Description: Global concern about human impact on biological diversity has triggered an intense research agenda on drivers and consequences of biodiversity change in parallel with international policy seeking to conserve biodiversity and associated ecosystem functions. Quantifying the trends in biodiversity is far from trivial, however, as recently documented by meta-analyses, which report little if any net change in local species richness through time. Here, we summarise several limitations of species richness as a metric of biodiversity change and show that the expectation of directional species richness trends under changing conditions is invalid. Instead, we illustrate how a set of species turnover indices provide more information content regarding temporal trends in biodiversity, as they reflect how dominance and identity shift in communities over time. We apply these metrics to three monitoring datasets representing different ecosystem types. In all datasets, nearly complete species turnover occurred, but this was disconnected from any species richness trends. Instead, turnover was strongly influenced by changes in species presence (identities) and dominance (abundances). We further show that these metrics can detect phases of strong compositional shifts in monitoring data and thus identify a different aspect of biodiversity change decoupled from species richness. Synthesis and applications: Temporal trends in species richness are insufficient to capture key changes in biodiversity in changing environments. In fact, reductions in environmental quality can lead to transient increases in species richness if immigration or extinction has different temporal dynamics. Thus, biodiversity monitoring programmes need to go beyond analyses of trends in richness in favour of more meaningful assessments of biodiversity change.

Description: While there is a lot of data on interactive effects of eutrophication and warming, to date, we lack data to generate reliable predictions concerning possible effects of nutrient decrease and temperature increase on community composition and functional responses. In recent years, a wide‐ranging trend of nutrient decrease (re‐oligotrophication) was reported for freshwater systems. Small lakes and ponds, in particular, show rapid responses to anthropogenic pressures and became model systems to investigate single as well as synergistic effects of warming and fertilization in situ and in experiments. Therefore, we set up an experiment to investigate the single as well as the interactive effects of nutrient reduction and gradual temperature increase on a natural freshwater phytoplankton community, using an experimental indoor mesocosm setup. Biomass production initially increased with warming but decreased with nutrient depletion. If nutrient supply was constant, biomass increased further, especially under warming conditions. Under low nutrient supply, we found a sharp transition from initially positive effects of warming to negative effects when resources became scarce. Warming reduced phytoplankton richness and evenness, whereas nutrient reduction at ambient temperature had positive effects on diversity. Our results indicate that temperature effects on freshwater systems will be altered by nutrient availability. These interactive effects of energy increase and resource decrease have major impacts on biodiversity and ecosystem function and thus need to be considered in environmental management plans.

Description: Estimates of biodiversity change are essential for the management and conservation of ecosystems. Accurate estimates rely on selecting representative sites, but monitoring often focuses on sites of special interest. How such site‐selection biases influence estimates of biodiversity change is largely unknown. Site‐selection bias potentially occurs across four major sources of biodiversity data, decreasing in likelihood from citizen science, museums, national park monitoring, and academic research. We defined site‐selection bias as a preference for sites that are either densely populated (i.e., abundance bias) or species rich (i.e., richness bias). We simulated biodiversity change in a virtual landscape and tracked the observed biodiversity at a sampled site. The site was selected either randomly or with a site‐selection bias. We used a simple spatially resolved, individual‐based model to predict the movement or dispersal of individuals in and out of the chosen sampling site. Site‐selection bias exaggerated estimates of biodiversity loss in sites selected with a bias by on average 300–400% compared with randomly selected sites. Based on our simulations, site‐selection bias resulted in positive trends being estimated as negative trends: richness increase was estimated as 0.1 in randomly selected sites, whereas sites selected with a bias showed a richness change of −0.1 to −0.2 on average. Thus, site‐selection bias may falsely indicate decreases in biodiversity. We varied sampling design and characteristics of the species and found that site‐selection biases were strongest in short time series, for small grains, organisms with low dispersal ability, large regional species pools, and strong spatial aggregation. Based on these findings, to minimize site‐selection bias, we recommend use of systematic site‐selection schemes; maximizing sampling area; calculating biodiversity measures cumulatively across plots; and use of biodiversity measures that are less sensitive to rare species, such as the effective number of species. Awareness of the potential impact of site‐selection bias is needed for biodiversity monitoring, the design of new studies on biodiversity change, and the interpretation of existing data.

Description: Antarctic krill (Euphausia superba; hereafter krill) are an incredibly abundant pelagic crustacean which has a wide, but patchy, distribution in the Southern Ocean. Several studies have examined the potential for population genetic structuring in krill, but DNA-based analyses have focused on a limited number of markers and have covered only part of their circum-Antarctic range. We used mitochondrial DNA and restriction site-associated DNA sequencing (RAD-seq) to investigate genetic differences between krill from five sites, including two from East Antarctica. Our mtDNA results show no discernible genetic structuring between sites separated by thousands of kilometres, which is consistent with previous studies. Using standard RAD-seq methodology, we obtained over a billion sequences from 〉140 krill, and thousands of variable nucleotides were identified at hundreds of loci. However, downstream analysis found that markers with sufficient coverage were primarily from multicopy genomic regions. Careful examination of these data highlights the complexity of the RAD-seq approach in organisms with very large genomes. To characterize the multicopy markers, we recorded sequence counts from variable nucleotide sites rather than the derived genotypes; we also examined a small number of manually curated genotypes. Although these analyses effectively fingerprinted individuals, and uncovered a minor laboratory batch effect, no population structuring was observed. Overall, our results are consistent with panmixia of krill throughout their distribution. This result may indicate ongoing gene flow. However, krill’s enormous population size creates substantial panmictic inertia, so genetic differentiation may not occur on an ecologically relevant timescale even if demographically separate populations exist.

