturbances (e.g., bioturbation) increase small-scale patchiness and local habitat heterogeneity to promote overall species diversity for larger faunal size classes (Jumars, 1975b; Thistle, 1979; Levin et al., 1986; McClain et al., 2011). However, meiofauna bioturbation has been observed to homogenize surface sediments in some cases, which may reduce surface patchiness (Cullen, 1973). Larger disturbances that significantly alter baseline habitat structure or food availability (e.g., an underwater landslide, a whale or wood fall), can create significant patchiness that results in colonization by faunal communities in a series of distinct successional stages (Bienhold et al., 2013; Harris, 2014; Smith et al., 2015).

The deep sea is also subjected to disturbance from human activities (Ramirez-Llodra et al., 2011; Clark et al., 2016; Chiba et al., 2018; Jamieson et al., 2022; Santibañez-Aguascalientes et al., 2023). This includes large quantities of pollution and litter (Tyler, 2003a; Ramirez-Llodra et al., 2011; Chiba et al., 2018; Abel et al., 2023), nuclear and chemical waste disposal (Looser et al., 2000; Tyler, 2003a; Kivenson et al., 2019), sunken infrastructure (Tyler, 2003a; Macreadie et al., 2011; Ramirez-Llodra et al., 2011), drilling and blasting (Coleman and Koenig, 2010; Montagna et al., 2013; Fisher et al., 2014; Nakajima et al., 2015; Gates et al., 2017), resource extraction (Roberts, 2002; Benn et al., 2010; Coleman and Koenig, 2010; Ramirez-Llodra et al., 2011; Bakke et al., 2013; Clark et al., 2016), and disturbance resulting from climate change (Company et al., 2008; Levin and Le Bris, 2015; Sweetman et al., 2017). In the future, the deep sea at abyssal depths (3000–6000 m) is likely to be subjected to disturbance from deep-seabed mining (Amon et al., 2022; Leduc et al., 2024a; Pickens et al., 2024). Proposed forms of mining would alter habitat heterogeneity by removing hard substrates (e.g., polymetallic nodules) and removing and mixing the top layers of sediment (Amon et al., 2016; Vanreusel et al., 2016; Simon-Lledó et al., 2019c; Uhlenkott et al., 2023b; Pickens et al., 2024). As a result, consideration of the effect of habitat heterogeneity on benthic faunal communities of these environments has become critical for developing management and conservation plans for regions targeted for mining. Most recent research on polymetallic nodule ecosystems has focused on establishing ecological baselines and cataloguing ecological communities in mining license areas in the Clarion-Clipperton Zone (CCZ) in the Central Pacific Ocean, with the goal of informing the management of deep-seabed mining under the jurisdiction of the International Seabed Authority (Durden et al., 2015; Amon et al., 2016; Vanreusel et al., 2016; Gooday et al., 2017; Simon-Lledó et al., 2019c; Weaver and Billett, 2019; Washburn et al., 2021a; Kaiser et al., 2023). Though earlier research focused on the impact of potential mining disturbances on nodule communities (Bluhm, 1994; Bluhm et al., 1995; Borowski and Thiel, 1998; Tkatchenko and Radziejewska, 1998; Fukushima et al., 2000; Radziejewska, 2002; Ingole et al., 2005) and on the physical environment (Jankowski et al., 1996; Koschinsky et al., 2001; Sharma et al., 2001; Khadge, 2005; Khripounoff et al., 2006), the potential alteration of habitat heterogeneity from mining has only recently begun to attract research interest (Simon-Lledó et al., 2019b; Cuvelier et al., 2020; Amon et al., 2022; Uhlenkott et al., 2023b).

Previous reviews that have included a focus on the influence of habitat heterogeneity on one or more size classes of benthic communities in the deep sea have considered continental margins (Levin and Sibuet, 2012), reducing ecosystems (Bernardino et al., 2012), and submarine canyons (De Leo and Puig, 2018). Although some reviews have explored abyssal polymetallic nodule ecosystems, these have focused solely on the CCZ (e.g., Gooday et al., 2021; Kaiser et al., 2023) or on disturbance experiments (e.g., Jones et al., 2017) without a dedicated focus on habitat heterogeneity, or have been part of a larger comprehensive review across habitats (e.g., Vanreusel et al., 2010).

This review covers three main size classes of benthic metazoans: megafauna, macrofauna, and meiofauna. Megafauna has been defined variably throughout the scientific literature, but generally refers to “animals readily visible in photographs” (Grassle et al., 1975) or collected on mesh sizes of 1–3 cm (as in Haedrich and Rowe, 1977), and are generally easy to see with the naked eye (e.g., holothuroids, ophiuroids, decapods). Macrofauna is the next-largest faunal size class, and generally refers to fauna collected in the deep sea on a 300-micron screen, though some European research institutes use a 250-micron screen with similar results (Gage et al., 2002). Macrofauna may be just visible, but not identifiable, with the naked eye (e.g., polychaetes, amphipods, tanaids). Meiofauna is the smallest faunal size class relevant to this review and is dominated by nematodes, but also includes other invertebrates such as harpacticoid copepods, tardigrades, and ostracods (Hakenkamp and Palmer, 2000). Sieve sizes used to separate meiofauna vary within a range of 20–64 microns, with 20–45 microns considered best practice in the deep sea (Leduc et al., 2014; Jones et al., 2017; Neira et al., 2018; dos Santos et al., 2020; Uhlenkott et al., 2020).

This review evaluates existing knowledge about habitat heterogeneity, the influence of disturbance on habitat heterogeneity, and the influence of this heterogeneity on benthic metazoan fauna in polymetallic nodule environments across faunal size classes and spatial scales. Current gaps in knowledge and the implications of this knowledge for the management of proposed deep-seabed mining are also discussed.

2 Polymetallic nodules

Polymetallic nodules, also referred to as manganese nodules, are small rocks found on the ocean floor in various parts of the world's oceans. While they commonly measure between 3 and 10 centimeters in diameter and exhibit a spherical or oblong shape (Kuhn et al., 2020), larger nodules exceeding 20 centimeters and displaying irregular shapes or structures are not uncommon (Joseph, 2017). Nodules originate from substrates such as rocks or shark's teeth, onto which minerals gradually precipitate and bind over geological timescales, growing at a rate of a few millimeters per million years (Cronan, 2019). Though nodules can occur at other depths, they are most abundant in the abyssal ocean basins of the Pacific, Indian, and Atlantic oceans between 4000–6500 m (Figure 2). Economically viable nodules are primarily iron or manganese-based (approximately 6 to 30%) and contain smaller concentrations of valuable minerals such as nickel, cobalt, copper, and rare earth elements (0.25-3%; Joseph, 2017).

Figure 2

Figure 2. (A) Map of polymetallic nodule environments of interest for mining (outlined in blue). Inset figure shows a whole polymetallic nodule and cross-section (1 cm scale bar). Map from World Ocean Review; inset photos from Earth Sciences New Zealand. (B) Map of the exploration and reserved areas for polymetallic nodules in the Clarion-Clipperton Zone. Map by the International Seabed Authority (https://www.isa.org.jm/).

As a geological feature, polymetallic nodules have been known to science since the Challenger Expedition of 1873-1876 (Murray and Renard, 1891). While this and other early oceanographic expeditions revealed a fair amount about the chemistry and geology of polymetallic nodules (Summerhayes, 1967; Glasby, 1976; Kerr, 1984), little was known about their associated fauna until technological developments facilitated better exploration of abyssal depths in the late 1900s (Danovaro et al., 2014). Recent studies into polymetallic nodule ecosystems—particularly those in proposed mining areas (e.g., the CCZ)—have provided greater knowledge about faunal communities associated with polymetallic nodules in the central Pacific (e.g., Simon-Lledó et al., 2020; Uhlenkott et al., 2021, Uhlenkott et al., 2023a; Washburn et al., 2021b). However, these environments remain understudied, particularly outside of the CCZ, and baselines for their associated communities are still being established (e.g., Simon-Lledó et al., 2019c, Simon-Lledó et al., 2019d).

