Stability of eelgrass (<Emphasis Type="Italic">Zostera marina</Emphasis> L.) depth limits: influence of habitat type

Seagrass meadows are generally considered stable although few studies have specified and tested this statement. On the basis of a large monitoring dataset from Danish coastal waters, we aimed to test whether the stability of deep eelgrass populations changes along a eutrophication gradient extending from inner bays over outer bays to open coastal waters. We defined stability in terms of the stability properties of constancy, resilience, and/or persistence. Our data allowed us to investigate the stability property constancy expressed as temporal variability in eelgrass depth limits over a time scale of 10 years. We hypothesised that colonisation depths were large and relatively constant along open coasts because of low and relatively constant levels of nutrients and turbidity. Conversely, colonisation depths were hypothesised to be low and variable in protected bays due to higher and more variable levels of nutrients and turbidity. We found that depth limits increased from inner bays towards open coastal waters, matching declines in nutrient concentration and increases in water clarity and oxygen concentration. Stability expressed as constancy of depth limits did not differ significantly between habitat types, and neither did stability of physicochemical variables. However, when data from all habitat types were analysed together, they showed that eelgrass populations at the depth limit were significantly more constant and thus, in this respect, more stable when occurring in deep waters as compared to shallow waters. Areas of good water quality may thus obtain the double benefit of deeper-growing and more stable eelgrass populations. The most likely reason why this pattern did not appear at habitat-type level is that the habitat types studied represented wide spatial variation in water quality and depth limit. We conclude that the question of whether eelgrass populations are stable depends on the stability property and the ecological situation in question. Populations may be considered unstable in terms of inter-annual variation but stable in terms of long-term persistence. Therefore, the common statement that eelgrass populations are stable is not universally true.Communicated by M. Kühl, Helsingør     

Reintroduction of eelgrass (Zostera marina) in the Dutch Wadden Sea; review of research and suggestions for management measures

Eelgrass (Zostera marina L.) in the Dutch Wadden Sea historically covered an area varying from 65–150 km² in the eulittoral as well as the sublittoral zones. At present, this area comprises less than 1 km² eulittoral eelgrass stands, with an associated decrease in habitat diversity. The causes for this decline are presumably connected with the ‘wasting disease’ and the closure of the former Zuiderzee in the early 1930s resulting in increased tidal range and increased currents. After a slight recovery of the eelgrass populations on the intertidal flats a definite decline started in the early 1970s, possibly connected to increased turbidity. The present water quality and turbidity do not negatively influence eelgrass growth up to a depth of at least 0.6m below Mean Sea Level. Based on mesocosm experiments and field experiments it is concluded that re-establishment of eelgrass should be possible in sheltered bays and on unexposed tidal flats. The most suitable depths for a reintroduction are those between 0 and 20–40 cm below mean sea level.     

Reintroduction of eelgrass ( Zostera marina ) in the Dutch Wadden Sea; Review of research and suggestions for management measures

Eelgras (Zostera marina L.) in the Dutch Wadden Sea historically covered an area varying from 65–150 km² in the eulittoral as well as the sublittoral zones. At present, this area comprises less than 1 km² eulittoral eelgrass stands, with an associated decrease in habitat diversity. The causes for this decline are presumably connected with the ‘wasting disease’ and the closure of the former Zuiderzee in the early 1930s resulting in increased tidal range and increased currents. After a slight recovery of the eelgrass populations on the intertidal flats a definite decline started in the early 1970s, possibly connected to increased turbidity. The present water quality and turbidity do not negatively influence eelgrass growth up to a depth of at least 0.6m below Mean Sea Level. Based on mesocosm experiments and field experiments it is concluded that re-establishment of eelgrass should be possible in sheltered bays and on unexposed tidal falts. The most suitable depths for a reintroduction are those between 0 and 20–40 cm below mean sea level.     

