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Catchment impacts on downstream ecosystems are difficult to quantify, but important for setting management targets. Here we compared 12 years of monitoring data of seagrass area and biomass in Cleveland Bay, northeast Australia, with discharge and associated sediment loads from nearby rivers. Seagrass biomass and area exhibited different trajectories in response to river inputs. River discharge was a slightly better predictor of seagrass indicators than total suspended solid (TSS) loads, indicating that catchment effects on seagrass are not restricted to sediment. Linear relationships between Burdekin River TSS loads delivered over 1–4 years and seagrass condition in Cleveland Bay generated Ecologically Relevant Targets (ERT) for catchment sediment inputs. Our predicted ERTs were comparable to those previously estimated using mechanistic models. This study highlights the challenges of linking catchment inputs to condition of downstream ecosystems, and the importance of integrating a variety of metrics and approaches to increase confidence in ERTs.

Seagrass ecosystems are inherently dynamic, responding to environmental change across a range of scales. Habitat requirements of seagrass are well defined, but less is known about their ability to resist disturbance. Specific means of recovery after loss are particularly difficult to quantify. Here we assess the resistance and recovery capacity of 12 seagrass genera. We document four classic trajectories of degradation and recovery for seagrass ecosystems, illustrated with examples from around the world. Recovery can be rapid once conditions improve, but seagrass absence at landscape scales may persist for many decades, perpetuated by feedbacks and/or lack of seed or plant propagules to initiate recovery. It can be difficult to distinguish between slow recovery, recalcitrant degradation, and the need for a window of opportunity to trigger recovery. We propose a framework synthesizing how the spatial and temporal scales of both disturbance and seagrass response affect ecosystem trajectory and hence resilience.

Trace element accumulation is an anthropogenic threat to seagrass ecosystems, which in turn may affect the health of humans who depend on these ecosystems. Trace element accumulation in seagrass meadows may vary temporally due to, e.g., seasonal patterns in sediment discharge from upstream areas. In addition, when several trace elements are present in sufficiently high concentrations, the risk of seagrass loss due to the cumulative impact of these trace elements is increased. To assess the seasonal variation and cumulative risk of trace element contamination to seagrass meadows, trace element (As, Cd, Cr, Cu, Pb, Hg, Mn and Zn) levels in surface sediment and seagrass tissues were measured in the largest Chinese Zostera japonica habitat, located in the Yellow River Estuary, at three sites and three seasons (fall, spring and summer) in 2014-2015. In all three seasons, trace element accumulation in the sediment exceeded background levels for Cd and Hg. Cumulative risk to Z. japonica habitat in the Yellow River Estuary, from all trace elements together, was assessed as "moderate" in all three seasons examined. Bioaccumulation of trace elements by seagrass tissues was highly variable between seasons and between above-ground and below-ground biomass. The variation in trace element concentration of seagrass tissues was much higher than the variation in trace element concentration of the sediment. In addition, for trace elements which tended to accumulate more in above-ground biomass than below-ground biomass (Cd and Mn), the ratio of above-ground to below-ground trace element concentration peaked at times corresponding to high water discharge and high sediment loads in the Yellow River Estuary. Overall, our results suggest that trace element accumulation in the sediment may not vary between seasons, but bioaccumulation in seagrass tissues is highly variable and may respond directly to trace elements in the water column.

Seagrasses are globally important coastal habitat‐forming species, yet it is unknown how seagrasses respond to the combined pressures of ocean acidification and warming of sea surface temperature. We exposed three tropical species of seagrass (Cymodocea serrulata, Halodule uninervis, and Zostera muelleri) to increasing temperature (21, 25, 30, and 35°C) and pCO2 (401, 1014, and 1949 μatm) for 7 wk in mesocosms using a controlled factorial design. Shoot density and leaf extension rates were recorded, and plant productivity and respiration were measured at increasing light levels (photosynthesis–irradiance curves) using oxygen optodes. Shoot density, growth, photosynthetic rates, and plant‐scale net productivity occurred at 25°C or 30°C under saturating light levels. High pCO2 enhanced maximum net productivity for Z. muelleri, but not in other species. Z. muelleri was the most thermally tolerant as it maintained positive net production to 35°C, yet for the other species there was a sharp decline in productivity, growth, and shoot density at 35°C, which was exacerbated by pCO2. These results suggest that thermal stress will not be offset by ocean acidification during future extreme heat events and challenges the current hypothesis that tropical seagrass will be a ‘winner’ under future climate change conditions.