3 Metrics of habitat heterogeneity used to describe polymetallic nodule environments

Though few studies focus explicitly on habitat heterogeneity, most studies in nodule environments include metrics that characterize heterogeneity in the form of environmental factors (standard for most ecological studies) and/or nodule characteristics (relevant both for its ecological influence and its focus for mining interests). At the smallest spatial scales, habitat heterogeneity in nodule environments is generally measured in the form of grain size heterogeneity for nearby sediments (Mewes et al., 2014; De Smet et al., 2017; Lefaible et al., 2023), or—in some cases—by nodule type or “facies” (a qualitative description of nodule surface texture and some aspects of nodule density or seafloor topography; Wright et al., 2005; Veillette et al., 2007a; Fleming et al., 2025). Intermediate spatial scales of heterogeneity are generally focused on nodule abundance or percent cover (Mewes et al., 2014; De Smet et al., 2017; Simon-Lledó et al., 2019c, Simon-Lledó et al., 2020; Durden et al., 2021), and may include other aspects of seafloor heterogeneity such as bottom topography (Simon-Lledó et al., 2019b, Simon-Lledó et al., 2020; Durden et al., 2021) or the occurrence of non-nodule hard substrates (Mejía-Saenz et al., 2023; Uhlenkott et al., 2023b). At larger spatial scales, heterogeneity is generally measured based on study area and its associated environmental conditions (e.g., depth, POC flux, etc.; Jones et al., 2021; Washburn et al., 2021a). However, since most studies in nodule environments focus on one or two spatial scales, the most prevalent metrics used to characterize substrate heterogeneity are nodule abundance (kg/m² or nodules/m²; e.g., Amon et al., 2016) or nodule cover (percent cover; e.g., Simon-Lledó et al., 2019b). Though other metrics have been used across a range of studies (e.g., nodule size, facies, volume), it is common for studies to use just one metric (typically nodule cover), which can cause the other aspects of habitat heterogeneity (e.g., nodule distribution, nodule patch size, bottom topography, sediment heterogeneity) to be underestimated or overlooked.

4 Habitat heterogeneity in polymetallic nodule environments

Habitat heterogeneity in polymetallic nodule environments depends on the spatial scale of focus (Figure 3). The smallest scale (millimeters to centimeters) depends on variability of the nodule itself, such as the presence or absence thereof, and—if present—differences in their minerality, rugosity, size, and shape, as well as the surrounding sediments (e.g., vertical resource gradients and grain size heterogeneity). At the patch-scale (centimeters to meters) heterogeneity is driven by differences in nodule density and arrangement. At the field-scale (10s to 1000s of meters), heterogeneity across a nodule field may take the form of nodule patch density and arrangement, differences in bottom topography, or in the occurrence of non-nodule hard substrates such as rock outcrops or seamounts. Finally, at the regional scale (10s to 1000s of kilometers), heterogeneity generally takes the form of broad environmental differences (e.g., resource availability such as organic matter flux, geomorphological structures, geological variability). Due to the different “windows of perception” of different faunal size classes (Kotliar and Wiens, 1990; Attrill et al., 2000), taxa naturally interact with these spatial scales differently (Figure 3). As a result, a deeper, more comprehensive assessment of habitat heterogeneity across these spatial scales is critical for understanding nodule faunal community structure and resilience to potential disturbance from seabed mining.

Figure 3

Figure 3. Habitat heterogeneity at different spatial scales of interest in polymetallic nodule environments from smallest (left) to largest (right). The variability at each spatial scale will hold different relevance for different size classes of fauna. For example, variability at the nodule scale (e.g., number and size of crevices) will be most relevant for meiofauna; while variability at the patch scale (e.g., density of nodules blocking sediment habitats or providing attachment surfaces for sessile fauna) may be more relevant for macrofauna; variability at the field scale (e.g., available sediment patches for mobile scavengers and density of nodule patches for connectivity between hard substrate communities) may be most relevant for megafauna.

4.1 Habitat heterogeneity among nodules and within sediments

At small spatial scales, there is substantial habitat heterogeneity within sediments, in both nodule-free and nodule-rich areas. Sediment depth is one of the most important drivers of infaunal communities (particularly meiofauna) due to heterogeneity in resource availability (namely organic matter content). As organic matter content decreases with depth, infaunal abundance often mirrors this decline, and community composition shifts (Thiel, 1983; Soetaert et al., 2002; Ingels and Vanreusel, 2013; Rosli et al., 2018). While infaunal abundance is generally higher at shallower sediment depths, peaks may occur in subsurface sediment layers (e.g., 1–2 or 2–3 cm deep) due to environmental conditions (e.g., strong currents, coarser sediments; Zeppilli et al., 2012, Zeppilli et al., 2014). In nodule-free areas, the effect of the vertical gradient through sediment layers is relatively consistent across habitat type (Ingels and Vanreusel, 2013; Rosli et al., 2018). In nodule environments, it remains unknown whether nodules may block the penetration of organic matter into the sediments beneath them, leading to the concentration of organic matter in exposed sediments between the nodule, creating coarser sediments through nodule fragments, or altering the flux of other nutrients (e.g., oxygen). However, it is possible that their presence in otherwise sediment-dominated environments may influence sediment depth-related patterns in community structure by contributing to greater resource patchiness.

Among nodules within a patch, variations in habitat heterogeneity are largely structural and geochemical. Polymetallic nodules can vary in size, shape, and composition (Joseph, 2017; Mizell et al., 2022). This heterogeneity not only influences the size of the hard substrate habitat provided by nodules (e.g., as an attachment surface for mega- and/or macrofaunal sessile fauna; Meyer et al., 2016; Simon-Lledó et al., 2019b), but also the rugosity (roughness) of the nodule. Higher rugosity nodules can provide additional habitat beyond acting as an attachment surface, as their pores and crevices often support distinct faunal communities dominated by smaller-sized meiofauna (namely small nematodes; Thiel et al., 1993; Singh et al., 2019). Though nodule crevices tend to be small, and therefore support fewer individuals and species than nearby sediments (Thiel et al., 1993; Singh et al., 2019; Pape et al., 2021), this heterogeneity within the nodule could have implications for nodule-specific faunal communities. Nodule-to-nodule faunal community comparisons that focus on this small-scale heterogeneity are not common, but a positive relationship between nodule dimensions and crevice meiofaunal abundance has been observed (Pape et al., 2021). Based on observations of distinct crevice-faunal communities on nodules (Thiel et al., 1993; Singh et al., 2019), it is likely that substantial differences in rugosity among nodules would influence the structure of meiofaunal nodule communities. The varied geochemical composition of nodules can also contribute to this small-scale habitat heterogeneity, as different minerals support different bacterial communities (Blöthe et al., 2015), which may influence metazoan communities through short-term carbon cycling and resource availability (Sweetman et al., 2019; Stratmann et al., 2021; Stratmann, 2023). For example, laboratory experiments have indicated that higher diversity of bacterial communities directly influences nematode community composition by supporting higher nematode abundance and reducing competitive exclusion amongst nematode species (Derycke et al., 2016; Guden et al., 2021).

