To inform non-indigenous species management and policy decisions it is often necessary to have a prioritized list of species and screening tools frequently are used for this purpose. However, despite numerous tools available that typically evaluate aspects of the introduction, establishment, and impacts of potential invasive species, there are still gaps in the criteria used meaning that not all tools are fit-for-purpose. Further, incorporating uncertainty in a way useful to managers has proven problematic. This paper introduces the Non-Indigenous Species Screening Tool, which was developed to fill such gaps and address common limitations in previous tools for screening potentially invasive species. Using a series of questions organized into three separate modules examining steps in the invasion process combined with both ecological impacts and socioeconomic impacts, this tool provides a semiquantitative valuation of risk which explicitly incorporates uncertainty into the score. Further, recognizing the increasing importance of considering climate change when assessing invasion risk, this tool also incorporates a modifier for this. We applied this tool to both existing non-indigenous species and potential ones (N = 44 species) across different taxa (plant, invertebrate, and fish) for the Columbia Glaciated Freshwater Ecoregion using four assessors. The question scores across all species and assessors showed strong correlation and the tool was able to differentiate low to high-risk species across taxa for species that were both present and not yet present. This suggests this tool is not taxa specific and can easily be applied for a variety of purposes.

Knowledge of the geographic distribution and connectivity of marine populations is essential for ecological understanding and informing management. Previous works have assessed spatial structure by quantifying exchange using Lagrangian particle-tracking simulations, but their scope of analysis is limited by their use of predefined subpopulations. To instead delineate subpopulations emerging naturally from marine population connectivity, we interpret this connectivity as a network, enabling the use of powerful analytic tools from the field of network theory. The modelling approach presented here uses particle-tracking to construct a transport network, and then applies the community detection algorithm Infomap to identify subpopulations that exhibit high internal connectivity and sparse connectivity with other subpopulations. An established quality metric, the coherence ratio, and a new metric we introduce indicating self-recruitment to subpopulations, dubbed the fortress ratio, are used to interpret community-level exchange. We use the Atlantic sea scallop (Placopecten magellanicus) in the northwest Atlantic as a case study. Results suggest that genetic lineages of P. magellanicus demonstrate spatial substructure that depends on horizontal transport, vertical motility, and suitable habitat. Our results support connectivity previously characterized on Georges Bank and Mid-Atlantic Bight. The Gulf of St. Lawrence genetic lineage is found to consist of five subpopulations that are classified as being a sink, source, permeable, or impermeable using quality metrics. This approach may be applied to other planktonic dispersers and prove useful to management.

In the coming decades, warming and deoxygenation of marine waters are anticipated to result in shifts in the distribution and abundance of fishes, with consequences for the diversity and composition of fish communities. Here, we combine fisheries independent trawl survey data spanning the west coast of the USA and Canada with high resolution regional ocean models to make projections of how 34 groundfish species will be impacted by changes in temperature and oxygen in British Columbia (B.C.) and Washington. In this region, species that are projected to decrease in occurrence are roughly balanced by those that are projected to increase, resulting in considerable compositional turnover. Many, but not all, species are projected to shift to deeper depths as conditions warm, but low oxygen will limit how deep they can go. Thus, biodiversity will likely decrease in the shallowest waters (< 100 m) where warming will be greatest, increase at mid depths (100—600 m) as shallow species shift deeper, and decrease at depths where oxygen is limited (> 600 m). These results highlight the critical importance of accounting for the joint role of temperature, oxygen, and depth when projecting the impacts of climate change on marine biodiversity.

Species distribution models (SDMs) have been widely used to project terrestrial species' responses to climate change and are increasingly being used for similar objectives in the marine realm. These projections are critically needed to develop strategies for resource management and the conservation of marine ecosystems. SDMs are a powerful and necessary tool; however, they are subject to many sources of uncertainty, both quantifiable and unquantifiable. To ensure that SDM projections are informative for management and conservation decisions, sources of uncertainty must be considered and properly addressed. Here we provide ten overarching guidelines that will aid researchers to identify, minimize, and account for uncertainty through the entire model development process, from the formation of a study question to the presentation of results. These guidelines focus on correlative models and were developed at an international workshop attended by over 50 researchers and practitioners. Although our guidelines are broadly applicable across biological realms, we provide particular focus to the challenges and uncertainties associated with projecting the impacts of climate change on marine species and ecosystems.

Pacific halibut (Hippoglossus stenolepis) are a large-bodied species of flatfish that are important culturally, economically, and as a key predator in marine systems in the USA and Canada. The species has a wide distribution, and complex life history including large-scale migrations to spawn and feed, making it potentially susceptible to climate change impacts. We examined the potential changes in halibut distribution and relative abundance that may arise from changing temperature and dissolved oxygen concentrations using species distribution models (SDMs) and future climate scenarios downscaled by two regional ocean models. SDMs were fit with both environmental variables (depth, near-bottom temperature and dissolved oxygen concentration) and spatial random field components (representing unknown habitat-related variables). The best-fitting models, trained on data from 2009 to 2013, were able to account for 33 % and 53 % of the variation in small and large halibut catch-per-unit-effort in the annual set-line survey data from 2014 to 2020. The results suggest that the response of Pacific halibut to climate change in British Columbia and Washington waters is likely to depend on changes in dissolved oxygen concentration. Pacific halibut appear sensitive to changes in dissolved oxygen, yet relatively tolerant to increases in temperature. Projections for 2046-2065 period suggest that future decreases in near-bottom dissolved oxygen in shallow waters that small halibut inhabit are likely to result in moderate decreases in relative abundance. Projected changes in relative abundance are less certain for large Pacific halibut, due to disagreement in the regional ocean models near-bottom dissolved oxygen projections at mid depths (300-600 m) where large Pacific halibut are more common. Overall, the relative abundance of Pacific halibut is expected to decrease in most areas of British Columbia. Future management strategies will need to account for the projected changes in distribution and abundance and their uncertainty.

