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Matrix population models (MPMs) are an important tool for biologists seeking to understand the causes and consequences of variation in vital rates (e.g. survival, reproduction) across life cycles. Empirical MPMs describe the age- or stage-structured demography of organisms and usually represent the life history of a population during a particular time frame at a specific geographical location. The COMPADRE Plant Matrix Database and COMADRE Animal Matrix Database are the most extensive resources for MPM data, collectively containing >12,000 individual projection matrices for >1,100 species globally. Although these databases represent an unparalleled resource for researchers, land managers and educators, the current computational tools available to answer questions with MPMs impose significant barriers to potential COM(P)ADRE database users by requiring advanced knowledge to handle diverse data structures and program custom analysis functions. To close this knowledge gap, we present two interrelated R packages designed to (a) facilitate the use of these databases by providing functions to acquire, quality control and manage both the MPM data contained in COMPADRE and COMADRE, and a user's own MPM data (Rcompadre) and (b) present a range of functions to calculate life-history traits from MPMs in support of ecological and evolutionary analyses (Rage). We provide examples to illustrate the use of both. Rcompadre and Rage will facilitate demographic analyses using MPM data and contribute to the improved replicability of studies using these data. We hope that this new functionality will allow researchers, land managers and educators to unlock the potential behind the thousands of MPMs and ancillary metadata stored in the COMPADRE and COMADRE matrix databases, and in their own MPM data.

International audience; Species extinction risk is accelerating due to anthropogenic climate change, making it urgent to protect vulnerable species through legal frameworks in order to facilitate conservation actions that help mitigate risk. Here, we discuss fundamental concepts for assessing climate change risks to species using the example of the emperor penguin (Aptenodytes forsteri), currently being considered for protection under the US Endangered Species Act (ESA). This species forms colonies on Antarctic sea ice, which is projected to significantly decline due to ongoing greenhouse gas (GHG) emissions. We project the dynamics of all known emperor penguin colonies under different GHG emission scenarios using a climate-dependent meta-population model including the effects of extreme climate events based on the observational satellite record of colonies. Assessments for listing species under the ESA require information about how species resiliency, redundancy and representation (3Rs) will be affected by threats within the foreseeable future. Our results show that if sea ice declines at the rate projected by climate models under current energy system trends and policies, the 3Rs would be dramatically reduced and almost all colonies would become quasi-extinct by 2100. We conclude that the species should be listed as threatened under the ESA.

Detailed, long-term datasets on the life histories of long-lived species such as great apes are necessary to understand their survival patterns but are relatively rare. Such information requires prolonged and consistent record-keeping over many generations, so for chimpanzees (Pan troglodytes), this equates to many decades of input. As life history variables can be altered by differences in environmental influences (whether natural or artificial), there is substantial value to being able to compare across populations. Here, we present the first comparative analysis of life history data for two ex situ chimpanzee populations residing in North America (1975–2020;n= 730) and Japan (1980–2020;n= 660). Overall, survival patterns were similar between regions, and the median life expectancy from birth is estimated at 35.7 (95% CI = [32.4–40.0]) years for females and 30.1 (27.3–34.3) years for males across both populations. Females who survive to their first birthday are estimated to survive 42.4 (40.0–46.3) years and males 35.5 (32.6–38.0) years. We found that birth type (wild-born or captive-born) did not influence survival patterns in either population, but there were differential effects of sex on longevity. In the America population, males had higher mortality rates than females, whereas in the Japan population we found no differences between the sexes. First year mortality did not differ between populations for males (18–20%), but for females it was lower in America (15%) compared to Japan (25%). Survival patterns of chimpanzees in the present study will be useful for future investigation into potential causes of regional differences and cross-species comparisons.