4.2 Habitat heterogeneity among nodule patches

The next largest spatial scale of interest is among nodule patches within a field, namely through differences in the density and arrangement of nodules among patches. Broadly, the occurrence of nodules (i.e., compared to sediments within a field without nodules) has been shown to increase megafaunal density (Amon et al., 2016; Vanreusel et al., 2016; Cuvelier et al., 2020; Simon-Lledó et al., 2020; Durden et al., 2021; Uhlenkott et al., 2023b), diversity (Uhlenkott et al., 2023b), and exhibit different community composition (Simon-Lledó et al., 2019c; Cuvelier et al., 2020; Simon-Lledó et al., 2020; Durden et al., 2021). Megafaunal abundance largely correlates with nodule abundance across the CCZ, particularly for suspension feeders (Tilot, 2006; Amon et al., 2016; Vanreusel et al., 2016; Simon-Lledó et al., 2019b). The relationship between nodule abundance and diversity, though positive, may be limited: the habitat heterogeneity provided by nodules enhances megafaunal species richness and diversity, but this effect exhibited diminishing returns above a certain level of nodule abundance in the eastern CCZ (UK-1; Amon et al., 2016). Certain macrofaunal taxa (e.g., polychaetes, tanaids, and isopods) in the eastern CCZ (GSR) have been observed to covary with nodule abundance, but sampling design may account for much of this trend (De Smet et al., 2017). Studies in both the Indian (CIOB) and Pacific Oceans (multiple areas in the CCZ) have indicated a positive relationship between nodule density and macrofaunal diversity (Parulekar et al., 1982; Yu et al., 2018) and/or abundance (Parulekar et al., 1982; Mullineaux, 1987; Tilot, 2006), while others indicate a unimodal relationship between nodule density and macrofaunal abundance (GSR, eastern CCZ; De Smet et al., 2017), or no discernible relationship at all (GSR, eastern CCZ; Pasotti et al., 2021). These varying relationships indicate that macrofaunal communities may be influenced by additional factors found at each study site. For example, in the southwest Pacific at around 400 m, macrofaunal community structure was found to correlate with phosphorite nodule abundance, but mesoscale (10-100s of m) topographical variability (e.g., uneven areas, seafloor depressions) drove diversity patterns at smaller spatial scales (< 1 m; Leduc et al., 2015). However, across study locations in the CCZ, macrofaunal community composition largely varied according to polymetallic nodule density, likely due to substrate preference (e.g., higher percent composition of sessile fauna at nodule-rich sites vs. higher percent composition of infauna at nodule-poor sites; Mullineaux, 1987; Tilot, 2006). Though the presence of nodules (and therefore nodule crevice fauna) may marginally increase local meiofaunal diversity at the centimeter-scale (Pape et al., 2021), nodules also occupy the first several centimeters of sediment that could otherwise serve as habitat for sediment infauna, often resulting in lower abundance of sediment meiofauna at nodule-rich sites compared to nodule-free areas in both the Indian and Pacific Oceans (Tilot, 2006; Mahatma, 2009; Miljutina et al., 2010; Singh et al., 2016; Hauquier et al., 2019; Pape et al., 2021).

4.3 Habitat heterogeneity among nodule fields

At larger spatial scales, habitat heterogeneity among nodule fields within a region may also influence benthic communities. In particular, among-field differences in local topography that occur on scales of 10s to 1000s of meters can influence mega- and macrofaunal communities at smaller spatial scales (< 1 m to 5 m) by providing additional habitat heterogeneity in the form of depressions, non-nodule hard substrates, or hills/seamounts (Durden et al., 2015, Durden et al., 2020; Leduc et al., 2015; Cuvelier et al., 2020; Leitner et al., 2021; Mejía-Saenz et al., 2023). Topographical variability has been observed to support higher mega- and macrofaunal diversity in deep-sea sediment communities, including in nodule regions, likely due to increased sediment heterogeneity and the alteration of small-scale environmental factors (e.g., the accumulation of POC in seafloor depressions; Durden et al., 2015, Durden et al., 2020; Leduc et al., 2015). The presence of non-nodule hard substrates (e.g., rocks, seamounts) has also been observed to strongly influence megafaunal community structure, with higher diversity and densities than sediment-dominated areas in the eastern CCZ (BGR, GSR, APEI-3, and APEI-6; Cuvelier et al., 2020; Mejía-Saenz et al., 2023; Uhlenkott et al., 2023b). The communities found on these substrates are distinct from nodule communities (Cuvelier et al., 2020; Laroche et al., 2020; Mejía-Saenz et al., 2023; Uhlenkott et al., 2023b), indicating that nodules provide unique habitat that may not be easily substituted by other hard substrates. Heterogeneity in the form of the distribution of nodule fields within a region could also have implications for the biodiversity of faunal communities. For example, higher density of nodule fields could enhance population connectivity and successful larval dispersion within regions, particularly for fauna dependent on hard substrates (Taboada et al., 2018). Smaller habitat patches acting as “stepping stones” that connect larger populations of fauna have been observed in other deep-sea ecosystems (e.g., organic falls connecting vents or seeps; Bienhold et al., 2013; Cunha et al., 2013). Scattered fields of nodules could similarly act as “stepping stones” that connect nodule fauna populations across sediment-dominated areas. However, connectivity and larval dispersion in the abyss remain understudied, particularly in nodule environments (Kersten et al., 2017), and no study has yet explored connectivity and larval dispersion with regard to habitat heterogeneity in nodule environments.

4.4 Habitat heterogeneity within and among regions

At the largest spatial scales (among nodule fields within and among regions), environmental variability (e.g., resource availability, geomorphological structures) influences faunal community structure both directly and through its influence on habitat heterogeneity.

4.4.1 Food flux variability

At within-region scales (100s of meters to 100s of kilometers), the influence of environmental variability—particularly food availability—on polymetallic nodule communities becomes more pronounced. For example, POC flux to the seafloor varies substantially (> 2x) across the CCZ, generally declining from east (closer to nutrient inputs from land) to west (Tyler, 2003b; Washburn et al., 2021a). Mega-, macro-, and meiofaunal community structure has been observed to vary accordingly across this gradient, with higher POC flux generally correlating with both higher faunal abundance and diversity (Hannides and Smith, 2003; Smith and Demopoulos, 2003; De Smet et al., 2017; Christodoulou et al., 2020; Laroche et al., 2020; Nomaki et al., 2021; Washburn et al., 2021a; Tong et al., 2022). However, when sites within a region exhibit substantial differences in both local habitat heterogeneity (e.g., nodule abundance) and POC flux, the influence of POC flux on community structure may be diminished or masked (Durden et al., 2021; Washburn et al., 2021b). For example, an area of particular environmental interest (APEI) in the CCZ with 73% higher POC flux but lower habitat heterogeneity (i.e., dominated by soft sediments; APEI-7) exhibited lower megafaunal densities than in sites with lower POC flux but high nodule abundance (APEI-1; Durden et al., 2021). Variability in these two ecological factors also influenced megafaunal community composition, as fauna with certain functional traits (e.g., sessile suspension feeders vs mobile scavengers) correlated with higher availability of related resources (e.g., hard substrates for attachment; Durden et al., 2021). However, related environmental factors (e.g., oxygen content), may have also played a role in this trend, as APEI-7 has lower dissolved oxygen content (3.84 ± 0.02 ml/L) than APEI-1 (4.12 ± 0.05 ml/L; (Washburn et al., 2021a).

POC flux to the seafloor also varies among regions (1000s of kilometers or more), including among ocean basins that contain large nodule reserves (e.g., the central Indian Ocean, the central Pacific, the southwest Pacific; Jahnke, 1996). Though the waters over polymetallic nodule environments tend to be oligotrophic (Mizell et al., 2022), POC flux to the seafloor does vary between ocean basins (Xie et al., 2019), which can contribute to differences in nodule fauna among regions (Washburn et al., 2021b). Equatorial ocean regions (e.g., the central Pacific) tend to exhibit higher POC flux to the seafloor than tropical and sub-tropical regions due to heightened surface productivity fed by equatorial upwelling (Honjo et al., 2008). The Indian Ocean basin, due to its proximity to large landmasses and the equator, tends to exhibit higher POC flux than the north or south Pacific Ocean basins (Jahnke, 1996; Rixen et al., 2019). As a result, in addition to among-basin variability in habitat heterogeneity that may influence faunal community patterns (e.g., presence of nodules, seamounts, rock outcrops), POC flux can create regional differences in faunal communities directly (e.g., higher abyssal benthic standing stock in the Pacific than the Indian Ocean; Neyman et al., 1973; Parulekar et al., 1982; Tyler, 2003b). Ultimately, the complexities of the relationship between mega-, macro-, and meiofaunal community structure and POC flux remain poorly understood and merit further investigation in nodule environments at different sites, in different regions, and on longer timescales. However, existing research indicates that neither the presence of certain habitat features (e.g., nodules) nor the level of certain environmental conditions (e.g., POC flux) can serve as a perfect proxy for faunal diversity or abundance. Though preliminary efforts to model polymetallic nodule meio- and megafauna communities in the eastern CCZ (BGR) have shown promise (Uhlenkott et al., 2020, Uhlenkott et al., 2021, Uhlenkott et al., 2022), the explanatory and predictive capabilities of these models remain constrained by limited baseline data.

