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• Short, F.T., T.J.R. Carruthers, B. van Tussenbroek, and J. Zieman. 2010. Halodule wrightii. The IUCN Red List of Threatened Species 2010: e.T173372A7001725. http://dx.doi.org/10.2305/IUCN.UK.2010-3.RLTS.T173372A7001725.en.
• Short, F.T., T.J.R. Carruthers, B. van Tussenbroek, and J. Zieman. 2010. Halophila baillonii. The IUCN Red List of Threatened Species 2010: e.T173382A7004500. http://dx.doi.org/10.2305/IUCN.UK.2010-3.RLTS.T173382A7004500.en.
• Short, F.T., T.J.R. Carruthers, B. van Tussenbroek, and J. Zieman. 2010. Syringodium filiforme. The IUCN Red List of Threatened Species 2010: e.T173378A7003203. http://dx.doi.org/10.2305/IUCN.UK.2010-3.RLTS.T173378A7003203.en.
• Short, F.T., T.J.R. Carruthers, M. Waycott, G.A. Kendrick, J.W. Fourqurean, A. Callabine, W.J. Kenworthy, and W.C. Dennison. 2010. Halophila decipiens. The IUCN Red List of Threatened Species 2010: e.T173352A6997485. http://dx.doi.org/10.2305/IUCN.UK.2010-3.RLTS.T173352A6997485.en.
• Short, F.T., T.J.R. Carruthers, M. Waycott, G.A. Kendrick, J.W. Fourqurean, A. Callabine, W.J. Kenworthy, and W.C. Dennison. 2010. Halophila ovalis. The IUCN Red List of Threatened Species 2010: e.T169015A6561794. http://dx.doi.org/10.2305/IUCN.UK.2010-3.RLTS.T169015A6561794.en.
• Short, F.T., T.J.R. Carruthers, M. Waycott, G.A. Kendrick, J.W. Fourqurean, A. Callabine, W.J. Kenworthy, and W.C. Dennison. 2010. Thalassia hemprichii. The IUCN Red List of Threatened Species 2010: e.T173364A7000000. http://dx.doi.org/10.2305/IUCN.UK.2010-3.RLTS.T173364A7000000.en.
• Short, F.T., R. Coles, M. Waycott, J.S. Bujang, M. Fortes, A. Prathep, A.H.M. Kamal, T.G. Jagtap, S. Bandeira, A. Freeman, P. Erftemeije, Y.A. La Nafie, S. Vergara, H.P. Calumpong, and I. Makm. 2010. Cymodocea serrulata. The IUCN Red List of Threatened Species 2010: e.T173358A6998619. http://dx.doi.org/10.2305/IUCN.UK.2010-3.RLTS.T173358A6998619.en.
• Short, F.T., R. Coles, M. Waycott, J.S. Bujang, M. Fortes, A. Prathep, A.H.M. Kamal, T.G. Jagtap, S. Bandeira, A. Freeman, P. Erftemeije, Y.A. La Nafie, S. Vergara, H.P. Calumpong, and I. Makm. 2010. Halophila hawaiiana. The IUCN Red List of Threatened Species 2010: e.T173338A6994270. http://dx.doi.org/10.2305/IUCN.UK.2010-3.RLTS.T173338A6994270.en.
• Short, F.T., R. Coles, M. Waycott, J.S. Bujang, M. Fortes, A. Prathep, A.H.M. Kamal, T.G. Jagtap, S. Bandeira, A. Freeman, P. Erftemeije, Y.A. La Nafie, S. Vergara, H.P. Calumpong, and I. Makm. 2010. Halophila minor. The IUCN Red List of Threatened Species 2010: e.T173376A7002822. http://dx.doi.org/10.2305/IUCN.UK.2010-3.RLTS.T173376A7002822.en.
• Short, F.T., R. Coles, M. Waycott, J.S. Bujang, M. Fortes, A. Prathep, A.H.M. Kamal, T.G. Jagtap, S. Bandeira, A. Freeman, P. Erftemeije, Y.A. La Nafie, S. Vergara, H.P. Calumpong, and I. Makm. 2010. Syringodium isoetifolium. The IUCN Red List of Threatened Species 2010: e.T173332A6992969. http://dx.doi.org/10.2305/IUCN.UK.2010-3.RLTS.T173332A6992969.en.
• Short, F.T. and J. Gaeckle. 2010. Zostera pacifica. The IUCN Red List of Threatened Species 2010: e.T173373A7002177. http://dx.doi.org/10.2305/IUCN.UK.2010-3.RLTS.T173373A7002177.en.
• Short, F.T. and M. Waycott. 2010. Cymodocea rotundata. The IUCN Red List of Threatened Species 2010: e.T173363A6999692. http://dx.doi.org/10.2305/IUCN.UK.2010-3.RLTS.T173363A6999692.en.
• Short, F.T. and W. Waycott. 2010. Enhalus acoroides. The IUCN Red List of Threatened Species 2010: e.T173331A6992567. http://dx.doi.org/10.2305/IUCN.UK.2010-3.RLTS.T173331A6992567.en.
• Short, F.T. and M. Waycott. 2010. Zostera asiatica. The IUCN Red List of Threatened Species 2010: e.T173339A6994461. http://dx.doi.org/10.2305/IUCN.UK.2010-3.RLTS.T173339A6994461.en.
• Short, F.T., S.L. Williams, T.J.R. Carruthers, M. Waycott, G.A. Kendrick, J.W. Fourqurean, A. Callabine, W.J. Kenworthy, and W.C. Dennison. 2010. Halodule pinifolia. The IUCN Red List of Threatened Species 2010: e.T173327A6991467. http://dx.doi.org/10.2305/IUCN.UK.2010-3.RLTS.T173327A6991467.en.