A water-quality model for the Lagoon of Venice,Italy

A water-quality model for the Lagoon of Venice is proposed. The model is based on the results of an existing, deterministic, hydraulic-dispersive model of the Lagoon to provide the distribution of salinity and residence time in the Lagoon of Venice. This model has been implemented by Magistrato alle Acque di Venezia and Consorzio Venezia Nuova to evaluate the environmental impact of the MOSE Project, that has the aim to defend the city of Venice from extraordinary high tides [CVN, 1997. Allegato allo studio di impatto ambientale del progetto di massima delle opere mobili per la difesa dei centri abitati lagunari dagli allagamenti, vol. 2., CVN, 2002. Studio di nuove configurazioni dei canali di bocca e del relativo adeguamento progettuale delle opere mobili alle bocche di porto].The water-quality is simulated by statistic analysis on water-quality data, monthly collected in 30 stations. The data-set covers a period of 2 years, and has been collected in the framework of MELa1, the institutional water-quality monitoring program (Magistrato alle Acque di Venezia, Consorzio Venezia Nuova). The Spearman correlation index of salinity and residence time versus the water-quality variables (nitrogen, phosphorus, chlorophyll-a and the trophic index TRIX) has been studied on a yearly average basis and for the spring–summer periods. The spatial distribution of the water-quality variables, based on the yearly average of nutrients, is mostly driven by the dispersive processes and is well correlated to salinity [Bianchi, F., Acri, F., Alberghi, M., Bastianini, M., Boldrin, A., Cavalloni, B., Cioce, F., Comaschi, A., Rabitti, S., Socal, G., Turchetto M.M., 1999. Biologocal variability in the Venice Lagoon. In: Lasserre, P., Marzollo, A. (Eds.), The Venice Lagoon Ecosystem. Input Interaction between Land and Sea, UNESCO, Man and Biosphere Series, vol. 25, pp. 97–125].The model has been applied to simulate the variation of nutrients and trophic index distribution in the Lagoon as a consequence of an increase of hydraulic dissipation at the Lagoon outlets.The work presented in this paper shows that, coupling a deterministic, distributed-parameters, dynamic, hydraulic-dispersive model to a statistic one that accounts for the correlation between hydraulic related forcing functions (salinity, residence time) and water-quality data is a promising and simple way to evaluate the water-quality of the Lagoon of Venice.Of course, this methodology is applicable because a very large data-set is now available.The usual limitations of the statistical model methodology are present in this application too. E.g., it cannot precisely estimate the values of the water-quality variables, but it can indicate how they react when the system hydrological features change. Besides, the outcomes depend strongly on site characteristics and on the actual ecosystem state.The model has not been validated yet, due to the short data time lag, but the aim of this work is to suggest a simple simulation tool whose reliability is at least the same of that obtained by complex, deterministic, dynamic water-quality models. These models, accounting for several processes and hence including a lot of parameters, require for calibration a much more detailed data-set not yet available.The increase of dissipation is altering nutrient concentrations in the Lagoon of an average +3.2%, while the average variation for TRIX is +0.4%, and for chlorophyll-a is +3.0%.These variations are small enough to confirm a posteriori the validity of the adopted statistical approach.     

Polychaete assemblages along a rocky shore on the South Adriatic coast (Mediterranean Sea): patterns of spatial distribution

This study reports on the distribution of polychaete assemblages along a depth gradient from 5 to 25 m, along a stretch of rocky coast near Otranto (South Adriatic sea, Italy). Three depths were sampled in May and November 2000. At each depth three sites (about 100 m apart) were sampled by scraping off three replicate quadrats of 20×20 cm. The experimental design enabled identification of across- and along-shore spatial patterns of variation of polychaete assemblages. A total of 4,168 specimens, belonging to 152 taxa were collected. Multivariate analysis showed that the polychaete assemblages differed significantly among depths with the clearest differences between the shallowest sites (5 m) and the deeper ones (15–25 m). A considerable source of variation among sites at each level of the shore was also exhibited by the analyses, with the greatest differences among sites within depths recorded at 5 m. The species most contributing to the differentiation of assemblages among depths and sites within each depth were identified. Some potential causes of the observed differences are hypothesized and discussed. The importance of quantitative observation to provide the context for studying the underlying ecological processes is also stressed.Communicated by R. Cattaneo-Vietti, Genova     