4.4.2 Temporal variability

Environmental conditions in abyssal regions can also vary considerably on temporal scales due to seasonality and climate oscillations affecting surface productivity, and thereby POC flux to the seafloor (Billett et al., 2001; Kuhnz et al., 2014; Taylor et al., 2017). Though evidence of temporal variability in food flux has been observed in nodule environments (Kaufmann and Smith, 1997; Hannides and Smith, 2003; Miljutin et al., 2015; Hoving et al., 2023), the results of the few studies monitoring temporal changes in nodule faunal communities have been mixed. Across the CCZ, isopod diversity exhibited strong temporal variation (Kaiser et al., 2023), and macrofaunal densities overall were higher during El Niño years, though low sample sizes limited statistical testing and inconsistencies in sampling methodology have contributed substantially to the observed results (Kaiser et al., 2024). Also in the CCZ (eastern CCZ; IOM and Ifremer areas), certain meiofauna taxa were found to exhibit a strong shift in community structure following natural episodes of phytodetritus input (Radziejewska et al., 2001; Radziejewska, 2002; Miljutin et al., 2015). However, a different study in the eastern CCZ (GSR area) found that meiofauna showed no significant temporal variation in abundance, diversity, or community composition (Pape et al., 2017), though this difference may be due to geographical variation among the contract areas, which span hundreds of kilometers. Additional research on megafaunal communities has been largely limited to disturbance response studies (see below), in which the effects of anthropogenic (experimental) disturbances and the effect of spatiotemporal cycles can be difficult to parse.

Among ocean basins, temporal variation can differ further. For example, the Indian Ocean is influenced by monsoons, which create seasonal nutrient inputs that boost surface productivity and therefore POC flux to the seafloor (Lutz et al., 2007). Due to its size, the Pacific Ocean does not have universal seasonal variation. However, the east Pacific Ocean experiences seasonal coastal upwelling that can have a cascading influence on POC flux to the deep sea (Lutz et al., 2007). The Pacific is also strongly influenced by the El Niño-Southern Oscillation (ENSO), which creates substantial temporal variation in POC flux to the seafloor on cycles of several years, and whose influence extends to the Indian and Southern Oceans (Wang et al., 2017; Xie et al., 2019). The effects of ENSO in the central and eastern equatorial Pacific (including around the CCZ) are particularly acute, with decreased POC flux during El Niño events (due to weakened equatorial upwelling) and increased during La Niña events (due to enhanced upwelling; Smith et al., 2006; Xie et al., 2019). The temporal variability in the southwestern Pacific tends to be less dramatic and less consistent, as it is further removed from both seasonal and climactic shifts in equatorial upwelling (Lutz et al., 2007; Wang et al., 2017). However, ENSO still influences regional ocean circulation and temperatures in the southwestern Pacific, which likely influences surface productivity and therefore POC flux to the seafloor (Chiswell et al., 2015). Though no consistent trends in temporal faunal variability among regions have yet emerged, food flux to the seafloor remains a strong environmental influence on abyssal communities. Due to the strong but variable influence of climatic cycles (e.g., ENSO) and seasonality on POC flux among regions, it remains likely that these temporal cycles have a strong influence on regional nodule faunal communities that could be revealed by future research (Hannides and Smith, 2003; Ruhl and Smith, 2004). However, to date, the paucity of long-term sampling and ocean monitoring programs in remote polymetallic nodule regions have prevented a robust assessment of the influence of large-scale temporal cycles on nodule-associated fauna.

4.4.3 Bathymetric and topographic variability

At within- and among-region scales, bathymetry becomes more influential, both through depth gradients and through the presence of large geomorphological structures. Though depth remains relatively consistent in most nodule environments, generally between 4000 and 5000 m, community structure can still be strongly influenced by this variability. For example, in the CCZ, the carbon compensation depth lies between 4,300 and 4,800 m (Berger et al., 1976). Across this threshold, megafaunal community composition shifts significantly as animals relying on calcium carbonate body parts (e.g., corals, shelled mollusks) are replaced by soft-bodied organisms (e.g., anemones, sea cucumbers; Simon-Lledó et al., 2023). Despite this dramatic shift in phylum-level community composition, megafaunal species richness across this threshold is maintained (Simon-Lledó et al., 2023). As in most deep-sea environments, food availability also declines with depth, and abyssal environments with lower POC flux often exhibit lower mega-, macro-, and meiofaunal densities (Thurston et al., 1998; Veillette et al., 2007b; Schmidt and Martínez Arbizu, 2015; Wilson, 2017; Błażewicz et al., 2019) and diversities (Glover et al., 2002; Veillette et al., 2007b; Wilson, 2017; Błażewicz et al., 2019; Laroche et al., 2020), though this can vary depending on the amount of substrate heterogeneity present (i.e., nodules vs. no nodules; Veillette et al., 2007a; Vanreusel et al., 2016) and across taxonomic groups (Wilson, 2017; Simon-Lledó et al., 2020).

Regional environmental variability in the form of larger topographical variations (e.g., seamounts, troughs) can also influence communities as bottom currents and hard substrate availability in nodule environments influence resource availability (e.g., food, habitat). For example, the occurrence of seamounts near polymetallic nodule fields in the eastern CCZ provides increased habitat heterogeneity that supports high faunal diversity and abundance (Cuvelier et al., 2020; Mejía-Saenz et al., 2023; Uhlenkott et al., 2023b). In the Bounty Trough of the southwest Pacific (1500–4800 m depth), bottom currents are strong enough to create ripples in sedimented areas (Daniel Leduc, personal communication), which may influence communities both directly and through the creation of greater habitat heterogeneity that can alter hydrodynamic conditions and influence sediment grain heterogeneity, larval settlement, and food availability (Leduc et al., 2012, Leduc et al., 2015; Durden et al., 2015). In the abyssal sediments of the Peru Basin (equatorial eastern Pacific), high-walled troughs created by an experimental disturbance collected pyrosomes (megafauna) at significantly higher concentrations (4-76x) than in the flat (undisturbed) sediments nearby (Hoving et al., 2023). Though the benthic community response to this influx of food was not assessed at this site, other studies of pyrosomes as a food source in the deep sea indicate that this substantial input of organic matter would likely have influenced the community structure (Lebrato and Jones, 2009; Smith et al., 2014). Additionally, topographic features such as trenches have been documented to share genera with nearby nodule environments, indicating that connectivity within regions is likely not impeded by these features (Vanreusel et al., 2010; Horacek et al., 2022).

Seafloor topographic complexity (e.g., seamounts, steppes, troughs) can also vary substantially among regions. The Pacific Ocean is estimated to contain significantly more seamounts (9,000-16,000/10⁶ km² seamounts) than the Indian Ocean (500-1600/10⁶ km² seamounts; Das et al., 2007). However, in polymetallic nodule environments specifically, the abundance of seamounts is relatively similar between the Indian and Pacific Oceans, despite the CCZ being almost 40x larger than the surveyed area of the Central Indian Ocean Basin (CIOB; Das et al., 2007; Vineesh et al., 2009; Leitner et al., 2021, and references therein). More seafloor features (e.g., steps, troughs, hills, rises) have been observed in the CCZ than the CIOB (Parianos and Madureira, 2021), but this could be a product of the different sizes of the two regions and/or of the differing research efforts to characterize them. Seafloor topographic complexity also varies among Pacific basins. The southern Pacific Ocean contains slightly more seamounts per square kilometer than the central Pacific, and nodule regions of the southwest Pacific can be topographically complex. For example, the Cook Islands (southwest Pacific) Exclusive Economic Zone (EEZ) contains over 50 large seamounts, many of which are connected through chains of smaller volcanic knolls and the majority of which lie within the nodule-rich areas of the country’s EEZ (Browne et al., 2023). Though recent research has found that seamounts provide additional habitat heterogeneity that supports distinct megafaunal communities (Cuvelier et al., 2020; Leitner et al., 2021; Uhlenkott et al., 2023b), there have not yet been any studies assessing the possible regional differences in these communities by comparing seamounts in different ocean basins.