Kolinksi, S.P., D.M. Parker, L.I. Ilo, and J.K. Ruak. 2001. An assessment of the sea turtles and their marine and terrestrial habitats at Saipan, Commonwealth of the Northern Mariana Islands. Micronesica 24(1):55-72.

Lobban, C.S. and R.T. Tsuda. 2003. Revised checklist of benthic marine macroalgae and seagrasses of Guam and Micronesia. Micronesica 35-36:54-99.

Miller, G.L. and A.E. Lugo. 2009. Guide to the Ecological Systems of Puerto Rico. General Technical Report IITF-GTR-35. USGA, Forest Service, International Institute of Tropical Forestry.

NRCS (Natural Resources Conservation Service). 2019. Plants Database. USDA, Natural Resources Conservation Service. https://plants.sc.egov.usda.gov/java/.

Ruiz, H., D.L. Balantine, and J. Sabater. 2017. Continued spread of the seagrass Halophila stipulacea in the Caribbean: documentation in Puerto Rico and the British Virgin Islands. Gulf and Caribbean Research 28(1):SC5-SC7.

Skelton, P.A. 2003. Seaweeds of American Samoa. Prepared for Department of Marine & Wildlife Resources and Government of American Samoa, by Skelton, P.A., Queensland, Australia.

Sturm, D.J., J. Stout, and T. Thibaut. 2007. Statewide summary for Alabama. In Seagrass Status and Trends in the Northern Gulf of Mexico: 1940-2002, ed. L. Dandley, D. Altsman, and R. DeMay, pp. 87-97. US Geological Survey, Reston, VA.

Tsuda, R.T., F.R. Fosberg, and M.H. Sachet. 1977. Distribution of Seagrasses in Micronesia. Micronesica 13(2):191-198.

Willette, D.A., J. Chalifour, A.O.D. Debrot, M.S. Engel, J. Miller, H.A. Oxenford, F.T. Short, S.C.C. Steiner, and F. Vedie. 2014. Continued expansion of the trains-Atlantic invasive marine angiosperm Halophila stipulacea in the Eastern Caribbean. Aquatic Botany 112:98-102.

Williams, S.L. 2007. Introduced species in seagrass ecosystems: status and concerns. Journal of Experimental Marine Biology and Ecology. 350:89-110.

Because of their high light requirements, the amount of light available to seagrasses is one of the key drivers affecting their distribution and health (Duarte 1991, Dennison et al. 1993, Ralph et al. 2007). The growth pattern of seagrasses along estuarine depth gradients is often characterized by an unvegetated zone near shore, a depth range with maximum seagrass coverage, and unvegetated bottom in deeper waters, defined by light requirements and local average water clarity (Beck et al. 2017). Several factors can affect the amount of light available to seagrasses; however, the most widespread and significant effects of nutrient pollution on seagrass’ growth are mediated through the effect of nutrients on the growth of phytoplankton, macroalgae, and epiphytes, and their subsequent reduction of the average amount of light available to seagrasses (Batiuk et al. 1992, 2000; Burkholder et al. 2007; Nelson 2009). The decrease in light reaching seagrasses shrinks the depth suitable for seagrasses, often to the degree that seagrasses can no longer inhabit an area (Tables 2-4).  Thus, whereas many other factors are potentially important and should be considered where most relevant, an understanding of interactions involving nutrients, light, and seagrasses is fundamental to development of seagrass as an assessment endpoint for nutrient pollution management.