The electric power grid is a critical societal resource connecting multiple infrastructural domains such as agriculture, transportation, and manufacturing. The electrical grid as an infrastructure is shaped by human activity and public policy in terms of demand and supply requirements. Further, the grid is subject to changes and stresses due to diverse factors including solar weather, climate, hydrology, and ecology. The emerging interconnected and complex network dependencies make such interactions increasingly dynamic, posing novel risks, and presenting new challenges to manage the coupled human–natural system. This paper provides a survey of models and methods that seek to explore the significant interconnected impact of the electric power grid and interdependent domains. We also provide relevant critical risk indicators (CRIs) across diverse domains that may be used to assess risks to electric grid reliability, including climate, ecology, hydrology, finance, space weather, and agriculture. We discuss the convergence of indicators from individual domains to explore possible systemic risk, i.e., holistic risk arising from cross-domain interconnections. Further, we propose a compositional approach to risk assessment that incorporates diverse domain expertise and information, data science, and computer science to identify domain-specific CRIs and their union in systemic risk indicators. Our study provides an important first step towards data-driven analysis and predictive modeling of risks in interconnected human–natural systems.

Recent concerns about the viability of zoo populations have motivated studies on the historic and current status of animal populations in North American and European zoos. However, these evaluations may not accurately reflect the populations' long-term viability in the decades to come. Here, we assessed the projected future status of North American zoo populations by conducting standardized population viability analyses (PVAs) for 137 cooperative breeding programs. We summarized PVA results to describe patterns in viability across populations, and examined whether viability can be predicted by biological or management-based factors. Under recent management practices and without imports or exports of animals, 64% of populations will decline in size over the next 25 years, and only 18% would retain ≥90% of the founding gene diversity (GD) in 100 years. However, viability would improve if programs can implement management changes (e.g., increasing reproduction, increasing holding space, and importing genetically unique individuals, as appropriate): only 16% of populations would still decline in 25 years, and 49% would retain ≥90% GD in 100 years. Programs with more participating institutions and a "green" Association of Zoos and Aquariums animal program designation were projected to have higher metrics of demographic viability, and those with longer lifespans and lower recent death rates were projected to have higher metrics of genetic viability. Due to the large variation in species life history, management goals, and constraints across programs, our findings suggest there is unlikely to be a single path to long-term viability that would be appropriate for all zoo populations.

SummaryMatrix population models (MPMs) are an important tool for biologists seeking to understand the causes and consequences of variation in vital rates (e.g., survival, reproduction) across life cycles. Empirical MPMs describe the age- or stage-structured demography of organisms and usually represent the life history of a population during a particular time frame at a specific geographic location.The COMPADRE Plant Matrix Database and COMADRE Animal Matrix Database are the most extensive resources for MPM data, collectively containing >12,000 individual projection matrices for >1,100 species globally. Although these databases represent an unparalleled resource for researchers, land managers, and educators, the current computational tools available to answer questions with MPMs impose significant barriers to potential COM(P)ADRE database users by requiring advanced knowledge to handle diverse data structures and program custom analysis functions.To close this knowledge gap, we present two interrelated R packages designed to (i) facilitate the use of these databases by providing functions to acquire, quality control, and manage both the MPM data contained in COMPADRE and COMADRE, and a user’s own MPM data (Rcompadre), and (ii) present a range of functions to calculate life history traits from MPMs in support of ecological and evolutionary analyses (Rage). We provide examples to illustrate the use of both.Rcompadre and Rage will facilitate demographic analyses using MPM data and contribute to the improved replicability of studies using these data. We hope that this new functionality will allow researchers, land managers, and educators to unlock the potential behind the thousands of MPMs and ancillary metadata stored in the COMPADRE and COMADRE matrix databases, and in their own MPM data.

