Phytoplankton sinking rate determination: Technical and theoretical aspects, an improved methodology

An analysis of technical and theoretical problems associated with the measurement of phytoplankton sinking rates by several commonly used methods indicates that these methods are both inaccurate and imprecise. Sinking rates estimated by the discrete sample layer (DSL) method tend systematically to over-estimate the mean sinking rate of the population due to the effect of inefficient detection of cells on the bottom of the settling chamber. Sinking rates estimated using the homogeneous sample (HS) method and so-called t_0–5 technique systematically under-estimate the mean sinking rate if any cells in the population sink faster than twice the estimated average sinking rate.

A rigorous mathematical framework is developed which, in conjunction with certain modifications in settling chamber design, allows calculation of the mean sinking rate (assuming that no cells are positively buoyant) for both the DSL and HS methods. These theoretical and technical modifications permit mean sinking rates to be estimated more rapidly and with greater accuracy and precision than has been possible by previous methods.     

Open removal models with temporary emigration and population dynamics to inform invasive animal management

Removal sampling data are the primary source of monitoring information for many populations (e.g., invasive species, fisheries). Population dynamics, temporary emigration, and imperfect detection are common sources of variation in monitoring data and are key parameters for informing management. We developed two open robust‐design removal models for simultaneously modeling population dynamics, temporary emigration, and imperfect detection: a random walk linear trend model (estimable without ancillary information), and a 2‐age class informed population model (InfoPM, closely related to integrated population models) that incorporated prior information for age‐structured vital rates and relative juvenile availability. We applied both models to multiyear, removal trapping time‐series of a large invasive lizard (Argentine black and white tegu, Salvator merianae) in three management areas of South Florida to evaluate the effectiveness of management programs. Although estimates of the two models were similar, the InfoPMs generally returned more precise estimates, partitioned dynamics into births, deaths, net migration, and provided a decision support tool to predict population dynamics under different effort scenarios while accounting for uncertainty. Trends in tegu superpopulation abundance estimates were increasing in two management areas despite generally high removal rates. However, tegu abundance appeared to decline in the Core management area, where trapping density was the highest and immigration the lowest. Finally, comparing abundance predictions of no‐removal scenarios to those estimated in each management area suggested significant population reductions due to management. These results suggest that local tegu population control via systematic trapping may be feasible with high enough trap density and limited immigration; and highlights the value of these trapping programs. We provided the first estimates of tegu abundance, capture probabilities, and population dynamics, which is critical for effective management. Furthermore, our models are applicable to a wide range of monitoring programs (e.g., carcass recovery or removal point‐counts).     

Poor nutritional quality of primary producers and zooplankton driven by eutrophication is mitigated at upper trophic levels

Eutrophication and rising water temperature in freshwaters may increase the total production of a lake while simultaneously reducing the nutritional quality of food web components. We evaluated how cyanobacteria blooms, driven by agricultural eutrophication (in eutrophic Lake Köyliöjärvi) or global warming (in mesotrophic Lake Pyhäjärvi), influence the biomass and structure of phytoplankton, zooplankton, and fish communities. In terms of the nutritional value of food web components, we evaluated changes in the ω‐3 and ω‐6 polyunsaturated fatty acids (PUFA) of phytoplankton and consumers at different trophic levels. Meanwhile, the lakes did not differ in their biomasses of phytoplankton, zooplankton, and fish communities, lake trophic status greatly influenced the community structures. The eutrophic lake, with agricultural eutrophication, had cyanobacteria bloom throughout the summer months whereas cyanobacteria were abundant only occasionally in the mesotrophic lake, mainly in early summer. Phytoplankton community differences at genus level resulted in higher arachidonic acid, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) content of seston in the mesotrophic than in the eutrophic lake. This was also reflected in the EPA and DHA content of herbivorous zooplankton (Daphnia and Bosmina) despite more efficient trophic retention of these biomolecules in a eutrophic lake than in the mesotrophic lake zooplankton. Planktivorous juvenile fish (perch and roach) in a eutrophic lake overcame the lower availability of DHA in their prey by more efficient trophic retention and biosynthesis from the precursors. However, the most efficient trophic retention of DHA was found with benthivorous perch which prey contained only a low amount of DHA. Long‐term cyanobacterial blooming decreased the nutritional quality of piscivorous perch; however, the difference was much less than previously anticipated. Our result shows that long‐term cyanobacteria blooming impacts the structure of plankton and fish communities and lowers the nutritional quality of seston and zooplankton, which, however, is mitigated at upper trophic levels.     