The general mechanism by which nutrient pollution affects the light environment for seagrasses is well understood. Increased nutrient availability stimulates primary productivity, thereby increasing the abundance of algae and other organic material in the water column, on the benthos among seagrasses, and on the seagrass leaves. This additional material absorbs and reflects light, reducing the amount of light reaching seagrasses. Reduced average light availability harms seagrasses by reducing their energetic potential to grow and overcome other natural and anthropogenic physiological stressors. Because seagrasses “leak” oxygen into otherwise anoxic sediments, and photosynthesis is a primary source of oxygen to benthic environments, reduced primary production can also lead to increased redox stress in the below-ground biomass of seagrass (Borum et al. 2007). 

The mechanisms of nutrient-related effects on seagrass point to several potential water quality related indicators tied to a seagrass endpoint. Like seagrasses, phytoplankton, macroalgae, and epiphytes are primary producers and are among the first organisms to respond to nutrient pollution in a waterbody. Among these, however, only seagrasses also can obtain and retain nutrients from sediments, making them good competitors in low-nutrient regimes. Under conditions of elevated water column nutrients, seagrass competitors are better able to increase in biomass. Because these organisms either occupy the water column (e.g., phytoplankton) or can directly shade seagrasses (e.g., macroalgae and epiphytes), their increased biomass can decrease the light reaching seagrasses and cause a variety of other issues (Tables 2-4).

Foremost, water column chlorophyll a (chl a), which is a widely used indicator of phytoplankton biomass, is sensitive to changes in nutrient concentrations and can be a key component in attenuation of light in the water column. Although colored dissolved organic material (CDOM) and suspended sediments are often important, or even dominant, components of water column light attenuation, chl a relates to the component of light attenuation most closely related to nutrient pollution. Regulatory limits for chl a have been adopted for many areas to limit light attenuation due to water column algal biomass, either alone or in combination with water clarity criteria, both in the context of numeric water quality standards or translations of narrative water quality standards in TMDLs. For example, chl a has been used as an endpoint for nutrient reduction efforts to protect seagrasses in Tampa Bay, Chesapeake Bay, Long Island Sound, and Massachusetts (Janicki and Wade 1996, Janicki et al. 2001, Tango and Batiuk 2013, Vaudrey et al. 2013, MEP 2019). California is also considering water column algal biomass as a primary numeric nutrient endpoint for estuaries to implement their narrative water quality standard (Sutula and Senn 2015). 

Microalgae growing as epiphytes on seagrass leaves can be an important nutrient-related mechanism that reduces light reaching seagrasses, especially when ecosystem changes have reduced the abundance of grazers that remove epiphytes, often called “mesograzers”, which may otherwise prevent such overgrowth (Heck et al. 2000; Kemp et al. 2004; Nelson 2017 a, b). However, regulatory approaches have generally not directly quantified epiphyte impacts on seagrasses because the epiphyte load and subsequent light reduction are highly variable both spatially and temporally, even at the scale of individual plants. There are also differences in epiphyte load between wet and dry seasons, location in the estuary, and between younger inner leaves and older outer leaves. Sampling epiphytes sufficiently is challenging enough that they are generally not quantified in most seagrass monitoring programs or are quantified only using comparative changes in abundance over time or space (Sutula et al. 2011).