Aim: We assess the role of contemporary oceanography and species traits in shaping observed patterns of biogeography over broad spatial scales. Location: Our study domain covers the east and west coasts of North America, from 30 degrees to 73 degrees N on the east coast and 33 degrees to 73 degrees N on the west coast. Time period: Hydrodynamic models use climatological fields from 1990 to 2015 on the east coast, and 1993 to 2018 on the west coast. Major taxa studied: Model simulations represent larval dispersal for generalized benthic invertebrate species distributed in the subtidal zone from 10 to 100 m depth, with planktonic larval durations ranging from 21-60 days. Methods: We conducted a literature review to identify major biogeographic barriers along the east and west coasts of North America, and then assessed the permeability of these barriers to larval dispersal using Lagrangian particle tracking. We ran a series of simulations in which we varied the suitable habitat distribution, planktonic larval duration, and spawning seasonality of simulated larvae (i.e., particles) to assess the effects of species traits on biogeography. Results: Our results showed a strong alignment of observed biogeographic barriers with larval dispersal patterns, with high variation in barrier permeability depending on the traits of the species considered. The location of suitable habitat and the season during which particle release occurred were the biological traits that drove much of the variation in barrier permeability among simulations on both coasts. Main conclusions: Our results indicate an important role of contemporary oceanographic and geographic features in determining the biogeography of species whose primary dispersal is during larval stages, suggesting that climate change is likely to alter patterns of species biogeography. Our results also demonstrate that species traits play a strong role in determining the location and strength of biogeographic barriers.

Understanding the difficult to predict interactive effects of anthropogenic stressors is recognized as one of the major challenges facing environmental scientists and ecosystem managers. Despite burgeoning research, predicting stressor interactions is still difficult, in part because the same two stressors can interact, or not, depending on their intensities. While laboratory experiments have provided useful insights about how organisms respond to serial doses of single stressors, we lack ‘response-surface’ field experiments in which naturally occurring assemblages are exposed to multiple types and concentrations of stressors. Here we used a field-based dosing system combined with a ‘response-surface’ design to test the individual and combined effects of two stressors (copper and chlorpyrifos) at five concentrations of each, for a total of 25 replicated treatments (n=4). After six weeks of dosing, chemical uptake and impacts at several levels of biological organization in mussel assemblages were measured. Stressor combinations produced interactive effects that would not have been revealed without using this replicated ‘response-surface approach’. Results show that non-additive effects of multiple stressors may be more complex and more common than previously thought. Additionally, our findings suggest that interactive effects of multiple stressors vary across levels of organization which has implications for monitoring and managing the chemical, biological and ecological impacts of priority pollutants in the real world.

Establishment of protected areas to maintain biodiversity requires identification, prioritization and management of stressors that may undermine conservation goals. Nonindigenous species and climate change are critical ecosystem stressors that need greater attention in the context of spatial planning and management of protected areas. Risk of invasion into protected areas needs to be quantified under current and projected climate conditions in conjunction with prioritization of key vectors and vulnerable areas to enable development of effective management strategies. We assessed the likelihood of invasion across networks of marine protected areas (MPAs) to determine how invaded MPAs may compromise MPA networks by sharing nonindigenous species. We evaluated invasion risk in 83 MPAs along Canada's Pacific coast for eight nonindigenous species based on environmental suitability under current and future (average conditions from 2041 to 2070) climate conditions and association with shipping and boating pathways. We applied species distribution models and network analysis of vessel tracking data for 805 vessels in 2016 that connected MPAs. The probability of occurrence within MPAs and the proportion of MPA area that is suitable to the modelled species significantly increased under future climate conditions, with six species reaching over 90% predicted occurrence across MPAs and over 70% of suitable area within MPAs. Vessel traffic created four network clusters of 61 highly connected MPAs that spanned the coastline. Occupancy of over 90% of the MPAs within the clusters was predicted for most species. Synthesis and applications. Our results indicate a high likelihood of marine protected area (MPA) network invasion based on current and future environmental conditions and vectors of spread, and the potential for extensive nonindigenous species distributions within MPAs. Our approach highlights how interacting stressors can exacerbate MPA susceptibility to nonindigenous species, adding further challenges for protected area management. Management planning that invests in understanding connectivity and vector processes (human behaviours) is more likely to derive effective policies to stem the flow of nonindigenous species under both current and future conditions. In particular, biosecurity measures including vessel biofouling regulations and MPA- and MPA network-specific plans for prevention, monitoring and mitigation of nonindigenous species are needed.