To mitigate and adapt to climate change, there is an urgent need to synthesize the state of our knowledge on plant responses to climate. The availability of open-access data, combined with our understanding of plant physiology and life history theory provide opportunities to examine quantitative generalizations regarding which biomes and species are most responsive to climate drivers. Here, we synthesized time series of structured population models from 165 populations from 62 plants around the globe to link plant population growth rates to precipitation and temperature drivers. We expected: (1) more pronounced demographic responses to precipitation than temperature, especially in arid biomes; (2) a higher climate sensitivity in short-lived rather than long-lived species; and (3) a stronger response to climate by species that reproduce more frequently. We found that precipitation anomalies have a nearly three-fold larger effect on λ than temperature. Precipitation has substantially more pronounced effects in more arid sites, but large noise makes this relationship non-significant. Species with shorter generation time have much stronger absolute responses to climate anomalies, while the degree of iteroparity does not correlate with population responses to climate. We conclude that key species-level traits can predict plant population responses to climate, and discuss the relevance of this generalization for conservation planning and evolutionary theory.

The U.S. Endangered Species Act (ESA) is widely considered the strongest biodiversity conservation law in the world. Part of its strength comes from the mandate to use the best available science to make decisions under the law, including whether to list a species, setting the criteria for when a species can be considered recovered, and determining when those criteria have been met and a species can be delisted. Both biological status and threat factors are considered at each stage of the listing and delisting process. In most cases, conservation science would suggest that species at risk enough to be listed under the Act should be more abundant and secure at delisting than they were at listing. Surprisingly, we identified 130 ESA-listed species that the U.S. Fish and Wildlife Service could consider recovered with fewer populations or individuals than existed at the time of listing. We ask whether their ESA recovery plans present scientific data, rationale, or evidence to support a decline in abundance as part of recovery. We find that almost no plan clearly explains why a decline is allowed. Fewer than half of the plans provide scientific support for a decline in the form of literature references or modeling results. We recommend that the U.S. Fish and Wildlife Service and the National Marine Fisheries Service create a decision support system to inform when species can decline in abundance and still recover, including guidance on (a) the need to explicitly address the declines and (b) the science used to support the decisions.

In recent years, the ex situ population of the endangered black-footed ferret (Mustela nigripes; ferret) has experienced a decline in normal sperm morphology (from 50% to 20%), which may be linked to inbreeding depression and/or a dietary change. We examined the effects of adding carcass and vitamin E to the diet on stress and reproductive biomarkers in male ferrets (n = 42 males including 16 juveniles and 26 adults) housed at the U.S. Fish and Wildlife National Black-footed Ferret Conservation Center (Carr, CO, USA). Fecal samples (3x/week) were collected from November and December (pre-breeding season, no diet change), February through May (breeding season, diet change) and June (post-breeding season, diet change) and analyzed for fecal glucocorticoid metabolites (FGM) via a corticosterone enzyme immunoassay (EIA). A subset of samples from adult males (n = 15) were analyzed for fecal androgen metabolites (FAM) via a testosterone EIA. We first used a linear mixed effects model to identify the important fixed effects among meat treatment, vitamin E treatment, age class (juvenile or adult), and all possible interactions on each hormone. We then examined the important factor’s effects across seasons using the non-parametric Friedman test. We found that age did not influence (p = 0.33) FGMs; however there was a significant effect of meat treatment on FGM (p = 0.04) and an effect of vitamin E on FAMs (p0.05) between during and post-breeding season periods. Males that were not fed carcass had higher (p0.05). Males supplemented with vitamin E had higher (p

Lack of demographic data for most of the world's threatened species is a widespread problem that precludes viability-based status assessments for species conservation. A commonly suggested solution is to use data from species that are closely related or biologically similar to the focal species. This approach assumes similar species and populations of the same species have similar demographic rates, an assumption that has yet to be thoroughly tested. We constructed a Bayesian hierarchical model with data on 425 plant species to predict demographic rates (intrinsic rate of population growth, recruit survival, juvenile survival, adult survival, and fecundity) based on biological traits and phylogenetic relatedness. Generally, we found small effects of species-level traits (except woody polycarpic species tended to have high adult survival rates that increased with plant height) and a weak phylogenetic signal for 4 of the 5 demographic parameters examined. Patterns were stronger in adult survival and fecundity than other demographic rates; however, the unexplained variances at both the species and population levels were high for all demographic rates. For species lacking demographic data, our model produced large, often inaccurate, prediction intervals that may not be useful in a management context. Our findings do not support the assumption that biologically similar or closely related species have similar demographic rates and provide further evidence that direct monitoring of focal species and populations is necessary for informing conservation status assessments.

