Revealing uncertainty in the status of biodiversity change

Biodiversity faces unprecedented threats from rapid global change1. Signals of biodiversity change come from time-series abundance datasets for thousands of species over large geographic and temporal scales. Analyses of these biodiversity datasets have pointed to varied trends in abundance, including increases and decreases. However, these analyses have not fully accounted for spatial, temporal and phylogenetic structures in the data. Here, using a new statistical framework, we show across ten high-profile biodiversity datasets2-11 that increases and decreases under existing approaches vanish once spatial, temporal and phylogenetic structures are accounted for. This is a consequence of existing approaches severely underestimating trend uncertainty and sometimes misestimating the trend direction. Under our revised average abundance trends that appropriately recognize uncertainty, we failed to observe a single increasing or decreasing trend at 95% credible intervals in our ten datasets. This emphasizes how little is known about biodiversity change across vast spatial and taxonomic scales. Despite this uncertainty at vast scales, we reveal improved local-scale prediction accuracy by accounting for spatial, temporal and phylogenetic structures. Improved prediction offers hope of estimating biodiversity change at policy-relevant scales, guiding adaptive conservation responses.

Acting pre-emptively reduces the long-term costs of managing herbicide resistance

Globally, pesticides improve crop yields but at great environmental cost, and their overuse has caused resistance. This incurs large financial and production losses but, despite this, very diversified farm management that might delay or prevent resistance is uncommon in intensive farming. We asked farmers to design more diversified cropping strategies aimed at controlling herbicide resistance, and estimated resulting weed densities, profits, and yields compared to prevailing practice. Where resistance is low, it is financially viable to diversify pre-emptively; however, once resistance is high, there are financial and production disincentives to adopting diverse rotations. It is therefore as important to manage resistance before it becomes widespread as it is to control it once present. The diverse rotations targeting high resistance used increased herbicide application frequency and volume, contributing to these rotations' lack of financial viability, and raising concerns about glyphosate resistance. Governments should encourage adoption of diverse rotations in areas without resistance. Where resistance is present, governments may wish to incentivise crop diversification despite the drop in wheat production as it is likely to bring environmental co-benefits. Our research suggests we need long-term, proactive, food security planning and more integrated policy-making across farming, environment, and health arenas.

Indigenous Peoples' Lands are critical for safeguarding vertebrate diversity across the tropics

Indigenous Peoples are long-term custodians of their lands, but only recently are their contributions to conservation starting to be recognized in biodiversity policy and practice. Tropical forest loss and degradation are lower in Indigenous lands than unprotected areas, yet the role of Indigenous Peoples' Lands (IPL) in biodiversity conservation has not been properly assessed from regional to global scales. Using species distribution ranges of 11,872 tropical forest-dependent vertebrates to create area of habitat maps, we identified the overlap of these species ranges with IPL and then compared values inside and outside of IPL for species richness, extinction vulnerability, and range-size rarity. Of assessed vertebrates, at least 76.8% had range overlaps with IPL, on average overlapping ~25% of their ranges; at least 120 species were found only within IPL. Species richness within IPL was highest in South America, while IPL in Southeast Asia had highest extinction vulnerability, and IPL in Dominica and New Caledonia were important for range-size rarity. Most countries in the Americas had higher species richness within IPL than outside, whereas most countries in Asia had lower extinction vulnerability scores inside IPL and more countries in Africa and Asia had slightly higher range-size rarity in IPL. Our findings suggest that IPL provide critical support for tropical forest-dependent vertebrates, highlighting the need for greater inclusion of Indigenous Peoples in conservation target-setting and program implementation, and stronger upholding of Indigenous Peoples' rights in conservation policy.

A mixed-model approach for estimating drivers of microbiota community composition and differential taxonomic abundance

Next-generation sequencing (NGS) and metabarcoding approaches are increasingly applied to wild animal populations, but there is a disconnect between the widely applied generalized linear mixed model (GLMM) approaches commonly used to study phenotypic variation and the statistical toolkit from community ecology typically applied to metabarcoding data. Here, we describe the suitability of a novel GLMM-based approach for analyzing the taxon-specific sequence read counts derived from standard metabarcoding data. This approach allows decomposition of the contribution of different drivers to variation in community composition (e.g., age, season, individual) via interaction terms in the model random-effects structure. We provide guidance to implementing this approach and show how these models can identify how responsible specific taxonomic groups are for the effects attributed to different drivers. We applied this approach to two cross-sectional data sets from the Soay sheep population of St. Kilda. GLMMs showed agreement with dissimilarity-based approaches highlighting the substantial contribution of age and minimal contribution of season to microbiota community compositions, and simultaneously estimated the contribution of other technical and biological factors. We further used model predictions to show that age effects were principally due to increases in taxa of the phylum Bacteroidetes and declines in taxa of the phylum Firmicutes. This approach offers a powerful means for understanding the influence of drivers of community structure derived from metabarcoding data. We discuss how our approach could be readily adapted to allow researchers to estimate contributions of additional factors such as host or microbe phylogeny to answer emerging questions surrounding the ecological and evolutionary roles of within-host communities. IMPORTANCE NGS and fecal metabarcoding methods have provided powerful opportunities to study the wild gut microbiome. A wealth of data is, therefore, amassing across wild systems, generating the need for analytical approaches that can appropriately investigate simultaneous factors at the host and environmental scale that determine the composition of these communities. Here, we describe a generalized linear mixed-effects model (GLMM) approach to analyze read count data from metabarcoding of the gut microbiota, allowing us to quantify the contributions of multiple host and environmental factors to within-host community structure. Our approach provides outputs that are familiar to a majority of field ecologists and can be run using any standard mixed-effects modeling packages. We illustrate this approach using two metabarcoding data sets from the Soay sheep population of St. Kilda investigating age and season effects as worked examples.

