Conservation implications of a mismatch between data availability and demographic impact.

Cost-effective use of limited conservation resources requires understanding which data most contribute to alleviating biodiversity declines. Interventions might reasonably prioritise life-cycle transitions with the greatest influence on population dynamics, yet some contributing vital rates are particularly challenging to document. This risks managers making decisions without sufficient empirical coverage of the spatiotemporal variation experienced by the species. Here, we aimed to explore whether the number of studies contributing estimates for a given life-stage transition aligns with that transition's demographic impact on population growth rate, λ. We parameterised a matrix population model using meta-analysis of vital rates for the common eider (Somateria mollissima), an increasingly threatened yet comparatively data-rich species of seaduck, for which some life stages are particularly problematic to study. Female common eiders exhibit intermittent breeding, with some established breeders skipping one or more years between breeding attempts. Our meta-analysis yielded a breeding propensity of 0.72, which we incorporated into our model with a discrete and reversible 'nonbreeder' stage (to which surviving adults transition with a probability of 0.28). The transitions between breeding and nonbreeding states had twice the influence on λ than fertility (summed matrix-element elasticities of 24% and 11%, respectively), whereas almost 15 times as many studies document components of fertility than breeding propensity (n = 103 and n = 7, respectively). The implications of such mismatches are complex because the motivations for feasible on-the-ground conservation actions may be different from what is needed to reduce uncertainty in population projections. Our workflow could form an early part of the toolkit informing future investment of finite resources, to avoid repeated disconnects between data needs and availability thwarting evidence-led conservation.

Laser ablation mass spectrometry blast through detection in R.

RATIONALE: Organisms that grow a hard carbonate shell or skeleton, such as foraminifera, corals or molluscs, incorporate trace elements into their shell during growth that reflect the environmental change and biological activity they experienced during life. These geochemical signals locked within the carbonate are archives used in proxy reconstructions to study past environments and climates, to decipher taxonomy of cryptic species and to resolve evolutionary responses to climatic changes. METHODS: Here, we use laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) as a time-resolved acquisition to quantify the elemental composition of carbonate shells and skeletons. We present the LABLASTER (Laser Ablation BLASt Through Endpoint in R) package, which imports a single time-resolved LA-ICP-MS analysis, then detects when the laser has ablated through the carbonate as a function of change in signal over time and outputs key summary statistics. We provide two examples within the package: a fossil planktic foraminifer and a tropical coral skeleton. RESULTS: We present the first R package that automates the selection of desired data during data reduction workflows. This is achieved by automating the detection of when the laser has ablated through a sample using a smoothed time series, followed by removal of off-target data points. The functions are flexible and adjust dynamically to maximise the duration of the desired geochemical target signal, making this package applicable to a wide range of heterogenous bioarchives. Visualisation tools for manual validation are also included. CONCLUSIONS: LABLASTER increases transparency and repeatability by algorithmically identifying when the laser has either ablated fully through a sample or across a mineral boundary and is thus no longer documenting a geochemical signal associated with the desired sample. LABLASTER's focus on better data targeting means more accurate extraction of biological and geochemical signals.

Epigenetic opportunities for evolutionary computation.

Evolutionary computation is a group of biologically inspired algorithms used to solve complex optimization problems. It can be split into evolutionary algorithms, which take inspiration from genetic inheritance, and swarm intelligence algorithms, that take inspiration from cultural inheritance. However, much of the modern evolutionary literature remains relatively unexplored. To understand which evolutionary mechanisms have been considered, and which have been overlooked, this paper breaks down successful bioinspired algorithms under a contemporary biological framework based on the extended evolutionary synthesis, an extension of the classical, genetics focused, modern synthesis. Although the idea of the extended evolutionary synthesis has not been fully accepted in evolutionary theory, it presents many interesting concepts that could provide benefits to evolutionary computation. The analysis shows that Darwinism and the modern synthesis have been incorporated into evolutionary computation but the extended evolutionary synthesis has been broadly ignored beyond: cultural inheritance, incorporated in the sub-set of swarm intelligence algorithms, evolvability, through covariance matrix adaptation evolution strategy (CMA-ES), and multilevel selection, through multilevel selection genetic algorithm (MLSGA). The framework shows a gap in epigenetic inheritance for evolutionary computation, despite being a key building block in modern interpretations of evolution. This leaves a diverse range of biologically inspired mechanisms as low hanging fruit that should be explored further within evolutionary computation and illustrates the potential of epigenetic based approaches through the recent benchmarks in the literature.