We present life expectancy estimates for hundreds of vertebrate species based on carefully vetted studbook data from North American zoos and aquariums. These data include sex-specific median life expectancies as well as sample size and 95% confidence limits for each estimate. Existing longevity data for animals primarily consist of maximum lifespan values, which are single observations rather than statistically derived estimates of longevity. Moreover, all of our estimates are based on the same type of data and calculated using consistent, standardized methods. To derive these estimates, we conducted Kaplan-Meier survival analyses using individual-level demographic data (i.e., records of birth and mortality events) from studbook records for each ex situ population. Our species set represents a range of vertebrate taxa (primarily mammals, birds, amphibians, and reptiles) and diverse life histories. This dataset will have broad utility, not only for informing comparative demographic and life history studies, but also more broadly for any research or conservation application that requires sex- or species-specific life expectancy information. Machine-accessible metadata file describing the reported data (ISA-Tab format)

The challenge of recovering threatened species necessitates collaboration among diverse conservation partners. Zoos and aquariums have long partnered with other conservation organizations and government agencies to help recover species through a range of in situ and ex situ conservation projects. These efforts tend to be conducted by individual facilities and for individual species, and thus the scope and magnitude of these actions at the national level are not well understood. Here we evaluate the means and extent to which North American zoos and aquariums contribute to the recovery of species listed under the U.S. Endangered Species Act (ESA), by synthesizing data from federal recovery plans for listed species and from annual surveys conducted by the Association of Zoos and Aquariums. We found that in addition to managing ex situ assurance populations, zoos frequently conduct conservation research and field-based population monitoring and assessments. Cooperatively managed populations in zoos tend to focus on species that are not listed on the ESA or on foreign listings, and thus it may be beneficial for zoos to manage more native threatened species. Our results highlight the existing contributions, but also identify additional opportunities for the zoo community to help recover threatened species.

Socio-environmental synthesis (S-E synthesis) is a research method and problem-solving approach that integrates existing knowledge and data from natural and social sciences to advance understanding of socio-environmental systems and to inform solutions to environmental problems. As science becomes more transdisciplinary and collaborative and as new opportunities presented by the information age change how we do science, the teaching of S-E synthesis is increasingly important for preparing future environmental problem solvers, scientists, and citizens. S-E synthesis also provides a rich context for classroom instruction that can facilitate the achievement of diverse learning objectives. Here, we discuss efforts to adapt the evidence-based teaching practice of the case study method for teaching about the complex and interdisciplinary approach of S-E synthesis. We provide insights about the effectiveness of this teaching approach and offer practical advice for writing and implementing S-E synthesis cases. These insights are informed by experiences creating and using S-E synthesis case studies, both ours and those of participants of a short course on “Teaching about Socio-Environmental Synthesis with Case Studies” held at the National Socio-Environmental Synthesis Center (SESYNC). Assessment of S-E synthesis learning goals and the effectiveness of the case study method for teaching S-E synthesis are also discussed. Full development of this approach for teaching S-E synthesis will require a community effort, and our intention here is to offer a preliminary vision and qualitative assessment, to stimulate discussion, and to invite readers to join our efforts to create, use, and assess S-E synthesis case studies for teaching.

Polar bears (Ursus maritimus) have always been one of the most popular animals in zoos. Though their charismatic nature has made them a good flagship species for the Arctic habitat, there has been very little examination of the co-relationship or need for collaboration between the in situ and ex situ polar bear worlds. In the 1990s, polar bear populations in North American and European zoos were declining, and many zoos were closing their polar bear exhibits (Meyerson 2006; Linke 2015; Poirier and Lanthier 1995). Though still popular with the public, animal well-being concerns and increasing governmental regulations made it evident that in order to appropriately house and exhibit this large and intelligent species, significant financial resources would need to be invested. Given that the wild population numbers had rebounded as a result of the cooperative regulations enacted by the five Polar Bear Nations (i.e., the Range States: USA, Canada, Union of Soviet Socialist Republics, Norway and Denmark/Greenland) (United Nations Environment Program Register of International Treaties 1973), which addressed issues such as illegal harvest and environmental toxins, the conservation threat for the species was relatively low, and zoos were choosing to use their limited financial resources to build exhibits for species that had a greater conservation need.