Incorporating capture heterogeneity in the estimation of autoregressive coefficients of animal population dynamics using capture–recapture data

Population dynamic models combine density dependence and environmental effects. Ignoring sampling uncertainty might lead to biased estimation of the strength of density dependence. This is typically addressed using state‐space model approaches, which integrate sampling error and population process estimates. Such models seldom include an explicit link between the sampling procedures and the true abundance, which is common in capture–recapture settings. However, many of the models proposed to estimate abundance in the presence of capture heterogeneity lead to incomplete likelihood functions and cannot be straightforwardly included in state‐space models. We assessed the importance of estimating sampling error explicitly by taking an intermediate approach between ignoring uncertainty in abundance estimates and fully specified state‐space models for density‐dependence estimation based on autoregressive processes. First, we estimated individual capture probabilities based on a heterogeneity model for a closed population, using a conditional multinomial likelihood, followed by a Horvitz–Thompson estimate for abundance. Second, we estimated coefficients of autoregressive models for the log abundance. Inference was performed using the methodology of integrated nested Laplace approximation (INLA). We performed an extensive simulation study to compare our approach with estimates disregarding capture history information, and using R‐package VGAM, for different parameter specifications. The methods were then applied to a real data set of gray‐sided voles Myodes rufocanus from Northern Norway. We found that density‐dependence estimation was improved when explicitly modeling sampling error in scenarios with low process variances, in which differences in coverage reached up to 8% in estimating the coefficients of the autoregressive processes. In this case, the bias also increased assuming a Poisson distribution in the observational model. For high process variances, the differences between methods were small and it appeared less important to model heterogeneity.     

Considering sampling bias in close‐kin mark–recapture abundance estimates of Atlantic salmon

Genetic methods for the estimation of population size can be powerful alternatives to conventional methods. Close‐kin mark–recapture (CKMR) is based on the principles of conventional mark–recapture, but instead of being physically marked, individuals are marked through their close kin. The aim of this study was to evaluate the potential of CKMR for the estimation of spawner abundance in Atlantic salmon and how age, sex, spatial, and temporal sampling bias may affect CKMR estimates. Spawner abundance in a wild population was estimated from genetic samples of adults returning in 2018 and of their potential offspring collected in 2019. Adult samples were obtained in two ways. First, adults were sampled and released alive in the breeding habitat during spawning surveys. Second, genetic samples were collected from out‐migrating smolts PIT‐tagged in 2017 and registered when returning as adults in 2018. CKMR estimates based on adult samples collected during spawning surveys were somewhat higher than conventional counts. Uncertainty was small (CV < 0.15), due to the detection of a high number of parent–offspring pairs. Sampling of adults was age‐ and size‐biased and correction for those biases resulted in moderate changes in the CKMR estimate. Juvenile dispersal was limited, but spatially balanced sampling of adults rendered CKMR estimates robust to spatially biased sampling of juveniles. CKMR estimates based on returning PIT‐tagged adults were approximately twice as high as estimates based on samples collected during spawning surveys. We suggest that estimates based on PIT‐tagged fish reflect the total abundance of adults entering the river, while estimates based on samples collected during spawning surveys reflect the abundance of adults present in the breeding habitat at the time of spawning. Our study showed that CKMR can be used to estimate spawner abundance in Atlantic salmon, with a moderate sampling effort, but a carefully designed sampling regime is required.     

