Search

Many of the implications of climate change for Aotearoa (New Zealand) remain unclear. To identify so-far unseen threats and opportunities related to climate change we applied a horizon-scanning process. First, we collated 171 threats and opportunities across our diverse fields of research. We then scored each item for novelty and potential impact and finally reduced the list to ten threats and ten opportunities through a prioritisation process. Within the 20 items presented in this paper, we uncover a range of climate-related costs and benefits. Unexpected opportunities evolve from economic reorganisation and changes to perspectives. The threats we highlight include the overall failure to interconnect siloed policy responses, as well as those relating to extreme events and feedbacks, as well pressures that undermine the coherence of society. A major theme of our work is that climate changes’ effects in Aotearoa are likely to transgress the boundaries of research disciplines, industry sectors and policy systems, emphasising the importance of developing transdisciplinary methods and approaches. We use this insight to connect potential responses to climate change with Aotearoa’s culture and geography.

Compared to their native range, non-native plants often experience reduced levels of herbivory in the introduced range. This may result in reduced pressure to produce chemical defences that act against herbivores. We measured the most abundant secondary metabolites found in Rumex spp., namely oxalates, phenols and tannins. To test this hypothesis, we compared native (UK) and introduced (NZ) provenances of three different Rumex species (R. obtusifolius, R. crispus and R. conglomeratus, Polygonaceae) to assess whether any significant differences existed in their levels of chemical defences in either leaves and roots. All three species have previously been shown to support a lower diversity of insect herbivores and experience less herbivory in the introduced range. We further examined leaf herbivory on plants from both provenances when grown together in a common garden experiment in New Zealand to test whether any differences in damage might be consistent with variation in the quantity of chemical defences. We found that two Rumex species (R. obtusifolius and R. crispus) showed no evidence for a reduction in chemical defences, while a third (R. conglomeratus) showed only limited evidence. The common garden experiment revealed that the leaves analysed had low levels of herbivory (~ 0.5%) with no differences in damage between provenances for any of the three study species. Roots tended to have a higher concentration of tannins than shoots, but again showed no difference between the provenances. As such, the findings of this study provide no evidence for lower plant investments in chemical defences, suggesting that other factors explain the success of Rumex spp. in New Zealand.