Submerged macrophytes can colonize shallow lakes via several reproductive mechanisms, and can in turn substantially alter these environments by modifying the thermal structure and dissolved oxygen levels within these lakes. Although multiple mechanisms of submerged macrophyte expansion have been described, the relative contribution of each of these in shallow lake environments has been largely overlooked. In this study we analyzed the spatial spread and patterning during seasonal growth of a globally invasive submerged macrophyte, Potamogeton crispus, in a shallow urban lake (Lake Monger, Western Australia). We used underwater and aerial imagery to estimate the spatial pattern of the P. crispus bed. By comparing the spatial extent of the bed at different times during the growing season, we found linear expansion rates two orders of magnitude higher than those previously estimated through rhizome elongation. We formulated a deterministic mathematical model that accounted for the ability of P. crispus to spread through rhizomes and fragments broken off by the feeding activities of aquatic birds, to assess the contribution of fragment dispersal to the emergent patterns of the submerged macrophyte bed. In addition to accounting for dispersal from fragments, the model also accounted for a hypothesized feedback between macrophyte-induced thermal stratification and central dieback. Comparison of our model results against field data indicated that the model accurately represented the spatial spread of the macrophyte bed when fragment dispersal was included. When fragment dispersal was not included in the model, the spatial spread of the bed was largely underestimated, suggesting that fragment dispersal may well account for the fast seasonal spread of this species. The model also captured the formation of a ring-shaped pattern in spatial macrophyte distribution suggesting that both fragment dispersal and the feedback between stratification and dieback are necessary to reproduce the spatial structure of the macrophyte bed. Our results highlight the potential important role of fragment dispersal in facilitating colonization and submerged macrophyte invasion in shallow lakes.

Catchment degradation causing increased sediment flow is one of the key stressors facing Great Barrier Reef (GBR) habitats. Ecologically relevant targets (ERTs) for sediment and nutrient loads have been previously proposed based on seagrass light requirements, the next step is to connect these to ecological response. The overarching goal of the present work is to recommend preliminary thresholds that can be used in the development of more refined ERTs. To achieve this, we perform statistical analysis on datasets for catchment flows and sediment loads and condition of the adjacent seagrass habitat, to identify what might be the direct impacts of catchment discharge on seagrass and the associated timescales of ecological response.Our case study focuses on Cleveland Bay, which is located in the central GBR, and has important seagrass habitat that is affected by discharge from the Burdekin River. Annual monitoring of seagrass biomass and area has been undertaken since 2007. We compare these ecological time-series with data for Burdekin River annual flow and total sediment load from 2005 onwards. Annual Burdekin River flow varied by nearly 40-fold within the 2005-2018 study period, and declines in biomass and area of both subtidal and intertidal seagrasses were associated with high flows and loads from the Burdekin. Subtidal seagrasses appeared more sensitive to changes in catchment discharges than intertidal seagrasses, exhibiting a 3 year timeframe for recovery, following high annual flows and loads. Based on our results, a linear model relating change in seagrass biomass to Burdekin River metrics was used to calculate predicted thresholds below which seagrass biomass was likely to increase, and above which biomass was likely to decline. For seagrass area, a growth threshold, below which seagrass area expanded; and a decline threshold, above which seagrass area fell, were defined for annual Burdekin River flow, and sediment load. Overall these thresholds provide the first steps towards refining ERTs based on ecological condition, which can directly inform the management of the GBR to protect its iconic seagrass habitats and associated communities. The next step is to examine whether the relationship between river discharge and sediment load was the primary cause of seagrass decline.