Description: Increasing air temperatures are changing the arctic tundra biome. Permafrost is thawing, snow duration is decreasing, shrub vegetation is proliferating, and boreal wildlife is encroaching. Here we present evidence of the recent range expansion of North American beaver (Castor canadensis) into the Arctic, and consider how this ecosystem engineer might reshape the landscape, biodiversity, and ecosystem processes. We developed a remote sensing approach that maps formation and disappearance of ponds associated with beaver activity. Since 1999, 56 new beaver pond complexes were identified, indicating that beavers are colonizing a predominantly tundra region (18,293 km2) of northwest Alaska. It is unclear how improved tundra stream habitat, population rebound following overtrapping for furs, or other factors are contributing to beaver range expansion. We discuss rates and likely routes of tundra beaver colonization, as well as effects on permafrost, stream ice regimes, and freshwater and riparian habitat. Beaver ponds and associated hydrologic changes are thawing permafrost. Pond formation increases winter water temperatures in the pond and downstream, likely creating new and more varied aquatic habitat, but specific biological implications are unknown. Beavers create dynamic wetlands and are agents of disturbance that may enhance ecosystem responses to warming in the Arctic.

Description: The concept of “blue growth,” which aims to promote the growth of ocean economies while holistically managing marine socioecological systems, is emerging within na-tional and international marine policy. The concept is often promoted as being novel; however, we show that historical analogies exist that can provide insights for contem-porary planning and implementation of blue growth. Using a case-study approach based on expert knowledge, we identified 20 historical fisheries or aquaculture ex-amples from 13 countries, spanning the last 40–800 years, that we contend embody blue growth concepts. This is the first time, to our knowledge, that blue growth has been investigated across such broad spatial and temporal scales. The past societies managed to balance exploitation with equitable access, ecological integrity and/or economic growth for varying periods of time. Four main trajectories existed that led to the success or failure of blue growth. Success was linked to equitable rather than open access, innovation and management that was responsive, holistic and based on scientific knowledge and monitoring. The inability to achieve or maintain blue growth resulted from failures to address limits to industry growth and/or anticipate the im-pacts of adverse extrinsic events and drivers (e.g. changes in international markets, war), the prioritization of short-term gains over long-term sustainability, and loss of supporting systems. Fourteen cross-cutting lessons and 10 recommendations were derived that can improve understanding and implementation of blue growth. Despite the contemporary literature broadly supporting our findings, these recommenda-tions are not adequately addressed by agendas seeking to realize blue growth.

Description: In many regions across the globe, extreme weather events such as storms have increased in frequency, intensity, and duration due to climate change. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. High winds and precipitation associated with storms can affect lakes via short‐term runoff events from watersheds and physical mixing of the water column. In addition, lakes connected to rivers and streams will also experience flushing due to high flow rates. Although we have a well‐developed understanding of how wind and precipitation events can alter lake physical processes and some aspects of biogeochemical cycling, our mechanistic understanding of the emergent responses of phytoplankton communities is poor. Here we provide a comprehensive synthesis that identifies how storms interact with lake and watershed attributes and their antecedent conditions to generate changes in lake physical and chemical environments. Such changes can restructure phytoplankton communities and their dynamics, as well as result in altered ecological function (e.g., carbon, nutrient and energy cycling) in the short‐ and long‐term. We summarize the current understanding of storm‐induced phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions across a gradient of lake types and environmental conditions.

Description: In many spatial resource models, it is assumed that an agent is able to harvest the resource over the complete spatial domain. However, agents frequently only have access to a resource at particular locations at which a moving biomass, such as fish or game, may be caught or hunted. Here, we analyze an infinite time‐horizon optimal control problem with boundary harvesting and (systems of) parabolic partial differential equations as state dynamics. We formally derive the associated canonical system, consisting of a forward–backward diffusion system with boundary controls, and numerically compute the canonical steady states and the optimal time‐dependent paths, and their dependence on parameters. We start with some one‐species fishing models, and then extend the analysis to a predator–prey model of the Lotka–Volterra type. The models are rather generic, and our methods are quite general, and thus should be applicable to large classes of structurally similar bioeconomic problems with boundary controls. Recommedations for Resource Managers Just like ordinary differential equation‐constrained (optimal) control problems and distributed partial differential equation (PDE) constrained control problems, boundary control problems with PDE state dynamics may be formally treated by the Pontryagin's maximum principle or canonical system formalism (state and adjoint PDEs). These problems may have multiple (locally) optimal solutions; a first overview of suitable choices can be obtained by identifying canonical steady states. The computation of canonical paths toward some optimal steady state yields temporal information about the optimal harvesting, possibly including waiting time behavior for the stock to recover from a low‐stock initial state, and nonmonotonic (in time) harvesting efforts. Multispecies fishery models may lead to asymmetric effects; for instance, it may be optimal to capture a predator species to protect the prey, even for high costs and low market values of the predators.