Made available in DSpace on 2022-04-28T19:52:06Z (GMT). No. of bitstreams: 0 Previous issue date: 2022-03-18 Urbanization transforms environments in ways that alter biological evolution. We examined whether urban environmental change drives parallel evolution by sampling 110,019 white clover plants from 6169 populations in 160 cities globally. Plants were assayed for a Mendelian antiherbivore defense that also affects tolerance to abiotic stressors. Urban-rural gradients were associated with the evolution of clines in defense in 47% of cities throughout the world. Variation in the strength of clines was explained by environmental changes in drought stress and vegetation cover that varied among cities. Sequencing 2074 genomes from 26 cities revealed that the evolution of urban-rural clines was best explained by adaptive evolution, but the degree of parallel adaptation varied among cities. Our results demonstrate that urbanization leads to adaptation at a global scale. Department of Biology University of Toronto Mississauga ON Centre for Urban Environments University of Toronto Mississauga ON Department of Biology University of North Carolina, Chapel Hill Department of Biology University of Louisiana LA Department of Biology Queen's University ON Department of Biology Concordia University QC Department of Biological Sciences DePaul University Department of Biology DePauw University IN Department of Urban Design and Planning, University of Washington, Seattle, WA, USA Colegio de Ciencias Biológicas y Ambientales Universidad San Francisco de Quito USFQ Department of Genetics University of Georgia Department of Ecology and Genetics Evolutionary Biology Centre Uppsala University Field Science Center for Northern Biosphere Hokkaido University Natural History Museum Zoology University of New England NSW Programa de Pós-Graduação em Geografia da UFMT campus de Rondonópolis Department of Botany and Biodiversity Research Centre University of British Columbia Graduate Program in Genome Sciences and Technology Genome Sciences Centre University of British Columbia Department of Microbiology and Immunology University of British Columbia Red de Biología Evolutiva Instituto de Ecología A. C. School of the Environment Yale University CT Departamento de Ciencias Ecológicas Universidad de Chile, Facultad de Ciencias Instituto de Ecología y Biodiversidad Universidad de Chile Department of Biology Mount Allison University Red de Ecoetología Instituto de Ecología A. C. Department of Biology University of Ottawa ON Department of Zoology University of Cambridge Department of Biology, Washington University in St. Louis, St. Louis, MO, USA Department of Biology University of Miami FL Centro de Investigación en Recursos Naturales y Sustentabilidad (CIRENYS) Universidad Bernardo O'Higgins Department of Biology, University of La Verne, La Verne, CA, USA Département des sciences du bois et de la forêt Université Laval QC Evolution & Ecology Research Centre School of Biological Earth and Environmental Sciences UNSW Sydney NSW Department of Biology Ghent University Department of Biology Monmouth University West Long Branch Centre for Ecology Evolution and Environmental Changes Faculdade de Ciências Universidade de Lisboa Lisboa Department of Biology KU Leuven School of Agriculture and Environment Wildlife and Ecology group Massey University, Palmerston North Department of Biological Sciences University of Cape Town Institute of Landscape Ecology University of Münster Gosnell School of Life Sciences, Rochester Institute of Technology, Rochester, NY, USA Department of Biological Sciences University of Alberta AB Louis Calder Center and Department of Biological Sciences, Fordham University, Armonk, NY, USA Departamento de Ecología Tropical, Universidad Autónoma de Yucatán, Mérida, Yucatán, México School of Life Sciences University of Sussex Department of Ecology Environment and Plant Sciences Stockholm University iBIOTROP Instituto de Biodiversidad Tropical Universidad San Francisco de Quito Department of Biology, San Francisco State University, San Francisco, CA, USA Unidad de Recursos Naturales, Centro de Investigación Científica de Yucatán AC, Mérida, Yucatán, México School of Ecological and Environmental Sciences East China Normal University Shanghai Engineering Research Center of Sustainable Plant Innovation Centre for Ecosystem Science School of Biological Earth and Environmental Sciences UNSW Sydney NSW Department of Ecology and Evolutionary Biology University of Michigan MI Department of Biosciences Rice University TX IFEVA Universidad de Buenos Aires Facultad de Agronomía, CONICET Biology Department Saint Mary's University NS Department of Biological Sciences, Universidad de los Andes Department of Biology and Biochemistry University of Houston TX Université de Rennes Department of Zoology and Biodiversity Research Centre University of British Columbia Department of Environmental Studies Dordt University Sioux Center IA Department of Biology Minneapolis Community and Technical College MN Department of Natural Sciences Ecology and Environment Research Centre Manchester Metropolitan University Instituto de Investigaciones en Ecosistemas y Sustentabilidad UNAM Department of Botany School of Biology Aristotle University of Thessaloniki Faculty of Biological and Environmental Science Organismal & Evolutionary Biology Research Programme University of Helsinki Institute of Biodiversity Animal Health and Comparative Medicine University of Glasgow Department of Biology Hendrix College Department of Ecological Science Vrije Universiteit Amsterdam Departamento de Ciencias Biológicas y Agropecuarias Universidad Técnica Particular de Loja Departamento de Biologia Universidade Federal de Santa Maria (UFSM) Department of Plant Sciences School of Biology College of Science University of Tehran NTNU University Museum Norwegian University of Science and Technology Red de Estudios Moleculares Avanzados Instituto de Ecología A. C. School of Biological Sciences, University of Reading, Whiteknights Park, Reading, Berkshire, UK Department of Biology Northern Arizona University AZ Department of Biological Sciences MacEwan University AB Max Planck Institute for Plant Breeding Research Departamento de Ecología Evolutiva Instituto de Ecología Universidad Nacional Autónoma de México Max Planck Institute of Molecular Plant Physiology Potsdam-Golm BIO5 Institute University of Arizona AZ Alaska Center for Conservation Science University of Alaska Anchorage Tropical Diversity, Royal Botanical Garden of Edinburgh Département de biologie Université de Moncton Department of Biological Sciences University of Manitoba MB Departments of Microbiology & Statistics University of Manitoba MB Department of Biology University of New Brunswick Department of Biology Kalamazoo College MI BioProtection Research Centre Lincoln University Departamento de Ciencias Facultad de Artes Liberales Universidad Adolfo Ibáñez Department of Ecology Evolution Behaviour University of Minnesota MN Department of Biological Sciences Brock University Department of Environmental Toxicology, University of California, Davis, CA, USA ICB - University of Talca School of Molecular and Life Science Curtin University College of Science Health Engineering and Education Murdoch University, Murdoch School of Life and Environmental Sciences University of Sydney NSW School of Biological Sciences, Monash University, Melbourne, VIC, Australia Department of Biological Sciences Wayne State University MI Department of Biology Western Oregon University, OR School of Natural Resources and the Environment University of Arizona AZ Departamento de Ecología Humana, Cinvestav Mérida Departamento de Ciencias Biológicas y Departamento de Ecología y Biodiversidad Facultad de Ciencias de la Vida, Universidad Andrés Bello Institute of Ecology and Biodiversity (IEB) Department of Biology Lund University Department of Biology Norwegian University of Science and Technology Escuela Superiro de Desarrollo Sustentable Universidad Autónoma de Guerrero -CONACYT Clarkson Secondary School Peel District School Board ON Homelands Sr. Public School Peel District School Board ON Department of Biological Sciences University of Illinois at Chicago Dufferin-Peel Catholic District School Board, St. James Catholic Global Learning Centre Department of Biosciences University of Calgary AB Ecological Processes Branch U.S. Army ERDC-CERL Department of Biology, Oberlin College, Oberlin, OH, USA Escuela Nacional de Estudios Superiores Unidad Morelia UNAM Institute of Evolution and Ecology University of Tübingen Tübingen Department of Evolutionary Biology and Environmental Studies University of Zurich, Winterthurerstrasse Urban Wildlife Institute Department of Conservation and Science, Lincoln Park Zoo Departamento de Ecología Universidad Católica de la Santísima Concepción Department of Biological Sciences University of Denver CO Department of Biological Sciences Mississippi State University MS Department of Biology Center for Computational & Integrative Biology Rutgers University-Camden Kunming Institute of Botany Chinese Academy of Sciences Department of Chemistry & Biochemistry Laurentian University ON Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering College of Life Sciences Beijing Normal University School of BioSciences, University of Melbourne, Melbourne, VIC, Australia Posgrado en Ciencias Biológicas Universidad Nacional Autónoma de México Department of Biological Sciences, Auburn University, Auburn, AL, USA Department of Entomology and Nematology, University of California, Davis, CA, USA Department of Biology University of New Mexico NM Department of Biology University of Wisconsin - Eau Claire Agriculture Institute Iranian Research Organization for Science and Technology (IROST) Department of Biology Colby College ME Instituto de Biología Universidad de Antioquia Department of Biology University of Massachusetts Boston MA Agricultural Biology Colorado State University CO Departamento de Biología Vegetal y Ecología Facultad de Biología Universidad de Sevilla, Av. Reina Mercedes s/n Facultad de Estudios Interdisciplinarios Centro GEMA- Genómica Universidad Mayor Evolutionary Ecology Group Naturalis Biodiversity Center Department of Biology and Chemistry Nipissing University ON, North Bay Center for Ecological Research Kyoto University Bonanza Creek Long Term Ecological Research Program University of Alaska Fairbanks Department of Botany and Molecular Evolution Senckenberg Research Institute and Natural History Museum Frankfurt Departamento de Biodiversidade Instituto de Biociências Univ Estadual Paulista - UNESP Nelson Institute for Environmental Studies University of Wisconsin-Madison WI Department of Biology, California State University, Northridge, Los Angeles, CA, USA Department of Ecology Swedish University of Agricultural Sciences Facultad de Ciencias y Biotecnologia Universidad CES Department of Biology Hofstra University Faculty of Biosciences and Aquaculture Nord University, Bodø Division of Biological Sciences, University of California San Diego, San Diego, CA, USA Department of Biology University of Richmond VA Estación de Biodiversidad Tiputini Colegio de Ciencias Biológicas y Ambientales Universidad San Francisco de Quito USFQ Department of Biological Sciences Institute of Environment Florida International University FL Agronomy Department University of Almería Department of Biological Sciences and Center for Urban Ecology and Sustainability Butler University IN Department of Biological Sciences Louisiana State University LA Faculty of Biological Sciences, Goethe University Frankfurt Institute of Biology Leiden Leiden University Department of Biological and Environmental Science University of Jyväskylä Jyväskylä Department of Biology University of Louisville KY Organization for Programs on Environmental Science University of Tokyo CNRS AgroParisTech Ecologie Systématique et Evolution, Université Paris-Saclay Department of Biology, Providence College, Providence, RI, USA General Zoology Institute for Biology Martin Luther University Halle-Wittenberg International Arctic Research Center University of Alaska Fairbanks Science, Technology and Society Department, Rochester Institute of Technology, Rochester, NY, USA SLU Swedish Species Information Centre Swedish University of Agricultural Sciences Department of Biology Westfield State University MA Centre of New Technologies University of Warsaw Department of Biology, Stanford University, Stanford, CA, USA Plant Biology Department Michigan State University MI Biology Department Davidson College College of Horticulture and Forestry Sciences/ Hubei Engineering Technology Research Center for Forestry Information Huazhong Agricultural University School of Life Sciences Technical University of Munich School of Life Sciences Lanzhou University Institute of Ecology and Evolution University of Bern Department of Evolution Ecology and Behaviour University of Liverpool Departamento de Biodiversidade Instituto de Biociências Univ Estadual Paulista - UNESP