湖泊蓝藻水华发生机理研究进展

蓝藻水华是富营养化湖泊常见的生态灾害,通过产生毒素、死亡分解时使水体缺氧和破坏正常的食物网威胁到饮用水安全、公众健康和景观,会造成严重的经济损失和社会问题,揭示其发生机理是进行防治的基础。综述了蓝藻水华发生机理的主要假说和证据,主要分为环境因子(营养盐、氮磷比、温度、微量元素、浮游动物牧食、水文和气象条件等)和生理生态特性(伪空泡、胶质鞘、CO2浓缩机制、适应低光强、贮藏营养物质、防晒、产毒素和固氮等)两个方面;评述了主要新理论,展望了今后的研究。到目前为止的研究表明寻找一两个关键因子并不能阐明蓝藻水华的发生机理。现存的理论或假说尽管已经在蓝藻水华的防治实践中产生重要作用,但仍然未能清楚地阐释其发生的客观规律。认为蓝藻水华是在各种环境因子(外因)的耦合驱动下,水华蓝藻由于其独特的生理生态特性(内因),产生巨大的生物量而在浮游植物群落中占绝对优势,在合适的水文气象条件下集聚于水表而形成。因此水华机理的研究应同时关注水华蓝藻的生理生态学规律和蓝藻水华发生的各种环境条件。不同环境因子协同影响水华蓝藻的不同生理生态特性的表达,从而影响水华的发生过程,将可能是以后研究的重点。蓝藻水华机理的研究在微观方面正趋向于应用分子生物学手段分析蓝藻生理过程,宏观方面则将广泛应用遥感遥测技术观测全湖蓝藻的变化规律。今后加强对水华蓝藻生理生态特性的基因表达与调控和环境多因子耦合作用于蓝藻水华过程的研究将有重要意义。蓝藻水华的机理研究包括现象、过程和原因3个层次的问题,通过大量的现象和过程的研究,不断揭示其发生过程中水华蓝藻的群落演替、种群发展、细胞活性和分子机理等变化规律,才能找到其发生的真正原因,为其防治提供理论依据和更好的治理措施。在蓝藻水华防治方面,控制营养盐和生态修复可能将是今后很长时间内最根本最有效和最具操作性的方法。     

Variability of Primary Production in an Antarctic Marine Ecosystem as Estimated Using a Multi-scale Sampling Strategy

A major objective of the multidisciplinary Palmer Long TermEcological Research (LTER) program is to obtain a comprehensiveunderstanding of various components of the Antarctic marineecosystem—the assemblage of plants, animals, ocean, seaice, and island components south of the Antarctic Convergence.Phytoplankton production plays a key role in this polar ecosystem,and factors that regulate production include those that controlcell growth (light, temperature, nutrients) and those that controlcell accumulation rate and hence population growth (water columnstability, advection, grazing, and sinking). Several of thesefactors are mediated by the annual advance and retreat of seaice. In this study, we examine the results from nearly a decade(1991–2000) of ecological research in the western AntarcticPeninsula region. We evaluate the spatial and temporal variabilityof phytoplankton biomass (estimated as chlorophyll-a concentration)and primary production (determined in-situ aboard ship as wellas estimated from ocean color satellite data). We also presentthe spatial and temporal variability of sea ice extent (estimatedfrom passive microwave satellite data). While the data recordis relatively short from a long-term perspective, evidence isaccumulating that statistically links the variability in seaice to the variability in primary production. Even though thismarine ecosystem displays extreme interannual variability inboth phytoplankton biomass and primary production, persistentspatial patterns have been observed over the many years of study(e.g., an on to offshore gradient in biomass and a growing seasoncharacterized by episodic phytoplankton blooms). This high interannualvariability at the base of the food chain influences organismsat all trophic levels.     