Production dynamics of the eelgrass, <Emphasis Type="Italic">Zostera marina</Emphasis> in two bay systems on the south coast of the Korean peninsula

Production dynamics of eelgrass, Zostera marina was examined in two bay systems (Koje Bay and Kosung Bay) on the south coast of the Korean peninsula, where few seagrass studies have been conducted. Dramatically reduced eelgrass biomass and growth have been observed during summer period on the coast of Korea, and we hypothesized that the summer growth reduction is due to increased water temperature and/or reduced light and nutrient availabilities. Shoot density, biomass, morphological characteristics, leaf productivities, and tissue nutrient content of eelgrass were measured monthly from June 2001 to April 2003. Water column and sediment nutrient concentrations were also measured monthly, and water temperature and underwater irradiance were monitored continuously at seagrass canopy level. Eelgrass shoot density, biomass, and leaf productivities exhibited clear seasonal variations, which were strongly correlated with water temperature. Optimal water temperature for eelgrass growth in the present study sites was about 15–20°C during spring period, and eelgrass growths were inhibited at the water temperature above 20°C during summer. Daily maximum underwater photon flux density in the study sites was usually much higher than the light saturation point of Z. marina previously reported. Densities of each terminal, lateral, and reproductive shoot showed their unique seasonal peak. Seasonal trends of shoot densities suggest that new eelgrass shoots were created through formation of lateral shoots during spring and a part of the vegetative shoots was transformed into flowering shoots from March. Senescent reproductive shoots were detached around June, and contributed to reductions of shoot density and biomass during summer period. Ambient nutrient level appeared to provide an adequate reserve of nutrient for eelgrass growth throughout the experimental period. The relationships between eelgrass growth and water temperature suggested that rapid reductions of eelgrass biomass and growth during summer period on the south coast of the Korean peninsula were caused by high temperature inhibition effects on eelgrass growth during this season.     

Imputing Unmeasured Explanatory Variables in Environmental Epidemiology With Application to Health Impact Analysis of Air Pollution

This paper presents the results of a reconsideration of earlier work that finds an association between daily hospital admissions for respiratory distress and daily concentrations of sulphate (lag 1) as well as daily maximum concentrations of ozone (lags 1 and 3). These associations are found even after clustering the data by hospital of admission and accounting for the effects of temperature. We use an adaptation of their generalized estimating equation technique for clustered data, that daily data being for southern Ontario summers from 1983 to 1988. Like them, we adjust for daily maximum temperatures. However, unlike the earlier work returned to ours includes daily average humidity as a potential explanatory variable in our model. Our analysis also differs from theirs in that we cluster the data by census subdivision to reduce the risk of confounding pollutant levels with population size within regions. Moreover, we log-transform the explanatory variables and then high-pass filter the resulting data. We also deviate from the earlier analysis by taking account of measurement error incurred in using surrogate measures of the explanatory variables. To do so we use new methodology designed for our study but of potential value in other applications. That methodology requires a spatial predictive distribution for the unmeasured explanatory variables. Each day about 700 missing measurements for each of these variables can then be imputed over the geographical domain of the study. With these imputations we get a measure of imputation error through the covariance of the predictive distribution. Along with the predictive distribution we require an impact model to link-up with the predictive distribution. We describe that model and show how it uses the imputed measurements of the missing values of the explanatory variables. We also show how through that model, uncertainty about these values is reflected in our analysis and in commensurate uncertainties in the inferences made. Apart from its substantive objectives, our analysis serves to test the new methods with the earlier results serving as a foil. The reassuring qualitative agreement between our findings and the earlier results seems encouraging.     