Whereas phytoplankton biomass and epiphytes primarily decrease the amount of light reaching seagrasses, macroalgae, in addition to reducing light available to seagrasses, can also accumulate in seagrass beds, smothering seagrass and reducing oxygenation of sediments, thereby harming seagrass roots and rhizomes (Hauxwell et al. 2001). A review by Young (2009) showed that macroalgae generally have negative impacts on Zostera spp. and Thalassia testudinum, often causing loss or complete replacement of seagrasses through shading or elevated sediment anoxia (see DO discussion in next section). Furthermore, a meta-analysis by Thomsen et al. (2012) affirmed the negative impacts of macroalgae on seagrasses, with the magnitude of impact being influenced by type of macroalgae, how they are attached to the benthos, and the size of seagrasses. However, although proliferation of macroalgae is a documented cause of seagrass loss in many estuaries (Valiela et al. 1997, Hauxwell et al. 2001, McGlathery et al. 2007, Young 2009, Thomsen et al. 2012), macroalgal abundance is, like epiphytes, not widely quantified and analyzed as a factor in the relationship between seagrass health and nutrient pollution in regulatory settings. One possibility is that relationships between macroalgae and seagrass are complex or context-dependent (Hessing-Lewis et al. 2011). Another possibility is that appropriate and practical measures of macroalgae abundance are not well developed in relation to effects on seagrass. For example, macroalgae could be measured as percent cover, thickness of canopy, or biomass. Spatial and temporal variability also present a challenge, since macroalgae are usually patchy, often breaking free from their benthic attachments, accumulating, and drifting to other locations based on currents. However, particularly in shallow estuaries (e.g., Waquoit Bay, Hauxwell et al. 2001), macroalgae may be a relatively important factor to be considered as a nutrient-related stressor of seagrasses.  

Light attenuation in the water column is not only due to stimulation of primary productivity by nutrient pollution (Gallegos and Moore 2000). Total suspended solids (TSS) and CDOM also affect light available to seagrass and thus seagrass growth and distribution. Although these factors can be affected by nutrient pollution, increased TSS and CDOM are frequently caused by other human activities (e.g., dredging, hydrological modification, watershed modification) and natural events (e.g., hurricanes, increases in river flow, wind and tide-driven sediment resuspension). Often, TSS is related to freshwater inflow, and is an important confounding factor to note in the nutrient pollution-seagrass relationship. CDOM is similarly associated with river flow, although input from marsh environments is another common source. The interaction of chl a with other light attenuating factors can be seen in some of the examples in Tables 2-4.

Seagrasses and their responses to nutrient pollution can be affected by biological interactions other than those that impact light. Examples include grazing on seagrasses and their epiphytes, invasive species effects, diseases affecting seagrasses, and modification of plant-sediment interactions by benthic fauna. When developing numeric nutrient criteria using seagrasses as an endpoint, it is helpful to conceptually, if not numerically, account for how these factors may or may not be impacting seagrass status in the target ecosystem.

Seagrasses and the algae that grow on them are grazed by a variety of herbivores (Valentine and Duffy 2006; Zieman 1982, Chapter 6). Grazing of seagrasses themselves, such as by turtles, manatees, urchins, fish, crabs, and birds, while temporally and spatially variable and generally limited, frequently due to reductions of grazer populations from historical levels, can be locally significant at times (Jackson 2001, Valentine and Duffy 2006). Overall, direct grazing on seagrasses can change the condition of seagrass beds in complex ways, although immediate effects are manifest as reductions in distribution or abundance (Valentine and Duffy 2006). Mesograzers benefit seagrasses by increasing the amount of light that reaches seagrass leaves. Mesograzer abundance is affected by trophic interactions that can modulate epiphyte effects related to overgrowth (Heck et al. 2000).  

Invasive species widely impact coastal ecosystems. Invasive species affecting seagrasses are taxonomically diverse and can include macroalgae, non-native seagrasses, and both invertebrate and vertebrate animals (Williams 2007). One example is non-native anemones and tunicates on both east and west coasts of the United States that grow on seagrass leaves, shading seagrass directly and weighing down seagrass leaves, causing them to eventually collapse (Williams 2007, Wong and Vercaemer 2012, Carman et al. 2016). In areas of the United States that have experienced significant population growth of the invasive European Green Crab, Carcinus maenas, widespread negative effects have been observed in seagrass meadows as a result of bioturbation damage to shoots and rhizomes (Malyshev and Quijon 2011, Neckles 2015). Observations of competition between non-native Zostera japonica and native species have not been widespread, although they have been observed in some places (Shafer et al. 2014). In the Caribbean, Halophila stipulaceae has been spreading extensively, including in Puerto Rico and the U.S. Virgin Islands, with indications that it is having impacts on native seagrasses (Willette and Ambrose 2012, Willette et al. 2014).