A feedback between seagrass presence, suspended sediment and benthic light can induce bistability between two ecosystem states: one where the presence of seagrass reduces suspended sediment concentrations to increase benthic light availability thereby favoring growth, and another where seagrass absence increases turbidity thereby reducing growth. This literature review identifies (1) how the environmental and seagrass meadow characteristics influence the strength and direction (stabilizing or destabilizing) of the seagrass-sediment-light feedback, and (2) how this feedback has been incorporated in ecosystem models proposed to support environmental decision making. Large, dense seagrass meadows in shallow subtidal, non-eutrophic systems, growing in sediments of mixed grain size and subject to higher velocity flows, have the greatest potential to generate bistability via the seagrass-sediment-light feedback. Conversely, seagrass meadows of low density, area and height can enhance turbulent flows that interact with the seabed, causing water clarity to decline. Using a published field experiment as a case study, we show that the seagrass-sediment-light feedback can induce bistability only if the suspended sediment has sufficient light attenuation properties. The seagrass-sediment-light feedback has been considered in very few ecosystem models. These models have the potential to identify areas where bistability occurs, which is information that can assist in spatial prioritization of conservation and restoration efforts. In areas where seagrass is present and bistability is predicted, recovery may be difficult once this seagrass is lost. Conversely, bare areas where seagrass presence is predicted (without bistability) may be better targets for seagrass restoration than bare areas where bistability is predicted.

Poor water quality and light reduction owing to anthropogenic impacts are the most widespread causes behind marine submerged angiosperm (seagrass) declines, worldwide. Seagrasses could respond to sustained environmental stresses, such as increasing water depth and light reduction, through morphological changes, particularly shoot density and/or biomass reductions. The seagrass Zostera japonica Asch. and Graebn. has been introduced to the Pacific Coast of North America, but it is widely threatened in its native northwestern Pacific Coast range alongside the east coast of China. The main aims of this study were to determine: 1) the depth limit of Z. japonica growth in its native range, and 2) how light availability affects the growth and recruitment of Z. japonica. To achieve these aims, we investigated the temporal responses of Z. japonica shoots and seeds from an intertidal donor site, Swan Lake, to light availability at water depths ranging from 1 to 6 m using in situ suspended cultures deployed in the experimental site, Ailian Bay, off the coast of Weihai City, China. The results showed that the transplanted Z. japonica shoots and seeds could survive for the duration of their annual growth cycle, permanently underwater, at a depth ≤2 m. There was a significant inverse relationship between water depth and time to complete shoot loss, despite temporally varying water clarity levels. Due to the local turbidity of the waters in Ailian Bay, a depth of 2 m yielded sufficient light deprivation (5%-37% surface irradiance) to negatively affect the seagrass shoot density. Our results suggest that this intertidal species can potentially persist in shallow subtidal areas following transplantation with shoots and seeds. The findings may also serve as useful information for local seagrass distribution limits, and will facilitate their habitat establishment and restoration efforts.

Implementing management actions to achieve environmental outcomes requires defining and quantifying ecological targets, but this is a complex challenge, and there are few examples of how to quantitatively set them in complex dynamic marine ecosystems. Here we develop a methodology to devise ‘desired state’ for tropical seagrasses in Cleveland Bay, northern Australia, in the Great Barrier Reef World Heritage Area. Analysis of diverse species assemblages was used to define seagrass communities as indicators of the region’s ecological value. Multivariate regression trees assigned 8000 observations of species presence/absence and habitat characteristics from 2007 to 2017 into seven community types. Generalized Linear Models were used to assess annual variation in above-ground biomass of each seagrass community. Reference subsets of the data expressing high biomass and spatial extent were identified, and desired state was defined as the mean and 95% confidence intervals. This approach rests on the assumption that seagrass resilience and its ecosystem services are met when the diverse seagrass communities reach desired state. This method required a data set that spanned a range in seagrass conditions, but which may have been compromised by a history of pressures. Our method for defining desired state provides evidence-based targets that can be used within an adaptive management framework that prioritises and implements management actions.

Seagrass ecosystems are increasingly subjected to multiple interacting stressors, making the consequent trajectories difficult to predict. Here, we present a new process-based model of seagrass decline in response to cumulative light and temperature stress. The model is calibrated to laboratory datasets for Great Barrier Reef seagrasses using Bayesian inference. Our model, which is fit to both physiological and morphological data, supports the hypothesis that physiological carbon loss rate controls the shoot density decline rate of seagrasses. The model predicts the time to complete shoot loss, and a new, generalisable, cumulative stress index that indicates the potential seagrass shoot density decline based on the time period of cumulative stress. All model predictions include uncertainty estimates based on uncertainty in the model fit to the data. The calibrated model is packaged into a computer program that can forecast the potential declines of seagrasses due to cumulative light and temperature stress.