Noccaea caerulescens (formerly Thlaspi caerulescens, Brassicaceae) is a model species for studying the genetics and physiology of metal hyperaccumulation and is economically valuable for phytoremediation. Its growth and survival under varying natural conditions remain relatively unstudied but such information would be essential for assessing the effectiveness and potential ecological impacts of using N. caerulescens for phytoremediation. In this study, we experimentally introduced N. caerulescens seeds and seedlings to three sites with zinc- and cadmium-contaminated mine tailings in southwestern Colorado. We observed its germination, growth, and survival at three distances from the tailings (‘locations’) and with and without native vegetation removal to assess its establishment potential. Overall plant growth was slow and plants did not reach reproductive stage after three growing seasons, but plant performance did vary by site and location. High soil copper concentrations in the tailings at one ...

Use of population viability analyses (PVAs) in endangered species recovery planning has been met with both support and criticism. Previous reviews promote use of PVA for setting scientifically based, measurable, and objective recovery criteria and recommend improvements to increase the framework's utility. However, others have questioned the value of PVA models for setting recovery criteria and assert that PVAs are more appropriate for understanding relative trade-offs between alternative management actions. We reviewed 258 final recovery plans for 642 plants listed under the U.S. Endangered Species Act to determine the number of plans that used or recommended PVA in recovery planning. We also reviewed 223 publications that describe plant PVAs to assess how these models were designed and whether those designs reflected previous recommendations for improvement of PVAs. Twenty-four percent of listed species had recovery plans that used or recommended PVA. In publications, the typical model was a matrix population model parameterized with ≤5 years of demographic data that did not consider stochasticity, genetics, density dependence, seed banks, vegetative reproduction, dormancy, threats, or management strategies. Population growth rates for different populations of the same species or for the same population at different points in time were often statistically different or varied by >10%. Therefore, PVAs parameterized with underlying vital rates that vary to this degree may not accurately predict recovery objectives across a species' entire distribution or over longer time scales. We assert that PVA, although an important tool as part of an adaptive-management program, can help to determine quantitative recovery criteria only if more long-term data sets that capture spatiotemporal variability in vital rates become available. Lacking this, there is a strong need for viable and comprehensive methods for determining quantitative, science-based recovery criteria for endangered species with minimal data availability.