Herbivore-driven disruption of arbuscular mycorrhizal carbon-for-nutrient exchange is ameliorated by neighboring plants

Arbuscular mycorrhizal fungi colonize the roots of most plants, forming a near-ubiquitous symbiosis¹ that is typically characterized by the bi-directional exchange of fungal-acquired nutrients for plant-fixed carbon.² Mycorrhizal fungi can form below-ground networks^3,4,5,6 with potential to facilitate the movement of carbon, nutrients, and defense signals across plant communities.^7,8,9 The importance of neighbors in mediating carbon-for-nutrient exchange between mycorrhizal fungi and their plant hosts remains equivocal, particularly when other competing pressures for plant resources are present. We manipulated carbon source and sink strengths of neighboring pairs of host plants through exposure to aphids and tracked the movement of carbon and nutrients through mycorrhizal fungal networks with isotope tracers. When carbon sink strengths of both neighboring plants were increased by aphid herbivory, plant carbon supply to extraradical mycorrhizal fungal hyphae was reduced, but mycorrhizal phosphorus supply to both plants was maintained, albeit variably, across treatments. However, when the sink strength of only one plant in a pair was increased, carbon supply to mycorrhizal fungi was restored. Our results show that loss of carbon inputs into mycorrhizal fungal hyphae from one plant may be ameliorated through inputs of a neighbor, demonstrating the responsiveness and resilience of mycorrhizal plant communities to biological stressors. Furthermore, our results indicate that mycorrhizal nutrient exchange dynamics are better understood as community-wide interactions between multiple players rather than as strict exchanges between individual plants and their symbionts, suggesting that mycorrhizal C-for-nutrient exchange is likely based more on unequal terms of trade than the "fair trade" model for symbiosis.

A predictive timeline of wildlife population collapse

Contemporary rates of biodiversity decline emphasize the need for reliable ecological forecasting, but current methods vary in their ability to predict the declines of real-world populations. Acknowledging that stressor effects start at the individual level, and that it is the sum of these individual-level effects that drives populations to collapse, shifts the focus of predictive ecology away from using predominantly abundance data. Doing so opens new opportunities to develop predictive frameworks that utilize increasingly available multi-dimensional data, which have previously been overlooked for ecological forecasting. Here, we propose that stressed populations will exhibit a predictable sequence of observable changes through time: changes in individuals' behaviour will occur as the first sign of increasing stress, followed by changes in fitness-related morphological traits, shifts in the dynamics (for example, birth rates) of populations and finally abundance declines. We discuss how monitoring the sequential appearance of these signals may allow us to discern whether a population is increasingly at risk of collapse, or is adapting in the face of environmental change, providing a conceptual framework to develop new forecasting methods that combine multi-dimensional (for example, behaviour, morphology, life history and abundance) data.

Indigenous lands in protected areas have high forest integrity across the tropics

Intact tropical forests have a high conservation value.¹ Although perceived as wild,² they have been under long-term human influence.³ As global area-based conservation targets increase, the ecological contributions of Indigenous peoples through their governance institutions and practices⁴ are gaining mainstream interest. Indigenous lands-covering a quarter of Earth's surface⁵ and overlapping with a third of intact forests⁶-often have reduced deforestation, degradation, and carbon emissions, compared with non-protected areas and protected areas.^7,8 A key question with implications for the design of more equitable and effective conservation policies is to understand the impacts of Indigenous lands on forest integrity and long-term use, as critical measures of ecosystem health included within the post-2020 Global Biodiversity Framework.⁹ Using the forest landscape integrity index¹⁰ and Anthromes¹¹ datasets, we find that high-integrity forests tend to be located within the overlap of protected areas and Indigenous lands (protected-Indigenous areas). After accounting for location biases through statistical matching and regression, protected-Indigenous areas had the highest protective effect on forest integrity and the lowest land-use intensity relative to Indigenous lands, protected areas, and non-protected controls pan-tropically. The protective effect of Indigenous lands on forest integrity was lower in Indigenous lands than in protected areas and non-protected areas in the Americas and Asia. The combined positive effects of state legislation and Indigenous presence in protected-Indigenous areas may contribute to maintaining tropical forest integrity. Understanding management and governance in protected-Indigenous areas can help states to appropriately support community-governed lands.

Mesostats—A multiplexed, low-cost, do-it-yourself continuous culturing system for experimental evolution of mesocosms

Microbial experimental evolution allows studying evolutionary dynamics in action and testing theory predictions in the lab. Experimental evolution in chemostats (i.e. continuous flow through cultures) has recently gained increased interest as it allows tighter control of selective pressures compared to static batch cultures, with a growing number of efforts to develop systems that are easier and cheaper to construct. This protocol describes the design and construction of a multiplexed chemostat array (dubbed “mesostats”) designed for cultivation of algae in 16 concurrent populations, specifically intended for studying adaptation to herbicides. We also present control data from several experiments run on the system to show replicability, data illustrating the effects of common issues like leaks, contamination and clumps, and outline possible modifications and adaptations of the system for future research.

Dissecting weed adaptation: Fitness and trait correlations in herbicide-resistant Alopecurus myosuroides

BACKGROUND

Unravelling the genetic architecture of non-target-site resistance (NTSR) traits in weed populations can inform questions about the inheritance, trade-offs and fitness costs associated with these traits. Classical quantitative genetics approaches allow study of the genetic architecture of polygenic traits even where the genetic basis of adaptation remains unknown. These approaches have the potential to overcome some of the limitations of previous studies into the genetics and fitness of NTSR.

RESULTS

Using a quantitative genetic analysis of 400 pedigreed Alopecurus myosuroides seed families from nine field-collected populations, we found strong heritability for resistance to the acetolactate synthase and acetyl CoA carboxylase inhibitors (h²  = 0.731 and 0.938, respectively), and evidence for shared additive genetic variance for resistance to these two different herbicide modes of action, r_g  = 0.34 (survival), 0.38 (biomass). We find no evidence for genetic correlations between life-history traits and herbicide resistance, indicating that resistance to these two modes of action is not associated with large fitness costs in blackgrass. We do, however, demonstrate that phenotypic variation in plant flowering characteristics is heritable, h²  = 0.213 (flower height), 0.529 (flower head number), 0.449 (time to flowering) and 0.372 (time to seed shed), demonstrating the potential for adaptation to other nonchemical management practices (e.g. mowing of flowering heads) now being adopted for blackgrass control.