4.4.4 Geological and geochemical variability

Finally, polymetallic nodules themselves can vary considerably in shape, size, and density at among-region scales. For nodules to form, environmental conditions must be relatively stable. Sedimentation rates, in particular, must be low (< 10 mm per thousand years) to prevent the burial of developing nodules (Kuhn et al., 2017; Hein et al., 2020; Mizell et al., 2022). As a result, nodules generally form in areas with relatively flat seafloor topography and in regions with lower rates of surface productivity (Kuhn et al., 2017; Hein et al., 2020; Mizell et al., 2022), due to their associated low sedimentation rates (Mewes et al., 2014; Mizell et al., 2022). Though polymetallic nodules are found globally, their mineral makeup and structure vary based on the environmental conditions and process under which they form (Hein and Mizell, 2022). There are several varieties of polymetallic nodules (Cronan, 2019), but the ones of greatest commercial interest are hydrogenetic nodules (formed by mineral precipitates from seawater; e.g., west and southwest Pacific nodules), diagenetic nodules (formed by mineral precipitates from sediment pore waters; e.g., Peru Basin nodules), and mixed hydrogenetic-diagenetic nodules (formed from both seawater and sediment pore waters; e.g., CCZ and CIOB nodules; Mizell et al., 2022). Hydrogenetic nodules are most common in regions with low surface productivity, while diagenetic nodules form in areas with moderate surface productivity, which provides the organic matter (and resulting suboxic sediment conditions) needed for diagenetic reactions in sediment pore waters (Mewes et al., 2014; Mizell et al., 2022). Based on these different processes—and differing mineral concentrations in seawater and sediment pore water among ocean basins—the mineral makeups of nodules vary according to both nodule type and location (Hein and Mizell, 2022; Mizell et al., 2022). This variability in both geology and biogeochemistry may also contribute directly to regional differences in faunal communities. Nodules of different varieties and/or from different regions have been shown to harbor distinct microbial communities and exhibit different local biogeochemistry (Blöthe et al., 2015; Wear et al., 2021; Bergo et al., 2022). Microbes play a critical role in nutrient cycling, metal sequestration, and abyssobenthic food webs (de Jonge et al., 2020; Orcutt et al., 2020), and biogeochemical conditions (e.g., high concentrations of certain metals, low oxygen penetration depths; Paul et al., 2018; Haffert et al., 2020) can favor or preclude certain fauna. As a result, it is likely that these regional differences in nodule composition or geochemistry may have a direct influence on regional faunal community structure.

The same broad-scale environmental conditions that influence the formation of nodule environments also directly influence the communities living in them. Due to the stability of nodule environments, nodule fauna are generally slow growing and many are sessile, particularly at larger faunal size classes (Veillette et al., 2007b; De Smet et al., 2017). Reproduction in polymetallic nodule communities remains poorly understood for all faunal size classes, but existing research indicates that they exhibit significantly lower larval abundance and flux (vertical movement of larvae to the seafloor over time; ind. d⁻¹ m⁻²) and higher retention of larvae near the benthos than in other deep-sea habitats (Kersten et al., 2017, Kersten et al., 2019). This may contribute to slow recovery rates (Miljutin et al., 2011; Jones et al., 2017; Simon-Lledó et al., 2019a), as larvae retained near the seafloor would be more vulnerable to disturbances that create adverse conditions near the benthos (e.g., sediment plumes).

5 Disturbance in polymetallic nodule environments

Disturbance in polymetallic nodule environments can influence fauna both directly and through the disturbance’s impact on habitat heterogeneity. Though many forms of disturbance occur naturally in polymetallic nodule environments, large-scale natural disturbances are uncommon. Polymetallic nodule mining would effectively act as a large-scale disturbance that would alter habitat heterogeneity through the removal of hard substrates, the creation of troughs or tracks in the sediment, and the deposition of sediment that may smother fauna and homogenize the texture of the seafloor (Figure 4). While existing research has offered valuable insights about disturbance in nodule environments, particularly at smaller spatial scales, the influence of disturbance on nodule communities—including through its impact on habitat heterogeneity—remains poorly understood.

Figure 4

Figure 4. Schematic of conceptual deep-sea polymetallic nodule mining system (figure adapted from Figure 2 in Gillard et al., 2022).

5.1 Natural disturbance

Due to most nodule fields’ locations beneath abyssal waters, naturally reoccurring disturbance in nodule ecosystems generally takes the form of biogenic disturbance (e.g., bioturbation; Volz et al., 2020) or food flux (e.g., Amon et al., 2017). Regular small-scale disturbances in the form of bioturbation and biogenic structures (i.e., Lebensspuren) generally correlate with higher faunal diversity and density throughout the deep sea (Kukert and Smith, 1992; Meadows and Meadows, 1994; Meadows et al., 2012), including at abyssal depths (Ruhl and Smith, 2004; Bell et al., 2016; Rosli et al., 2018). Bioturbation lowers sediment shear strength, which may provide more microhabitats that support higher infaunal diversity or abundance (Tong et al., 2022) and helps to transport critical resources (namely food and oxygen) into deeper sediments where they support life ranging from microbes to megafauna (Rosli et al., 2018; Bonaglia et al., 2020; Haffert et al., 2020; Tong et al., 2022). The openings to biogenic structures also increase the texture of the seafloor. This texture creates greater habitat heterogeneity and promotes the resuspension of materials at the sediment-water interface (Huettel et al., 1996), which facilitates nutrient cycling and supports local faunal communities through the resuspension of organic matter (Levinton, 1995; Ford et al., 1999).

As in other ecosystems in the food-limited deep sea, food flux can also act as a disturbance agent in polymetallic nodule environments. Though thought to be less common than on continental margins, organic falls do occur in nodule environments (Amon et al., 2017), and exhibit similar faunal communities to continental margin organic falls (Bienhold et al., 2013; Cunha et al., 2013; Amon et al., 2017). Organic falls observed throughout the CCZ hosted common organic fall specialists (e.g., Xylophagaidae mollusks, mobile scavengers), along with several other species not observed elsewhere in the CCZ (Amon et al., 2017). While temporal variability in the influx of food (e.g., phytodetritus, pyrosome carcasses) has been observed in some nodule environments, the extent to which these food fluxes may be cyclical or act as a disturbance remains poorly understood (Durden et al., 2021; Uhlenkott et al., 2021). However, based on the influence of large food fluxes in other abyssal environments, it remains likely that these events may temporarily restructure local faunal communities (Thurston et al., 1998; Ruhl and Smith, 2004; Bailey et al., 2006; Woolley et al., 2016).

Large natural disturbances are not uncommon in abyssal environments, which can be impacted by gravity currents such as turbidity flows that reach abyssal plains through canyons and channels on the continental rise (Bigham et al., 2021) or from benthic storms (Miguez-Salas et al., 2020). The CCZ is subject to energetic mesoscale eddies (Aleynik et al., 2017), which may cause episodic environmental stress from strengthened bottom currents and sediment resuspension. However, the characteristics that facilitate the formation of nodules over long time frames indicate that nodule environments are generally relatively stable, with flat topography and low sedimentation rates. As a result, catastrophic large-scale disturbances are unlikely to occur naturally in polymetallic nodule environments.