Comparative survival of bay scallops in eelgrass and the introduced alga, Codium fragile, in a New York estuary

Eelgrass, Zostera marina, is generally regarded as the preferred habitat of bay scallops, but in some cases scallop populations have persisted or increased in areas lacking eelgrass. This suggests that some other substrate(s) may serve important ecological functions for bay scallops. One candidate is Codium fragile, a macroalgal species with which bay scallops are known to associate and in which we commonly find juvenile and adult bay scallops in eastern Long Island, New York. In this study, we examined whether survival of planted bay scallops differed in Codium, eelgrass, and Codium + eelgrass substrates at two sites during August and October of 2 years. Survival of tethered scallops and recoveries of live free-planted individuals varied with scallop size, planting season and year, but no differences were observed between the three substrates for a given scallop size and planting date. Crab (particularly Dyspanopeus sayi) and whelk predation were implicated as important causes of tethered scallop mortalities while emigration and removal by predators likely contributed to scallop losses. Densities of naturally recruited 0+ years scallops recovered by visual and suction dredge sampling were similar in the eelgrass and Codium substrates. While our results suggest that Codium may offer some degree of predation refuge for bay scallops, further work needs to weigh the potential disadvantages of this substrate (such as low DO levels, potential attachment and transport of scallops, and differences in current flow, food availability and sedimentation relative to eelgrass) to determine if Codium may serve as a valuable habitat for bay scallops throughout their lifespan.     

Mapping species distributions in one dimension by non-homogeneous hidden Markov models: the case of freshwater pearl mussels in the River Dee

The investigation of species distributions in rivers involves data which are inherently sequential and unlikely to be fully independent. To take these characteristics into account, we develop a Bayesian hierarchical model for mapping the distribution of freshwater pearl mussels in the River Dee (Scotland). At the top of the hierarchy the likelihood is used to describe the sequence of sites in which mussels were observed or not. Given that false observations can occur, and that “not observed” means both that the species was not present and that it was not observed, a Markov prior is introduced at the second level of the hierarchy to represent the sequence of sites in which mussels are estimated to occur. The Markov prior allows modelling the spatial dependency between neighbouring sites. A third level in the hierarchy is given by the representation of the transition probabilities of the Markov chain in terms of site-specific explanatory variables, through a logistic regression. The selection of the explanatory variables which influence the Markov process is performed by means of a simulation-based procedure, in the complex case of association between covariates. Four features were found to be associated with reduced chance of finding a local mussel population: tributaries, bridges, dredging, and waste water treatment works. These results complement the results of a previous study, providing new evidence for the causes of the deterioration of a highly threatened species.     

Observation and collection of deep-reef fishes off the coasts of Jamaica and British Honduras (Belize)

Over 60 species of reef fishes were observed from submersibles between 50 and 305 m depth, and 25 species were collected from the same depth range using fish traps and submersibles. Short transects gave relative abundance of some species with depth. Many shallow-water coral-reef fishes reach depths far below the lower growth limits of reef-building corals. A true “deep-reef” fauna exists, but the juveniles of some of these species are found at depths of less than 50 m.     

Patterns of distribution and composition of sea urchin assemblages on Brazilian subtropical rocky reefs