Invasive ecosystem engineers (IEE) are potentially one of the most influential types of biological invaders. They are expected to have extensive ecological impacts by altering the physical-chemical structure of ecosystems, thereby changing the rules of existence for a broad range of resident biota. To test the generality of this expectation, we used a global systematic review and meta-analysis to examine IEE effects on the abundance of individual species and communities, biodiversity (using several indices) and ecosystem functions, focusing on marine and estuarine environments. We found that IEE had a significant effect (positive and negative) in most studies testing impacts on individual species, but the overall (cumulative) effect size was small and negative. Many individual studies showed strong IEE effects on community abundance and diversity, but the direction of effects was variable, leading to statistically non-significant overall effects in most categories. In contrast, there was a strong overall effect on most ecosystem functions we examined. IEE negatively affected metabolic functions and primary production, but positively affected nutrient flux, sedimentation and decomposition. We use the results to develop a conceptual model by highlighting pathways whereby IEE impact communities and ecosystem functions, and identify several sources of research bias in the IEE-related invasion literature. Only a few of the studies simultaneously quantified IEE effects on community/diversity and ecosystem functions. Therefore, understanding how IEE may alter biodiversity-ecosystem function relationships should be a primary focus of future studies of invasion biology. Moreover, the clear effects of IEE on ecosystem functions detected in our study suggest that scientists and environmental managers ought to examine how the effects of IEE might be manifested in the services that marine ecosystems provide to humans.

Altitudinal and latitudinal gradients are excellent venues for investigating the direct and indirect effects of air temperature, solar irradiance, and insularity on spatial patterns of aquatic biodiversity. The findings can be used to predict how lake communities will respond to increasingly extreme climate events. We explored hypotheses of energy/climate, geography, and glacial history explaining patterns in species richness in a historical dataset of crustacean zooplankton communities from 436 lakes in the Canadian Rocky Mountains. GIS-based estimates of solar and thermal energy inputs combined with habitat area and insularity provided the best prediction of local species richness. Energetic and geographic factors explained a moderate proportion of the total variation in species richness (Generalized R-2 = 0.50), and were sufficient to account for both altitudinal and latitudinal gradients in zooplankton diversity. History of deglaciation was not supported as a predictor of patterns in species richness. A post hoc analysis with a smaller dataset also found strong support for lake pH, and some support for fish presence as predictors of species richness, but these only increased the proportion of the total variation explained very slightly relative to the model including only energetic and geographic factors (Generalized R-2 = 0.55 vs. 0.53). Our findings highlight the multiplicity of local and regional factors of zooplankton species richness in mountain lakes, forecasting that it will increase under a scenario of warmer and drier (i.e., less cloud cover) conditions, especially in high connectivity lakes that cease to be fed by rapidly disappearing glaciers.