Extensive crop-wild hybridization during Brassica evolution and selection during the domestication and diversification of Brassica crops.

Adaptive genetic diversity in crop wild relatives (CWRs) can be exploited to develop improved crops with higher yield and resilience if phylogenetic relationships between crops and their CWRs are resolved. This further allows accurate quantification of genome-wide introgression and determination of regions of the genome under selection. Using broad sampling of CWRs and whole genome sequencing, we further demonstrate the relationships among two economically valuable and morphologically diverse Brassica crop species, their CWRs, and their putative wild progenitors. Complex genetic relationships and extensive genomic introgression between CWRs and Brassica crops were revealed. Some wild Brassica oleracea populations have admixed feral origins; some domesticated taxa in both crop species are of hybrid origin, while wild Brassica rapa is genetically indistinct from turnips. The extensive genomic introgression that we reveal could result in false identification of selection signatures during domestication using traditional comparative approaches used previously; therefore, we adopted a single-population approach to study selection during domestication. We used this to explore examples of parallel phenotypic selection in the two crop groups and highlight promising candidate genes for future investigation. Our analysis defines the complex genetic relationships between Brassica crops and their diverse CWRs, revealing extensive cross-species gene flow with implications for both crop domestication and evolutionary diversification more generally.

A new sea-level record for the Neogene/Quaternary boundary reveals transition to a more stable East Antarctic Ice Sheet.

Sea-level rise resulting from the instability of polar continental ice sheets represents a major socioeconomic hazard arising from anthropogenic warming, but the response of the largest component of Earth's cryosphere, the East Antarctic Ice Sheet (EAIS), to global warming is poorly understood. Here we present a detailed record of North Atlantic deep-ocean temperature, global sea-level, and ice-volume change for ∼2.75 to 2.4 Ma ago, when atmospheric partial pressure of carbon dioxide (pCO2) ranged from present-day (>400 parts per million volume, ppmv) to preindustrial (<280 ppmv) values. Our data reveal clear glacial-interglacial cycles in global ice volume and sea level largely driven by the growth and decay of ice sheets in the Northern Hemisphere. Yet, sea-level values during Marine Isotope Stage (MIS) 101 (∼2.55 Ma) also signal substantial melting of the EAIS, and peak sea levels during MIS G7 (∼2.75 Ma) and, perhaps, MIS G1 (∼2.63 Ma) are also suggestive of EAIS instability. During the succeeding glacial-interglacial cycles (MIS 100 to 95), sea levels were distinctly lower than before, strongly suggesting a link between greater stability of the EAIS and increased land-ice volumes in the Northern Hemisphere. We propose that lower sea levels driven by ice-sheet growth in the Northern Hemisphere decreased EAIS susceptibility to ocean melting. Our findings have implications for future EAIS vulnerability to a rapidly warming world.

Intraspecific size variation in planktonic foraminifera cannot be consistently predicted by the environment.

The size structure of plankton communities is an important determinant of their functions in marine ecosystems. However, few studies have quantified how organism size varies within species across biogeographical scales. Here, we investigate how planktonic foraminifera, a ubiquitous zooplankton group, vary in size across the tropical and subtropical oceans of the world. Using a recently digitized museum collection, we measured shell area of 3,799 individuals of nine extant species in 53 seafloor sediments. We first analyzed potential size biases in the collection. Then, for each site, we obtained corresponding local values of mean annual sea-surface temperature (SST), net primary productivity (NPP), and relative abundance of each species. Given former studies, we expected species to reach largest shell sizes under optimal environmental conditions. In contrast, we observe that species differ in how much their size variation is explained by SST, NPP, and/or relative abundance. While some species have predictable size variation given these variables (Trilobatus sacculifer, Globigerinoides conglobatus, Globigerinella siphonifera, Pulleniatina obliquiloculata, Globorotalia truncatulinoides), other species show no relationships between size and the studied covariates (Globigerinoides ruber, Neogloboquadrina dutertrei, Globorotalia menardii, Globoconella inflata). By incorporating intraspecific variation and sampling broader geographical ranges compared to previous studies, we conclude that shell size variation in planktonic foraminifera species cannot be consistently predicted by the environment. Our results caution against the general use of size as a proxy for planktonic foraminifera environmental optima. More generally, our work highlights the utility of natural history collections and the importance of studying intraspecific variation when interpreting macroecological patterns.

Animal life history is shaped by the pace of life and the distribution of age-specific mortality and reproduction.