Lions in a coexistence landscape: Repurposing a traditional field technique to monitor an elusive carnivore

Throughout Africa, lions are thought to have experienced dramatic population decline and range contraction. The greatest declines are likely occurring in human‐dominated landscapes where reliably estimating lion populations is particularly challenging. By adapting a method that has thus far only been applied to animals that are habituated to vehicles, we estimate lion density in two community areas in Kenya''s South Rift, located more than 100 km from the nearest protected area (PA). More specifically, we conducted an 89‐day survey using unstructured spatial sampling coupled with playbacks, a commonly used field technique, and estimated lion density using spatial capture‐recapture (SCR) models. Our estimated density of 5.9 lions over the age of 1 year per 100 km² compares favorably with many PAs and suggests that this is a key lion population that could be crucial for connectivity across the wider landscape. We discuss the possible mechanisms supporting this density and demonstrate how rigorous field methods combined with robust analyses can produce reliable population estimates within human‐dominated landscapes.     

Building integral projection models with nonindependent vital rates

Population dynamics are functions of several demographic processes including survival, reproduction, somatic growth, and maturation. The rates or probabilities for these processes can vary by time, by location, and by individual. These processes can co‐vary and interact to varying degrees, e.g., an animal can only reproduce when it is in a particular maturation state. Population dynamics models that treat the processes as independent may yield somewhat biased or imprecise parameter estimates, as well as predictions of population abundances or densities. However, commonly used integral projection models (IPMs) typically assume independence across these demographic processes. We examine several approaches for modelling between process dependence in IPMs and include cases where the processes co‐vary as a function of time (temporal variation), co‐vary within each individual (individual heterogeneity), and combinations of these (temporal variation and individual heterogeneity). We compare our methods to conventional IPMs, which treat vital rates independent, using simulations and a case study of Soay sheep (Ovis aries). In particular, our results indicate that correlation between vital rates can moderately affect variability of some population‐level statistics. Therefore, including such dependent structures is generally advisable when fitting IPMs to ascertain whether or not such between vital rate dependencies exist, which in turn can have subsequent impact on population management or life‐history evolution.     

Estimation of phytoplankton production from space: current status and future potential of satellite remote sensing

A new generation of ocean colour satellites is now operational, with frequent observation of the global ocean. This paper reviews the potential to estimate marine primary production from satellite images. The procedures involved in retrieving estimates of phytoplankton biomass, as pigment concentrations, are discussed. Algorithms are applied to SeaWiFS ocean colour data to indicate seasonal variations in phytoplankton biomass in the Celtic Sea, on the continental shelf to the south west of the UK. Algorithms to estimate primary production rates from chlorophyll concentration are compared and the advantages and disadvantage discussed. The simplest algorithms utilise correlations between chlorophyll concentration and production rate and one equation is used to estimate daily primary production rates for the western English Channel and Celtic Sea; these estimates compare favourably with published values. Primary production for the central Celtic Sea in the period April to September inclusive is estimated from SeaWiFS data to be 102 gC m⁻² in 1998 and 93 gC m⁻² in 1999; published estimates, based on in situ incubations, are ca. 80 gC m⁻². The satellite data demonstrate large variations in primary production between 1998 and 1999, with a significant increase in late summer in 1998 which did not occur in 1999. Errors are quantified for the estimation of primary production from simple algorithms based on satellite-derived chlorophyll concentration. These data show the potential to obtain better estimates of marine primary production than are possible with ship-based methods, with the ability to detect short-lived phytoplankton blooms. In addition, the potential to estimate new production from satellite data is discussed.     

Phytoplankton growth rates in the freshwater tidal reaches of the Schelde estuary (Belgium) estimated using a simple light-limited primary production model