CONCLUSION

These results highlight that quantitative genetics can provide important insight into the inheritance and genetic architecture of NTSR, and can be used alongside emerging molecular techniques to better understand the evolutionary and fitness landscape of herbicide resistance. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Population level consequences of facultatively cooperative behaviour in a stochastic environment

The social environment in which individuals live affects their fitness and in turn population dynamics as a whole. Birds with facultative cooperative breeding can live in social groups with dominants, subordinate helpers that assist with the breeding of others, and subordinate non-helpers. Helping behaviour benefits dominants through increased reproductive rates and reduced extrinsic mortality, such that cooperative breeding might have evolved in response to unpredictable, harsh conditions affecting reproduction and/or survival of the dominants. Additionally, there may be different costs and benefits to both helpers and non-helpers, depending on the time-scale. For example, early-life costs might be compensated by later-life benefits. These differential effects are rarely analysed in the same study. We examined whether helping behaviour affects population persistence in a stochastic environment and whether there are direct fitness consequences of different life-history tactics adopted by helpers and non-helpers. We parameterised a matrix population model describing the population dynamics of female Seychelles warblers Acrocephalus sechellensis, birds that display facultative cooperative breeding. The stochastic density-dependent model is defined by a (st)age structure that includes life-history differences between helpers and non-helpers and thus can estimate the demographic mechanisms of direct benefits of helping behaviour. We found that population dynamics are strongly influenced by stochastic variation in the reproductive rates of the dominants, that helping behaviour promotes population persistence and that there are only early-life differences in the direct fitness of helpers and non-helpers. Through a matrix population model, we captured multiple demographic rates simultaneously and analysed their relative importance in determining population dynamics of these cooperative breeders. Disentangling early-life versus lifetime effects of individual tactics sheds new light on the costs and benefits of helping behaviour. For example, the finding that helpers and non-helpers have similar lifetime reproductive outputs and that differences in reproductive values between the two life-history tactics arise only in early life suggests that overall, helpers and non-helpers have a similar balance of costs and benefits when analysing direct benefits. We recommend analysing the consequence of different life-history tactics, during both early life and over the lifetime, as analyses of these different time frames may produce conflicting results.

PHENOTYPIC PLASTICITY MASKS RANGE-WIDE GENETIC DIFFERENTIATION FOR VEGETATIVE BUT NOT REPRODUCTIVE TRAITS IN A SHORT-LIVED PLANT

Genetic differentiation and phenotypic plasticity jointly shape intraspecific trait variation, but their roles differ among traits. In short-lived plants, reproductive traits may be more genetically determined due to their impact on fitness, whereas vegetative traits may show higher plasticity to buffer short-term perturbations. Combining a multi-treatment greenhouse experiment with observational field data throughout the range of a widespread short-lived herb, Plantago lanceolata, we (1) disentangled genetic and plastic responses of functional traits to a set of environmental drivers and (2) assessed how genetic differentiation and plasticity shape observational trait-environment relationships. Reproductive traits showed distinct genetic differentiation that largely determined observational patterns, but only when correcting traits for differences in biomass. Vegetative traits showed higher plasticity and opposite genetic and plastic responses, masking the genetic component underlying field-observed trait variation. Our study suggests that genetic differentiation may be inferred from observational data only for the traits most closely related to fitness.

Bridging gaps in demographic analysis with phylogenetic imputation

Phylogenetically informed imputation methods have rarely been applied to estimate missing values in demographic data but may be a powerful tool for reconstructing vital rates of survival, maturation, and fecundity for species of conservation concern. Imputed vital rates could be used to parameterize demographic models to explore how populations respond when vital rates are perturbed. We used standardized vital rate estimates for 50 bird species to assess the use of phylogenetic imputation to fill gaps in demographic data. We calculated imputation accuracy for vital rates of focal species excluded from the data set either singly or in combination and with and without phylogeny, body mass, and life-history trait data. We used imputed vital rates to calculate demographic metrics, including generation time, to validate the use of imputation in demographic analyses. Covariance among vital rates and other trait data provided a strong basis to guide imputation of missing vital rates in birds, even in the absence of phylogenetic information. Mean NRMSE for null and phylogenetic models differed by <0.01 except when no vital rates were available or for vital rates with high phylogenetic signal (Pagel's λ > 0.8). In these cases, including body mass and life-history trait data compensated for lack of phylogenetic information: mean normalized root mean square error (NRMSE) for null and phylogenetic models differed by <0.01 for adult survival and <0.04 for maturation rate. Estimates of demographic metrics were sensitive to the accuracy of imputed vital rates. For example, mean error in generation time doubled in response to inaccurate estimates of maturation time. Accurate demographic data and metrics, such as generation time, are needed to inform conservation planning processes, for example through International Union for Conservation of Nature Red List assessments and population viability analysis. Imputed vital rates could be useful in this context but, as for any estimated model parameters, awareness of the sensitivities of demographic model outputs to the imputed vital rates is essential.

Characterizing the environmental drivers of the abundance and distribution of Alopecurus myosuroides on a national scale

BACKGROUND

Arable weeds threaten farming and food production, impacting on productivity. Large-scale data on weed populations are typically lacking, and changes are frequently undocumented until they reach problem levels. Managing the future spread of weeds requires that we understand the factors that influence current densities and distributions. In doing so, one of the challenges is to measure populations at a large enough scale to be able to accurately measure changes in densities and distributions. Here we analyse the density and distribution of a major weed (Alopecurus myosuroides) on a large scale. Our objectives were to (i) develop a methodology for rapid measurement of occurrence and abundance, (ii) test hypotheses about the roles of soils and climate variation in determining densities, and (iii) use this information to identify areas in which occurrence could increase in the future.

RESULTS

Populations were mapped through England over 4 years in 4631 locations. We also analysed UK atlas data published over the past 50 years. Densities of populations show significant interannual variability, but historical data show that the species has spread. We find significant impacts of soil and rainfall on densities, which increase with the proportion of heavy soils, but decrease with increasing rainfall. Compared with independent atlas data we found that our statistical models provide good predictions of large-scale occupancy and we provide maps of current and potential densities.