Changes in biodiversity reflect processes acting on the success of individual species at multiple spatial scales, including in communities, biogeographic regions, and globally. This complexity makes it difficult to analyse the mechanisms shaping diversity change using traditional approaches. To resolve this, we propose a novel approach to partition total biodiversity changes according to mechanisms reflecting species’ success at multiple scales. We apply this approach to study changes in the diversity of invertebrate herbivores from a large-scale, plant community experiment. This partitioning showed that rapid changes in the relative abundances of individual species resulted in surprisingly small changes in diversity across scales. Our novel analytical method reveals how strong ecological effects at different hierarchical levels can counteract each other, resulting in weak effects on diversity across broad spatial scales.

Understanding how the spatial variation in species composition (beta-diversity) varies with biotic and abiotic conditions is one of the ultimate goals in biology. Theory predicts that beta-diversity is a consequence of two factors, species-level differences (defined as the variations among species in the probabilities that species are present in the landscape) and spatial heterogeneity (defined as the difference, between two sites, in the probabilities with which species are present). At present, however, the importance of each factor is unclear. Here, we take a probabilistic and combinatorial approach to examine the effects of species differences and spatial heterogeneity on the degree to which species assemblages in two spatial locations differ in species compositions. We first derived analytical and approximation formulae of the expectation and variance of the pairwise beta-diversity, based on the assumption that the presence probabilities of species are independent of each other. Though it seems intuitive that greater species differences leads to greater beta-diversity, our methods predict that the reverse is likely to occur under some circumstances; strikingly, when space is homogeneous, beta-diversity decreases with increasing species differences. This prediction suggests that policy making for increasing species traits-variation would, without adequately managing environmental heterogeneity, induce biotic homogeneization, resulting in undesired outcomes. Second, we illustrate our method using data from five woodpecker species in Switzerland, showing that the woodpecker species’ joint distributions change considerably with time, and also that such changes are basically explained by the changes in the incidences of some of the species. The new framework can improve our understanding of how pairwise beta-diversity responds to species differences and spatial heterogeneity.

Biodiversity describes the variety of organisms on planet earth. Ecologists have long hoped for a synthesis between analyses of biodiversity and analyses of biotic interactions among species, such as predation, competition, and mutualism. However, it is often unclear how to connect details of these interactions with complex modern analyses of biodiversity. To resolve this gap, we propose a unification of models of biotic interactions and measurements of diversity. We show that analyses of biodiversity obscure details about biotic interactions. For example, identical changes in biodiversity can arise from predation, competition or mutualism. Our approach indicates that traditional models of community assembly miss key facets of diversity change. Instead, we suggest that analyses of diversity change should focus on partitions, which measure mechanisms that directly shape changes in diversity, notably species level selection and immigration, rather than traditional analyses of biotic interactions.SpeculationsOur paper proposes that observations of biodiversity cannot be used to distinguish different types of biotic interactions. For generations ecologists have been fascinated with the links between biodiversity and biotic interactions (i.e. competition, mutualism and predation). Many of us expect that observations of biodiversity provide vital clues about how biotic interactions operate in nature, but it is hard to tell when these clues are reliable.Our work integrates models of biotic interactions and measurements of biodiversity diversity change. This highlights how an observed change in diversity can be compatible with any type of biotic interaction (i.e. competition, mutualism, predation etc.). So for example, the same increase in Shannon diversity could indicate the superior ability of a competitor the success of mutualists or a predator’s tendency to harvest dominant prey species. This is so because diversity measures are designed to be concerned with changes in relative abundances but not account for absolute abundance changes.Observations of biodiversity change are unlikely to yield insights about biotic interactions per se because biodiversity itself obscures species’ absolute abundances. Therefore, models of diversity change should focus on mechanisms that are less influenced by changes in absolute abundances such as species-level selection.