Predicting algal population dynamics using models informed by experimental data has been used as a strategy to inform the management and control of harmful cyanobacterial blooms. We selected toxic bloom-forming species Microcystis spp. and Raphidiopsis raciborskii (basionym Cylindrospermopsis raciborskii) for further examination as they dominate in 78 % and 17 %, respectively, of freshwater cyanobacterial blooms (cyanoHABs) reported globally over the past 30 years. Field measurements of cyanoHABs are typically based on biomass accumulation, but laboratory experiments typically measure growth rates, which are an important variable in cyanoHAB models. Our objective was to determine the usefulness of laboratory studies of these cyanoHAB growth rates for simulating the species dominance at a global scale. We synthesized growth responses of M. aeruginosa and R. raciborskii from 20 and 16 culture studies, respectively, to predict growth rates as a function of two environmental variables, light and temperature. Predicted growth rates of R. raciborskii exceeded those of M. aeruginosa at temperatures ≳ 25 °C and light intensities ≳ 150 μmol photons m−2 s-1. Field observations of biomass accumulation, however, show that M. aeruginosa dominates over R. raciborskii, irrespective of climatic zones. The mismatch between biomass accumulation measured in the field, and what is predicted from growth rate measured in the laboratory, hinders effective use of culture studies to predict formation of cyanoHABs in the natural environment. The usefulness of growth rates measured may therefore be limited, and field experiments should instead be designed to examine key physiological attributes such as colony formation, buoyancy regulation and photoadaptation. Improving prediction of cyanoHABs in a changing climate requires a more effective integration of field and laboratory approaches, and an explicit consideration of strain-level variability.

This chapter describes the distribution of key seagrass species in the estuarine-nearshore coastal (ENC) continuum of the south-east region of Australia. We explore the potential influences of hydrodynamics (e.g. tidal currents, wave energy), estuary entrance dynamics (recruitment) and water quality, in addition to light, as primary stressors on seagrass processes and resilience. Despite primary controls exerted by light over seagrass distribution, there are significant areas of euphotic sediments in south-east region that are not colonised by seagrasses. In addition, seagrasses commonly display high degrees of inter-annual variability in coverage which cannot be explained solely by variations in light. We describe the main ecosystem types within the region, and demonstrate how the temporal and spatial gradients in hydrodynamic and water quality stressors (hence light climate), and the availability of suitable substrates for seagrass are controlled by the physical setting or geomorphology of the ecosystem. The opportunistic species Zostera muelleri is the most abundant species within the region, primarily occupying the highly dynamic estuarine niche. We provide a focus on Zostera muelleri to illustrate the direct positive/negative impacts of hydrodynamic, water quality and estuary entrance morphology stressors on seagrass metabolism and morphology across light gradients.

Seagrass habitat is strongly constrained by light availability. Decline in benthic light due to anthropogenic activities (e.g. eutrophication, dredging and catchment modification) is a major threat to seagrass ecosystems, both within Australia and internationally. Even in pristine conditions, light available to seagrasses can be highly variable on timescales ranging from seconds to years. This chapter outlines the three primary mechanisms which enable seagrass to adapt to and/or resist temporary light deprivation: (1) consumption of accumulated carbon; (2) reduction in rates of growth and carbon loss; and (3) increased efficiency of radiation capture and usage. The capacity to withstand severe light deprivation ranges from only two weeks for small, colonising seagrass species such as Halophila ovalis , to beyond two years for large, persistent species such as Posidonia sinuosa. This “tolerance time” depends on the magnitude and timing of the light deprivation, current environmental conditions (e.g. temperature and sediment sulphides) as well as preceding conditions. This chapter proposes a simple conceptual model for seagrass resilience to temporary light reduction , combining both resistance (the capacity of seagrass to survive the light deprivation event), and the capacity to recover once the disturbance ends. Data is synthesized for several potential indicators of seagrass resistance to light reduction.

Oxygen flux between aquatic ecosystems and the water column is a measure of ecosystem metabolism. However, the oxygen flux varies during the day in a “hysteretic” pattern: there is higher net oxygen production at a given irradiance in the morning than in the afternoon. In this study, we investigated the mechanism responsible for the hysteresis in oxygen flux by measuring the daily pattern of oxygen flux, light, and temperature in a seagrass ecosystem (Zostera muelleri in Swansea Shoals, Australia) at three depths. We hypothesised that the oxygen flux pattern could be due to diel variations in either gross primary production or respiration in response to light history or temperature. Hysteresis in oxygen flux was clearly observed at all three depths. We compared this data to mathematical models, and found that the modification of ecosystem respiration by light history is the best explanation for the hysteresis in oxygen flux. Light history-dependent respiration might be due to diel variations in seagrass respiration or the dependence of bacterial production on dissolved organic carbon exudates. Our results indicate that the daily variation in respiration rate may be as important as the daily changes of photosynthetic characteristics in determining the metabolic status of aquatic ecosystems.