Recovery plans for species listed under the U.S. Endangered Species Act are required to specify measurable criteria that can be used to determine when the species can be delisted. For the 642 listed endangered and threatened plant species that have recovery plans, we applied recursive partitioning methods to test whether the number of individuals or populations required for delisting can be predicted on the basis of distributional and biological traits, previous abundance at multiple time steps, or a combination of traits and previous abundances. We also tested listing status (threatened or endangered) and the year the recovery plan was written as predictors of recovery criteria. We analyzed separately recovery criteria that were stated as number of populations and as number of individuals (population-based and individual-based criteria, respectively). Previous abundances alone were relatively good predictors of population-based recovery criteria. Fewer populations, but a greater proportion of historically known populations, were required to delist species that had few populations at listing compared with species that had more populations at listing. Previous abundances were also good predictors of individual-based delisting criteria when models included both abundances and traits. The physiographic division in which the species occur was also a good predictor of individual-based criteria. Our results suggest managers are relying on previous abundances and patterns of decline as guidelines for setting recovery criteria. This may be justifiable in that previous abundances inform managers of the effects of both intrinsic traits and extrinsic threats that interact and determine extinction risk. Prediccion de Criterios de Recuperacion para Especies de Plantas en Peligro y Amenazadas con Base en Abundancias Pasadas y Atributos Biologicos Resumen Los planes de recuperacion para especies enlistadas en el Acta de Especies en Peligro de E.U.A. deben especificar criterios medibles que pueden ser utilizados para determinar cuando se puede suprimir de la lista a la especie. Para las 642 especies de plantas enlistadas en peligro o amenazadas y que tienen planes de recuperacion, aplicamos metodos de particion recursiva para probar si se podia predecir el numero de individuos o poblaciones que se requieren para suprimir de la lista a la especie con base en atributos de la distribucion y biologicos, en la abundancia previa en multiples frecuencias temporales, o en una combinacion de atributos y abundancias previas. Tambien probamos como predictores de criterios de recuperacion al estatus en la lista (amenazada o en peligro) y el ano en que se escribio el plan de recuperacion. Analizamos por separado los criterios de recuperacion definidos como numero de poblaciones y como numero de individuos (criterios basados en poblaciones y basados en individuos, respectivamente). Las abundancias previas por si solas fueron predictores relativamente buenos de criterios de recuperacion basados en poblaciones. Se requirieron menos poblaciones, pero una mayor proporcion de poblaciones conocidas historicamente, para suprimir de la lista a especies que tenian pocas poblaciones cuando fueron enlistadas en comparacion con especies que tenian mas poblaciones al ser enlistadas. Las abundancias previas tambien fueron buenos predictores de criterios basados en individuos cuando los modelos incluyeron tanto abundancias como atributos. La division fisiografica en la que ocurren las especies tambien fue un buen predictor de criterios basados en individuos. Nuestros resultados sugieren que los manejadores estan confiando en abundancias previas y patrones de declinacion como lineamientos para definir criterios de recuperacion. Esto puede ser justificable debido a las abundancias previas informan a los manejadores sobre los efectos tanto de atributos intrinsecos como de las amenazas extrinsecas que interactuan para determinar el riesgo de extincion.

1. The open-access scientific philosophy has been widely adopted and proven to promote considerable progress in the fields of ecology and evolution. Open-access global databases now exist on animal migration, the distribution of species, and conservation status, to mention a few. However, a gap exists for databases on population dynamics spanning the rich diversity of the animal kingdom. This information is fundamental to our understanding of the conditions that have shaped variation in animal life histories and their relationships with the environment. Furthermore, an animal population schedules of reproduction and mortality determine its invasive potential, and its risk of local extinction, which are at the core of conservation biology. 2. Matrix population models (MPMs) are among the most widely used demographic tools by animal ecologists. MPMs project population dynamics in terms of reproduction, mortality, and development over the entire life cycle. The results of MPMs have direct biological interpretations, facilitating comparisons among animal species as different as Caenorhabditis elegans, Loxodonta africana and Homo sapiens. 3. Thousand of animal demographic records exist in the form of MPMs, but they are dispersed throughout the literature, rendering comparative analyses difficult. Here, we introduce the COMADRE Animal Matrix Database version 1.0.0, an open-source online repository containing data on 402 species worldwide, from 272 studies, with a total of 1,575 population projection matrices. COMADRE also contains ancillary information (e.g. ecoregion, taxonomy, biogeography, etc.) that facilitates interpretation of the numerous demographic metrics that can be derived from its MPMs. 4. Synthesis: We introduce the COMADRE Animal Matrix Database, a resource for animal demography. The open access nature of this database, together with its ancillary information will facilitate comparative analysis, as will the growing availability of databases focusing on other traits, and tools to query and combine them. Through future frequent updates of COMADRE, and its integration with other online resources, we encourage animal ecologists to tackle global ecological and evolutionary questions with unprecedented statistical power.