Animals exhibit an extraordinary diversity of life history strategies. These realized combinations of survival, development and reproduction are predicted to be constrained by physiological limitations and by trade-offs in resource allocation. However, our understanding of these patterns is restricted to a few taxonomic groups. Using demographic data from 121 species, ranging from humans to sponges, we test whether such trade-offs universally shape animal life history strategies. We show that, after accounting for body mass and phylogenetic relatedness, 71% of the variation in animal life history strategies can be explained by life history traits associated with the fast-slow continuum (pace of life) and with a second axis defined by the distribution of age-specific mortality hazards and the spread of reproduction. While we found that life history strategies are associated with metabolic rate and ecological modes of life, surprisingly similar life history strategies can be found across the phylogenetic and physiological diversity of animals.

Temperature is a poor proxy for synergistic climate forcing of plankton evolution.

Changes in biodiversity at all levels from molecules to ecosystems are often linked to climate change, which is widely represented univariately by temperature. A global environmental driving mechanism of biodiversity dynamics is thus implied by the strong correlation between temperature proxies and diversity patterns in a wide variety of fauna and flora. Yet climate consists of many interacting variables. Species probably respond to the entire climate system as opposed to its individual facets. Here, we examine ecological and morphological traits of 12 633 individuals of two species of planktonic foraminifera with similar ecologies but contrasting evolutionary outcomes. Our results show that morphological and ecological changes are correlated to the interactions between multiple environmental factors. Models including interactions between climate variables explain at least twice as much variation in size, shape and abundance changes as models assuming that climate parameters operate independently. No dominant climatic driver can be identified: temperature alone explains remarkably little variation through our highly resolved temporal sequences, implying that a multivariate approach is required to understand evolutionary response to abiotic forcing. Our results caution against the use of a 'silver bullet' environmental parameter to represent global climate while studying evolutionary responses to abiotic change, and show that more comprehensive reconstruction of palaeobiological dynamics requires multiple biotic and abiotic dimensions.

Evolutionary history biases inferences of ecology and environment from δ13C but not δ18O values.

Closely related taxa are, on average, more similar in terms of their physiology, morphology and ecology than distantly related ones. How this biological similarity affects geochemical signals, and their interpretations, has yet to be tested in an explicitly evolutionary framework. Here we compile and analyze planktonic foraminiferal size-specific stable carbon and oxygen isotope values (δ13C and δ18O, respectively) spanning the last 107 million years. After controlling for dominant drivers of size-δ13C and size-δ18O trends, such as geological preservation, presence of algal photosymbionts, and global environmental changes, we identify that shared evolutionary history has shaped the evolution of species-specific vital effects in δ13C, but not in δ18O. Our results lay the groundwork for using a phylogenetic approach to correct species δ13C vital effects through time, thereby reducing systematic biases in interpretations of long-term δ13C records-a key measure of holistic organismal biology and of the global carbon cycle.

The Breakdown of Static and Evolutionary Allometries during Climatic Upheaval.

The influence of within-species variation and covariation on evolutionary patterns is well established for generational and macroevolutionary processes, most prominently through genetic lines of least resistance. However, it is not known whether intraspecific phenotypic variation also directs microevolutionary trajectories into the long term when a species is subject to varying environmental conditions. Here we present a continuous, high-resolution bivariate record of size and shape changes among 12,633 individual planktonic foraminifera of a surviving and an extinct-going species over 500,000 years. Our study interval spans the late Pliocene to earliest Pleistocene intensification of northern hemisphere glaciation, an interval of profound climate upheaval that can be divided into three phases of increasing glacial intensity. Within each of these three Plio-Pleistocene climate phases, the within-population allometries predict evolutionary change from one time step to the next and that the within-phase among-population (i.e., evolutionary) allometries match their corresponding static (within-population) allometries. However, the evolutionary allometry across the three climate phases deviates significantly from the static and phase-specific evolutionary allometries in the extinct-going species. Although intraspecific variation leaves a clear signature on mean evolutionary change from one time step to the next, our study suggests that the link between intraspecific variation and longer-term micro- and macroevolutionary phenomena is prone to environmental perturbation that can overcome constraints induced by within-species trait covariation.

Divergent demographic strategies of plants in variable environments.