CONCLUSION

Models of spread highlight the localised nature of colonisation, and this emphasises the need for management to limit dispersal. Comparisons of current, historical and potential distributions suggest sizeable habitable areas in which increases in abundance are still possible. © 2021 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

The myriad of complex demographic responses of terrestrial mammals to climate change and gaps of knowledge: A global analysis

Approximately 25% of mammals are currently threatened with extinction, a risk that is amplified under climate change. Species persistence under climate change is determined by the combined effects of climatic factors on multiple demographic rates (survival, development and reproduction), and hence, population dynamics. Thus, to quantify which species and regions on Earth are most vulnerable to climate-driven extinction, a global understanding of how different demographic rates respond to climate is urgently needed. Here, we perform a systematic review of literature on demographic responses to climate, focusing on terrestrial mammals, for which extensive demographic data are available. To assess the full spectrum of responses, we synthesize information from studies that quantitatively link climate to multiple demographic rates. We find only 106 such studies, corresponding to 87 mammal species. These 87 species constitute <1% of all terrestrial mammals. Our synthesis reveals a strong mismatch between the locations of demographic studies and the regions and taxa currently recognized as most vulnerable to climate change. Surprisingly, for most mammals and regions sensitive to climate change, holistic demographic responses to climate remain unknown. At the same time, we reveal that filling this knowledge gap is critical as the effects of climate change will operate via complex demographic mechanisms: a vast majority of mammal populations display projected increases in some demographic rates but declines in others, often depending on the specific environmental context, complicating simple projections of population fates. Assessments of population viability under climate change are in critical need to gather data that account for multiple demographic responses, and coordinated actions to assess demography holistically should be prioritized for mammals and other taxa.

Herbaceous perennial plants with short generation time have stronger responses to climate anomalies than those with longer generation time

There is an urgent need to synthesize the state of our knowledge on plant responses to climate. The availability of open-access data provide opportunities to examine quantitative generalizations regarding which biomes and species are most responsive to climate drivers. Here, we synthesize time series of structured population models from 162 populations of 62 plants, mostly herbaceous species from temperate biomes, to link plant population growth rates (λ) to precipitation and temperature drivers. We expect: (1) more pronounced demographic responses to precipitation than temperature, especially in arid biomes; and (2) a higher climate sensitivity in short-lived rather than long-lived species. We find that precipitation anomalies have a nearly three-fold larger effect on λ than temperature. Species with shorter generation time have much stronger absolute responses to climate anomalies. We conclude that key species-level traits can predict plant population responses to climate, and discuss the relevance of this generalization for conservation planning.

Fine-scale spatial variation in fitness is comparable to disturbance-induced fluctuations in a fire-adapted species

The spatial scale at which demographic performance (e.g., net reproductive output) varies can profoundly influence landscape-level population growth and persistence, and many demographically pertinent processes such as species interactions and resource acquisition vary at fine scales. We compared the magnitude of demographic variation associated with fine-scale heterogeneity (<10 m), with variation due to larger-scale (>1 ha) fluctuations associated with fire disturbance. We used a spatially explicit model within an IPM modeling framework to evaluate the demographic importance of fine-scale variation. We used a measure of expected lifetime fruit production, E_F , that is assumed to be proportional to lifetime fitness. Demographic differences and their effects on E_F were assessed in a population of the herbaceous perennial Hypericum cumulicola (~2,600 individuals), within a patch of Florida rosemary scrub (400 × 80 m). We compared demographic variation over fine spatial scales to demographic variation between years across 6 yr after a fire. Values of E_F changed by orders of magnitude over <10 m. This variation in fitness over fine spatial scales (<10 m) is commensurate to postfire changes in fitness for this fire-adapted perennial. A life table response experiment indicated that fine-scale spatial variation in vital rates, especially survival, explains as much change in E_F as demographic changes caused by time-since-fire, a key driver in this system. Our findings show that environmental changes over a few tens of meters can have ecologically meaningful implications for population growth and extinction.

Strengthening the evidence base for temperature-mediated phenological asynchrony and its impacts

Climate warming has caused the seasonal timing of many components of ecological food chains to advance. In the context of trophic interactions, the match-mismatch hypothesis postulates that differential shifts can lead to phenological asynchrony with negative impacts for consumers. However, at present there has been no consistent analysis of the links between temperature change, phenological asynchrony and individual-to-population-level impacts across taxa, trophic levels and biomes at a global scale. Here, we propose five criteria that all need to be met to demonstrate that temperature-mediated trophic asynchrony poses a growing risk to consumers. We conduct a literature review of 109 papers studying 129 taxa, and find that all five criteria are assessed for only two taxa, with the majority of taxa only having one or two criteria assessed. Crucially, nearly every study was conducted in Europe or North America, and most studies were on terrestrial secondary consumers. We thus lack a robust evidence base from which to draw general conclusions about the risk that climate-mediated trophic asynchrony may pose to populations worldwide.

Environmental change reduces body condition, but not population growth, in a high-arctic herbivore

Environmental change influences fitness-related traits and demographic rates, which in herbivores are often linked to resource-driven variation in body condition. Coupled body condition-demographic responses may therefore be important for herbivore population dynamics in fluctuating environments, such as the Arctic. We applied a transient Life-Table Response Experiment ('transient-LTRE') to demographic data from Svalbard barnacle geese (Branta leucopsis), to quantify their population-dynamic responses to changes in body mass. We partitioned contributions from direct and delayed demographic and body condition-mediated processes to variation in population growth. Declines in body condition (1980-2017), which positively affected reproduction and fledgling survival, had negligible consequences for population growth. Instead, population growth rates were largely reproduction-driven, in part through positive responses to rapidly advancing spring phenology. The virtual lack of body condition-mediated effects indicates that herbivore population dynamics may be more resilient to changing body condition than previously expected, with implications for their persistence under environmental change.

