Modeling fisheries and carbon sequestration ecosystem services under deep uncertainty in the ocean twilight zone.

Mesopelagic fishes are a vital component of the biological carbon pump and are, to date, largely unexploited. In recent years, there has been an increased interest in harvesting the mesopelagic zone to produce fish feed for aquaculture. However, great uncertainties exist in how the mesopelagic zone interacts with the climate and food webs, presenting a dilemma for policy. Here, we investigate the consequences of potential policies relating to mesopelagic harvest quotas with a dynamic social-ecological modeling approach, combining system dynamics and global sensitivity analyses informed by participatory modeling. Our analyses reveal that, in simulations of mesopelagic fishing scenarios, uncertainties about mesopelagic fish population dynamics have the most pronounced influence on potential outcomes. The analysis also shows that prioritizing the development of the fishing industry over environmental protection would lead to a significantly higher social cost of climate change to society. Given the large uncertainties and the potential large impacts on oceanic carbon sequestration, a precautionary approach to developing mesopelagic fisheries is warranted.

Interactive effects of extreme temperature and a widespread coastal metal contaminant reduce the fitness of a common tropical copepod across generations.

Tropical coastal areas are increasingly exposed to temperature extremes from marine heatwaves and contaminants from anthropogenic activities. The interactive effects of these environmental changes on marine life are understudied. We investigated the direct and cross-generational effects of copper (Cu) on F0 and F1 generations of the common tropical copepod Pseudodiaptomus annandalei under extreme temperatures (30 and 34 °C). In F0, Cu exposure reduced survival and nauplii production; these patterns were more pronounced at 34 °C and in females. F0 Copepods produced more faecal pellets at 34 °C than 30 °C, indicating a higher energetic demand. In F1, the number of F1 adults was lower in CuF0 and at 34 °C. Cu-exposed F0 produced larger adult F1, while exposure to 34 °C resulted in smaller adult F1. Our results show that tropical copepods are highly vulnerable to the interactive effects of contaminants and extreme temperatures.

Author Correction: Extreme temperature impairs growth and productivity in a common tropical marine copepod.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Extreme temperature impairs growth and productivity in a common tropical marine copepod.

Shallow, tropical marine ecosystems provide essential ecosystem goods and services, but it is unknown how these ecosystems will respond to the increased exposure to the temperature extremes that are likely to become more common as climate change progresses. To address this issue, we tracked the fitness and productivity of a key zooplankton species, the copepod Pseudodiaptomus annandalei, acclimated at two temperatures (30 and 34 °C) over three generations. 30 °C is the mean temperature in the shallow water of the coastal regions in Southeast Asia, while 34 °C simulated a temperature extreme that occurs frequently during the summer period. For each generation, we measured the size at maturity and reproductive success of individuals. In all three generations, we found strong negative effects of warming on all measured fitness-related parameters, including prolonged development time, reduced size at maturity, smaller clutch sizes, lower hatching success, and reduced naupliar production. Our results suggest that P. annandalei are already exposed to temperatures that exceed their upper thermal optimum. Increased exposure to extreme temperatures may reduce the abundance of these tropical marine copepods, and thus reduce the availability of resources to higher trophic levels.

Archived DNA reveals fisheries and climate induced collapse of a major fishery.

Fishing and climate change impact the demography of marine fishes, but it is generally ignored that many species are made up of genetically distinct locally adapted populations that may show idiosyncratic responses to environmental and anthropogenic pressures. Here, we track 80 years of Atlantic cod (Gadus morhua) population dynamics in West Greenland using DNA from archived otoliths in combination with fish population and niche based modeling. We document how the interacting effects of climate change and high fishing pressure lead to dramatic spatiotemporal changes in the proportions and abundance of different genetic populations, and eventually drove the cod fishery to a collapse in the early 1970s. Our results highlight the relevance of fisheries management at the level of genetic populations under future scenarios of climate change.

Forecasted coral reef decline in marine biodiversity hotspots under climate change.

Coral bleaching events threaten coral reef habitats globally and cause severe declines of local biodiversity and productivity. Related to high sea surface temperatures (SST), bleaching events are expected to increase as a consequence of future global warming. However, response to climate change is still uncertain as future low-latitude climatic conditions have no present-day analogue. Sea surface temperatures during the Eocene epoch were warmer than forecasted changes for the coming century, and distributions of corals during the Eocene may help to inform models forecasting the future of coral reefs. We coupled contemporary and Eocene coral occurrences with information on their respective climatic conditions to model the thermal niche of coral reefs and its potential response to projected climate change. We found that under the RCP8.5 climate change scenario, the global suitability for coral reefs may increase up to 16% by 2100, mostly due to improved suitability of higher latitudes. In contrast, in its current range, coral reef suitability may decrease up to 46% by 2100. Reduction in thermal suitability will be most severe in biodiversity hotspots, especially in the Indo-Australian Archipelago. Our results suggest that many contemporary hotspots for coral reefs, including those that have been refugia in the past, spatially mismatch with future suitable areas for coral reefs posing challenges to conservation actions under climate change.

Quaternary coral reef refugia preserved fish diversity.