One of the best-supported patterns in life history evolution is that organisms cope with environmental fluctuations by buffering their most important vital rates against them. This demographic buffering hypothesis is evidenced by a tendency for temporal variation in rates of survival and reproduction to correlate negatively with their contribution to fitness. Here, we show that widespread evidence for demographic buffering can be artefactual, resulting from natural relationships between the mean and variance of vital rates. Following statistical scaling, we find no significant tendency for plant life histories to be buffered demographically. Instead, some species are buffered, whereas others have labile life histories with higher temporal variation in their more important vital rates. We find phylogenetic signal in the strength and direction of variance-importance correlations, suggesting that clades of plants are prone to being either buffered or labile. Species with simple life histories are more likely to be demographically labile. Our results suggest important evolutionary nuances in how species deal with environmental fluctuations.

Fluctuating effects of genetic and plastic changes in body mass on population dynamics in a large herbivore.

Recent studies suggest that evolutionary changes can occur on a contemporary time scale. Hence, evolution can influence ecology and vice-versa. To understand the importance of eco-evolutionary dynamics in population dynamics, we must quantify the relative contribution of ecological and evolutionary changes to population growth and other ecological processes. To date, however, most eco-evolutionary dynamics studies have not partitioned the relative contribution of plastic and evolutionary changes in traits on population, community, and ecosystem processes. Here, we quantify the effects of heritable and non-heritable changes in body mass distribution on survival, recruitment, and population growth in wild bighorn sheep (Ovis canadensis) and compare their importance to the effects of changes in age structure, population density, and weather. We applied a combination of a pedigree-based quantitative genetics model, statistical analyses of demography, and a new statistical decomposition technique, the Geber method, to a long-term data set of bighorn sheep on Ram Mountain (Canada), monitored individually from 1975 to 2012. We show three main results: (1) The relative importance of heritable change in mass, non-heritable change in mass, age structure, density, and climate on population growth rate changed substantially over time. (2) An increase in body mass was accompanied by an increase in population growth through higher survival and recruitment rate. (3) Over the entire study period, changes in the body mass distribution of ewes, mostly through non-heritable changes, affected population growth to a similar extent as changes in age structure or in density. The importance of evolutionary changes was small compared to that of other drivers of changes in population growth but increased with time as evolutionary changes accumulated. Evolutionary changes became increasingly important for population growth as the length of the study period considered increased. Our results highlight the complex ways in which ecological and evolutionary changes can affect population dynamics and illustrate the large potential effect of trait changes on population processes.

Resource partitioning between ungulate populations in arid environments.

Herbivores are major drivers of ecosystem structure, diversity, and function. Resilient ecosystems therefore require viable herbivore populations in a sustainable balance with environmental resource availability. This balance is becoming harder to achieve, with increasingly threatened species reliant on small protected areas in increasingly harsh and unpredictable environments. Arid environments in North Africa exemplify this situation, featuring a biologically distinct species assemblage exposed to extreme and volatile conditions, including habitat loss and climate change-associated threats. Here, we implement an integrated likelihood approach to relate scimitar-horned oryx (Oryx dammah) and dorcas gazelle (Gazella dorcas) density, via dung distance sampling, to habitat, predator, and geographic correlates in Dghoumes National Park, Tunisia. We show how two threatened sympatric ungulates partition resources on the habitat axis, exhibiting nonuniform responses to the same vegetation gradient. Scimitar-horned oryx were positively associated with plant species richness, selecting for vegetated ephemeral watercourses (wadis) dominated by herbaceous cover. Conversely, dorcas gazelle were negatively associated with vegetation density (herbaceous height, litter cover, and herbaceous cover), selecting instead for rocky plains with sparse vegetation. We suggest that adequate plant species richness should be a prerequisite for areas proposed for future ungulate reintroductions in arid and semi-arid environments. This evidence will inform adaptive management of reintroduced ungulates in protected environments, helping managers and planners design sustainable ecosystems and effective conservation programs.

Environmental changes define ecological limits to species richness and reveal the mode of macroevolutionary competition.

Co-dependent geological and climatic changes obscure how species interact in deep time. The interplay between these environmental factors makes it hard to discern whether ecological competition exerts an upper limit on species richness. Here, using the exceptional fossil record of Cenozoic Era macroperforate planktonic foraminifera, we assess the evidence for alternative modes of macroevolutionary competition. Our models support an environmentally dependent macroevolutionary form of contest competition that yields finite upper bounds on species richness. Models of biotic competition assuming unchanging environmental conditions were overwhelmingly rejected. In the best-supported model, temperature affects the per-lineage diversification rate, while both temperature and an environmental driver of sediment accumulation defines the upper limit. The support for contest competition implies that incumbency constrains species richness by restricting niche availability, and that the number of macroevolutionary niches varies as a function of environmental changes.