Publisher Correction: Evolution of generalist resistance to herbicide mixtures reveals a trade-off in resistance management

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

Changes in age-structure over four decades were a key determinant of population growth rate in a long-lived mammal

A changing environment directly influences birth and mortality rates, and thus population growth rates. However, population growth rates in the short term are also influenced by population age-structure. Despite its importance, the contribution of age-structure to population growth rates has rarely been explored empirically in wildlife populations with long-term demographic data. Here we assessed how changes in age-structure influenced short-term population dynamics in a semi-captive population of Asian elephants Elephas maximus. We addressed this question using a demographic dataset of female Asian elephants from timber camps in Myanmar spanning 45 years (1970-2014). First, we explored temporal variation in age-structure. Then, using annual matrix population models, we used a retrospective approach to assess the contributions of age-structure and vital rates to short-term population growth rates with respect to the average environment. Age-structure was highly variable over the study period, with large proportions of juveniles in the years 1970 and 1985, and made a substantial contribution to annual population growth rate deviations. High adult birth rates between 1970 and 1980 would have resulted in large positive population growth rates, but these were prevented by a low proportion of reproductive-aged females. We highlight that an understanding of both age-specific vital rates and age-structure is needed to assess short-term population dynamics. Furthermore, this example from a human-managed system suggests that the importance of age-structure may be accentuated in populations experiencing human disturbance where age-structure is unstable, such as those in captivity or for endangered species. Ultimately, changes to the environment drive population dynamics by influencing birth and mortality rates, but understanding demographic structure is crucial for assessing population growth.

Evolution of generalist resistance to herbicide mixtures reveals a trade-off in resistance management

Intense selection by pesticides and antibiotics has resulted in a global epidemic of evolved resistance. In agriculture and medicine, using mixtures of compounds from different classes is widely accepted as optimal resistance management. However, this strategy may promote the evolution of more generalist resistance mechanisms. Here we test this hypothesis at a national scale in an economically important agricultural weed: blackgrass (Alopecurus myosuroides), for which herbicide resistance is a major economic issue. Our results reveal that greater use of herbicide mixtures is associated with lower levels of specialist resistance mechanisms, but higher levels of a generalist mechanism implicated in enhanced metabolism of herbicides with diverse modes of action. Our results indicate a potential evolutionary trade-off in resistance management, whereby attempts to reduce selection for specialist resistance traits may promote the evolution of generalist resistance. We contend that where specialist and generalist resistance mechanisms co-occur, similar trade-offs will be evident, calling into question the ubiquity of resistance management based on mixtures and combination therapies.

Mixtures of antibiotics or pesticides can help reduce the evolution of resistance to individual compounds. Here, Comont et al. show that in blackgrass, an important agricultural weed, herbicide mixtures do reduce specialized resistance but instead can select for a generalized resistance mechanism.

Long-term trends in wild-capture and population dynamics point to an uncertain future for captive elephants

Maintaining sustainable populations in captivity without supplementation through wild-capture is a major challenge in conservation that zoos and aquaria are working towards. However, the capture of wild animals continues for many purposes where conservation is not the primary focus. Wild-capture hinders long-term conservation goals by reducing remaining wild populations, but the direct and long-term indirect consequences of wild-capture for captive population viability are rarely addressed using longitudinal data. We explored the implications of changes in wild-capture on population dynamics in captivity over 54 years using a multi-generational studbook of working Asian elephants ( Elephas maximus) from Myanmar, the largest remaining captive elephant population. Here we show that population growth and birth rates declined between 1960 and 2014 with declines in wild-capture. Importantly, wild-caught females had reduced birth rates and a higher mortality risk. However, despite the disadvantages of wild-capture, the population may not be sustainable without it, with immediate declines owing to an unstable age-structure that may last for 50 years. Our results highlight the need to assess the long-term demographic consequences of wild-capture to ensure the sustainability of captive and wild populations as species are increasingly managed and conserved in altered or novel environments.

Feeding a city - Leicester as a case study of the importance of allotments for horticultural production in the UK

The process of urbanization has detached a large proportion of the global population from involvement with food production. However, there has been a resurgence in interest in urban agriculture and there is widespread recognition by policy-makers of its potential contribution to food security. Despite this, there is little data on urban agricultural production by non-commercial small-scale growers. We combine citizen science data for self-provisioning crop yields with field-mapping and GIS-based analysis of allotments in Leicester, UK, to provide an estimate of allotment fruit and vegetable production at a city-scale. In addition, we examine city-scale changes in allotment land provision on potential crop production over the past century. The average area of individual allotment plots used to grow crops was 52%. Per unit area yields for the majority of crops grown in allotments were similar to those of UK commercial horticulture. We estimate city-wide allotment production of >1200 t of fruit and vegetables and 200 t of potatoes per annum, equivalent to feeding >8500 people. If the 13% of plots that are completely uncultivated were used this could increase production to >1400 t per annum, feeding ~10,000 people, however this production may not be located in areas where there is greatest need for increased access to fresh fruits and vegetables. The citywide contribution of allotment cultivation peaked in the 1950s when 475 ha of land was allotments, compared to 97 ha currently. This suggests a decline from >45,000 to <10,000 of people fed per annum. We demonstrate that urban allotments make a small but important contribution to the fruit and vegetable diet of a UK city. However, further urban population expansion will exert increasing development pressure on allotment land. Policy-makers should both protect allotments within cities, and embed urban agricultural land within future developments to improve local food security.

Global gene flow releases invasive plants from environmental constraints on genetic diversity

When plants establish outside their native range, their ability to adapt to the new environment is influenced by both demography and dispersal. However, the relative importance of these two factors is poorly understood. To quantify the influence of demography and dispersal on patterns of genetic diversity underlying adaptation, we used data from a globally distributed demographic research network comprising 35 native and 18 nonnative populations of Plantago lanceolata Species-specific simulation experiments showed that dispersal would dilute demographic influences on genetic diversity at local scales. Populations in the native European range had strong spatial genetic structure associated with geographic distance and precipitation seasonality. In contrast, nonnative populations had weaker spatial genetic structure that was not associated with environmental gradients but with higher within-population genetic diversity. Our findings show that dispersal caused by repeated, long-distance, human-mediated introductions has allowed invasive plant populations to overcome environmental constraints on genetic diversity, even without strong demographic changes. The impact of invasive plants may, therefore, increase with repeated introductions, highlighting the need to constrain future introductions of species even if they already exist in an area.