1. Seagrass habitat is globally threatened from the cumulative impact of human activities on coastal ecosystems. Successful conservation and restoration of seagrass requires knowledge of the environmental factors that limit seagrass presence; however, quantifying the relative importance of these environmental factors is a significant challenge. 2. To resolve this issue, a species distribution model (SDM) for seagrass was constructed from a range of data collected at different spatial and temporal resolutions in Moreton Bay, Australia. Mean annual benthic light availability, significant wave height, and sediment settling time (calculated from sediment size distribution) were the environmental factors predicting seagrass presence in the model, which was calibrated and validated using maps of seagrass cover from 2004 and 2011, respectively. 3. The SDM correctly classified seagrass presence/absence in 85% of cases for calibration to 2004 data and 88% of cases for validation to 2011 data. 4. Application of the SDM to 12 regions of 10–100 km2 size within the study area demonstrated that the environmental factors limiting seagrass presence (i.e. either threatening seagrass that is present or hindering its colonization if seagrass is absent) varied substantially between these regions. For example, seagrass presence in the regions Waterloo Bay and Central West was predicted to be limited by their high mud content, while in the region Deception Bay South, light availability was the major limiting factor. 5. The results demonstrate that SDMs need to be developed on a sufficiently broad scale to capture significant variability in environmental conditions. These models can then be applied at finer scales to assess management options based on the local environmental conditions.

Cylindrospermopsis raciborskii is a global invasive cyanobacterium, with some ecotypes (i.e. strains) producing the toxin cylindrospermopsin, CYN. Multiple ecotypes can co-exist, complicating prediction of toxin concentrations based on cell concentrations. This study examined the growth response and toxin production of three Australian ecotypes of C. raciborskii, two toxic (CS-505, CS-506) and one non-toxic (CS-510), to a range of nitrogen (N) and phosphorus (P) concentrations. CYN cell quota was constant under all N:P ratios and concentration conditions, indicative of a constitutive response, yet the CYN cell quota was 6-fold higher in CS-506 compared to CS-505. The ecotypes differed in response to dissolved N depletion: there was a 4-fold difference in the number of cells heterocyst mL−1 between CS-505 and CS-510, while CS-506 did not produce any heterocysts and was unable to grow in N deplete conditions. Growth rates were lower for all ecotypes as [P] increased, indicative of a species with a strategy of P storage rather than increased growth. Presumably this is an adaptation to low and fluctuating P conditions. However, the negative effect of increasing [P] on growth is surprising. In contrast, increasing [N] resulted in higher growth rates across ecotypes. This study highlights the importance of understanding differences in growth and toxin production between ecotypes in response to environmental conditions in order to more effectively predict blooms and toxin yields.

Submerged macrophytes can have a profound effect on shallow lake ecosystems through their ability to modify the thermal structure and dissolved oxygen levels within the lake. Invasive macrophytes, in particular, can grow rapidly and induce thermal gradients in lakes that may substantially change the ecosystem structure and challenge the survival of aquatic organisms. We performed fine-scale measurements and 3D numerical modeling at high spatiotemporal resolution to assess the effect of the seasonal growth of Potamogeton crispus L. on the spatial and temporal dynamics of temperature and dissolved oxygen in a shallow urban lake (Lake Monger, Perth, WA, Australia). Daytime stratification developed during the growing season and was clearly observed throughout the macrophyte bed. At all times measured, stratification was stronger at the center of the macrophyte bed compared to the bed edges. By fitting a logistic growth curve to changes in plant height over time (r2 = 0.98), and comparing this curve to temperature data at the center of the macrophyte bed, we found that stratification began once the macrophytes occupied at least 50% of the water depth. This conclusion was strongly supported by a 3D hydrodynamic model fitted to weekly temperature profiles measured at four time periods throughout the growing season (r2 > 0.78 at all times). As the macrophyte height increased and stratification developed, dissolved oxygen concentration profiles changed from vertically homogeneous oxic conditions during both the day and night to expression of night-time anoxic conditions close to the sediments. Spatially interpolated maps of dissolved oxygen and 3D numerical modeling results indicated that the plants also reduced horizontal exchange with surrounding unvegetated areas, preventing flushing of low dissolved oxygen water out of the center of the bed. Simultaneously, aerial imagery showed central dieback occurring toward the end of the growing season. Thus, we hypothesized that stratification-induced anoxia can lead to accelerated P. crispus dieback in this region, causing formation of a ring-shaped pattern in spatial macrophyte distribution. Overall, our study demonstrates that submerged macrophytes can alter the thermal characteristics and oxygen levels within shallow lakes and thus create challenging conditions for maximizing their spatial coverage.