Sea urchins are a key group of herbivores in both temperate and tropical food webs because they control macroalgal cover, and consequently influence primary productivity and phase shifts on reefs. Despite being abundant on southwestern Atlantic reefs, sea urchin distributions, and their association with abiotic and biotic variables, are poorly known. In this study, sea urchin assemblages were surveyed in 2011 at multiple depths at eight sites in Arraial do Cabo (Brazil, 22°57′S/41°01′W), with sites split between a colder, more wave-exposed location, and a warmer, more sheltered location. The influence of this large-scale physical gradient, along with changes in depth and substrate complexity, on sea urchin densities was then investigated. Predator biomass was low and did not vary significantly among sites. Among the seven species recorded, Paracentrotus gaimardi, Echinometra lucunter and Arbacia lixula were dominant. Linear mixed-effects models indicated that location was important, with mid-sized P. gaimardi individuals and A. lixula more common at cooler, exposed sites and E. lucunter more abundant at warmer, sheltered sites. Sea urchin densities typically decreased with increasing depth, probably caused by changes in factors such as light, wave exposure, and sedimentation. Substrate complexity had a positive effect on the abundance of all species, presumably because of the increased availability of refuges. Physical gradients have important consequences for urchin distributions and their ecological functions at relatively small spatial scales on these reefs, and should be incorporated into herbivore monitoring programmes. Research is also required to examine how differential sea urchin distributions affect benthic dynamics.     

Habitat associations and diet of young-of-the-year Pacific cod (<Emphasis Type="Italic">Gadus macrocephalus</Emphasis>) near Kodiak,Alaska

The influence of environmental variables and habitat on growth and survival of juvenile gadoid species in the Atlantic has been clearly demonstrated; conversely, in the North Pacific little is known about the habitat and ecology of juvenile Pacific cod (Gadus macrocephalus Tilesius). The hypothesis that density of young-of-the-year (YOY) Pacific cod in nearshore habitats is predicted by shallow depth and the presence of eelgrass and macroalgae was tested in a variety of nearshore habitats adjacent to commercial fishing grounds near Kodiak Island, AK. From 10 to 22 August 2002, a beach seine and small-meshed beam trawl were used to capture YOY Pacific cod (n = 254) ranging from 42 to 110 mm fork length. Depth, water temperature, salinity, sediment grain size, and percent cover by emergent structure (i.e. tube-dwelling polychaetes, sea cucumber mounds, macroalgae) were measured prior to fishing. Density of YOY Pacific cod was highest in areas of moderate depth (15–20 m) and positively and linearly related to percent cover by sea cucumber mounds and to salinity. No previous studies have documented fish utilizing sea cucumber mounds as habitat. Furthermore, eelgrass and macroalgae were inconsequential to cod distribution. Diets consisted mainly of small calanoid copepods, mysids, and gammarid amphipods and were significantly related to cod length and depth. This work provides important information on previously undocumented factors that affect distribution and feeding of YOY Pacific cod, which ultimately influence growth and survival in this species.     

Variation in concentrations of trace elements in otoliths and eye lenses of a temperate reef fish, Parma microlepis, as a function of depth, spatial scale, and age

 Territorial Parma microlepis (Günther) (Pomacentridae) were collected at different depths, at three sites in each of four estuaries near Sydney, Australia. Element concentrations were measured by induc- tively-coupled–plasma mass spectrometry. Significant differences in concentrations of Mn and Ba were found in the otoliths of fish sampled in different depth strata, with concentrations generally greatest in fish found in water <4 m deep. Depth-related differences varied among estuaries (e.g. 0 to 1.2 μg Ba g⁻¹ otolith). In most estuaries there was a negative linear relationship between concentrations of Mn and Ba in otoliths and actual depth. Great variation was found within an estuary among sites separated by 0.5 to 3 km. In the eye lenses, concentrations of Rb differed according to depth of capture of fish. The age of fish (1+ to 34 yr) had no influence on the concentrations of elements in otoliths or lenses. Multivariate comparisons of elemental composition (= fingerprints) detected significant differences among depth strata. Fish collected from shallow water had the clearest multivariate classification according to depth. There was a close match between our shallow strata and the average depths reached by low-salinity/high-temperature estuarine plumes. The element composition of whole otoliths and lenses represents average concentrations experienced by the fish. The temporal resolution of differences in ambient conditions is likely to be coarse in the fish (i.e. months to years). Received: 9 April 1999 / Accepted: 29 February 2000     

Acoustic Observations of Bottom Surge From Dredged Material Discharge in the Open Ocean