During the course of 1996, phytoplankton was monitored in the turbid, freshwater tidal reaches of the Schelde estuary. Using a simple light-limited primary production model, phytoplankton growth rates were estimated to evaluate whether phytoplankton could attain net positive growth rates and whether growth rates were high enough for a bloom to develop. Two phytoplankton blooms were observed in the freshwater tidal reaches. The first bloom occurred in March and was mainly situated in the most upstream reaches of the freshwater tidal zone, suggesting that it was imported from the tributary river Schelde. The second bloom occurred in July and August. This summer bloom was situated more downstream in the freshwater tidal reaches and appeared to have developed within the estuary. A comparison between phytoplankton growth rates estimated using a simple primary production model and flushing rate of the water indicated that no net increase in phytoplankton biomass was possible in March while phytoplankton could theoretically increase its biomass by 20% per day during summer. Chlorophyllaconcentrations at all times decreased strongly at salinities between 5–10 psu. This decline was ascribed to a combination of salinity stress and light limitation. Phytoplankton biomass and estimated annual net production were much higher in the freshwater tidal zone compared to the brackish reaches of the estuary (salinity > 10 psu) despite mixing depth to euphotic depth ratios being similar. Possible reasons for this high production include high nutrient concentrations, low zooplankton grazing pressure and import of phytoplankton blooms from the tributary rivers.     

Can effective population size estimates be used to monitor population trends of woodland bats? A case study of Myotis bechsteinii

Molecular approaches to calculate effective population size estimates (Ne) are increasingly used as an alternative to long‐term demographic monitoring of wildlife populations. However, the complex ecology of most long‐lived species and the consequent uncertainties in model assumptions means that effective population size estimates are often imprecise. Although methods exist to incorporate age structure into Ne estimations for long‐lived species with overlapping generations, they are rarely used owing to the lack of relevant information for most wild populations. Here, we performed a case study on an elusive woodland bat, Myotis bechsteinii, to compare the use of the parentage assignment Ne estimator (EPA) with the more commonly used linkage disequilibrium (LD) Ne estimator in detecting long‐term population trends, and assessed the impacts of deploying different overall sample sizes. We used genotypic data from a previously published study, and simulated 48 contrasting demographic scenarios over 150 years using the life history characteristics of this species The LD method strongly outperformed the EPA method. As expected, smaller sample sizes resulted in a reduced ability to detect population trends. Nevertheless, even the smallest sample size tested (n = 30) could detect important changes (60%–80% decline) with the LD method. These results demonstrate that genetic approaches can be an effective way to monitor long‐lived species, such as bats, provided that they are undertaken over multiple decades.     

Cyanobacterial blooms in a temperate river-floodplain ecosystem: the importance of hydrological extremes

In the past decade, extreme hydrological events were expressed with extreme droughts and floods in temperate regions. The aim of this paper is to explain how such changes in hydrology can influence cyanobacterial populations in floodplain ecosystems. We therefore analyzed a 6-year (2003–2008) study of the phytoplankton in the Kopački Rit floodplain, one of the largest natural floodplains in the middle section of the Danube River (Europe). During the studied period, the shallow floodplain lake shifted between a state of turbid water, characterized by high phytoplankton biomass and regular appearance of cyanobacteria blooms, to a state of clear water with very low phytoplankton biomass and absence of cyanobacteria, and back to the turbid state. Apparently, the major forces driving the cyclic shift were closely related to extremely high and long-lasting flood events. Significant increase in water level, low hydraulic residence time of water, decrease in transparency and low-light climate, together with mass developed aquatic macrophyte vegetation in the whole inundated floodplain were unfavorable conditions for growth and proliferation of cyanobacteria. With the establishment of the flood regime characterized by long-lasting periods without flooding, in-lake processes prevailed leading to cyanobacterial bloom. The most successful were filamentous non-N-fixing cyanobacteria tolerant to mixed and low-light conditions (Planktothrix and Limnothrix) and invasive species Cylindrospermopsis raciborskii. Their massive development led to the establishment of a phytoplankton steady state. All our results demonstrate that the altered intensity and frequency of flood events will have pronounced effects on the appearance of cyanobacterial blooms and generally on alternative stable states in the floodplain. Relating to this, management objectives should be focused on qualifications of changes in hydrology and projecting those effects for potential floodplain restoration.     