Seagrasses can also be affected on a large scale by diseases, resulting in episodic declines in coverage. An early example is eelgrass wasting disease, caused by slime mold of the genus Labyrinthula, which destroyed approximately 90 percent of all eelgrass along the western North Atlantic in the 1930s (Muehlstein 1989). The disease has since been found to occur in other estuaries around the country, in places such as New Hampshire, Massachusetts, Washington, Florida, and North Carolina (Short et al. 1987, Sullivan et al. 2013). 

Harmful algal blooms (HABs), which are an important concern from both a human health and aquatic life perspective, also can affect seagrass growth. Because they form dense blooms, their impact on light availability can be dramatic and abrupt, causing acute impacts on seagrasses, including seagrass die-offs, characterized by widespread loss of seagrass shoots over a short period of time (Lee et al. 2007, Lopez et al. 2008). HAB effects can be magnified when blooms decline, causing oxygen depletion from the decay of organic matter, in turn driving a variety of negative impacts (see following section). Finally, HAB toxicity may also impact mesograzers, favoring epiphyte overgrowth. In combination, these consequences of HABs can lead to dramatic declines in seagrass coverage. For example, in Indian River Lagoon, Florida, increasing nutrient levels, combined with other factors, led to intense and protracted blooms from 2010-2013 characterized by monthly average chl a levels from approximately 50 µg/L to 200 µg/L (Gobler et al. 2013, Phlips et al. 2015, Barile 2018). The decrease in light attenuation caused by the blooms was one of the factors associated with a subsequent widespread and rapid loss of seagrass species (Phlips et al. 2015).  

Although sediment bioturbation (i.e., burrowing, sediment re-working, feeding activities) and bioirrigation (i.e., ventilation of burrows and tubes) may affect seagrass growth, these factors are generally not used in water quality management programs when evaluating confounding impacts on seagrass responses to nutrients. This is typically because temporal and spatial availability of data is low and variability of measurements can be high, and because sampling can be difficult and costly. In general, bioturbation has been associated with negative effects on seagrass, whereas bioirrigation has been associated with positive or neutral effects; however, the effect, magnitude, and spatial scale is variable and can be site dependent (Short and Wyllie-Echeverria 1996, Nelson 2009).

Growth and survival of seagrass often depend on chemical properties of seawater, including salinity, carbonate chemistry (e.g., pH, CO2, alkalinity), and DO. 

Whereas many seagrass taxa are adapted to short term changes in salinity, and often tolerate sustained exposure to a broad range of salinity, extreme and sustained changes can affect seagrass health and distribution, with tolerance ranges that vary by species (Tables 2-4). For example, eelgrass (Zostera marina) tolerates salinity from 5 to 42, making it tolerant of the full range of salinity that typically occurs in estuaries (i.e., euryhaline), exclusive of hypersaline waters. In contrast, turtle grass (Thalassia testudinum), which dominates seagrass species in Florida and the Caribbean, is less tolerant of low salinity, preferring polyhaline to euhaline environments (salinity between 17 and 48). Changes in estuarine hydrology associated with changes in climate or weather extremes, freshwater diversions, or dredge and fill activities can change temporal and spatial patterns of salinity in estuaries, which affects seagrass growth, distribution, and species composition (Boese 2009). 

Because seagrasses are primary producers, their growth requires assimilation of CO2 from the water.  Because seagrasses are usually not saturated with respect to CO2, increased CO2 associated with increased atmospheric CO2 generally benefits seagrass growth (Koch et al. 2013). However, other factors associated with increased dissolved CO2, such as pH and other acidification-related effects, have complex effects on seagrasses as well. 

Dissolved oxygen is an important water quality variable affecting the ecological processes of estuaries because of its effects on biogeochemical transformations and the physiology of marine species. The interaction between DO and seagrasses is dynamic. Because seagrasses are present in shallow waters, they are unlikely to be affected by seasonally persistent hypoxia associated with the bottom layer of stratified waters. In contrast, seagrasses may be most affected by diel cycling hypoxia, wherein low oxygen occurs overnight, and in low oxygen micro-habitats. Seagrasses can contribute directly to diel cycling via strong primary production by seagrasses and associated epiphytes, and through high oxygen consumption associated with heterotrophic metabolism. Mortality or other diminishment of mesograzer abundance or activity resulting from low DO can lead to increased epiphytic algal overgrowth, reducing primary production by seagrasses and associated oxygen flux to below-ground biomass. Sediment anoxia can increase sulfide in sediment and associated phytotoxicity, resulting in metabolic stress on below-ground seagrass biomass. Finally, low DO micro-habitats may also be formed in seagrass beds with high macroalgal cover. Hypoxia or anoxia beneath a macroalgae canopy likely promotes more reducing conditions in sediments and at the sediment water interface (Valiela et al. 1997, Hauxwell et al. 2001, McGlathery et al. 2007). This can stress seagrasses physiologically while increasing nutrient recycling via sediment ammonium and phosphorus releases into the water column (McGlathery et al. 2007).