Assessing seasonal demographic covariation to understand environmental-change impacts on a hibernating mammal

Natural populations are exposed to seasonal variation in environmental factors that simultaneously affect several demographic rates (survival, development and reproduction). The resulting covariation in these rates determines population dynamics, but accounting for its numerous biotic and abiotic drivers is a significant challenge. Here, we use a factor-analytic approach to capture partially unobserved drivers of seasonal population dynamics. We use 40 years of individual-based demography from yellow-bellied marmots (Marmota flaviventer) to fit and project population models that account for seasonal demographic covariation using a latent variable. We show that this latent variable, by producing positive covariation among winter demographic rates, depicts a measure of environmental quality. Simultaneously, negative responses of winter survival and reproductive-status change to declining environmental quality result in a higher risk of population quasi-extinction, regardless of summer demography where recruitment takes place. We demonstrate how complex environmental processes can be summarized to understand population persistence in seasonal environments.

The costs of human-induced evolution in an agricultural system

Pesticides have underpinned significant improvements in global food security, albeit with associated environmental costs. Currently, the yield benefits of pesticides are threatened as overuse has led to wide-scale evolution of resistance. Yet despite this threat, there are no large-scale estimates of crop yield losses or economic costs due to resistance. Here, we combine national-scale density and resistance data for the weed Alopecurus myosuroides (black-grass) with crop yield maps and a new economic model to estimate that the annual cost of resistance in England is £0.4bn in lost gross profit (2014 prices), and annual wheat yield loss due to resistance is 0.8 million tonnes. A total loss of herbicide control against black-grass would cost £1bn and 3.4 million tonnes of lost wheat yield annually. Worldwide, there are 253 herbicide-resistant weeds, so the global impact of resistance could be enormous. Our research provides an urgent case for national-scale planning to combat further evolution of resistance, and an incentive for policies focused on increasing yields through more sustainable food-production systems rather than relying so heavily on herbicides.

Cumulative weather effects can impact across the whole life cycle

Predicting how species will be affected by future climatic change requires the underlying environmental drivers to be identified. As vital rates vary over the lifecycle, structured population models derived from statistical environment-demography relationships are often used to inform such predictions. Environmental drivers are typically identified independently for different vital rates and demographic classes. However, these rates often exhibit positive temporal covariance, suggesting that vital rates respond to common environmental drivers. Additionally, models often only incorporate average weather conditions during a single, a priori chosen time window (e.g. monthly means). Mismatches between these windows and the period when the vital rates are sensitive to variation in climate decrease the predictive performance of such approaches. We used a demographic structural equation model (SEM) to demonstrate that a single axis of environmental variation drives the majority of the (co)variation in survival, reproduction, and twinning across six age-sex classes in a Soay sheep population. This axis provides a simple target for the complex task of identifying the drivers of vital rate variation. We used functional linear models (FLMs) to determine the critical windows of three local climatic drivers, allowing the magnitude and direction of the climate effects to differ over time. Previously unidentified lagged climatic effects were detected in this well-studied population. The FLMs had a better predictive performance than selecting a critical window a priori, but not than a large-scale climate index. Positive covariance amongst vital rates and temporal variation in the effects of environmental drivers are common, suggesting our SEM-FLM approach is a widely applicable tool for exploring the joint responses of vital rates to environmental change.

Testing the ability of unmanned aerial systems and machine learning to map weeds at subfield scales: a test with the weed Alopecurus myosuroides (Huds)

BACKGROUND

It is important to map agricultural weed populations to improve management and maintain future food security. Advances in data collection and statistical methodology have created new opportunities to aid in the mapping of weed populations. We set out to apply these new methodologies (unmanned aerial systems; UAS) and statistical techniques (convolutional neural networks; CNN) to the mapping of black-grass, a highly impactful weed in wheat fields in the UK. We tested this by undertaking extensive UAS and field-based mapping over the course of 2 years, in total collecting multispectral image data from 102 fields, with 76 providing informative data. We used these data to construct a vegetation index (VI), which we used to train a custom CNN model from scratch. We undertook a suite of data engineering techniques, such as balancing and cleaning to optimize performance of our metrics. We also investigate the transferability of the models from one field to another.

RESULTS

The results show that our data collection methodology and implementation of CNN outperform pervious approaches in the literature. We show that data engineering to account for 'artefacts' in the image data increases our metrics significantly. We are not able to identify any traits that are shared between fields that result in high scores from our novel leave one field our cross validation (LOFO-CV) tests.

CONCLUSION

We conclude that this evaluation procedure is a better estimation of real-world predictive value when compared with past studies. We conclude that by engineering the image data set into discrete classes of data quality we increase the prediction accuracy from the baseline model by 5% to an area under the curve (AUC) of 0.825. We find that the temporal effects studied here have no effect on our ability to model weed densities. © 2019 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Measuring the effectiveness of management interventions at regional scales by integrating ecological monitoring and modelling

BACKGROUND

Because of site-specific effects and outcomes, it is often difficult to know whether a management strategy for the control of pests has worked or not. Population dynamics of pests are typically spatially and temporally variable. Moreover, interventions at the scale of individual fields or farms are essentially unreplicated experiments; a decrease in a target population following management cannot safely be interpreted as success because, for example, it might simply be a poor year for that species. Here, we argue that if large-scale data are available, population models can be used to measure outcomes against the prevailing mean and variance. We apply this approach to the problem of rotational management of the weed Alopecurus myosuroides.

RESULTS

We derived density-structured population models for a set of fields that were not subject to rotational management (continuous winter wheat) and another group that were (rotated into spring barley to control A. myosuroides). We used these models to construct means and variances of the outcomes of management for given starting conditions, and to conduct transient growth analysis. We show that, overall, this management strategy is successful in reducing densities of weeds, albeit with considerable variance. However, we also show that one variant (rotation to spring barley along with variable sowing) shows little evidence for additional control.

CONCLUSION

Our results suggest that rotational strategies can be effective in the control of this weed, but also that strategies require careful evaluation against a background of spatiotemporal variation. © 2017 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Transient LTRE analysis reveals the demographic and trait-mediated processes that buffer population growth

Temporal variation in environmental conditions affects population growth directly via its impact on vital rates, and indirectly through induced variation in demographic structure and phenotypic trait distributions. We currently know very little about how these processes jointly mediate population responses to their environment. To address this gap, we develop a general transient life table response experiment (LTRE) which partitions the contributions to population growth arising from variation in (1) survival and reproduction, (2) demographic structure, (3) trait values and (4) climatic drivers. We apply the LTRE to a population of yellow‐bellied marmots (Marmota flaviventer) to demonstrate the impact of demographic and trait‐mediated processes. Our analysis provides a new perspective on demographic buffering, which may be a more subtle phenomena than is currently assumed. The new LTRE framework presents opportunities to improve our understanding of how trait variation influences population dynamics and adaptation in stochastic environments.