In a recent letter, Thomsen & Wernberg (2015) reanalyzed data compiled for our recent paper (Lyons et al., 2014). In that paper, we examined the effects of macroalgal blooms and macroalgal mats on seven important measures of community structure and ecosystem functioning and explored several ecological and methodological factors that might explain some of the variation in the observed effects. Thomsen & Wernberg (2015) re-analyzed two small subsets of the data, focusing on experimental studies examining effects of blooms/mats on invertebrate abundance. Their analyses revealed two interesting patterns. First, they showed that macroalgal blooms reduced the abundance of communities that Thomsen and Wernberg categorized as ‘mainly infauna’, while increasing the abundance of communities categorized as ‘mainly epifauna’. Second, they showed that the impacts of macroalgal blooms on ‘mainly infauna’ communities increased with algal density in experiments that included multiple levels of algal density. These findings, as well as the conclusions that Thomsen & Wernberg (2015) draw from them, are largely consistent with our own expectations and interpretations. However, we also feel that some caution is required when interpreting the results of their analyses. Ideally, syntheses comparing the effects of ecological phenomena on different subgroups would rely on a set of studies that had been designed for this specific aim. This is rarely possible, so synthetic works often rely on disparate studies that focus on the individual groups. None of the studies in the dataset analyzed by Thomsen & Wernberg (2015) overtly compared the effects of macroalgal blooms on infauna or epifauna, and only a proportion of them explicitly focused on either of these groups individually. The sampling methods used by many studies in this dataset are likely to capture both infauna and epifauna living on the surface of the sediment, macroalgae, or other vegetation. Thus, classifying the communities investigated in these studies as ‘mainly infauna’ or ‘mainly epifauna’ requires subjective decisions that are difficult to make, and prone to error. We elected not to present a comparison of epifaunal and infaunal invertebrate communities in Lyons et al. (2014) because of these weaknesses, and the need to present a concise, coherent manuscript. Nevertheless, examining whether blooms affect infauna and epifauna differently is a useful and interesting exercise. Our dataset is likely the best currently available to make the comparison, and responding to Thomsen & Wernberg (2015) provides us with the opportunity to present our own broader analysis of the effects of macroalgal blooms on benthic marine invertebrates. Our analysis examined the effects of macroalgal blooms on both the abundance and species richness of benthic marine invertebrates, as measured by both experiments and observational studies (below). Following the methods of Lyons et al. (2014), we conducted a mixed-model meta-analysis for invertebrate abundance and another for invertebrate species richness. We included study type (experimental vs. observational), invertebrate functional group (‘mainly’ infauna vs. epifauna, see Supporting information), and their interaction as explanatory variables in the analysis. This allowed us to directly assess the hypothesis that the observed effects of blooms and mats depend on each of these variables. For invertebrate abundance, there was very little support for the inclusion of the interaction term (z = 0.518, P = 0.604), so we present the results from a simplified model. Our analysis suggests that the impacts of blooms differ between epifauna and infauna (Fig. 1, z = −2.596, P = 0.009) and that observational studies tend to find effects that are more negative than experimental studies (Fig. 1, z = −2.527, P = 0.012). Like Thomsen & Wernberg (2015), we found a negative effect of blooms on infauna, and a positive effect of blooms on epifauna in experiments, but the magnitude of our summary effect size estimates was smaller, and the negative effect on infauna was nonsignificant. These disparities may be partially due to differences in the specific data included in each of the estimates. In several instances, Thomsen & Wernberg (2015) came to different conclusions about whether studies focused primarily on epifauna or infauna than we did. They also excluded some studies we chose to include in our analysis, and they used different data than we did when estimating the effect observed in some individual studies (see Supporting information). Differences in how meta-analyses were conducted may also contribute to the disparity between our results and those of Thomsen & Wernberg (2015). We used variance-weighted mixed models and used pooled estimates of the within-subgroup variance (recommended for subgroup analyses when sample sizes are relatively small, Borenstein et al., 2009). Thomsen & Wernberg (2015) used separate, unweighted random-effects models for infauna and epifauna. They included multiple effect sizes from some of the multifactorial experiments in the study set. We always estimated a single effect size from multifactorial experiments. These differences affect the weight given to each study in the estimation of the effect sizes: Our approach gives less weight to studies with more uncertain effect sizes; their approach gives equal weights to all studies, except those for which they included multiple effect sizes. For invertebrate richness, our analysis found a significant interaction between study type and invertebrate functional group affecting the observed effects of macroalgal blooms (z = −2.158, P = 0.031). Both experimental and observational studies found nonsignificant positive effects of blooms on epifaunal species richness (Fig. 2). Both also found significant negative effects on infaunal species richness, but the effects observed in observational studies were more severe (Fig. 2). Like Thomsen & Wernberg (2015), we found significant residual heterogeneity among studies (abundance: Q = 1071.9, P < 0.001; richness: Q = 170.8, P < 0.001), indicating that the effects of blooms are inconsistent, even after differences between subgroups (e.g., experiments examining epifauna, observational studies examining infauna) have been taken into account. There are many potential explanations for residual among-study heterogeneity, including variation in algal density, study duration, the size/extent of the bloom or mat, and methodological differences in how response variables were measured. It is also likely that both epifaunal and infaunal communities vary in their sensitivity to blooms. Members of both groups vary in their ability to tolerate anoxia and hydrogen sulfide (Riedel et al., 2012). In addition, some infaunal species will move out of the sediment and into the overlying macroalgal mat when a bloom occurs (e.g., Österling & Pihl, 2001). This repositioning may help them to avoid hypoxic conditions while remaining within a bloom-affected area. It may also cause infaunal species to be collected and counted as epifauna in some studies. Conversely, some sessile epifaunal organisms are smothered by macroalgal accumulations, and epifauna living among the algae may die when rotting blooms induce hypoxia or release hydrogen sulfide. Thus, assemblages composed of different proportions of sensitive and resistant organisms will respond differently. Thomsen & Wernberg (2015) consider differences between epifauna and infauna to be a ‘devil in the detail’ of Lyons et al.'s (2014) analysis comparing how communities of invertebrates, fish, bacteria, microalgae, macroalgae, seagrasses, or mixtures (of invertebrates and algae) respond to macroalgal blooms. However, pooling data from ‘sensitive’ and ‘resistant’ organisms within epifaunal and infaunal communities cancels out potentially important contrasts in a similar way that pooling studies of epifaunal and infaunal invertebrate communities does. We point this out because the existence of this ‘devil in the detail’ of analyses intended to ‘promote more nuanced conclusions’ about the effects of blooms illustrates the tension inherent in ecological synthesis and raises important questions. With ecological processes and outcomes contingent on so many factors, which differences do we pay attention to? In the context of ecological meta-analyses, which effects can be meaningfully combined? The answers should be determined by the ecological question or management problem of interest, but are likely to be influenced by the availability of sufficient data, as well as the opinions and interests of the researcher. For instance, we chose not to calculate an overall effect size synthesizing all of the community-level responses in our study because we question the meaningfulness of an effect size that includes studies of disparate responses such as species richness, organism abundance, and benthic community respiration. Others have estimated such effect sizes, and they might argue they are both meaningful and useful. The density, size, and duration of macroalgal blooms and mats are likely to play a very important role in determining the nature and magnitude of their effects. Nearly two decades ago, Raffaelli et al. (1998) suggested that much of the variation in blooms’ effects is due to differences in the intensity and size of macroalgal blooms and that rigorous definition of these factors would improve our understanding by facilitating comparisons between blooms. However, many studies of blooms’ effects lack detailed information about algal densities and the spatial extent of blooms, and when information is available, it is recorded in such a way that comparisons are difficult (e.g., measures of % cover, wet mass per area, dry mass per area, thickness of the algal mat for measures of algal density) (Lyons et al., 2014). The paucity of data prevented us from conducting a broad analysis of how these factors alter the impacts of blooms on marine ecosystems, and is reflected in the fact that Thomsen & Wernberg (2015) are forced to rely on just four studies in their second analysis. Their results provide an indication that the positive effect of macroalgal blooms on epifaunal abundance is larger at higher algal densities. However, it is unclear whether the increasing effect of blooms with increased algal density is linear, nonlinear, or part of a more complex, nonmonotonic relationship. This question, along with the broader one of how algal density alters blooms’ other effects, will be answered more easily if researchers record algal density information (preferably in wet or dry mass per unit area) or directly study this specific question more often. Despite our minor cautions, concerns, and preference for our own methodology, we largely agree with the decisions, findings, and interpretations of Thomsen & Wernberg (2015), and we are glad they took the initiative to look more deeply into the data we compiled. We feel that their analyses, and the additional analyses we present above, are interesting and potentially useful to ecosystem managers. However, these analyses do not alter our interpretation of blooms’ effects on invertebrate communities: If we combine all of the available evidence, it appears that blooms have a negative effect, but that effect is highly variable (Lyons et al., 2014). Nor do we see variation due to different invertebrate functional groups or sensitivities, algal abundance, or other untested factors as ‘devils in the details’. This term has pejorative connotations: referring to a troublesome part of a larger whole, or a detail with potential to mar something larger if not handled correctly. We have always seen such factors as opportunities for future work. And we discussed many of them in Lyons et al. (2014). The goal of meta-analysis is to synthesize and summarize in order to describe general patterns, and meta-analysts must ‘average over’ many of the details that make studies different from one another to accomplish this goal. Rather than worry about devils in details when we use meta-analysis, it is more important that we treat the generalizations they provide appropriately, remembering that ‘There are no whole truths: all truths are half-truths. It is trying to treat them as whole truths that plays the devil’ (Whitehead, 1954). The research leading to these results was supported by funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under Grant Agreement No. 266445 for the project Vectors of Change in Oceans and Seas Marine Life, Impact on Economic Sectors (VECTORS), which was coordinated by Melanie Austen. DL was also supported by a postdoctoral fellowship from the NSERC Canadian Aquatic Invasive Species Network (CAISN). PS and AQ were supported in part by the Natural Environment Research Council and Department for Environment, Food and Rural Affairs [grant number NE/L003279/1, Marine Ecosystems Research Programme]. Data S1. Supplemental methods, data, and references. Table S1. Effect sizes (Hedge's g) and variances used in the analysis of macroalgal blooms and mats effects on invertebrate abundance. Table S2. Effect sizes (Hedge's g) and variances used in the analysis of macroalgal blooms and mats effects on invertebrate species richness. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Effective management and the maintenance of marine ecosystem services rely on a capacity to predict the ecological consequences of environmental change and potential management interventions (Chapter 1). Making these predictions is difficult because anthropogenic stressors do not produce uniform or consistent impacts on biodiversity and ecosystem functioning. Rather, their effects can be modified by a variety of factors that cause them to vary among locations and different points in time. Thus, the effectiveness of actions taken to manage environmental problems is likely to vary in a similar way: interventions that are sufficient to mitigate a stressor's impacts in one situation might be inadequate or excessive in others. Both sound science and efficient management require us to recognise that spatial and temporal variability are inherent to natural systems, and that the ecosystem complexity places inherent limits on our ability to predict future ecological conditions. However, many of the causes of this variability have been identified. Careful consideration of these factors will enhance scientific understanding, improve ecological prediction and enhance our efforts to optimise marine policy and management by reducing the uncertainty associated with the effects of stressors.