The most prominent pattern in global marine biogeography is the biodiversity peak in the Indo-Australian Archipelago. Yet the processes that underpin this pattern are still actively debated. By reconstructing global marine paleoenvironments over the past 3 million years on the basis of sediment cores, we assessed the extent to which Quaternary climate fluctuations can explain global variation in current reef fish richness. Comparing global historical coral reef habitat availability with the present-day distribution of 6316 reef fish species, we find that distance from stable coral reef habitats during historical periods of habitat loss explains 62% of the variation in fish richness, outweighing present-day environmental factors. Our results highlight the importance of habitat persistence during periods of climate change for preserving marine biodiversity.

Combining food web and species distribution models for improved community projections.

The ability to model biodiversity patterns is of prime importance in this era of severe environmental crisis. Species assemblage along environmental gradients is subject to the interplay of biotic interactions in complement to abiotic filtering and stochastic forces. Accounting for complex biotic interactions for a wide array of species remains so far challenging. Here, we propose using food web models that can infer the potential interaction links between species as a constraint in species distribution models. Using a plant-herbivore (butterfly) interaction dataset, we demonstrate that this combined approach is able to improve species distribution and community forecasts. The trophic interaction network between butterfly larvae and host plant was phylogenetically structured and driven by host plant nitrogen content allowing forecasting the food web model to unknown interactions links. This combined approach is very useful in rendering models of more generalist species that have multiple potential interaction links, where gap in the literature may occur. Our combined approach points toward a promising direction for modeling the spatial variation in entire species interaction networks.

Spatiotemporal SNP analysis reveals pronounced biocomplexity at the northern range margin of Atlantic cod Gadus morhua.

Accurate prediction of species distribution shifts in the face of climate change requires a sound understanding of population diversity and local adaptations. Previous modeling has suggested that global warming will lead to increased abundance of Atlantic cod (Gadus morhua) in the ocean around Greenland, but the dynamics of earlier abundance fluctuations are not well understood. We applied a retrospective spatiotemporal population genomics approach to examine the temporal stability of cod population structure in this region and to search for signatures of divergent selection over a 78-year period spanning major demographic changes. Analyzing >900 gene-associated single nucleotide polymorphisms in 847 individuals, we identified four genetically distinct groups that exhibited varying spatial distributions with considerable overlap and mixture. The genetic composition had remained stable over decades at some spawning grounds, whereas complete population replacement was evident at others. Observations of elevated differentiation in certain genomic regions are consistent with adaptive divergence between the groups, indicating that they may respond differently to environmental variation. Significantly increased temporal changes at a subset of loci also suggest that adaptation may be ongoing. These findings illustrate the power of spatiotemporal population genomics for revealing biocomplexity in both space and time and for informing future fisheries management and conservation efforts.

Horizontal, but not vertical, biotic interactions affect fine-scale plant distribution patterns in a low-energy system.

Studies of species range determinants have traditionally focused on abiotic variables (typically climatic conditions), and therefore the recent explicit consideration of biotic interactions represents an important advance in the field. While these studies clearly support the role of biotic interactions in shaping species distributions, most examine only the influence of a single species and/or a single interaction, failing to account for species being subject to multiple concurrent interactions. By fitting species distribution models (SDMs), we examine the influence of multiple vertical (i.e., grazing, trampling, and manuring by mammalian herbivores) and horizontal (i.e., competition and facilitation; estimated from the cover of dominant plant species) interspecific interactions on the occurrence and cover of 41 alpine tundra plant species. Adding plant-plant interactions to baseline SDMs (using five field-quantified abiotic variables) significantly improved models' predictive power for independent data, while herbivore-related variables had only a weak influence. Overall, abiotic variables had the strongest individual contributions to the distribution of alpine tundra plants, with the importance of horizontal interaction variables exceeding that of vertical interaction variables. These results were consistent across three modeling techniques, for both species occurrence and cover, demonstrating the pattern to be robust. Thus, the explicit consideration of multiple biotic interactions reveals that plant-plant interactions exert control over the fine-scale distribution of vascular species that is comparable to abiotic drivers and considerably stronger than herbivores in this low-energy system.

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling.

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.

Do pseudo-absence selection strategies influence species distribution models and their predictions? An information-theoretic approach based on simulated data.

BACKGROUND: Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a) real absences b) pseudo-absences selected randomly from the background and c) two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA) or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. RESULTS: Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors) was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97), and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. CONCLUSION: If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have limited fit.

Spectral measures and mixed models as valuable tools for investigating controls on land surface phenology in high arctic Greenland.

BACKGROUND: Changes in land surface phenology are of major importance to the understanding of the impact of recent and future climate changes in the Arctic. This paper presents an extensive study from Zackenberg Ecological Research Operations (ZERO) where snow melt, climate and growing season characteristics of six major high arctic vegetation types has been monitored during 1999 to 2005. We investigate the growth dynamics for dry, mesic and wet types using hand held measurements of far red normalised difference vegetation index (NDVI-FR) and generalized additive mixed models (GAMM). RESULTS: Snow melt and temperature are of major importance for the timing of the maximum growth as well as for the seasonal growth. More than 85% of the variance in timing of the maximum growth is explained by the models and similar for the seasonal growth of mesic and wet vegetation types. We find several non-linear growth responses to the environmental variables. CONCLUSION: We conclude that the uses of GAMMs are valuable for investigating growth dynamics in the Arctic. Contrary to several other studies in the Arctic we found a significant decreasing trend of the seasonally integrated NDVI-FR (SINDVI) in some vegetation types. This indicates that although greening might occur wide-spread in the Arctic there are variations on the local scale that might influence the regional trends on the longer term.