Rising sea water temperature will play a significant role in responses of the world's seagrass meadows to climate change. In this study, we investigated seasonal and latitudinal variation (spanning more than 1,500 km) in seagrass productivity, and the optimum temperatures at which maximum photosynthesis and net productivity (for the leaf and the whole plant) occurs, for three seagrass species (Cymodocea serrulata, Halodule uninervis, and Zostera muelleri). To obtain whole plant net production, photosynthesis, and respiration rates of leaves and the root/rhizome complex were measured using oxygen-sensitive optodes in closed incubation chambers at temperatures ranging from 15 to 43°C. The temperature-dependence of photosynthesis and respiration was fitted to empirical models to obtain maximum metabolic rates and thermal optima. The thermal optimum (Topt) for gross photosynthesis of Z. muelleri, which is more commonly distributed in sub-tropical to temperate regions, was 31°C. The Topt for photosynthesis of the tropical species, H. uninervis and C. serrulata, was considerably higher (35°C on average). This suggests that seagrass species are adapted to water temperature within their distributional range; however, when comparing among latitudes and seasons, thermal optima within a species showed limited acclimation to ambient water temperature (Topt varied by 1°C in C. serrulata and 2°C in H. uninervis, and the variation did not follow changes in ambient water temperature). The Topt for gross photosynthesis were higher than Topt calculated from plant net productivity, which includes above- and below-ground respiration for Z. muelleri (24°C) and H. uninervis (33°C), but remained unchanged at 35°C in C. serrulata. Both estimated plant net productivity and Topt are sensitive to the proportion of below-ground biomass, highlighting the need for consideration of below- to above-ground biomass ratios when applying thermal optima to other meadows. The thermal optimum for plant net productivity was lower than ambient summer water temperature in Z. muelleri, indicating likely contemporary heat stress. In contrast, thermal optima of H. uninervis and C. serrulata exceeded ambient water temperature. This study found limited capacity to acclimate: thus the thermal optima can forewarn of both the present and future vulnerability to ocean warming during periods of elevated water temperature.

Cyanobacteria Microcystis aeruginosa and Cylindrospermopsis raciborskii are two harmful species which co-occur and successively dominate in freshwaters globally. Within-species strain variability affects cyanobacterial population responses to environmental conditions, and it is unclear which species/strain would dominate under different environmental conditions. This study applied a Monte Carlo approach to a phytoplankton dynamic growth model to identify how growth variability of multiple strains of these two species affects their competition. Pairwise competition between four M. aeruginosa and eight C. raciborskii strains was simulated using a deterministic model, parameterized with laboratory measurements of growth and light attenuation for all strains, and run at two temperatures and light intensities. 17 000 runs were simulated for each pair using a statistical distribution with Monte Carlo approach. The model results showed that cyanobacterial competition was highly variable, depending on strains present, light and temperature conditions. There was no absolute 'winner' under all conditions as there were always strains predicted to coexist with the dominant strains, which were M. aeruginosa strains at 20°C and C. raciborskii strains at 28°C. The uncertainty in prediction of species competition outcomes was due to the substantial variability of growth responses within and between strains. Overall, this study demonstrates that within-species strain variability has a potentially large effect on cyanobacterial population dynamics, and therefore this variability may substantially reduce confidence in predicting outcomes of phytoplankton competition in deterministic models, that are based on only one set of parameters for each species or strain.