Abstract

Bottom surges generated from dredged material discharges in the open ocean have been observed using high frequency acoustic concentration profilers in several field studies during the past five years. the locations, water depths, bottom slopes, oceanographic conditions, and dredged material composition differed from study to study. Observed surges at three dredged material disposal sites may develop more than one surge peak for a single discharge. for water depths of the order of 10 m, surge height of the leading peak was estimated to be about one quarter of the water depth. for water of greater depth, of the order of 100 m, surge height reached 70 m, about 70% of the water depth. Surge height is established instantaneously when dredged material hits the bottom, and remains relatively constant as the surge advances horizontally. Total surge length reached 150 m for water depths of 10 m when measured from the impact point to the leading edge. for water depths of more than 100 m, the surge length reached more than 100 m. Length of the leading surge peak was as large as 45 m at this water depth.

Dimensional analysis was applied to relate the surge height of the leading surge peak to discharge parameters and oceanographic conditions. Results showed that the ratio of surge height to water depth was proportional to 1/10 power of the ratio of discharge volume to the third power of water depth.     

Using artificial neural network for reservoir eutrophication prediction

Reservoirs provide approximately 70% of water supply for domestic and industrial use in Taiwan. The water quality of reservoirs is now one of the key factors in the operation and water quality management of reservoirs. Transient weather patterns result in highly variable magnitudes of precipitation and thereby sharp fluctuations in the surface elevation of the reservoirs. In addition, excessive watershed development in the past two decades has contributed to continuing increase in nutrient loads to the reservoirs. The difficulty in quantifying watershed nutrient loads and uncentainties in kinetic mechanism in the water column present a technical challenge to the mass balance based modeling of reservoir eutrophication. This study offers an alternative approach to quantifying the cause-and-effect relationship in reservoir eutrophication with a data-driven method, i.e., capturing non-linear relationships among the water quality variables in the reservoir. A commonly used back-propagation neural network was used to relate the key factors that influence a number of water quality indicators such as dissolved oxygen (DO), total phosphorus (TP), chlorophyll-a (Chl-a), and secchi disk depth (SD) in a reservoir in central Taiwan. Study results show that the neural network is able to predict these indicators with reasonable accuracy, suggesting that the neural network is a valuable tool for reservoir management in Taiwan.     

Genetic structure and gene flow of eelgrass <Emphasis Type="Italic">Zostera marina</Emphasis> populations in Tokyo Bay,Japan: implications for their restoration

Massive losses of eelgrass Zostera marina beds in Japan have occurred over the past 100 years. Toward their restoration, transplantation of eelgrass has been attempted in some areas, including Tokyo Bay. This study examined population genetic structures and gene flow in eelgrass in Tokyo Bay to establish guidelines for conducting restoration. Genotypes of a total of 360 individuals from 12 beds were determined using five microsatellite markers. The eelgrass beds in inner bay had above-average genetic diversity. A neighbor-joining tree based on F _ST values among beds revealed that a strong gene flow had occurred among six beds in the inner bay. Genetic assignment testing of drifting shoots indicated that those with seeds migrate in both directions between the inner and outer bay. We suggested that the restoration of eelgrass in the innermost part of Tokyo Bay, where natural habitats have been lost, should be conducted using the inner bay beds.     

Bayesian hierarchical spatio-temporal modelling of trends and future projections in the ocean wave climate with a \text{ CO }_2 regression component