The challenges to inferring the regulators of biodiversity in deep time.

Attempts to infer the ecological drivers of macroevolution in deep time have long drawn inspiration from work on extant systems, but long-term evolutionary and geological changes complicate the simple extrapolation of such theory. Recent efforts to incorporate a more informed ecology into macroevolution have moved beyond the descriptive, seeking to isolate generating mechanisms and produce testable hypotheses of how groups of organisms usurp each other or coexist over vast timespans. This theme issue aims to exemplify this progress, providing a series of case studies of how novel modelling approaches are helping infer the regulators of biodiversity in deep time. In this Introduction, we explore the challenges of these new approaches. First, we discuss how our choices of taxonomic units have implications for the conclusions drawn. Second, we emphasize the need to embrace the interdependence of biotic and abiotic changes, because no living organism ignores its environment. Third, in the light of parts 1 and 2, we discuss the set of dynamic signatures that we might expect to observe in the fossil record. Finally, we ask whether these dynamics represent the most ecologically informative foci for research efforts aimed at inferring the regulators of biodiversity in deep time. The papers in this theme issue contribute in each of these areas.

A meta-analysis of functional group responses to forest recovery outside of the tropics.

Both active and passive forest restoration schemes are used in degraded landscapes across the world to enhance biodiversity and ecosystem service provision. Restoration is increasingly also being implemented in biodiversity offset schemes as compensation for loss of natural habitat to anthropogenic development. This has raised concerns about the value of replacing old-growth forest with plantations, motivating research on biodiversity recovery as forest stands age. Functional diversity is now advocated as a key metric for restoration success, yet it has received little analytical attention to date. We conducted a meta-analysis of 90 studies that measured differences in species richness for functional groups of fungi, lichens, and beetles between old-growth control and planted or secondary treatment forests in temperate, boreal, and Mediterranean regions. We identified functional-group-specific relationships in the response of species richness to stand age after forest disturbance. Ectomycorrhizal fungi averaged 90 years for recovery to old-growth values (between 45 years and unrecoverable at 95% prediction limits), and epiphytic lichens took 180 years to reach 90% of old-growth values (between 140 years and never for recovery to old-growth values at 95% prediction limits). Non-saproxylic beetle richness, in contrast, decreased as stand age of broadleaved forests increased. The slow recovery by some functional groups essential to ecosystem functioning makes old-growth forest an effectively irreplaceable biodiversity resource that should be exempt from biodiversity offsetting initiatives.

Fitness consequences of maternal and grandmaternal effects.

Transgenerational effects are broader than only parental relationships. Despite mounting evidence that multigenerational effects alter phenotypic and life-history traits, our understanding of how they combine to determine fitness is not well developed because of the added complexity necessary to study them. Here, we derive a quantitative genetic model of adaptation to an extraordinary new environment by an additive genetic component, phenotypic plasticity, maternal and grandmaternal effects. We show how, at equilibrium, negative maternal and negative grandmaternal effects maximize expected population mean fitness. We define negative transgenerational effects as those that have a negative effect on trait expression in the subsequent generation, that is, they slow, or potentially reverse, the expected evolutionary dynamic. When maternal effects are positive, negative grandmaternal effects are preferred. As expected under Mendelian inheritance, the grandmaternal effects have a lower impact on fitness than the maternal effects, but this dual inheritance model predicts a more complex relationship between maternal and grandmaternal effects to constrain phenotypic variance and so maximize expected population mean fitness in the offspring.

Lack of quantitative training among early-career ecologists: a survey of the problem and potential solutions.

Proficiency in mathematics and statistics is essential to modern ecological science, yet few studies have assessed the level of quantitative training received by ecologists. To do so, we conducted an online survey. The 937 respondents were mostly early-career scientists who studied biology as undergraduates. We found a clear self-perceived lack of quantitative training: 75% were not satisfied with their understanding of mathematical models; 75% felt that the level of mathematics was "too low" in their ecology classes; 90% wanted more mathematics classes for ecologists; and 95% more statistics classes. Respondents thought that 30% of classes in ecology-related degrees should be focused on quantitative disciplines, which is likely higher than for most existing programs. The main suggestion to improve quantitative training was to relate theoretical and statistical modeling to applied ecological problems. Improving quantitative training will require dedicated, quantitative classes for ecology-related degrees that contain good mathematical and statistical practice.