Beta diversity describes the differences in species composition among communities. Changes in beta diversity over time are thought to be due to selection based on species' niche characteristics. For example, theory predicts that selection that favors habitat specialists will increase beta diversity. In practice, ecologists struggle to predict how beta diversity changes. To remedy this problem, we propose a novel solution that formally measures selection's effects on beta diversity. Using the Price equation, we show how change in beta diversity over time can be partitioned into fundamental mechanisms including selection among species, variable selection among communities, drift, and immigration. A key finding of our approach is that a species' short-term impact on beta diversity cannot be predicted using information on its long-term environmental requirements (i.e., its niche). We illustrate how our approach can be used to partition causes of diversity change in a montane tropical forest before and after an intense hurricane. Previous work in this system highlighted the resistance of habitat specialists and the recruitment of light-demanding species but was unable to quantify the importance of these effects on beta diversity. Using our approach, we show that changes in beta diversity were consistent with ecological drift. We use these results to highlight the opportunities presented by a synthesis of beta diversity and formal models of selection.

Sunbirds play a major role in the pollination of Old World nectivorous plants. However, with the exception of the Cape Floristic Region there is a major knowledge gap around African nectivore interaction networks—a stark contrast from the abundance of neotropical hummingbird–plant networks. Here, we describe a sunbird pollen transfer network (PTN) which we use in conjunction with a sunbird flower visitation network (FVN) to explore levels of sunbird specialization within an Afromontane forest habitat. Both networks were generalized compared with similar‐sized hummingbird networks, reflecting the wide range of flower types visited, the generalist diet, and bill characteristics of sunbirds. Three sunbird species from the genus Cinnyris accounted for 85% of flower visits and 77% of all pollen transported. Of the 17 plant species across both networks, 15 are predominantly pollinated by insects while Anthonotha noldeae (Fabaceae–Caesalpinioideae) and Globimetula braunii (Loranthaceae) depend on sunbirds for seed set. Sunbird species average bill lengths varied between 14.5 mm (the variable sunbird) and 23.6 mm (the Green‐headed Sunbird), but, while more pollen was carried on longer bills, we found no evidence for a relationship between bill length and type of flower visited. Both networks were nested. Some specialization was observed in both networks although this does not appear to be driven much by sunbird–flower trait matching. Overall, our results suggest that in contrast to nectivores elsewhere, factors such as phenology and/or environment, rather than morphology, may play important roles in limiting potential sunbird–flower interactions and need further investigation.

Climatic niche shifts occur when species occupy different climates in the introduced range than in their native range. We know that climatic niche shifts are common occurrences, however we do not currently understand whether climatic niche shifts can consistently be predicted across the globe. Using three congeneric weed species, we investigate whether the known presence of a climatic niche shift in one range can help predict a species’ distribution in other ranges. We consider whether data either from other ranges or from closely related species can help predict whether climatic niche shifts will occur. We compared the climatic conditions occupied by Rumex obtusifolius, R. crispus, and R. conglomeratus between their native range (Eurasia) and three different introduced ranges (North America, Australia, New Zealand). We consider metrics of niche overlap, expansion, unfilling, pioneering, and similarity to determine whether i) climatic niche shifts have occurred and ii) climatic niche shifts were consistent across ranges and congeners. We found that the presence and direction of climatic niche shifts is inconsistent across ranges for all three species. Within an introduced range, however, niche shifts were similar between species. Despite this, species distributions outside of their native range could not be reliably predicted by the distributions of congeners in either their native or introduced ranges. This study is the first of its kind to consider niche shifts across multiple introduced ranges and species, highlighting new challenges in predicting species distributions when species undergo climatic niche shifts.

Beta diversity describes the differences in species composition among communities. Changes in beta diversity over time are thought to be due to selection based on species’ niche characteristics. For example, theory predicts that selection that favours habitat specialists will increase beta diversity. In practice, ecologists struggle to predict how beta diversity changes. To remedy this problem, we propose a novel solution that formally measures selection’s effects on beta diversity. Using the Price equation, we show how change in beta diversity over time can be partitioned into fundamental mechanisms including selection among species, variable selection among communities, drift, and immigration. A key finding of our approach is that a species’ short-term impact on beta diversity cannot be predicted using information on its long-term environmental requirements (i.e. its niche). We illustrate how our approach can be used to partition causes of diversity change in a montane tropical forest before and after an intense hurricane. Previous work in this system highlighted the resistance of habitat specialists and the recruitment of light-demanding species but was unable to quantify the importance of these effects on beta diversity. Using our approach, we show that changes in beta diversity were consistent with ecological drift. We use these results to highlight the opportunities presented by a synthesis of beta diversity and formal models of selection.

Antimicrobial materials are tools used to reduce the transmission of infectious microorganisms. Photo-illuminated titania (TiO2) is a known antimicrobial material. Used as a coating on door handles and similar surfaces, it may reduce viability and colonization by pathogens and limit their spread. We tested the survival of Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus and Saccharomyces cerevisiae on a nano-structured TiO2-based thin film, called ‘NsARC’, and on stainless steel under a variety of light wavelengths and intensities. There was significantly less survival (P

Effective detection and monitoring tools are essential to manage the major ecological and economic problems posed by alien conifer invasions. Low-cost aerial imagery has been promoted as a promising tool for the detection of alien trees over large landscapes, but as yet there have been few attempts to assess its reliability for monitoring invasions. In particular, studies have not yet examined how well aerial imagery can detect densities of trees across invasions. To evaluate this, we used freely available, high-resolution aerial imagery to examine how age structure, spatial patterns and density of alien conifers varied across an invasion front. Overall, we were able to detect both the spatial pattern and distribution of trees with canopy diameters greater than 2.5 m, but we could only detect smaller trees with certainty where they were found at low density. These results point to aerial imagery being suitable for detecting trees at the edge of the invasion front, where they are often small and at low density. While assessments of the overall age-structure will underestimate the number of small trees, the number and spatial pattern of larger reproductive individuals can still be adequately captured. Thus low-cost aerial imagery can inform managers of where best to target control efforts at the invasion edge and also the location of large reproductive trees that are likely to contribute to future population expansion.