Reviewing research priorities in weed ecology, evolution and management: a horizon scan

Weedy plants pose a major threat to food security, biodiversity, ecosystem services and consequently to human health and wellbeing. However, many currently used weed management approaches are increasingly unsustainable. To address this knowledge and practice gap, in June 2014, 35 weed and invasion ecologists, weed scientists, evolutionary biologists and social scientists convened a workshop to explore current and future perspectives and approaches in weed ecology and management. A horizon scanning exercise ranked a list of 124 pre-submitted questions to identify a priority list of 30 questions. These questions are discussed under seven themed headings that represent areas for renewed and emerging focus for the disciplines of weed research and practice. The themed areas considered the need for transdisciplinarity, increased adoption of integrated weed management and agroecological approaches, better understanding of weed evolution, climate change, weed invasiveness and finally, disciplinary challenges for weed science. Almost all the challenges identified rested on the need for continued efforts to diversify and integrate agroecological, socio-economic and technological approaches in weed management. These challenges are not newly conceived, though their continued prominence as research priorities highlights an ongoing intransigence that must be addressed through a more system-oriented and transdisciplinary research agenda that seeks an embedded integration of public and private research approaches. This horizon scanning exercise thus set out the building blocks needed for future weed management research and practice; however, the challenge ahead is to identify effective ways in which sufficient research and implementation efforts can be directed towards these needs.

Funder Restrictions on Application Numbers Lead to Chaos

Restricting application rates is an attractive way for funders to reduce time and money wasted evaluating uncompetitive applications. However, mathematical models show that this could induce chaotic cycles in total application numbers, increasing uncertainty in the funding process. One emergent property is that smaller institutions spend disproportionally more time unfunded.

Using an integral projection model to assess the effect of temperature on the growth of gilthead seabream Sparus aurata

Accurate information on the growth rates of fish is crucial for fisheries stock assessment and management. Empirical life history parameters (von Bertalanffy growth) are widely fitted to cross-sectional size-at-age data sampled from fish populations. This method often assumes that environmental factors affecting growth remain constant over time. The current study utilized longitudinal life history information contained in otoliths from 412 juveniles and adults of gilthead seabream, Sparus aurata, a commercially important species fished and farmed throughout the Mediterranean. Historical annual growth rates over 11 consecutive years (2002-2012) in the Gulf of Lions (NW Mediterranean) were reconstructed to investigate the effect of temperature variations on the annual growth of this fish. S. aurata growth was modelled linearly as the relationship between otolith size at year t against otolith size at the previous year t-1. The effect of temperature on growth was modelled with linear mixed effects models and a simplified linear model to be implemented in a cohort Integral Projection Model (cIPM). The cIPM was used to project S. aurata growth, year to year, under different temperature scenarios. Our results determined current increasing summer temperatures to have a negative effect on S. aurata annual growth in the Gulf of Lions. They suggest that global warming already has and will further have a significant impact on S. aurata size-at-age, with important implications for age-structured stock assessments and reference points used in fisheries.

Interactions between immunotoxicants and parasite stress: Implications for host health

Many organisms face a wide variety of biotic and abiotic stressors which reduce individual survival, interacting to further reduce fitness. Here we studied the effects of two such interacting stressors: immunotoxicant exposure and parasite infection. We model the dynamics of a within-host infection and the associated immune response of an individual. We consider both the indirect sub-lethal effects on immunosuppression and the direct effects on health and mortality of individuals exposed to toxicants. We demonstrate that sub-lethal exposure to toxicants can promote infection through the suppression of the immune system. This happens through the depletion of the immune response which causes rapid proliferation in parasite load. We predict that the within-host parasite density is maximised by an intermediate toxicant exposure, rather than continuing to increase with toxicant exposure. In addition, high toxicant exposure can alter cellular regulation and cause the breakdown of normal healthy tissue, from which we infer higher mortality risk of the host. We classify this breakdown into three phases of increasing toxicant stress, and demonstrate the range of conditions under which toxicant exposure causes failure at the within-host level. These phases are determined by the relationship between the immunity status, overall cellular health and the level of toxicant exposure. We discuss the implications of our model in the context of individual bee health. Our model provides an assessment of how pesticide stress and infection interact to cause the breakdown of the within-host dynamics of individual bees.

Evaluating the potential of Unmanned Aerial Systems for mapping weeds at field scales: a case study with Alopecurus myosuroides

Mapping weed densities within crops has conventionally been achieved either by detailed ecological monitoring or by field walking, both of which are time-consuming and expensive. Recent advances have resulted in increased interest in using Unmanned Aerial Systems (UAS) to map fields, aiming to reduce labour costs and increase the spatial extent of coverage. However, adoption of this technology ideally requires that mapping can be undertaken automatically and without the need for extensive ground-truthing. This approach has not been validated at large scale using UAS-derived imagery in combination with extensive ground-truth data. We tested the capability of UAS for mapping a grass weed, Alopecurus myosuroides, in wheat crops. We addressed two questions: (i) can imagery accurately measure densities of weeds within fields and (ii) can aerial imagery of a field be used to estimate the densities of weeds based on statistical models developed in other locations? We recorded aerial imagery from 26 fields using a UAS. Images were generated using both RGB and Rmod (Rmod 670-750 nm) spectral bands. Ground-truth data on weed densities were collected simultaneously with the aerial imagery. We combined these data to produce statistical models that (i) correlated ground-truth weed densities with image intensity and (ii) forecast weed densities in other fields. We show that weed densities correlated with image intensity, particularly Rmod image data. However, results were mixed in terms of out of sample prediction from field-to-field. We highlight the difficulties with transferring models and we discuss the challenges for automated weed mapping using UAS technology.

The evolution of labile traits in sex- and age-structured populations

Many quantitative traits are labile (e.g. somatic growth rate, reproductive timing and investment), varying over the life cycle as a result of behavioural adaptation, developmental processes and plastic responses to the environment. At the population level, selection can alter the distribution of such traits across age classes and among generations. Despite a growing body of theoretical research exploring the evolutionary dynamics of labile traits, a data‐driven framework for incorporating such traits into demographic models has not yet been developed.