Recovery planning for species listed under the U.S. Endangered Species Act has been hampered by a lack of consistency and transparency, which can be improved by implementing a standardized approach for evaluating species status and developing measurable recovery criteria. However, managers lack an assessment method that integrates threat abatement and can be used when demographic data are limited. To help meet these needs, we demonstrated an approach for evaluating species status based on habitat configuration data. We applied 3 established persistence measures (patch occupancy, metapopulation capacity, and proportion of population lost) to compare 2 conservation strategies (critical habitat designated by the U.S. Fish and Wildlife Service and the Forest Service's Carbonate Habitat Management Strategy) and 2 threat scenarios (maximum limestone mining, removal of all habitat in areas with mining claims; minimum mining, removal of habitat only in areas with existing operations and high-quality ore) against a baseline of existing habitat for 3 federally listed plant species. Protecting all area within the designated critical habitat maintained a similar level (83.9-99.9%) of species persistence as the baseline, whereas maximum mining greatly reduced persistence (0.51-38.4% maintained). The 3 persistence measures provided complementary insights reflecting different aspects of habitat availability (total area, number of patches, patch size, and connectivity). These measures can be used to link recovery criteria developed following the 3 R principles (representation, redundancy, and resilience) to the resulting improvements in species viability. By focusing on amount and distribution of habitat, our method provides a means of assessing the status of data-poor species to inform decision making under the Endangered Species Act.

Summary: Schedules of survival, growth and reproduction are key life-history traits. Data on how these traits vary among species and populations are fundamental to our understanding of the ecological conditions that have shaped plant evolution. Because these demographic schedules determine population growth or decline, such data help us understand how different biomes shape plant ecology, how plant populations and communities respond to global change and how to develop successful management tools for endangered or invasive species. Matrix population models summarize the life cycle components of survival, growth and reproduction, while explicitly acknowledging heterogeneity among classes of individuals in the population. Matrix models have comparable structures, and their emergent measures of population dynamics, such as population growth rate or mean life expectancy, have direct biological interpretations, facilitating comparisons among populations and species. Thousands of plant matrix population models have been parameterized from empirical data, but they are largely dispersed through peer-reviewed and grey literature, and thus remain inaccessible for synthetic analysis. Here, we introduce the compadre Plant Matrix Database version 3.0, an open-source online repository containing 468 studies from 598 species world-wide (672 species hits, when accounting for species studied in more than one source), with a total of 5621 matrices. compadre also contains relevant ancillary information (e.g. ecoregion, growth form, taxonomy, phylogeny) that facilitates interpretation of the numerous demographic metrics that can be derived from the matrices. Synthesis. Large collections of data allow broad questions to be addressed at the global scale, for example, in genetics (genbank), functional plant ecology (try, bien, d3) and grassland community ecology (nutnet). Here, we present compadre, a similarly data-rich and ecologically relevant resource for plant demography. Open access to this information, its frequent updates and its integration with other online resources will allow researchers to address timely and important ecological and evolutionary questions. Synthesis: Large collections of data sets allow broad questions to be addressed at the global scale, for example, in genetics (genbank), functional plant ecology (try, bien, d3) and grassland community ecology (nutnet). Here, we present compadre, a similarly data-rich and ecologically relevant resource for plant demography. Open access to this information, its frequent updates and its integration with other online resources will allow researchers to address timely and important ecological and evolutionary questions.

There is renewed interest in implementing surrogate species approaches in conservation planning due to the large number of species in need of management but limited resources and data. One type of surrogate approach involves selection of one or a few species to represent a larger group of species requiring similar management actions, so that protection and persistence of the selected species would result in conservation of the group of species. However, among the criticisms of surrogate approaches is the need to test underlying assumptions, which remain rarely examined. In this study, we tested one of the fundamental assumptions underlying use of surrogate species in recovery planning: that there exist groups of threatened and endangered species that are sufficiently similar to warrant similar management or recovery criteria. Using a comprehensive database of all plant species listed under the U.S. Endangered Species Act and tree-based random forest analysis, we found no evidence of species groups based on a set of distributional and biological traits or by abundances and patterns of decline. Our results suggested that application of surrogate approaches for endangered species recovery would be unjustified. Thus, conservation planning focused on individual species and their patterns of decline will likely be required to recover listed species.

