Assessing cumulative impacts of human-induced pressures on reef and sandbank habitats and associated biotopes in the northeastern Baltic Sea.

Marine ecosystems are impacted by multiple individual and combined anthropogenic pressures. We used meta-analysis and data-driven PlanWise4Blue decision support tool to predict individual and combined impacts of wind park development, nutrient loading, and invasive species on vulnerable reef and sandbank habitats and associated species-specific biotopes in the northeastern Baltic Sea. Many impacts were not statistically significant due to large between-study variance in effect sizes. Wind park development is predicted to have less impact than nutrient loading and invasive species. Predicted impacts varied greatly among larger-scale habitats versus smaller-scale biotopes with impacts being generally stronger at small scale. Excessive nutrient loading damages algae-based biotopes, the presence of nonnative species has substantial negative impacts on larger-scale reef and sandbank habitats. The results showed that a 25 % reduction of nutrient loading improves all examined benthic habitats, whereas nonnative species, which cannot be removed from ecosystems, pose a significant threat to these habitats.

Assessing the potential for sea-based macroalgae cultivation and its application for nutrient removal in the Baltic Sea.

Marine eutrophication is a pervasive and growing threat to global sustainability. Macroalgal cultivation is a promising circular economy solution to achieve nutrient reduction and food security. However, the location of production hotspots is not well known. In this paper the production potential of macroalgae of high commercial value was predicted across the Baltic Sea region. In addition, the nutrient limitation within and adjacent to macroalgal farms was investigated to suggest optimal site-specific configuration of farms. The production potential of Saccharina latissima was largely driven by salinity and the highest production yields are expected in the westernmost Baltic Sea areas where salinity is >23. The direct and interactive effects of light availability, temperature, salinity and nutrient concentrations regulated the predicted changes in the production of Ulva intestinalis and Fucus vesiculosus. The western and southern Baltic Sea exhibited the highest farming potential for these species, with promising areas also in the eastern Baltic Sea. Macroalgal farming did not induce significant nutrient limitation. The expected spatial propagation of nutrient limitation caused by macroalgal farming was less than 100-250 m. Higher propagation distances were found in areas of low nutrient and low water exchange (e.g. offshore areas in the Baltic Proper) and smaller distances in areas of high nutrient and high water exchange (e.g. western Baltic Sea and Gulf of Riga). The generated maps provide the most sought-after input to support blue growth initiatives that foster the sustainable development of macroalgal cultivation and reduction of in situ nutrient loads in the Baltic Sea.

Blueprint for the ideal microplastic effect study: Critical issues of current experimental approaches and envisioning a path forward.

This article presents a novel conceptual blueprint for an 'ideal', i.e., ecologically relevant, microplastic effect study. The blueprint considers how microplastics should be characterized and applied in laboratory experiments, and how biological responses should be measured to assure unbiased data that reliably reflect the effects of microplastics on aquatic biota. This 'ideal' experiment, although practically unachievable, serves as a backdrop to improve specific aspects of experimental research on microplastic effects. In addition, a systematic and quantitative literature review identified and quantified departures of published experiments from the proposed 'ideal' design. These departures are related mainly to the experimental design of microplastic effect studies failing to mimic natural environments, and experiments with limited potential to be scaled-up to ecosystem level. To produce a valid and generalizable assessment of the effect of microplastics on biota, a quantitative meta-analysis was performed that incorporated the departure of studies from the 'ideal' experiment (a measure of experimental quality) and inverse variance (a measure of the study precision) as weighting coefficients. Greater weights were assigned to experiments with higher quality and/or with lower variance in the response variables. This double-weighting captures jointly the technical quality, ecological relevance and precision of estimates provided in each study. The blueprint and associated meta-analysis provide an improved baseline for the design of ecologically relevant and technically sound experiments to understand the effects of microplastics on single species, populations and, ultimately, entire ecosystems.

Impacts of coastal land use change in the wet tropics on nearshore coral reefs: Case studies from Papua New Guinea.