Relationships between cyanobacterial production and the physical and chemical properties of a Midwestern Reservoir,USA

Drinking water reservoirs in agricultural dominated watersheds are particularly vulnerable to cyanobacterial blooms. A major byproduct of cyanobacteria is the production of objectionable taste and odor compounds such as geosmin. During May 1997 to September 1998, we studied spatial and temporal patterns of cyanobacterial abundance and composition with respect to a series of physical and chemical properties in Clinton Lake, located in east central Kansas, USA. Our results suggest that nutrients (in particular TN, NO₃–N concentrations), turbidity, and hydrologic regime all played potentially important roles in regulating cyanobacterial production. Specifically, low levels of nitrogen coupled with the internal release of phosphorus from the lake sediment under brief periods of anoxia may have helped promote cyanobacterial blooms. There was also a strong association between cyanobacterial blooms, geosmin production, and most taste and odor events in Clinton Lake. Anabaena circinalis appeared to be the source for geosmin production as a result of senescing algal cells just after the primary die-off of cyanobacteria.     

“Third‐wave” cognitive and behavioral therapies and the emergence of a process‐based approach to intervention in psychiatry

For decades, cognitive and behavioral therapies (CBTs) have been tested in randomized controlled trials for specific psychiatric syndromes that were assumed to represent expressions of latent diseases. Although these protocols were more effective as compared to psychological control conditions, placebo treatments, and even active pharmacotherapies, further advancement in efficacy and dissemination has been inhibited by a failure to focus on processes of change. This picture appears now to be evolving, due both to a collapse of the idea that mental disorders can be classified into distinct, discrete categories, and to the more central attention given to processes of change in newer, so‐called “third‐wave” CBTs. Here we review the context for this historic progress and evaluate the impact of these newer methods and models, not as protocols for treating syndromes, but as ways of targeting an expanded range of processes of change. Five key features of “third‐wave” therapies are underlined: a focus on context and function; the view that new models and methods should build on other strands of CBT; a focus on broad and flexible repertoires vs. an approach to signs and symptoms; applying processes to the clinician, not just the client; and expanding into more complex issues historically more characteristic of humanistic, existential, analytic, or system‐oriented approaches. We argue that these newer methods can be considered in the context of an idiographic approach to process‐based functional analysis. Psychological processes of change can be organized into six dimensions: cognition, affect, attention, self, motivation and overt behavior. Several important processes of change combine two or more of these dimensions. Tailoring intervention strategies to target the appropriate processes in a given individual would be a major advance in psychiatry and an important step toward precision mental health care.     

Mesozooplankton and microzooplankton grazing during cyanobacterial blooms in the western basin of Lake Erie

Lake Erie is the most socioeconomically important and productive of the Laurentian (North American) Great Lakes. Since the mid-1990s cyanobacterial blooms dominated primarily by Microcystis have emerged to become annual, late summer events in the western basin of Lake Erie yet the effects of these blooms on food web dynamics and zooplankton grazing are unclear. From 2005 to 2007, grazing rates of cultured (Daphnia pulex) and natural assemblages of mesozooplankton and microzooplankton on five autotrophic populations were quantified during cyanobacterial blooms in western Lake Erie. While all groups of zooplankton grazed on all prey groups investigated, the grazing rates of natural and cultured mesozooplankton were inversely correlated with abundances of potentially toxic cyanobacteria (Microcystis, Anabaena, and Cylindrospermopsis; p < 0.05) while those of the in situ microzooplankton community were not. Microzooplankton grazed more rapidly and consistently on all groups of phytoplankton, including cyanobacteria, compared to both groups of mesozooplankton. Cyanobacteria displayed more rapid intrinsic cellular growth rates than other phytoplankton groups under enhanced nutrient concentrations suggesting that future nutrient loading to Lake Erie could exacerbate cyanobacterial blooms. In sum, while grazing rates of mesozooplankton are slowed by cyanobacterial blooms in the western basin of Lake Erie, microzooplankton are likely to play an important role in the top-down control of these blooms; this control could be weakened by any future increases in nutrient loads to Lake Erie.     