Integral projection models (IPMs) are increasingly being used to understand the interplay between changes in labile characters, life histories and population dynamics. One limitation of the IPM approach is that it relies on phenotypic associations between parents and offspring traits to capture inheritance. However, it is well‐established that many different processes may drive these associations, and currently, no clear consensus has emerged on how to model micro‐evolutionary dynamics in an IPM framework.

We show how to embed quantitative genetic models of inheritance of labile traits into age‐structured, two‐sex models that resemble standard IPMs. Commonly used statistical tools such as GLMs and their mixed model counterparts can then be used for model parameterization. We illustrate the methodology through development of a simple model of egg‐laying date evolution, parameterized using data from a population of Great tits (Parus major).

We demonstrate how our framework can be used to project the joint dynamics of species' traits and population density. We then develop a simple extension of the age‐structured Price equation (ASPE) for two‐sex populations, and apply this to examine the age‐specific contributions of different processes to change in the mean phenotype and breeding value.

The data‐driven framework we outline here has the potential to facilitate greater insight into the nature of selection and its consequences in settings where focal traits vary over the lifetime through ontogeny, behavioural adaptation and phenotypic plasticity, as well as providing a potential bridge between theoretical and empirical studies of labile trait variation.

Eco-evolutionary Biology: Feeding and Feedback Loops

A dogma in ecology and evolution holds that the environment is an extrinsic force that is not, in turn, shaped by the adaptive evolution of species. Recent work on stickleback life history, community ecology and speciation challenges this dogma.

The effects of asymmetric competition on the life history of Trinidadian guppies

The effects of asymmetric interactions on population dynamics has been widely investigated, but there has been little work aimed at understanding how life history parameters like generation time, life expectancy and the variance in lifetime reproductive success are impacted by different types of competition. We develop a new framework for incorporating trait‐mediated density‐dependence into size‐structured models and use Trinidadian guppies to show how different types of competitive interactions impact life history parameters. Our results show the degree of symmetry in competitive interactions can have dramatic effects on the speed of the life history. For some vital rates, shifting the competitive superiority from small to large individuals resulted in a doubling of the generation time. Such large influences of competitive symmetry on the timescale of demographic processes, and hence evolution, highlights the interwoven nature of ecological and evolutionary processes and the importance of density‐dependence in understanding eco‐evolutionary dynamics.

Opportunities and challenges of Integral Projection Models for modelling host-parasite dynamics

Epidemiological dynamics are shaped by and may in turn shape host demography. These feedbacks can result in hard to predict patterns of disease incidence. Mathematical models that integrate infection and demography are consequently a key tool for informing expectations for disease burden and identifying effective measures for control.

A major challenge is capturing the details of infection within individuals and quantifying their downstream impacts to understand population‐scale outcomes. For example, parasite loads and antibody titres may vary over the course of an infection and contribute to differences in transmission at the scale of the population. To date, to capture these subtleties, models have mostly relied on complex mechanistic frameworks, discrete categorization and/or agent‐based approaches.

Integral Projection Models (IPMs) allow variance in individual trajectories of quantitative traits and their population‐level outcomes to be captured in ways that directly reflect statistical models of trait–fate relationships. Given increasing data availability, and advances in modelling, there is considerable potential for extending this framework to traits of relevance for infectious disease dynamics.

Here, we provide an overview of host and parasite natural history contexts where IPMs could strengthen inference of population dynamics, with examples of host species ranging from mice to sheep to humans, and parasites ranging from viruses to worms. We discuss models of both parasite and host traits, provide two case studies and conclude by reviewing potential for both ecological and evolutionary research.

The ecological forecast horizon, and examples of its uses and determinants

Forecasts of ecological dynamics in changing environments are increasingly important, and are available for a plethora of variables, such as species abundance and distribution, community structure and ecosystem processes. There is, however, a general absence of knowledge about how far into the future, or other dimensions (space, temperature, phylogenetic distance), useful ecological forecasts can be made, and about how features of ecological systems relate to these distances. The ecological forecast horizon is the dimensional distance for which useful forecasts can be made. Five case studies illustrate the influence of various sources of uncertainty (e.g. parameter uncertainty, environmental variation, demographic stochasticity and evolution), level of ecological organisation (e.g. population or community), and organismal properties (e.g. body size or number of trophic links) on temporal, spatial and phylogenetic forecast horizons. Insights from these case studies demonstrate that the ecological forecast horizon is a flexible and powerful tool for researching and communicating ecological predictability. It also has potential for motivating and guiding agenda setting for ecological forecasting research and development.

Inferring the temperature dependence of population parameters: the effects of experimental design and inference algorithm

Understanding and quantifying the temperature dependence of population parameters, such as intrinsic growth rate and carrying capacity, is critical for predicting the ecological responses to environmental change. Many studies provide empirical estimates of such temperature dependencies, but a thorough investigation of the methods used to infer them has not been performed yet. We created artificial population time series using a stochastic logistic model parameterized with the Arrhenius equation, so that activation energy drives the temperature dependence of population parameters. We simulated different experimental designs and used different inference methods, varying the likelihood functions and other aspects of the parameter estimation methods. Finally, we applied the best performing inference methods to real data for the species Paramecium caudatum. The relative error of the estimates of activation energy varied between 5% and 30%. The fraction of habitat sampled played the most important role in determining the relative error; sampling at least 1% of the habitat kept it below 50%. We found that methods that simultaneously use all time series data (direct methods) and methods that estimate population parameters separately for each temperature (indirect methods) are complementary. Indirect methods provide a clearer insight into the shape of the functional form describing the temperature dependence of population parameters; direct methods enable a more accurate estimation of the parameters of such functional forms. Using both methods, we found that growth rate and carrying capacity of Paramecium caudatum scale with temperature according to different activation energies. Our study shows how careful choice of experimental design and inference methods can increase the accuracy of the inferred relationships between temperature and population parameters. The comparison of estimation methods provided here can increase the accuracy of model predictions, with important implications in understanding and predicting the effects of temperature on the dynamics of populations.