Physical factors including water temperature, exposure stress, and current or wave energy affect the distribution of seagrasses both within a single estuary and across estuaries (Koch 2001). The lack of vegetation in very shallow water near the shore is often associated with exposure to high or low temperature and desiccation due to exposure at low tide. Complete loss of seagrass may occur when the depth interval between low light availability at depth and exposure stress decreases to zero. The physical forces of water movement, due to natural factors and human activities, can also cause loss at all depths to occur.

Optimal temperature varies among seagrass species (Bulthuis 1987; Koch et al. 2013, Tables 2-4). Seagrasses experience physiological stress when temperatures are outside their optimal temperature range, which may reduce growth and fitness, making them more vulnerable to other stressors (e.g., the effects of nutrient pollution) and increasing the likelihood of mortality (Lee et al. 2007, Phlips et al. 2015). The probability of thermal impacts is higher where a seagrass species is at the edge of its thermal tolerance, particularly temperate species, or extreme fluctuations of temperature occur (Thom et al. 2003, Koch et al. 2013, Moore et al. 2014, Arnold et al. 2017, Lefcheck et al. 2017). Temperature fluctuations are associated with altered hydrology, point source discharges, and changing climate. 

Seagrasses rely on water movement to bring nutrients, but water movement can also affect the physical stability of the environment around seagrasses. Anthropogenic activities such as freshwater diversions, channelization, shoreline hardening, and damming can modify the current and wave exposure of seagrass communities, impacting growth and distribution (Patrick et al. 2016, Prosser et al. 2018). These alterations affect salinity patterns, tidal dynamics, and circulation patterns, in addition to the supply of nutrients, toxics, and sediments. Boat and ship traffic also affect seagrasses by physically removing or disturbing seagrasses and by producing currents and waves that decrease sediment stability. Other factors such as storms and hurricanes influence the survival and distribution of seagrasses through physical disturbance.

Changes in areal distribution of seagrass are a well-established result of nutrient pollution (Batiuk et al. 1992, Dennison et al. 1993, Short and Wyllie-Echeverria 1996, Short and Burdick 1996, Batiuk et al. 2000, Orth et al. 2006, Burkholder et al. 2007, Wazniak et al. 2007). There is a variety of methods to quantify the areal distribution of seagrass, including diver surveys, aerial photography, towed video surveys, and sidescan sonar surveys, among others (Norris et al. 1997, Pulich et al. 1997, Fourqurean et al. 2001, Berry et al. 2003, Steward et al. 2005, Clinton et al. 2007, Virnstein et al. 2007). The choice of which method to use is often driven by seagrass depth, as well as trade-offs between resources, scale, and resolution. It is important to use a consistent method over time and space, or have interpretability, and use the method consistently, when doing a change analysis. Recently, methodologies have gravitated towards the application of aerial imagery and video surveys, and a combination of methods is often used (Sutula et al. 2011).

Regardless of method chosen, the user should decide how to define what constitutes seagrass existence in an area. Some organizations use a percent cover metric (e.g., 10% cover) to define a minimum threshold, while others consider presence of any seagrass the threshold. Other times, presence/absence is used, sometimes parsing into dense, sparse, or absent categories. If presence/absence is used it should be kept in mind that often many changes have occurred in a seagrass meadow before seagrass no longer occurs in an area.

Areal coverage can be an effective way to present data to the public, and to identify conspicuous, long-term impacts, but may not alone capture other shifts like changes in seagrass density or species composition.