Testing the precision and sensitivity of density estimates obtained with a camera‐trap method revealed limitations and opportunities

The use of camera traps in ecology helps affordably address questions about the distribution and density of cryptic and mobile species. The random encounter model (REM) is a camera‐trap method that has been developed to estimate population densities using unmarked individuals. However, few studies have evaluated its reliability in the field, especially considering that this method relies on parameters obtained from collared animals (i.e., average speed, in km/h), which can be difficult to acquire at low cost and effort. Our objectives were to (1) assess the reliability of this camera‐trap method and (2) evaluate the influence of parameters coming from different populations on density estimates. We estimated a reference density of black bears (Ursus americanus) in Forillon National Park (Québec, Canada) using a spatial capture–recapture estimator based on hair‐snag stations. We calculated average speed using telemetry data acquired from four different bear populations located outside our study area and estimated densities using the REM. The reference density, determined with a Bayesian spatial capture–recapture model, was 2.87 individuals/10km² [95% CI: 2.41–3.45], which was slightly lower (although not significatively different) than the different densities estimated using REM (ranging from 4.06–5.38 bears/10km² depending on the average speed value used). Average speed values obtained from different populations had minor impacts on REM estimates when the difference in average speed between populations was low. Bias in speed values for slow‐moving species had more influence on REM density estimates than for fast‐moving species. We pointed out that a potential overestimation of density occurs when average speed is underestimated, that is, using GPS telemetry locations with large fix‐rate intervals. Our study suggests that REM could be an affordable alternative to conventional spatial capture–recapture, but highlights the need for further research to control for potential bias associated with speed values determined using GPS telemetry data.     

Modelling of autumn plankton bloom dynamics

A simple system of parametrically forced ordinary differentialequations is used to model autumn phytoplankton blooms in temperateoceans by a mechanism involving deepening of the upper mixedlayer. Blooms are triggered provided the increase in nutrientsin the mixed layer is rapid within the first few days of deepeningand provided light-limited phytoplankton growth rate is relativelyhigh. Blooms exist as transient trajectories between quasi-equilibriumstates, rather than as bifurcations of steady states; thereforevery gradual deepening cannot trigger blooms. Very rapid deepeningalso prevents blooms due to the deleterious effect on phytoplanktongrowth rate. The mechanisms identified by this simple modelare vindicated by considering alternative grazing and deepeningregimes and by comparison with a more ecologically complex model(Fasham, 1993, in The Global Carbon Cycle, Springer-Verlag).Modelled estimates of primary productivity from both the simplemodel and the complex model parameterized for Ocean WeatherStation ‘India’ are around 0.5 g C m^–2 day^–1during the autumn bloom, therefore comprising a significantcomponent of annual production in temperate areas.     

Plasticity is a locally adapted trait with consequences for ecological dynamics in novel environments

Phenotypic plasticity is predicted to evolve in more variable environments, conferring an advantage on individual lifetime fitness. It is less clear what the potential consequences of that plasticity will have on ecological population dynamics. Here, we use an invertebrate model system to examine the effects of environmental variation (resource availability) on the evolution of phenotypic plasticity in two life history traits—age and size at maturation—in long‐running, experimental density‐dependent environments. Specifically, we then explore the feedback from evolution of life history plasticity to subsequent ecological dynamics in novel conditions. Plasticity in both traits initially declined in all microcosm environments, but then evolved increased plasticity for age‐at‐maturation, significantly so in more environmentally variable environments. We also demonstrate how plasticity affects ecological dynamics by creating founder populations of different plastic phenotypes into new microcosms that had either familiar or novel environments. Populations originating from periodically variable environments that had evolved greatest plasticity had lowest variability in population size when introduced to novel environments than those from constant or random environments. This suggests that while plasticity may be costly it can confer benefits by reducing the likelihood that offspring will experience low survival through competitive bottlenecks in variable environments. In this study, we demonstrate how plasticity evolves in response to environmental variation and can alter population dynamics—demonstrating an eco‐evolutionary feedback loop in a complex animal moderated by plasticity in growth.