Despite considerable evidence that alien plants impact the fecundity, productivity and abundance of native plant species, support for alien plant species causing the widespread decline of native species is rare. Coexistence theory proposes that the outcome of competition between two species can be predicted through the invasion criterion, measured as a positive population-level growth rate of each competitor when that species is rare. Here we make use of coexistence theory to examine the likelihood of persistence of a native water fern (Azolla rubra) following invasion by an alien congener (Azolla pinnata) which has apparently displaced the native wherever their ranges overlap in New Zealand. We evaluate coexistence between the two water fern species using experimental measurements of population-level growth rates. We show that the alien A. pinnata has a higher fitness than A. rubra, which hinders coexistence between the two species. These experimental results match the rapid expansion of A. pinnata and the apparent decline of A. rubra observed in nature. Our study predicts that A. pinnata is capable of replacing its native congener, highlights the importance of fitness differences in invasion success, and demonstrates the value of experimental analyses of species coexistence for predicting longer-term invasion dynamics and impacts. Using experiments to test coexistence mechanisms between alien and native species is a valuable approach to predict invasion outcomes and one that can lead to insights on the long-term impacts of alien species, including extinction, on native species populations.

Herbicides are frequently released into both rural and urban environments. Commercial herbicide formulations induce adaptive changes in the way bacteria respond to antibiotics. Salmonella enterica sv. Typhimurium and Escherichia coli were exposed to common co-formulants of formulations, and S. enterica sv. Typhimurium was exposed to active ingredients dicamba, 2,4-D and glyphosate to determine what ingredients of the commercial formulations caused this effect. Co-formulants Tween80 and carboxymethyl cellulose induced changes in response, but the pattern of the responses differed from the active ingredients, and effect sizes were smaller. A commercial wetting agent did not affect antibiotic responses. Active ingredients induced changes in antibiotic responses similar to those caused by complete formulations. This occurred at or below recommended application concentrations. Targeted deletion of efflux pump genes largely neutralized the adaptive response in the cases of increased survival in antibiotics, indicating that the biochemistry of induced resistance was the same for formulations and specific ingredients. We found that glyphosate, dicamba, and 2,4-D, as well as co-formulants in commercial herbicides, induced a change in susceptibility of the potentially pathogenic bacteria E. coli and S. enterica to multiple antibiotics. This was measured using the efficiency of plating (EOP), the relative survival of the bacteria when exposed to herbicide and antibiotic, or just antibiotic, compared to survival on permissive media. This work will help to inform the use of non-medicinal chemical agents that induce changes in antibiotic responses.

One of the important issues in ecology is to predict which species will be present (or absent) across a geographical region. Dispersal is thought to have an important influence on the range limits of species, and understanding this problem in a multi-species community with priority effects (i.e. initial abundances determine species presence-absence) is a challenging task because dispersal also interacts with biotic and abiotic factors. Here, we propose a simple multi-species model to investigate the joint effects of biotic interactions and dispersal on species presence-absence. Our results show that dispersal can substantially expand species ranges when biotic and abiotic forces are present; consequently, coexistence of multiple species is possible. The model also exhibits ecologically interesting priority effects, mediated by intense biotic interactions. In the absence of dispersal, competitive exclusion of all but one species occurs. We find that dispersal reduces competitive exclusion effects that occur in no-dispersal case and promotes coexistence of multiple species. These results also show that priority effects are still prevalent in multi-species communities in the presence of dispersal process. We also illustrate the existence of threshold values of competitive strength (i.e. transcritical bifurcations), which results in different species presence-absence in multi-species communities with and without dispersal.

A large array of species distribution model (SDM) approaches has been developed for explaining and predicting the occurrences of individual species or species assemblages. Given the wealth of existing models, it is unclear which models perform best for interpolation or extrapolation of existing data sets, particularly when one is concerned with species assemblages. We compared the predictive performance of 33 variants of 15 widely applied and recently emerged SDMs in the context of multispecies data, including both joint SDMs that model multiple species together, and stacked SDMs that model each species individually combining the predictions afterward. We offer a comprehensive evaluation of these SDM approaches by examining their performance in predicting withheld empirical validation data of different sizes representing five different taxonomic groups, and for prediction tasks related to both interpolation and extrapolation. We measure predictive performance by 12 measures of accuracy, discrimination power, calibration, and precision of predictions, for the biological levels of species occurrence, species richness, and community composition. Our results show large variation among the models in their predictive performance, especially for communities comprising many species that are rare. The results do not reveal any major trade-offs among measures of model performance; the same models performed generally well in terms of accuracy, discrimination, and calibration, and for the biological levels of individual species, species richness, and community composition. In contrast, the models that gave the most precise predictions were not well calibrated, suggesting that poorly performing models can make overconfident predictions. However, none of the models performed well for all prediction tasks. As a general strategy, we therefore propose that researchers fit a small set of models showing complementary performance, and then apply a cross-validation procedure involving separate data to establish which of these models performs best for the goal of the study., This work was funded by the Research Foundation of the University of Helsinki (A. Norberg), the Academy of Finland (CoE grant 284601 and grant 309581 to O. Ovaskainen, grant 308651 to N. Abrego, grant 1275606 to A. Lehikoinen), the Research Council of Norway (CoE grant 223257), the Jane and Aatos Erkko Foundation, and the Ministry of Science, Innovation and Universities (grant CGL2015‐68438‐P to M. B. Araújo).

Baseline studies are needed to identify environmental reservoirs of non-pathogenic but associating microbiota or pathogenic bacteria that are resistant to antibiotics and to inform safe use of freshwater ecosystems in urban and agricultural settings. Mesophilic bacteria and Escherichia coli were quantified and isolated from water and sediments of two rivers, one in an urban and one in an agricultural area near Christchurch, New Zealand. Resistance of E. coli to one or more of nine different antibiotics was determined. Additionally, selected strains were tested for conjugative transfer of resistances. Despite having similar concentrations of mesophilic bacteria and E. coli, the rivers differed in numbers of antibiotic-resistant E. coli isolates. Fully antibiotic-susceptible and -resistant strains coexist in the two freshwater ecosystems. This study was the first phase of antibiotic resistance profiling in an urban setting and an intensifying dairy agroecosystem. Antibiotic-resistant E. coli may pose different ingestion and contact risks than do susceptible E. coli. This difference cannot be seen in population counts alone. This is an important finding for human health assessments of freshwater systems, particularly where recreational uses occur downstream.