The maximum depth of colonization is an important indicator of declining water quality. It is related to areal distribution and is another widely-used indicator for developing nutrient criteria to protect seagrass beds (Beck et al. 2017). Depth of colonization is a useful metric principally because it is directly affected by water clarity and nutrient-related water quality variables that directly affect clarity (i.e., chl a, TSS, and CDOM). Water clarity is connected to depth of colonization via estimates of seagrass light requirements (Tables 2-4). Specifically, as water clarity decreases, so does the maximum depth of colonization of seagrasses (Dennison et al. 1993). Meadows retreat into shallower water in response to light limitation because plants at the deep edge of a seagrass bed are receiving the average minimum amount of light with which they can sustain maintenance processes, and when the amount of light they are receiving decreases they can no longer inhabit that depth (Ralph et al. 2007).

The maximum depth limit can be defined in a variety of ways, such as the limits of well-defined meadows or shoots, or the mean or median depth of occurrence. There is some natural variability in the movement of the edge, so it can be useful to have a reference meadow or have long-term measurements to evaluate whether change is within normal variation. The maximum depth of colonization is often quantified using the same methods used to determine areal cover and evaluated to track changes over time.

Shoot density is another commonly used metric of seagrass abundance and expresses the number of shoots per unit area. Measures of seagrass density have been the backbone of many seagrass monitoring plans and are robust and repeatable (Fourqurean et al. 2001, Sutula et al. 2011). Density estimates are typically made by counting the number of shoots in a known area using divers or coring methods. Field counts are generally scaled and reported per unit area. Alternatively, large scale seagrass monitoring programs (e.g., Florida Bay) often utilize rapid visualization techniques, such as the Braun-Blanquet method, to classify shoot density into density categories (Fourqurean et al. 2001). Both methods require reasonable visibility to make estimates and put divers or snorkelers into the water to make measurements. Remote sensing-based methods are being explored which may ease the need for divers in the water, but still require acceptable water clarity.

A related measure to shoot density is percent cover, which is affected by both shoot density and shoot length. This measure can be less sensitive to light changes than density because with increasing depth (and decreasing light) shoot density generally decreases but shoot length increases. Additionally, estimates of percent cover can vary with tidal stage, particularly in intertidal zones, and with the individual making the measurement. If this metric is used, these sources of variability should be considered and accounted for.

As the ability to track changes in depth of colonization and areal coverage have become more accessible, shoot density and percent cover are often used as supporting measures.

As researchers learn more about the relationship between seagrasses and nutrient pollution, more methods to assess and monitor changes in seagrasses are being developed. For example, the Nutrient Pollution Index (NPI) is the ratio of leaf nitrogen content to leaf mass and has been related to nitrogen loading (Kaldy et al. 2017). Other measures to quantify seagrass health or the potential impact of nutrient pollution on seagrasses include nutrient ratios, stable isotope content of the plants, and leaf epiphyte load.

Often, when developing numeric nutrient criteria, there will be a set of measures the state or other associated sampling programs have been using to monitor seagrass health. When considering how to use that information for numeric nutrient criteria development, it is important to consider how the sampled data represent the temporal and spatial drivers of seagrass extent, distribution, species composition, and abundance, as these can vary over time and space. For example, temporal variability in seagrass change can occur over different periods. Examining data for cyclical, rainfall-driven changes in salinity, TSS, and dissolved color over annual or longer periods can help to evaluate interaction of these factors on nutrient pollution driven seagrass effects. Alternatively, changes in nutrients often happen incrementally over long periods of time, so it can be helpful to examine as long a period of record as possible. It is also important to look for incremental, small-scale changes over time as they can be indicative of building negative pressures and precede a sudden, large-scale change, as seen in Indian River Lagoon, Florida (Phlips et al. 2015). Spatially, it is important to think about variability in depth of colonization on a patch level and landscape level, as drivers may vary across scales. For example, freshwater inputs can drive patterns in seagrasses through short and long-term changes in salinity, TSS, and CDOM.

Temporal or spatial reference approaches (described in the Reference Condition section) can be important tools for numeric nutrient criteria development using seagrasses (e.g., Tampa Bay). To use a temporal based reference, having comparable methods over time is important to allow the incorporation of long-term datasets. If comparisons are to be made between waterbodies, having comparable methods across a region is useful.

Lastly, when developing numeric nutrient criteria, it is also important to recognize potential limitations of the methods needed to monitor, such as the cost or amount of required effort, as it may affect the feasibility of maintaining the monitoring program in the future. With the increasing availability of remote sensing derived measures and the ability to analyze them in an automated fashion, the cost and effort needed to monitor can be greatly reduced. Additionally, other free resources such as SeagrassNet (www.seagrassnet.org Exit) can be useful sources of information.

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