AimBiological invasions are among the main threats to biodiversity. To promote a mechanistic understanding of the ecological impacts of non-native seaweeds, we assessed how effects on resident organisms vary according to their trophic level.LocationGlobal.MethodsWe performed meta-analytical comparisons of the effects of non-native seaweeds on both individual species and communities. We compared the results of analyses performed on the whole dataset with those obtained from experimental data only and, when possible, between rocky and soft bottoms.ResultsMeta-analyses of data from 100 papers revealed consistent negative effects of non-native seaweeds across variables describing resident primary producer communities. In contrast, negative effects of seaweeds on consumers emerged only on their biomass and, limited to rocky bottoms, diversity. At the species level, negative effects were consistent across primary producers' response variables, while only the survival of consumers other than herbivores or predators (e.g. deposit/suspension feeders or detritivores) decreased due to invasion. Excluding mensurative data, negative effects of seaweeds persisted only on resident macroalgal communities and consumer species survival, while switched to positive on the diversity of rocky-bottom consumers. However, negative effects emerged for biomass and, in rocky habitats, density of consumers other than herbivores or predators.Main conclusionsOur results support the hypothesis that seaweeds' effects on resident biodiversity are generally more negative within the same trophic level than on higher trophic guilds. Finer trophic grouping of resident organisms revealed more complex impacts than previously detected. High heterogeneity in the responses of some consumer guilds suggests that impacts of non-native seaweeds at higher trophic levels may be more invader- and species-specific than competitive effects at the same trophic level. Features of invaded habitats may further increase variability in seaweeds' impacts. More experimental data on consumers' response to invasion are needed to disentangle the effects of non-native seaweeds from those of other environmental stressors.

Eutrophication, coupled with loss of herbivory due to habitat degradation and overharvesting, has increased the frequency and severity of macroalgal blooms worldwide. Macroalgal blooms interfere with human activities in coastal areas, and sometimes necessitate costly algal removal programmes. They also have many detrimental effects on marine and estuarine ecosystems, including induction of hypoxia, release of toxic hydrogen sulphide into the sediments and atmosphere, and the loss of ecologically and economically important species. However, macroalgal blooms can also increase habitat complexity, provide organisms with food and shelter, and reduce other problems associated with eutrophication. These contrasting effects make their overall ecological impacts unclear. We conducted a systematic review and meta-analysis to estimate the overall effects of macroalgal blooms on several key measures of ecosystem structure and functioning in marine ecosystems. We also evaluated some of the ecological and methodological factors that might explain the highly variable effects observed in different studies. Averaged across all studies, macroalgal blooms had negative effects on the abundance and species richness of marine organisms, but blooms by different algal taxa had different consequences, ranging from strong negative to strong positive effects. Blooms' effects on species richness also depended on the habitat where they occurred, with the strongest negative effects seen in sandy or muddy subtidal habitats and in the rocky intertidal. Invertebrate communities also appeared to be particularly sensitive to blooms, suffering reductions in their abundance, species richness, and diversity. The total net primary productivity, gross primary productivity, and respiration of benthic ecosystems were higher during macroalgal blooms, but blooms had negative effects on the productivity and respiration of other organisms. These results suggest that, in addition to their direct social and economic costs, macroalgal blooms have ecological effects that may alter their capacity to deliver important ecosystem services.