Logging and plantation agriculture are vital to economies and livelihoods in tropical nations, including Papua New Guinea. To meet global demand, hundreds of thousands of ha of diverse natural habitat have been logged, cleared and replaced with monoculture crops. Resulting hydrological changes have increased sediment, nutrient and pesticide runoff, impacting down-stream habitats. Here, case studies from Kimbe Bay (New Britain) and Mullins Harbour (Milne Bay), examine effects on nearshore coral reefs. In both places, logging and oil palm development had destabilized soils and removed or degraded riparian vegetation. Downstream, nearshore reefs had high silt levels, which, coincident with minor coral bleaching and predation by crown-of-thorns starfish, were correlated with high levels of coral mortality and low coral species richness. Sediment and related impacts can be reduced by effective catchment management, such as avoiding steep slopes, expanding stream and coastal buffer zones, minimizing fertilizer and pesticide use, monitoring and reactive management.

Historical biome distribution and recent human disturbance shape the diversity of arbuscular mycorrhizal fungi.

The availability of global microbial diversity data, collected using standardized metabarcoding techniques, makes microorganisms promising models for investigating the role of regional and local factors in driving biodiversity. Here we modelled the global diversity of symbiotic arbuscular mycorrhizal (AM) fungi using currently available data on AM fungal molecular diversity (small subunit (SSU) ribosomal RNA (rRNA) gene sequences) in field samples. To differentiate between regional and local effects, we estimated species pools (sets of potentially suitable taxa) for each site, which are expected to reflect regional processes. We then calculated community completeness, an index showing the fraction of the species pool present, which is expected to reflect local processes. We found significant spatial variation, globally in species pool size, as well as in local and dark diversity (absent members of the species pool). Species pool size was larger close to areas containing tropical grasslands during the last glacial maximum, which are possible centres of diversification. Community completeness was greater in regions of high wilderness (remoteness from human disturbance). Local diversity was correlated with wilderness and current connectivity to mountain grasslands. Applying the species pool concept to symbiotic fungi facilitated a better understanding of how biodiversity can be jointly shaped by large-scale historical processes and recent human disturbance.

Functional diversity through the mean trait dissimilarity: resolving shortcomings with existing paradigms and algorithms.

While an increasing number of indices for estimating the functional trait diversity of biological communities are being proposed, there is a growing demand by ecologists to clarify their actual implications and simplify index selection. Several key indices relate to mean trait dissimilarity between species within biological communities. Among them, the most widely used include (a) the mean species pairwise dissimilarity (MPD) and (b) the Rao quadratic entropy (and related indices). These indices are often regarded as redundant and promote the unsubstantiated yet widely held view that Rao is a form of MPD. Worryingly, existing R functions also do not always simplify the use and differentiation of these indices. In this paper, we show various distinctions between these two indices that warrant mathematical and biological consideration. We start by showing an existing form of MPD that considers species abundances and is different from Rao both mathematically and conceptually. We then show that the mathematical relationship between MPD and Rao can be presented simply as Rao = MPD × Simpson, where the Simpson diversity index is defined as 1 - dominance. We further show that this relationship is maintained for both species abundances and presence/absence. This evidence dismantles the paradigm that the Rao diversity is an abundance-weighted form of MPD and indicates that both indices can differ substantially at low species diversities. We discuss the different interpretations of trait diversity patterns in biological communities provided by Rao and MPD and then provide a simple R function, called "melodic," which avoids the unintended results that arise from existing mainstream functions.

Biodiversity patterns along ecological gradients: unifying ß-diversity indices.