5.2 Anthropogenic disturbance

Understanding the potential impact that deep-seabed mining may have on nodule communities has necessitated in-situ experimentation or the study of proxies in similar environments, though these have remained limited in scope and scale (Gollner et al., 2017; Jones et al., 2017; Cuvelier et al., 2018). The study of proxies, in particular, has yielded little information about the possible reaction of nodule communities due either to the scale of the proxy disturbance (e.g., Jamieson et al., 2022) or its location (e.g., at bathyal depths, close to shore, at hydrothermal vents; Gollner et al., 2017; Bigham et al., 2024; Leduc et al., 2024a; Murray et al., 2024). As a result, in-situ experimentation remains the most promising avenue for estimating the possible impacts of polymetallic nodule mining on faunal communities.

5.2.1 Historic disturbance experiments

Experiments conducted in the late 1980s and 1990s throughout nodule areas of the Central and Eastern Pacific provided the first glimpses of ecological responses to disturbances meant to mimic the effects of mining in the CCZ (Brockett and Richards, 1994; Trueblood and Ozturgut, 1997; Borowski and Thiel, 1998; Tkatchenko and Radziejewska, 1998) and in the Peru Basin (Thiel and Schriever, 1990; Borowski and Thiel, 1998; Bluhm, 2001; Borowski, 2001; Thiel et al., 2001; Radziejewska, 2014)(Table 1). The footprint of these experiments varied, with most experiments disturbing at the patch or field scale, using either a series of unidirectional tracks (generally 2–4 km each in length) or disturbed plots (up to 11 km²; Jones et al., 2017). Across all the experiments, the disturbances left physical marks (troughs or scars generally 2–8 m wide and 2–4 km long) on the seafloor that remained visible throughout the timeframes of the experiments (1–26 years) (Figure 5). All experiments resulted in a decrease in both faunal abundance and diversity immediately following the disturbances (Bluhm et al., 1995; Schriever et al., 1997; Borowski and Thiel, 1998; Ahnert and Schriever, 2001; Borowski, 2001; Radziejewska, 2014). Most experiments resulted in long-term reductions of both faunal density and diversity, though some faunal groups (e.g., meiofauna in the Indian Ocean, mobile deposit feeders in the CCZ) showed partial recovery towards pre-disturbance densities on the timescale of months to years, depending on the site (Jones et al., 2017, Jones et al., 2025). The only studies investigating fauna living directly associated with the nodules saw a shift in megafauna community composition from mixed sessile and mobile fauna to solely mobile fauna (e.g., holothurians, ophiuroids) at study sites where nodules were removed, and recovery by sessile fauna (e.g., gorgonians, sponges, crinoids) was not observed after 26 years—likely due to the lack of hard substrates for attachment (Bluhm et al., 1995; Bluhm, 2001; Miljutin et al., 2011; Amon et al., 2016; Jones et al., 2025).

Table 1

Table 1. Historic and recent disturbance experiments conducted to simulate the effects of deep-seabed mining, including the equipment used and the scale of the disturbance, along with an inexhaustive list of relevant references.

Figure 5

Figure 5. Example of plough-disturbed seafloor from a disturbance experiment (top) and undisturbed seafloor from a nearby site (bottom) in the Peru Basin. Photographs from Figure 1 of Simon-Lledó et al., 2019d.

These first long-term studies of mining-like disturbances in polymetallic nodule environments provided important early observations of the resilience of nodule communities. However, the studies were limited in scope, scale, and sampling integrity (Radziejewska, 2014; Gollner et al., 2017; Jones et al., 2017). Each of the experiments used different methodologies and sampling devices, and the wider applicability of the findings in many cases suffered from technological limitations and low replicate numbers (Fukushima, 1995; Fukushima et al., 2000; Gollner et al., 2017; Jones et al., 2017; Fukushima and Tsune, 2019). The devices used to create the disturbances also varied between studies (e.g., nodules removed vs displaced or buried; different depths of sediment disturbance; different sediment plume scales; Jones et al., 2017), which may have contributed to the different results observed across sites (e.g., increased sediment heterogeneity supporting increased nematode diversity at some experiment sites in the CCZ; Jones et al., 2017; Fukushima et al., 2022). This research also focused on soft sediment communities in areas with lower nodule densities, and, with the exception of megafauna studies, did not investigate the impact of disturbance on nodule-specific fauna, despite their vulnerability to nodule removal (Jones et al., 2017). Since the scale of the experiments was small (a maximum of tens of square kilometers over a few days), it remains difficult to extrapolate their results to the scale of proposed commercial mining (tens of thousands of square kilometers over years), which will influence habitat heterogeneity with greater totality (i.e., complete removal of nodules over large spatial and temporal scales), and therefore benthic communities are likely to exhibit longer recovery times (Borowski and Thiel, 1998; Borowski, 2001; Jones et al., 2017).

5.2.2 Recent disturbance experiments

Given the limitations of previous research, further experimentation has begun in the CCZ and the Peru Basin to fill in the gaps of earlier research (e.g., Gollner et al., 2022; Muñoz-Royo et al., 2022; Stenvers et al., 2023; Lefaible et al., 2024; Vornsand et al., 2024)(Table 1). However, the timescales of these experiments currently remain short, as many of these studies began only within the past several years (e.g., Lefaible et al., 2024) and/or rely on the limited data collected in the aforementioned studies to serve as baselines (e.g., Vornsand et al., 2024; Jones et al., 2025). Furthermore, while many recent disturbance experiments use nodule collector prototypes that closely imitate proposed mining (e.g., nodule removal, movement via caterpillar tracks), the spatial scales of these experiments (<0.05 km²) remain small compared to commercial exploitation (10–100 km²; Muñoz-Royo et al., 2022; Lefaible et al., 2024; Vornsand et al., 2024).

A study of a sediment track in the Peru Basin (near the 1989 experiment site) exhibited 50% lower abundance of Lebensspuren (track, trails and other visible signs of benthic epi- and in-fauna activity) six months after a disturbance event compared to pre-disturbance levels, potentially due to reduced labile carbon availability in the sediments (Vornsand et al., 2024). This speculation is supported by a recent study in the CCZ, which found significantly lower total organic carbon in sediments along the path of a mining prototype and lower food availability in nearby sediments covered by settling sediment plumes (Lefaible et al., 2024). This disturbance and its associated reduction in organic carbon may effectively homogenize sediments and resource availability, therefore reducing patch-scale habitat heterogeneity that supports biodiversity. Additionally, the deposition of sediments may smother sediment fauna and disrupt natural processes of nutrient flux along sediment depths (Miljutin et al., 2011; Gollner et al., 2017). An ongoing study in the CCZ is currently investigating the potential for restoration through the provision of artificial hard substrates, but the feasibility of this possible restoration method will not be known until the completion of the decades-long experiment (expected to end in approximately 30 years; Gollner et al., 2022). The initial observation of colonization after eight weeks of deployment found only one mobile polychaete on the deployment apparatus and no sessile fauna on the ceramic “nodules” (Gollner et al., 2022), which aligns with the slow colonization and recovery rates known to characterize nodule ecosystems. Though still in the early stages of long-term monitoring (and still limited in scale compared to proposed commercial mining), the CCZ experiments using nodule collector prototypes will likely provide a more robust estimation of the potential effects of industrial mining than historic experiments, including on habitat heterogeneity, as the devices use similar collection and locomotory mechanisms to devices proposed for industrial-scale operations.