Bad weather and rough seas continue to be a major cause for ship losses and is thus a significant contributor to the risk to maritime transportation. This stresses the importance of taking severe sea state conditions adequately into account, with due treatment of the uncertainties involved, in ship design and operation in order to enhance safety. Hence, there is a need for appropriate stochastic models describing the variability of sea states. These should also incorporate realistic projections of future return levels of extreme sea states, taking into account long-term trends related to climate change and inherent uncertainties. The stochastic ocean wave model presented in this paper exploits the flexible framework of Bayesian hierarchical space-time models. It allows modelling of complex dependence structures in space and time and incorporation of physical features and prior knowledge, yet at the same time remains intuitive and easily interpreted. Furthermore, by taking a Bayesian approach, the uncertainties of the model parameters are also taken into account. A regression component with $\text{ CO }_2$ as an explanatory variable has been introduced in order to extract long-term trends in the data. The model has been fitted by monthly maximum significant wave height data for an area in the North Atlantic ocean. The different components of the model will be outlined in the paper, and the results will be discussed. Furthermore, a discussion of possible extensions to the model will be given.     

Empirical realised niche models for British coastal plant species

Coastal environments host plant taxa adapted to a wide range of salinity conditions. Salinity, along with other abiotic variables, constrains the distribution of coastal plants in predictable ways, with relatively few taxa adapted to the most saline conditions. However, few attempts have been made to quantify these relationships to create niche models for coastal plants. Quantification of the effects of salinity, and other abiotic variables, on coastal plants is essential to predict the responses of coastal ecosystems to external drivers such as sea level rise. We constructed niche models for 132 coastal plant taxa in Great Britain based on eight abiotic variables. Paired measurements of vegetation composition and abiotic variables are rare in coastal habitats so four of the variables were defined using community mean values for Ellenberg indicators, i.e. scores assigned according to the typical alkalinity, fertility, moisture availability and salinity of sites where a species occurs. The remaining variables were the canopy height, annual precipitation, and maximum and minimum temperatures. Salinity and moisture indicator scores were significant terms in over 80 % of models, suggesting the distributions of most coastal species are at least partly determined by these variables. When the models were used to predict species occurrence against an independent dataset 64 % of models gave moderate to good predictions of species occurrence. This indicates that most models had successfully captured the key determinants of the niche. The models could potentially be applied to predict changes to habitats and species-dependent ecosystem services in response to rising sea levels.     

Can spatial isolation help predict dispersal-limited sites for native species restoration?

When the distribution of species is limited by propagule supply, new populations may be initiated by seed addition, but identifying suitable sites for efficiently targeted seed addition remains a major challenge for restoration. In addition to the biotic or abiotic variables typically used in species distribution models, spatial isolation from conspecifics could help predict the suitability of unoccupied sites. Site suitability might be expected to increase with spatial isolation after other factors are accounted for, since isolation increases the chance that a site is unoccupied only because of propagule limitation. For two native annual forbs in Californian grasslands, we combined experimental seeding and niche modeling to ask whether suitability of unoccupied sites could be predicted by spatial variables (either distances from, or densities of, conspecific populations), either by themselves or in combination with niche models. We also asked whether experimental tests of these predictions held up not only in the short term (one year), but also in the longer term (three years). For Lasthenia californica, seed additions were only successful relatively near existing populations. For Lupinus nanus, seeding success was low and was positively related to the number of conspecifics within 1 km. For both species, a few previously unoccupied sites remained occupied three years after seeding, but this subset was not predictable based on either spatial or niche variables. Seed addition alone may be a limited means of native forb restoration if suitable unoccupied sites are either rare or unpredictable, or if they tend to be close to where the species already occurs.     

Effects of mixing-induced irradiance fluctuations on photosynthesis of natural assemblages of coastal phytoplankton

Photosynthesis versus irradiance relations were determined from field incubations of natural assemblages of phytoplankton that were either cycled at three different rates between the surface and a depth of 5 m or kept at constant depths. Photoinhibition of photosynthesis was not observed in the bottles kept at constant depths during 3.5-h experiments. Photosynthesis versus irradiance (P-I) curves derived from bottles kept at constant depths and the irradiance time course received by each of the cycled bottles were used to predict photosynthesis within each of the cycled bottles. P-I curves derived from measurements under relatively constant irradiance accurately predicted the mean photosynthetic response of phytoplankton that experienced large fluctuations in irradiance.