A key problem in ecology is to predict the presence–absence of species across a geographical region. Dispersal is thought to have an important influence on the range limits of species, and understanding this problem in a multi-species community with priority effects (i.e. initial abundances determine the presence–absence of species) is a challenging task because dispersal interacts with biotic and abiotic factors as well as demographic stochasticity. By using stochastic individual-based models (IBM) and deterministic models consisting of biotic interactions and environmental gradients, we investigate the joint effects of dispersal and stochasticity on the occurrence of priority effects that can shape the presence–absence of multiple species. Our analysis shows the conditions under which priority effects occur and disappear as dispersal intensity changes. Without dispersal, priority effects emerge in the presence of intense biotic interactions; only one species surviving at any given location, with no overlap in their ranges. Inclusion of dispersal first reduces the prevalence of priority effects (i.e. for weak dispersal), and then leads to their increase (i.e. for moderate dispersal); consequently, dispersal enhances the possibility for species ranges to overlap. Increasing dispersal strength above a threshold value leads to the disappearance of priority effects and causes extinction of some species. We also demonstrate contrasting observations of stochasticity on priority effects: while this phenomenon is more prevalent in the stochastic IBM than in the deterministic models for large populations, we observe fewer occurrences of priority effects in IBM for small populations; in particular, our IBM results show that priority effects are eliminated by weaker values of dispersal when population sizes are small than when they are large. This situation can induce an uncertainty in the predictions of species presence–absence. Overall, our results demonstrate how the interplay of dispersal and stochasticity can combine to result in the (dis-)appearance of priority effects that strongly determine the presence–absence of species.

There is a great need to understand how and why biodiversity, which we define as the variety of organisms found in a given place, changes over time. Current estimates suggest strikingly slow change in traditional measures of biodiversity. These estimates seem to contradict rapid shifts in the abundance of individual species and have led to a rethinking of the mechanisms shaping biodiversity. Conceptual models emphasize the role of competition among species or, more recently, selection on species identity (i.e. selection that favors some species at the expense of others). However, it is difficult to quantify how these mechanisms contribute to biodiversity change. To illustrate this point we present cases where strong competition or selection on species identity leads to no biodiversity change. In view of this disconnect we develop a new approach to studying biodiversity change using the Price equation. We show that biodiversity change responds to selection on species’ rarity, rather than to either competition or selection on species identity. We then show how this insight can be used to quantify the effects of the mechanisms previously thought to influence biodiversity: 1) selection, 2) (ecological) drift, 3) immigration and 4) speciation. Our results suggest the connection between species’ fates and their rarity is fundamental to understanding biodiversity change.

Ecological niches reflect not only adaptation to local circumstances but also the tendency of related lineages to share environmental tolerances. As a result, information on phylogenetic relationships has underappreciated potential to inform ecological niche modeling. Here we review three strategies for incorporating evolutionary information into niche models: splitting lineages into subunits, lumping across lineages, and partial pooling of lineages into a common statistical framework that implicitly or explicitly accounts for evolutionary relationships. We challenge the default practice of modeling at the species level, which ignores the process of niche evolution and erroneously assumes that the species is always the appropriate level for niche estimation. Progress in the field requires reexamination of how we assess models of niches versus models of distributions.

Entomopathogenic fungi from the genus Beauveria (Vuillemin) play an important role in controlling insect populations and have been increasingly utilized for the biological control of insect pests. Various studies have reported that Beauveria bassiana (Bals.), Vuill. also has the ability to colonize a broad range of plant hosts as endophytes without causing disease but while still maintaining the capacity to infect insects. Beauveria is often applied as an inundative spore application, but little research has considered how plant colonization may alter the ability to persist in the environment. The aim of this study was to investigate potential interactions between B. bassiana and Zea mays L. (maize) in the rhizosphere following inoculation, in order to understand the factors that may affect environmental persistence of the fungi. The hypothesis was that different isolates of B. bassiana have the ability to colonize maize roots and/or rhizosphere soil, resulting in effects to the plant microbiome. To test this hypothesis, a two-step nested PCR protocol was developed to find and amplify Beauveria in planta or in soil; based on the translation elongation factor 1-alpha (ef1α) gene. The nested protocol was also designed to enable Beauveria species differentiation by sequence analysis. The impact of three selected B. bassiana isolates applied topically to roots on the rhizosphere soil community structure and function were consequently assessed using denaturing gradient gel electrophoresis (DGGE) and MicroRespTM techniques. The microbial community structure and function were not significantly affected by the presence of the isolates, however, retention of the inocula in the rhizosphere at 30 days after inoculation was enhanced when plants were subjected to intensive wounding of foliage to crudely simulate herbivory. The plant defense response likely changed under wound stress resulting in the apparent recruitment of Beauveria in the rhizosphere, which may be an indirect defensive strategy against herbivory and/or the result of induced systemic susceptibility in maize enabling plant colonization.

Antibiotic resistance is medicine’s climate change: caused by human activity, and resulting in more extreme outcomes. Resistance emerges in microbial populations when antibiotics act on phenotypic variance within the population. This can arise from either genotypic diversity (resulting from a mutation or horizontal gene transfer), or from ‘adaptive’ differences in gene expression due to environmental variation. Adaptive changes can increase fitness allowing bacteria to survive at higher concentrations of the antibiotic. They can also decrease fitness, potentially leading to selection for antibiotic resistance at lower concentrations. There are opportunities for other environmental stressors to promote antibiotic resistance in ways that are hard to predict using conventional assays. Exploiting our observation that commonly used herbicides can increase or decrease the minimum inhibitory concentration (MIC) of different antibiotics, we provide the first comprehensive test of the hypothesis that the rate of antibiotic resistance evolution under specified conditions can increase, regardless of whether a herbicide increases or decreases the antibiotic MIC. Short term evolution experiments were used for various herbicide and antibiotic combinations. We found conditions where acquired resistance arises more frequently regardless of whether the exogenous non-antibiotic agent increased or decreased antibiotic effectiveness. This “damned if you do/damned if you don’t” outcome suggests that the emergence of antibiotic resistance is exacerbated by additional environmental factors that influence competition between bacteria. Our work demonstrates that bacteria may acquire antibiotic resistance in the environment at rates substantially faster than predicted from laboratory conditions.