5.3 Climate change

In addition to the impact of direct anthropogenic disturbance, polymetallic nodule environments are also increasingly influenced by climate change. Climate change is expected to impact primary productivity throughout the ocean, including through the disruption of regular large-scale climate oscillations (e.g., ENSO), which will have cascading impacts on food flux to the deep sea and therefore on faunal communities (Jones et al., 2014; Yasuhara and Danovaro, 2016; Sweetman et al., 2017; Intergovernmental Panel on Climate Change, 2022). Though the influence of large-scale climatic variations on nodule communities remains understudied, climate oscillations have been observed to influence abyssal fauna, including nodule fauna, through their influence on regional habitat heterogeneity via their effect on resource availability (Billett et al., 2001; Smith et al., 2006; Kaiser et al., 2024). The deep sea is also vulnerable to other climate impacts, including ocean acidification and deoxygenation, whose impacts are only beginning to be understood in abyssal environments (Hennige et al., 2015; Levin and Le Bris, 2015; Sweetman et al., 2017), and which could degrade biogenic structures that provide patch- and field-scale substrate heterogeneity, or reduce regional habitat heterogeneity through the homogenization of environmental conditions, respectively. As the impacts of climate change intensify and accelerate, these disruptions to the environmental conditions of the deep sea are likely to compound with direct anthropogenic disturbances such as deep-seabed mining (Sweetman et al., 2017; Levin et al., 2020; Smith et al., 2020). Proponents of deep-seabed mining have presented nodules as essential for addressing climate change by providing minerals for green energy technologies. However, new discoveries (e.g., the possible production of “dark oxygen” in nodule environments; Sweetman et al., 2024) indicate that knowledge gaps about nodule environments remain, including unknown ecological or environmental phenomena that may interact with known climate impacts. It is therefore critical that these effects are studied further and considered in concert with ongoing mining disturbance studies and other baseline research to inform the development of environmental management plans for the mining of polymetallic nodules.

6 Knowledge gaps and management implications

Among polymetallic nodule environments, studies of habitat heterogeneity (e.g., Simon-Lledó et al., 2019b; Mejía-Saenz et al., 2023; Uhlenkott et al., 2023b) remain relatively rare, and are often limited in size or scope (e.g., covering only one faunal size class or spatial scale). While existing studies represent a crucial advancement on the subject, it is critical to include considerations of habitat heterogeneity in a greater breadth of future studies spanning faunal size classes, spatial scales, and sites.

Examinations of multiple faunal size classes in the same study ensures the most holistic approach to investigating benthic faunal communities, however, this is rarely achieved in deep-sea studies. Size differences naturally influence the interaction between faunal communities and different spatial scales of habitat heterogeneity (Gee and Warwick, 1994a; McClain and Barry, 2010; van der Grient and Rogers, 2019), as organisms of different sizes have different windows of perception (e.g., a sessile macrofaunal polychaete will interact with its environment at a smaller spatial scale than a mobile megafaunal scavenger will; Kotliar and Wiens, 1990; Attrill et al., 2000). Therefore, while a nodule-rich area of only a few square meters could be enough to support macrofaunal diversity and connectivity, megafauna communities may require a larger area that encompasses multiple spatial scales of habitat heterogeneity, which could have substantial implications for the designation of areas protected from mining. Furthermore, fauna of different size classes generally exhibit different life cycles and other biological traits which influence their response to disturbance (Gage and Tyler, 1991; Warwick and Clarke, 1996; Rex and Etter, 2010; Zeppilli et al., 2015), including any disturbance affecting habitat heterogeneity. If mining regulators decided that mining operators needed to leave patches of untouched nodule habitat between mining tracks to facilitate recolonization and recovery, information about the complex interactions between faunal size class, community structure, and nodule density and distribution would be crucial to determine the most effective patch size and arrangement to leave undisturbed. Though multiple studies of nodule fauna have included multiple size classes (e.g., Veillette et al., 2007a; Jones et al., 2021; Stratmann et al., 2021), no studies have yet done so with a specific focus on the habitat heterogeneity-community structure relationship. Future studies should therefore include an assessment of the influence of habitat heterogeneity on multiple faunal size classes together within the same study to increase comparability, help elucidate this habitat heterogeneity-community structure relationship, and inform relevant management decisions.

In conjunction with understanding the influence of habitat heterogeneity across faunal size classes, its influence must be further investigated across spatial scales to help determine at what scale habitat heterogeneity most profoundly affects faunal communities (e.g., what metric of habitat heterogeneity supports the highest biodiversity, and at what magnitude). Though a growing body of research has compared faunal communities among nodule fields (e.g., sampling sites; Simon-Lledó et al., 2019c; Chuar et al., 2020; Pasotti et al., 2021) and regions (Vanreusel et al., 2016; Hauquier et al., 2019; Cuvelier et al., 2020; Simon-Lledó et al., 2020), little research has compared communities at the nodule or patch scales (Veillette et al., 2007a; Singh et al., 2019; Pape et al., 2021). Furthermore, though studies have investigated the influence of habitat heterogeneity at more than one spatial scale, no research has yet examined its influence comprehensively across a broad range of spatial scales, from among nodules to among regions. Due to the size of mining contract areas and the variability in sampling methodology, comparing results at different scales from different studies can be difficult. As a result, conducting these scale-dependent assessments comprehensively within one research endeavor could ensure more reliable results about how the influence of habitat heterogeneity changes with the spatial scale of focus. Information about how habitat heterogeneity supports faunal diversity, density, or rarity can inform which areas should be prioritized for protection (e.g., via an Area of Particular Environmental Interest or other marine protected area) and can ensure that rare or endemic species are protected from extinction (e.g., Reed et al., 2006; Lowry et al., 2011). Additionally, this information can be used to protect areas of higher faunal diversity or abundance on spatial scales that preserve population connectivity and facilitate the recolonization of areas disturbed by mining. More knowledge about the habitat heterogeneity-biodiversity relationship will ultimately be crucial for managing nodule mining.

Multiple studies have explored and developed management frameworks to assess the environmental impact of proposed mining activities and avoid “serious harm” as required by ISA regulations (Levin et al., 2016; Durden et al., 2017; Ellis et al., 2017; Christiansen and Bräger, 2023; Leduc et al., 2024a). These frameworks use an assessment of both the mining disturbance (e.g., duration, size, frequency, etc.) and the structural components of the ecosystem being impacted (e.g., rarity/endemism, productivity, growth rates, etc.; Leduc et al., 2024b). An understanding of the relationship between habitat heterogeneity and community structure—particularly biodiversity—could be a critical contribution to the assessment of these structural ecosystem components and could therefore help inform the designation of thresholds that trigger management or mitigation requirements under these frameworks. Figure 6 illustrates the different theoretical habitat heterogeneity-biodiversity relationships that could exist at the field scale (10s to 1000s of meters) in a polymetallic nodule contract area, and the associated levels of caution with which management decisions should be made for seabed mining. For example, if a positive linear relationship exists between habitat heterogeneity and biodiversity in a mining contract area (as has been found in other deep-sea habitats; Etter and Grassle, 1992), serious harm to benthic communities in areas with high levels of heterogeneity may impact more fauna than in areas with low levels of heterogeneity if mining occurs there. As a result, mining regulator authorities may decide to exercise increased caution when determining if and how mining may occur in these high heterogeneity areas (Figure 6A). If a unimodal relationship between habitat heterogeneity and biodiversity is observed (as suggested for nodule environments in Amon et al., 2016), this may increase the level of caution with which management occurs for areas with moderate levels of habitat heterogeneity, where biodiversity is highest and therefore serious harm from mining more likely to occur to more fauna (Figure 6B). Alternatively, an asymptotic relationship may be discovered or predicted between habitat heterogeneity and biodiversity in a contract area, in which habitat heterogeneity only supports high diversity up to a certain threshold after which there are diminishing returns (as suggested for cold water coral reefs in Rowden et al., 2020), mining regulators could exercise less caution in the bottom half of the curve, but may take a more conservative management approach to avoid serious harm for areas at or near the maximum point in the biodiversity-habitat heterogeneity curve (Figure 6C). In this case, the required level of caution would likely vary on a case-by-case basis, depending on the scale of proposed mining, the habitats or communities of interest, and the overall management goals. Ultimately, the biodiversity-habitat heterogeneity relationship will be just one of many factors informing the management of claim areas under a future mining scenario. However, the nature of the habitat heterogeneity-biodiversity relationship can be used to help inform managers which areas in the claim area may be vulnerable to serious harm from seabed mining, and thus where mitigation measures or a more precautionary approach are likely to be required (Figure 6).