Background: Anthropogenic activities are believed to have caused an increase in the magnitude, frequency, and extent of macroalgal blooms in marine and estuarine environments. These blooms may contribute to declines in seagrasses and non-blooming macroalgal beds, increasing hypoxia, and reductions in the diversity of benthic invertebrates. However, they may also provide other marine organisms with food and habitat, increase secondary production, and reduce eutrophication. The objective of this systematic review will be to quantify the positive and negative impacts of anthropogenically induced macroalgal blooms in order to determine their effects on ecosystem structure and functioning, and to identify factors that cause their effects to vary.Methods: We will search a number of online databases to gather empirical evidence from the literature on the impacts of macroalgal blooms on: (1) species richness and other univariate measures of biodiversity; (2) productivity and abundance of algae, plants, and animals; and (3) biogeochemical cycling and other flows of energy and materials, including trophic interactions and cross-ecosystem subsidies. Data from relevant studies will be extracted and used in a random effects meta-analysis in order to estimate the average effect of macroalgal blooms on each response of interest. Where possible, sub-group analyses will be conducted in order to evaluate how the effects of macroalgal blooms vary according to: (1) which part of the ecosystem is being studied (e.g. which habitat type, taxonomic group, or trophic level); (2) the size of blooms; (3) the region in which blooms occurred; (4) background levels of ecosystem productivity; (5) physical and chemical conditions; (6) aspects of study design and quality (e.g. lab vs. field, experimental vs. observational, degree of replication); and (7) whether the blooms are believed to be anthropogenically induced or not.

One of the most influential forms of biological invasions is that of invasive ecosystem engineers, species that affect other biota via alterations to the abiotic environment. Such species can have wide-reaching consequences because they alter ecosystems and essentially “change the rules of existence” for a broad suite of resident biota. They thus affect resources or stressors that affect other organisms.The objective of this systematic review will be to quantify the positive and negative impacts of invasive ecosystem engineers on ecosystem structure and functioning, and to identify factors that cause their effects to vary.

Background: Biological invasions are among the most severe threats to marine biodiversity. The impacts of introduced seaweeds on native macroalgal assemblages have been thoroughly reviewed. In contrast, no attempt has been made to synthesize the available information on the effects of exotic seaweeds on other trophic levels. In addition, it has not been clarified whether the effects of introduced seaweeds on native assemblages vary according to background physical and biological conditions.Methods: This protocol provides details of our proposed method to carry out a systematic review aiming to identify and synthesize existing knowledge to answer the following primary questions: a) how does the impact of the presence of exotic seaweeds on native primary consumers (across trophic levels) compare in magnitude and extent to that observed on native primary producers (same trophic level)?; b) does the intensity of the effects of the presence of exotic seaweeds on native benthic ecosystems vary along a gradient of human disturbance (i.e. from urban/industrial areas to extra-urban areas to pristine areas)?