One of the key problems in ecology is our need to anticipate the set of locations in which a species will be found (hereafter species' distributions). A major source of uncertainty in these models is the role of interactions among species (hereafter biotic interactions). Unfortunately, it is difficult to directly study this problem at large spatial scales and we lack a clear understanding of when biotic interactions shape species' distributions. We show a simple, direct link between the ease of species' coexistence and the importance of competition for shaping species' distributions. We show that increasing the ease of species' coexistence reduces the influence of biotic interactions. Changing the spatial scale of the analysis can reduce the influence of species interactions, but only when it promotes regional coexistence. Using these ideas, we analyze the conditions under which biotic interactions alter species' distributions in a Lotka–Volterra model of competition along an environmental gradient and argue that coexistence theory, rather than scale alone, provides a guide to the influence of species interactions. Our results provide a guide to the facets of biotic interactions that are necessary to anticipate their effects on species distributions. As such, we expect our work will help the development of more realistic distribution models.

Herbicides are frequently released into both rural and urban environments. Commercial herbicide formulations induce adaptive changes in the way bacteria respond to antibiotics. Salmonella enterica sv. Typhimurium and Escherichia coli were exposed to common co-formulants of formulations, and S. enterica sv. Typhimurium was exposed to active ingredients dicamba, 2,4-D and glyphosate to determine what ingredients of the commercial formulations caused this effect. Co-formulants Tween80 and carboxymethyl cellulose induced changes in response, but the pattern of the responses differed from the active ingredients, and effect sizes were smaller. A commercial wetting agent did not affect antibiotic responses. Active ingredients induced changes in antibiotic responses similar to those caused by complete formulations. This occurred at or below recommended application concentrations. Targeted deletion of efflux pump genes largely neutralized the adaptive response in the cases of increased survival in antibiotics, indicating that the biochemistry of induced resistance was the same for formulations and specific ingredients. We found that glyphosate, dicamba, and 2,4-D, as well as co-formulants in commercial herbicides, induced a change in susceptibility of the potentially pathogenic bacteria E. coli and S. enterica to multiple antibiotics. This was measured using the efficiency of plating (EOP), the relative survival of the bacteria when exposed to herbicide and antibiotic, or just antibiotic, compared to survival on permissive media. This work will help to inform the use of non-medicinal chemical agents that induce changes in antibiotic responses.

There is a great deal of interest in the effects of biotic interactions on geographic distributions. Nature contains many different types of biotic interactions (notably mutualism, commensalism, predation, amensalism, and competition), and it is difficult to compare the effects of multiple interaction types on species’ distributions. To resolve this problem, we analyze a general, flexible model of pairwise biotic interactions that can describe all interaction types. In the absence of strong positive feedback, a species’ ability to be present depends on its ability to increase in numbers when it is rare and the species it is interacting with is at equilibrium. This insight leads to counterintuitive conclusions. Notably, we often predict the same range limit when the focal species experiences competition, predation, or amensalism. Similarly, we often predict the same range margin or when the species experiences mutualism, commensalism, or benefits from prey. In the presence of strong positive density-dependent feedback, different species interactions produce different range limits in our model. In all cases, the abiotic environment can indirectly influence the impact of biotic interactions on range limits. We illustrate the implications of this observation by analyzing a stress gradient where biotic interactions are harmful in benign environments but beneficial in stressful environments. Our results emphasize the need to consider the effects of all biotic interactions on species’ range limits and provide a systematic comparison of when biotic interactions affect distributions.

Summary 1. Organismal biologists need to detect and anticipate the effects of niche evolution. An increasing number of studies use information on changes in species’ distribution to test for niche evolution. Typically, these studies will test to see whether the range of environments occupied by a species is similar in each biogeographic region. 2. Niche evolution can change the occurrence probability (the frequency with which we observe a species) rather than the range of environments occupied. Using simulation, we test whether 13 previously implemented methods, and a novel approach (Expected Shared Presences), can identify shifts in occurrence probability. 3. We show that even the best previously implemented methods detect shifts in the range of environments occupied, but provide poor inferences for shifts in occurrence probability. The expected shared presences approach provides a strong estimate of niche evolution due to shifts in niche overlap and shifts in occurrence probability. 4. This work indicates that previous studies may have missed a substantial source of niche evolution. We argue that rigorous tests of niche overlap must account for shifts in both the range of environments occupied and the frequency of suitable environments.

The niche is a fundamental ecological concept that underpins many explanations of patterns of biodiversity. The complexity of niche processes in ecological systems, however, means that it is difficult to capture them accurately in theoretical models of community assembly. In this study, we build upon simple neutral biodiversity models by adding the important ingredient of overlapping niche structure. Our model is spatially implicit and contains a fixed number of equal-sized habitats. Each species in the metacommunity arises through a speciation event; at which time, it is randomly assigned a fundamental niche or set of environments/habitats in which it can persist. Within each habitat, species compete with other species that have different but overlapping fundamental niches. Species abundances then change through ecological drift; each, however, is constrained by its maximum niche breadth and by the presence of other species in its habitats. Using our model, we derive analytical expressions for steady-state species abundance distributions, steady-state distributions of niche breadth across individuals and across species, and dynamic distributions of niche breadth across species. With this framework, we identify the conditions that produce the log-series species abundance distribution familiar from neutral models. We then identify how overlapping niche structure can lead to other species abundance distributions and, in particular, ask whether these new distributions differ significantly from species abundance distributions predicted by non-overlapping niche models. Finally, we extend our analysis to consider additional distributions associated with realized niche breadths. Overall, our results show that models with overlapping niches can exhibit behavior similar to neutral models, with the caveat that species with narrow fundamental niche breadths will be very rare. If narrow-niche species are common, it must be because they are in a non-overlapping niche or have countervailing advantages over broad-niche species. This result highlights the role that niches can play in establishing demographic neutrality.