Ecologists have developed an abundance of conceptions and mathematical expressions to define ß-diversity, the link between local (α) and regional-scale (γ) richness, in order to characterize patterns of biodiversity along ecological (i.e., spatial and environmental) gradients. These patterns are often realized by regression of ß-diversity indices against one or more ecological gradients. This practice, however, is subject to two shortcomings that can undermine the validity of the biodiversity patterns. First, many ß-diversity indices are constrained to range between fixed lower and upper limits. As such, regression analysis of ß-diversity indices against ecological gradients can result in regression curves that extend beyond these mathematical constraints, thus creating an interpretational dilemma. Second, despite being a function of the same measured α- and γ-diversity, the resultant biodiversity pattern depends on the choice of ß-diversity index. We propose a simple logistic transformation that rids beta-diversity indices of their mathematical constraints, thus eliminating the possibility of an uninterpretable regression curve. Moreover, this transformation results in identical biodiversity patterns for three commonly used classical beta-diversity indices. As a result, this transformation eliminates the difficulties of both shortcomings, while allowing the researcher to use whichever beta-diversity index deemed most appropriate. We believe this method can help unify the study of biodiversity patterns along ecological gradients.

Pattern without bias: local-regional richness relationship revisited.

For decades, ecologists have been testing for species saturation by using regression analysis to determine the relationship between local and regional species richness. The cumulative result of scores of studies and meta-analyses has led to a general consensus that evidence of species saturation is relatively uncommon. However, the bias induced on the regression by the arbitrary choice of local and regional area has threatened to undermine this consensus and has even led to the proposal to abandon the regression method entirely. Nonetheless, the use of regression analysis to determine local-regional richness relationships continues. We performed a meta-analysis of almost 100 data sets using a log-ratio-based regression model that is free of the scale-induced bias inherent in more commonly used models. This reanalysis contradicts the general consensus: saturated relationships are at least as common as unsaturated patterns. However, a discouragingly large proportion of studies produce no discernable patterns at all. An explanation for such a plethora of species saturation patterns poses a challenge to our understanding of the processes that govern community assembly.

Microfragmentation concept explains non-positive environmental heterogeneity-diversity relationships.

Although recent studies have revealed that the relationship between diversity and environmental heterogeneity is not always positive, as classical niche theory predicts, scientists have had difficulty interpreting these results from an ecological perspective. We propose a new concept-microfragmentation-to explain how small-scale heterogeneity can have neutral or even negative effect on species diversity. We define microfragmentation as a community level process of splitting habitat into a more heterogeneous environment that can have non-positive effects on the diversity through habitat loss and subsequent isolation. We provide support for the microfragmentation concept with results from spatially explicit heterogeneity-diversity model simulations, in which varying sets of species (with different ratios of specialist and generalist species) were modeled at different levels of configurational heterogeneity (meaning that only the habitat structure was changed, not its composition). Our results indicate that environmental heterogeneity can affect community diversity in the same way as fragmentation at the landscape level. Although generalist species might not be seriously affected by microfragmentation, the persistence of specialist species can be seriously disturbed by small-scale patchiness. The microfragmentation concept provides new insight into community level diversity dynamics and can influence conservation and management strategies.

Dark diversity: shedding light on absent species.

Ecological theory and nature conservation have traditionally relied solely on observed local diversity. In this review, we recommend including those species that are absent from an ecosystem but which belong to its species pool; that is, all species in the region that can potentially inhabit those particular ecological conditions. We call the set of absent species 'dark diversity'. Relating local and dark diversities enables biodiversity comparisons between regions, ecosystems and taxonomic groups, and the evaluation of the roles of local and regional processes in ecological communities. Dark diversity can also be used to counteract biodiversity loss and to estimate the restoration potential of ecosystems. We illustrate the dark diversity concept by globally mapping plant dark diversity and the local:dark diversity ratio.

Grain-size normalization as a tool to assess contamination in marine sediments: is the <63 micron fraction fine enough?

A common method for compensating for grain-size differences in suites of sediment samples is to normalize potential contaminants by regression with a particular grain-size fraction, the <63 microm fraction being most often selected. However, this fraction is unlikely to represent accurately the clay content, which represents a major factor in the ability of sediments to adsorb contaminants. Moreover, no reliable estimation of clay content can be made from a coarser grain-size fraction. As a result, regression with coarser-grained fractions can produce spurious interpretations of background values and contamination. Normalization with the clay content or by an alternative grain-size proxy is recommended.