Note: William Bromer is the editor of Ecology 101. Anyone wishing to contribute articles or reviews to this section should contact him at the Department of Natural Sciences, University of St. Francis, 500 N. Wilcox, Joliet, IL 60435, (815) 740-3467, E-mail: wbromer@stfrancis.edu. This paper is the product of a seminar led by JC Cahill in response to a request by many graduate students and post-docs in our department to teach effective writing strategies. Rather than go over the mechanics of writing, JC introduced the concept of “pitch” and its importance in scientific writing. Many students requested a text version of his presentation, which was ultimately transformed into the current document. In this paper, we define and present “pitch,” and layout guidelines for bringing pitch to the two most common types of scientific writing, papers and grant applications. We suggest that once students have learned the mechanics of writing, the single most important thing students can do to write effectively is to find a clear pitch. A decade ago, the “top” ecological journals tended to be those that focused on integrative papers, allowed the researcher to develop arguments, and commonly involved multiple studies in single papers. Many established researchers looked derisively at those scientists who published LPUs “Least Publishable Units,” rather than telling a more complete story. Those scientists who decried the LPU approach also sat on the editorial boards, grants panels, and search committees, and today, most of our top-ranked journals increasingly focus on publishing short papers. Whether one likes it or not, we live in the age of the LPU and the call is out for short, focused papers. One of the best ways for students to increase the likelihood of getting their papers published in top journals and having their grant applications funded is to learn to write with “pitch.” Writing with pitch requires a unique set of skills, the most important of which is having a story and not deviating from the narrative. This goes against the instinct of the scientist, as we typically want to explain every implication, caveat, and limitation of what we do. These tendencies will result in much agony. Here, we describe some alternatives. None of what we discuss below, however, will help unless a good research question has been asked, a solid study design developed, and data properly collected, analyzed, and interpreted. With students in mind, we define pitch, and outline tips for finding pitch for the two most common types of scientific writing, papers and grant applications. “to attempt to promote or sell, often in a high-pressure manner. (American Heritage Dictionary 2000) “promotion by means of an argument and demonstration.” (WordNet, Princeton University 2010, available online)1 When one writes a great novel, it is fine (perhaps even preferred) to have the readers connect the dots in the story; to have them use some brainpower to understand how the pieces of the book connect to each other and to larger issues. This form of writing will typically fail in science at one of two stages: (1) peer review, and, if that is somehow passed, (2) use by colleagues. Professors are busy. Really busy. Professors also tend to be editors, reviewers, and researchers—the people who will judge written work at every stage, both for suitability of publication or funding, and less explicitly, for whether it has any impact in the field. When it comes to developing pitch, there are two things that are likely going to reduce success: A high-pressured “sell” won't work in scientific writing, at least not for peer-reviewed writing. Scientists tend to be independent, strong-willed people. We don't like to be told what to believe. Instead, we like to be shown what is likely true. A paper without pitch won't work, as we don't have time to figure out what you mean to say, and why it is important. If you don't lay these things out right in front of us, we are not likely to give your paper or grant application a positive review, nor are we likely to use your work as we prepare our own manuscripts. Thus the right pitch in ecology has to navigate these two constraints rising like mountains of rejection; too much of a “sell” and reviewers get grumpy; too little, and reviewers get grumpy. Grumpy reviewers result in rejection. The middle ground, what you should be aiming for, we will call the “valley of happiness.” So what does this valley look like? In that world, single papers will typically have a single story. The research objectives are an obvious extension of the introduction. The research methods are succinct, and their connection to the research objectives are clear. The results are short and directly answer the research questions. The most important information comes first. The discussion is brief and focused, with clear topic sentences. It will read as a coherent whole. A key aspect of a well-written paper with a solid pitch is that someone reading ANY section of the paper should have a clear understanding of the main objectives of the paper, even without reading any other parts of the paper. Or put another way, your pitch is your research question, and this should be returned to in every part of the paper. Importantly, the wording of your research questions in your paper rarely would be the wording you used in your original research proposal. You must modify your pitch as your project develops, and as your interpretation changes. Below, we provide some suggestions on how to develop your pitch in scientific writing, the first of which is a need to understand who your audience is, and to tailor your pitch to their needs and expectations. The most common types of scientific writing are (1) peer-reviewed papers, and (2) grant applications. Each has a different goal, and different audiences. We do not write these documents for ourselves, instead we write them for others. Once you realize this, it becomes obvious that you need to write according to what other people want to see and need to know. An effective pitch is tailored to your audience. When we write a paper, we hope the ultimate audience will be other scientists, in fields related to our own. However, to reach that audience we first have to satisfy an audience made up of specialist peer reviewers and editors. Reviewers are typically specialists in your field who will focus most on the details of your study. Prior to reading your manuscript, some reviewers might think positively of your prior work, some will think negatively, and others won't have any idea who you are. This doesn't mean they are unable to fairly review your manuscript, but the peer review is a socio-political process, and you need to be aware of this. Reviewers will want to see that you both understand what research has already been done in your field, and that your research will truly make advances. It is critical that you develop the context for your research questions from a broad literature, and not focus exclusively on work done in your lab. Similarly, your impact needs to be on the field as a whole, not just your lab. The handling editor is a secondary audience with some unique concerns. They tend to be strongly influenced by the quality of the reviews, but they will also judge a submitted manuscript based upon their own read of the paper. Believe it or not, split decisions among reviews are the exception, not the rule. Bad papers are obvious, as are outstanding papers. As a result, it is very easy for the handling editor to reject or accept these papers without needing to fret too much about the decision. When split decisions do occur, the handling editor judges the reviews and weighs their own feelings about the potential impacts of the work on the field as a whole. Here, pitch is critical. The handling editor is generally looking for a reason to reject, not accept. If the strengths of your work are hidden, then you had better hope that you received two outstanding reviews; otherwise don't hold your breath. Historically, handling editors used the “reject and resubmit” option when they and the reviewers felt that the underlying data were strong, but poorly presented (e.g., bad pitch) and/or incorrectly analyzed and interpreted. Some journals are encouraging handling editors to use this option less frequently and instead to reject papers outright. This will put increased emphasis on getting one's pitch right in the first submission. Many journals frequently reject papers without review, and in such cases, the Editor-in-Chief may be an important audience. Typically, they will focus on the more general aspects of the paper presented in the abstract and cover letter. Satisfying the Editor-in-Chief requires stating your pitch in clear, general terms and making sure that all parts of your writing relate to your central ideas. The goal of a grant application is simple: to get money for future research. Grant applications