A fundamental goal of ecology is to understand the determinants of species' distributions (i.e., the set of locations where a species is present). Competition among species (i.e., interactions among species that harms each of the species involved) is common in nature and it would be tremendously useful to quantify its effects on species' distributions. An approach to studying the large‐scale effects of competition or other biotic interactions is to fit species' distributions models (SDMs) and assess the effect of competitors on the distribution and abundance of the species of interest. It is often difficult to validate the accuracy of this approach with available data. Here, we simulate virtual species that experience competition. In these simulated datasets, we can unambiguously identify the effects that competition has on a species' distribution. We then fit SDMs to the simulated datasets and test whether we can use the outputs of the SDMs to infer the true effect of competition in each simulated dataset. In our simulations, the abiotic environment influenced the effects of competition. Thus, our SDMs often inferred that the abiotic environment was a strong predictor of species abundance, even when the species' distribution was strongly affected by competition. The severity of this problem depended on whether the competitor excluded the focal species from highly suitable sites or marginally suitable sites. Our results highlight how correlations between biotic interactions and the abiotic environment make it difficult to infer the effects of competition using SDMs.

There is no consensus on when biotic interactions impact the range limits of species. Starting from MacArthur's use of invasibility to understand how biotic interactions influence coexistence, here we examine how biotic interactions shape species distributions. Range limits emerge from how birth, death, and movement rates vary with the environment. We clarify some basic issues revolving around niche definitions, illustrated with simple resource–consumer theory. We then highlight two different avenues for linking community theory and range theory; the first based on calculating the effects of biotic interactions on range limits across scales and landscape configurations, and the second based on aggregate measures of diffuse interactions and network strength. We conclude with suggestions for a future research agenda.

International audience; Global environmental change is altering the patterns of biodiversity worldwide. Observation and theory suggest that species' distributions and abundances depend on a suite of processes, notably abiotic filtering and biotic interactions, both of which are constrained by species' phylogenetic history. Models predicting species distribution have historically mostly considered abiotic filtering and are only starting to integrate biotic interaction. However, using information on present interactions to forecast the future of biodiversity supposes that biotic interactions will not change when species are confronted with new environments. Using bacterial microcosms, we illustrate how biotic interactions can vary along an environmental gradient and how this variability can depend on the phylogenetic distance between interacting species.

A major problem in ecology is to understand how environmental requirements change over space and time. To this end, numerous authors have attempted to use comparisons of species’ distributions as a surrogate for comparisons of environmental requirements. Unfortunately, it is currently unclear when comparisons of species’ distributions produce reliable inferences about changes in environmental requirements. To address this problem, I develop an analytic model that identifies the conditions under which a comparison of species’ distribution models can serve as surrogate for a comparison of environmental requirements. This work demonstrates that 1) comparisons of species’ distributions typically produce biased comparisons of environmental requirements, 2) assuming distribution models are fit appropriately, it is possible to compare environmental requirements of distinct taxa, 3) there are multiple biologically relevant questions we can address using comparisons of distribution models, with each question corresponding to a distinct measure of the difference between distribution models. By developing an analytic model for comparisons of species’ distributions this work helps to clarify and remedy poorly understood sources of error associated with existing methods.

Coevolution is thought to promote evolutionary change between demes that ultimately results in speciation. If this is the case, then we should expect to see similar patterns of trait matching and phenotypic divergence between populations and between species in model systems for coevolution. As measures of divergence are frequently only available at one scale (population level or taxon level), this contention is rarely tested directly. Here, we use the case of co-divergence between different varieties of Joshua tree Yucca brevifolia (Agavaceae) and their obligate pollinators, two yucca moths (Tegeticula spp. Prodoxidae), to test for trait matching between taxa and among populations. Using model selection, we show that there is trait matching between mutualists at the taxon level, but once we account for differences between taxa, there is no indication of trait matching in local populations. This result differs from similar studies in other coevolving systems. We hypothesize that this discrepancy arises because coevolution in obligate mutualisms favours divergence less strongly than coevolution in other systems, such as host–parasite interactions.

Ecological opportunity – through entry into a new environment, the origin of a key innovation or extinction of antagonists – is widely thought to link ecological population dynamics to evolutionary diversification. The population-level processes arising from ecological opportunity are well documented under the concept of ecological release. However, there is little consensus as to how these processes promote phenotypic diversification, rapid speciation and adaptive radiation. We propose that ecological opportunity could promote adaptive radiation by generating specific changes to the selective regimes acting on natural populations, both by relaxing effective stabilizing selection and by creating conditions that ultimately generate diversifying selection. We assess theoretical and empirical evidence for these effects of ecological opportunity and review emerging phylogenetic approaches that attempt to detect the signature of ecological opportunity across geological time. Finally, we evaluate the evidence for the evolutionary effects of ecological opportunity in the diversification of Caribbean Anolis lizards. Some of the processes that could link ecological opportunity to adaptive radiation are well documented, but others remain unsupported. We suggest that more study is required to characterize the form of natural selection acting on natural populations and to better describe the relationship between ecological opportunity and speciation rates.

Traditionally, the goal of systematics has been to produce classifications that are both strongly supported and biologically meaningful. In recent years several authors have advocated complementing phylogenetic analyses with measures of another form of evolutionary change, ecological divergence. These analyses frequently rely on ecological niche models to determine if species have comparable environmental requirements, but it has heretofore been difficult to test the accuracy of these inferences. To address this problem, I simulate the geographic distributions of allopatric species with identical environmental requirements. I then test whether existing analyses based on geographic distributions will correctly infer that the 2 species' requirements are identical. This work demonstrates that when taxa disperse to different environments, many analyses can erroneously infer changes in environmental requirements, but the severity of the problem depends on the method used. As this could exaggerate the number of ecologically distinct taxa in a clade, I suggest diagnostics to mitigate this problem.