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

Seagrasses are a critical component of the healthy functioning of many coastal marine ecosystems. Capturing the dynamics of seagrass communities requires both a detailed representation of processes such as seagrass nutrient uptake and photosynthesis, as well as models of light penetration, water column and sediment biogeochemical processes and other ecosystem characteristics that determine the environmental state. Here we develop a new two-state, 13-parameter seagrass model with the aim of providing sufficient detail to represent light and nutrient limitation, but simple enough to be coupled into a 60 state variable biogeochemical model. The novel formulation is built around a nitrogen-specific leaf area parameter, Ω, that is well-constrained and is used in calculating both the rate of photosynthesis and the fraction of the seafloor covered by seagrass, Aeff, where Aeff = 1 − exp(− ΩSGA) and SGA is the aboveground areal seagrass biomass. The model also contains terms for the uptake of nutrients from multiple layers of varying-porosity sediments, translocation of organic matter between leaves and roots, respiration and simple mortality terms. The model is applied to Gladstone Harbour, a macro-tidal sub-tropical estuary in northeast Australia, and is able to simulate realistic spatial seagrass distributions. A simplified form of the model is derived, which can be used to predict seagrass light-limited growth based on five measurable species-specific parameters (maximum growth rate, mortality rate, compensation irradiance, leaf blade angle and nitrogen-specific leaf area). The steady-state percent coverage of seagrass achieved at varying light levels and mortality intensity is calculated as a means of understanding the dynamics of the new seagrass model.

The use of surrogates for biodiversity is a practical tool to improve the cost effectiveness of regional conservation planning. However, there is still much uncertainty about the biological representativeness of surrogates. Using a biophysical classification system known as the Mitchell Landscapes, we compare plant species composition in contiguous versus disjunct units of nine Landscape types and hence the ability of this surrogate to capture patterns of plant species composition. We found that plant species homogeneity was higher within a contiguous Landscape than between non-contiguous units of the same Landscape. Overall, the dissimilarity between non-contiguous units and their contiguous counterparts was significant (P = 0.004). Biophysical classes with very high dissimilarities between non-contiguous units of the same region may be of limited utility.

A distinct calcium profile is strongly implicated in regulating the multi-layered structure of the epidermis. However, the mechanisms that govern the regulation of this calcium profile are currently unclear. It clearly depends on the relatively impermeable barrier of the stratum corneum (passive regulation) but may also depend on calcium exchanges between keratinocytes and extracellular fluid (active regulation). Using a mathematical model that treats the viable sublayers of unwounded human and murine epidermis as porous media and assumes that their calcium profiles are passively regulated, we demonstrate that these profiles are also actively regulated. To obtain this result, we found that diffusion governs extracellular calcium motion in the viable epidermis and hence intracellular calcium is the main source of the epidermal calcium profile. Then, by comparison with experimental calcium profiles and combination with a hypothesised cell velocity distribution in the viable epidermis, we found that the net influx of calcium ions into keratinocytes from extracellular fluid may be constant and positive throughout the stratum basale and stratum spinosum, and that there is a net outflux of these ions in the stratum granulosum. Hence, the calcium exchange between keratinocytes and extracellular fluid differs distinctly between the stratum granulosum and the underlying sublayers, and these differences actively regulate the epidermal calcium profile. Our results also indicate that plasma membrane dysfunction may be an early event during keratinocyte disintegration in the stratum granulosum.

We propose and mathematically examine a theory of calcium profile formation in unwounded mammalian epidermis based on: changes in keratinocyte proliferation, fluid and calcium exchange with the extracellular fluid during these cells’ passage through the epidermal sublayers, and the barrier functions of both the stratum corneum and tight junctions localised in the stratum granulosum. Using this theory, we develop a mathematical model that predicts epidermal sublayer transit times, partitioning of the epidermal calcium gradient between intracellular and extracellular domains, and the permeability of the tight junction barrier to calcium ions. Comparison of our model’s predictions of epidermal transit times with experimental data indicates that keratinocytes lose at least 87% of their volume during their disintegration to become corneocytes. Intracellular calcium is suggested as the main contributor to the epidermal calcium gradient, with its distribution actively regulated by a phenotypic switch in calcium exchange between keratinocytes and extracellular fluid present at the boundary between the stratum spinosum and the stratum granulosum. Formation of the extracellular calcium distribution, which rises in concentration through the stratum granulosum towards the skin surface, is attributed to a tight junction barrier in this sublayer possessing permeability to calcium ions that is less than 15 nm s−1 in human epidermis and less than 37 nm s−1 in murine epidermis. Future experimental work may refine the presented theory and reduce the mathematical uncertainty present in the model predictions.