Adaptive traits are hypothesised to incur fitness trade-offs, and a classical example is metal-tolerant plants that exhibit reduced competitive ability when grown on low-metal substrates. In the present study, we examined whether metal-hyperaccumulating plants exhibit a similar trade-off, by assessing competition across a soil-metal gradient in the context of phytoremediation. We studied the cadmium- and zinc-hyperaccumulator Noccaea caerulescens (J. Presl & C. Presl) F.K. Mey., which has been introduced to potential remediation sites contaminated with those metals, and the nickel- and zinc-hyperaccumulator Noccaea fendleri subsp. glauca (A. Nelson) Al-Shehbaz & M. Koch, which is native to our study sites. We performed a greenhouse experiment with a response-surface design to quantify their competitive interactions on higher- and lower-metal substrates from each of three mine sites. Overall competitive effects between the species were weak, but we did find evidence of competition on the substrates that supported the highest rates of plant growth and reproduction. Abiotic factors were more limiting than competitive interactions for both species, and both performed better on substrates containing higher zinc, lower cadmium and lower copper concentrations. A complementary field trial supported these findings. Our results also showed that substrates outside of contaminated mine tailings can still contain sufficiently high zinc concentrations to support N. caerulescens, suggesting that the use of these plants for phytoremediation should be monitored to prevent the unintentional establishment of non-native species.

Frasera speciosa (Gentianaceae) is a long-lived monocarpic plant with mast seeding, a type of plant whose demography is rarely studied. Using a 35-year dataset from an ongoing study, we described the population dynamics of F. speciosa using matrix projection models, addressed how many years of data are needed to estimate population growth and elasticity values consistently, and examined the effects of mast seeding on demographic parameter estimates. Our results indicated that our population is likely stable, with the annual population growth rate near one (λ = 0.969, λs = 0.967 with 95% CI = 0.923–1.013). Mean generation time was 40 years and the mean estimated lifespan was 6.86 years with a high variance of 181.8 years for individuals starting in the seedling stage, consistent with observations of very long-lived individuals in the field. Elasticity values were highest for the transitions representing stasis and lowest for reproduction. For dataset length, 15 years of data yielded lambda estimates that were within 1% of the long-term estimate, but 20 years of data were needed to yield lambdas with confidence intervals that consistently overlap one. Although mast seeding is generally defined using the inter-annual variation in seed production per unit area, stochastic lambdas were not correlated with this measure of reproduction but instead correlated with per capita dormant seed production and per capita recruit production. Mean survival rate was also positively correlated with stochastic lambda estimates, despite the necessary increase in mortality in years with high reproduction. Our results indicated that the demography of F. speciosa is similar to that of other long-lived monocarps without mast seeding, that long datasets may be needed to capture the variation in demographic rates even for stable populations, and that life history stages with low elasticity values can still be very important to population growth.

Approximately 25 % of mammals are threatened globally with extinction, a risk that is amplified under climate change1. Persistence under climate change is determined by the combined effects of climatic factors on multiple demographic rates (survival, development, reproduction), and hence, on population dynamics2. Thus, to quantify which species and places on Earth are most vulnerable to climate-driven extinction, a global understanding of how demographic rates respond to climate is needed3. We synthesise information on such responses in terrestrial mammals, where extensive demographic data are available4. Given the importance of assessing the full spectrum of responses, we focus on studies that quantitatively link climate to multiple demographic rates. We identify 106 such studies, corresponding to 86 mammal species. We reveal a strong mismatch between the locations of demographic studies and the regions and taxa currently recognised as most vulnerable to climate change5,6. Moreover, we show that the effects of climate change on mammals will operate via complex demographic mechanisms: a vast majority of mammal populations display projected increases in some demographic rates but declines in others. Assessments of population viability under climate change therefore need to account for multiple demographic responses. We advocate to prioritise coordinated actions to assess mammal demography holistically for effective conservation worldwide.