Figure 6

Figure 6. Different theoretical relationships between biodiversity and habitat heterogeneity in nodule environments at the field scale (solid lines) and potential associated levels of caution (shaded colors) recommended for determining management strategies for nodule mining license claim areas: (A) linear, (B) unimodal, and (C) asymptotic. Shaded colors indicate lower (yellow), intermediate (orange), and high (red) levels of caution, based on the hypothetical ranges at which disturbance to habitat heterogeneity would be more likely to cause serious harm. Levels of caution could be associated with different impact assessment or mitigation requirements for mining contractors, with higher levels of caution necessitating adherence to more stringent requirements.

Another substantial knowledge gap regarding habitat heterogeneity is a lack of research across nodule-rich geographic locations. Understandably, the recent surge of research activity on the benthic fauna associated with polymetallic nodules has been focused in the CCZ, where proposed mining is under the most immediate consideration. However, even the best-studied nodule environments in the CCZ remain poorly understood compared to other deep-sea environments, and areas considered for nodule mining within countries’ EEZs (e.g., the Cook Islands nodule fields in the Penrhyn Basin) have never been the subject of any formal ecological research. In the deep sea, habitat heterogeneity and broad-scale environmental variability are often deeply intertwined. As a result, both habitat heterogeneity and its influence on benthic fauna may vary substantially between different geographical regions, making area-specific research both necessary and urgent. Without understanding the composition of different nodule communities and how the habitat heterogeneity-biodiversity relationship varies across geographic regions, management practices suitable to one area may be applied universally with ineffective results.

In addition to the above knowledge gaps, current methodology and metrics for studying habitat heterogeneity in nodule ecosystems may be insufficient to thoroughly describe it and its associated fauna. The metrics used to describe habitat heterogeneity in nodule environments vary considerably (Table 2), but most studies focus on just one metric (generally related to nodule abundance) at one spatial scale. Many of these metrics only measure habitat area or volume, simplifying patch- and field-scale habitat complexity into the presence or absence of hard substrates and overlooking heterogeneity at the smallest scale (millimeters to centimeters) entirely. Quantifying habitat heterogeneity is notoriously difficult, as the irregularity and complexity of natural heterogeneity makes simple equations difficult to create and apply broadly (Loke and Chisholm, 2022). Furthermore, measuring the relationship between habitat heterogeneity and biodiversity can be confounded by the species-area relationship (Arrhenius, 1921) when using simply habitat area or volume (or metrics based on area or volume) as a metric (Steinmann et al., 2011). However, metrics like rugosity or fractal dimension, which allow a quantitative assessment of surface complexity along a continuous scale, have successfully quantified habitat heterogeneity in other studies (e.g., on coral reefs, macroalgae; Gee and Warwick, 1994b; McAbendroth et al., 2005; Walker et al., 2009), and show promise as a method for nodule environments, particularly at the nodule scale. Rugosity is calculated as the ratio of a surface’s actual 3D area to its planar (projected) area, providing a measure of surface roughness relative to flatness. Fractal dimension quantifies surface complexity by evaluating how detail or irregularity scales with measurement resolution (e.g., using box-counting or other multi-scale methods), making it particularly successful at describing fine-scale habitat heterogeneity. However, fractal dimension requires habitats or objects to be fractal (or nearly fractal), which is done by testing its proximity to fractal at 2–3 orders of magnitude (Gonzato et al., 1998), making it difficult to apply to real-world heterogeneity, and particularly to objects as small as nodules. Vector dispersion, which describes the heterogeneity of surface angles at a specific resolution (with higher values indicating greater roughness), has also showed promise in some heterogeneity studies (e.g., on coral reefs; (Carleton and Sammarco, 1987; McCormick, 1994; Young et al., 2017), but has not been as widely tested and, like many metrics (Table 2), can be confounded with area (Loke and Chisholm, 2022). There are also metrics of habitat heterogeneity that can be borrowed from studies of landscape ecology which can be usefully applied at the patch and field scale in nodule environments. Metrics such as spatial congruence and nearest neighbor distance have been used for many years to examine the habitat heterogeneity-biodiversity relationship in terrestrial environments (e.g., Watling et al., 2011; Huntington and Lirman, 2012; Xu et al., 2019), and can provide information about the uniformity or irregularity of patches and their spatial arrangement, respectively. The application of metrics like these, and those indicated for examining the nodule scale, could more robustly characterize habitat heterogeneity—and therefore its influence-in nodule environments, and do so in a more standardized way. Although there are some commonalities, sampling devices vary in both design and size, which can complicate comparing these metrics of habitat heterogeneity across studies (Washburn et al., 2021b; Kaiser et al., 2023). Semi-quantitative, information-based metrics (e.g., defining a metric for nodule patch density) also show promise at intermediate spatial scales (Loke and Chisholm, 2022), but would similarly require standardization to ensure the metric is comparable across study designs and sampling devices.

Table 2

Table 2. Metrics for measuring habitat heterogeneity in nodule environments and their associated advantages and disadvantages, according to spatial scale and faunal size class of focus.

Finally, the monetary and temporal costs of more focused sampling and analysis remain hurdles to closing the knowledge gaps around the influence of habitat heterogeneity and disturbance on benthic community structure. However, closing these gaps remains critical to informing the successful management and conservation of polymetallic nodule ecosystems.

7 Conclusion

There is a growing body of knowledge regarding the community structure and disturbance resilience of benthic communities associated with polymetallic nodule environments. However, better ecological baselines and other knowledge, particularly in understanding the relationship between habitat heterogeneity and benthic community structure, will be required to accurately predict—and therefore manage—the impact that mining may have on faunal communities (Gollner et al., 2017; Jones et al., 2017; Haffert et al., 2020). Current research indicates that nodules play an important role in structuring communities (Veillette et al., 2007a, Veillette et al., 2007b; Simon-Lledó et al., 2019c; Chuar et al., 2020; Cuvelier et al., 2020; Leitner et al., 2021). Nodules have been consistently found to support higher diversity and abundance in megafauna (Amon et al., 2016; Vanreusel et al., 2016; Tilot et al., 2018; Mejía-Saenz et al., 2023; Uhlenkott et al., 2023b, Uhlenkott et al., 2023a) and macrofauna (De Smet et al., 2017; Yu et al., 2018; Chuar et al., 2020) compared to nodule-free sediments. Though some studies have indicated an inverse relationship between meiofauna abundance and nodule abundance (Hauquier et al., 2019; Pape et al., 2021), nodules have also been found to support slightly higher meiofaunal diversity in others (Singh et al., 2016; Pape et al., 2021). Other forms of habitat heterogeneity in nodule environments (e.g., seamounts, rocks, topographical variations) have been shown to support distinct communities with higher diversity than flat, soft sediments (Cuvelier et al., 2020; Leitner et al., 2021; Mejía-Saenz et al., 2023; Uhlenkott et al., 2023b). However, the full extent of the relationship between habitat heterogeneity and faunal community structure remains ambiguous in polymetallic nodule environments, particularly across different spatial scales and faunal size classes, and due in part to the limited metrics currently used to measure it. Without the development of robust knowledge about the habitat heterogeneity-community structure relationship in polymetallic nodule environments, extractive industries may irreversibly alter the habitat heterogeneity that nodules provide before its importance is fully understood.

Author contributions

AU: Investigation, Writing – original draft, Visualization, Writing – review & editing, Conceptualization. AR: Supervision, Writing – original draft, Writing – review & editing. DL: Writing – review & editing, Writing – original draft, Supervision. DZ: Writing – original draft, Writing – review & editing, Supervision.

Funding

The author(s) declare financial support was received for the research and/or publication of this article. DZ was supported by the Ifremer Marine Mineral Resources project (REMIMA project) and by the French National Research Agency under France 2030 (reference ANR-22-MAFM-0001). DZ was also supported by the project “Massive mEIOfauna DiscoverY of new Species of our oceans and SEAs (MEIODYSSEA) funded by the Ocean Shot Research Grant Program of the Sasakawa Peace Foundation, supported by the Nippon Foundation.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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