need to be very well written (sloppy writing suggests careless research). Your pitch will lead the reader to a specific conclusion, one for which there is no answer, and thus money is needed to solve it. There are no shortcuts here; you must be very knowledgeable about your field, understand how the pieces fit together, and identify real holes in understanding. The audience for a grant application depends upon the specific grant, but will generally consist of specialists in your field (reviewers) and generalists in ecology (some panel members). However, many grant panels also include stakeholder representatives and/or administrators. Within a single grant you will need several different pitches, each tailored to these different audiences. Specialists are reviewers with objectives similar to those described for papers. They focus on the quality and originality of the science. Panel members are usually scientists who may not be from your specific field. This group will focus most on the general objectives of your study, and the quality of the reviews, so obviously having strong reviews will help you. Doing your research on likely panel members makes sense, as there will be some opportunities for you to use examples from the panel member's areas of expertise. You do this, not to pander, but to frame your objectives partly in a context that they are already familiar with. One must make it easy for reviewers to understand why your work is important. Stakeholders are a group of readers who will focus most on their own objectives, and whether yours match theirs. You need to be certain you are using the language they are used to, and that you link your ideas to the specific objectives they list in the call for proposals. You are unlikely to convince them to fund great ideas unless you show very explicitly in your pitch that your work meets their goals. This form of writing needs to be plain and succinct. Pay attention to the front and back ends of your grant application —the summary and conclusion. These sections are typically targeted to stakeholders. Whether you are writing a paper or a grant application, you need to convince all of your reviewers of the great merit in your elegant ideas in a single document of limited length. How? First, have elegant ideas. Second, write well. Third, have a sense of what your pitch is, and how it will interest the reviewers (and thus likely influence other scientists too). Aside from this, you need also to pay attention to how you reference other researchers. Researchers have egos, and they are not usually small. If you work in a relatively small field, you can likely identify a specific person (or laboratory) that will provide a review, and you would be crazy not to include their work in the development of your story. If you need to critique their work, cast that critique in a way that highlights the positives of their contributions, even when you disagree with other aspects of their work. A pitch should not antagonize your reviewers, nor should it be biased in presentation of material. Be sure to be very balanced in your writing, because you won't know who all of your reviewers are. You want to be certain not to unintentionally snub one faction of researchers through omission and/or sloppy writing that conveys critique when you don't intend it. This does not mean you need to cite everyone; instead, you must show balance. Trying to add pitch at the end of constructing a document will be a frustrating experience for you, your co-authors, and your supervisor. The key is to construct your document in a way that lets you integrate your pitch into every section from the beginning. Here we focus on developing pitch for papers (see Table 1 for guidelines on specific sections). There are at least two common approaches to constructing a paper. We call the first “Intelligent Design.” This is the traditional approach of working from front to back that most students initially use, as this is what is typically taught in school. In conversations with colleagues, this approach appears to be used relatively rarely by scientists. Nonetheless, here is the idea: First, make a clear outline of the story from front to back. This outline forms the skeleton of your paper. The backbone of this skeleton is your well-crafted research question, and it connects to every other part of the skeleton. Next, add guts and muscle. These are the essential references that the intended audience needs to understand your research question; the methods needed to answer that question; the data and figures needed to answer the question; and the conclusions that immediately emerge from the answers. It is absolutely essential that every single thing you add be directly connected to the skeleton. Avoid constructing any vestigial organs, tumors, or unsightly growths that will need to be excised. Regularly ask yourself whether your creature could still live if you removed certain bits and pieces. If the answer is yes, remove them. Remember, the goal of the paper is NOT to tell the audience everything you know. Instead, it is to get your paper published and have it be cited. So, just because you spent many hours of hard labor collecting certain data does not justify their inclusion in this paper. Also remember that you are not trying to create the most attractive creature on the planet—just one that is functional enough to get published and cited. Perfectionism reduces research productivity (Sherry et al. 2010), and any time you spend on the bells and whistles (e.g., wonderfully elegant writing) is time that is neither needed to meet your goals, nor time you can spend on your next paper or grant application. As scientists we disseminate our findings through published papers with the goals of being cited, influencing policy, shifting public opinion, or establishing oneself in a field. Importantly, the goal of a paper is NOT to produce the “best” written paper possible. Instead you should aim for a paper that is written well enough for your target journal. Unlike grants, we typically have choices about the journals to which we choose to submit a paper. The choice has importance, and affects our ability to achieve our short-term goals, as well as the potential impact of a paper on longer-term career development. It is important to recognize that the choice of venue influences the necessary pitch and the relative importance of your cover letter. In brief, the broader the audience of the journal (e.g., Science vs. American Fern Journal), the more general your pitch needs to be. The quality of the science needs to be strong in all cases, but you need to be able to relate your work to increasing numbers of nonspecialists as you move from field-specific to broader-impact journals. It is critical that you structure your entire manuscript accordingly; know your audience and write for them. Working on a paper or grant application with your supervisor can be a (mutually) frustrating experience. Learning how to work effectively with co-authors is an important part of scientific writing. You can help to minimize frustrating your supervisor by working with them as needed, rather than as desired. In other words, go to them when you run into a problem that you can't solve for yourself. If you are going to be a successful scientist, you need to learn to work independently, so don't turn to your supervisor because they would do something faster. Also, do not waste your supervisor's time with first drafts, poorly constructed verbiage, or manuscripts with 20 figures and no focus. When it comes to receiving feedback on your manuscript, understanding why your supervisor does certain things can help to limit your frustration. For example, try not to be offended when your supervisor edits part of your paper, and sends it back without reading the rest. As described above, we typically write in a logical sequence, and if one section needs to be completely gutted, time spent on any other section will be time wasted. Also, do not be surprised when supervisors contradict themselves in subsequent drafts. Typically they do this because as the story changes, so too do the needed bits. This is no different from you cutting and repasting. It is part of the writing process. Of course, other times they do it just because it's fun. You write in the academic world of today, not that of the last century. As such, you will be expected to produce more, shorter, papers than previous generations of ecologists. Staying focused on your pitch will help make these papers better, and easier to write. Remember your goals. At some point, you need to submit your paper. Your goal is not perfection, it is simply for your paper to be good enough. Learn to know where that bar is. Similarly, grant applications have deadlines. Writing a clear, cogent argument as to why your research deserves funding demands pitch. Make pitch your path through all the rubble.