Could green infrastructure supplement ecosystem service provision from semi-natural grasslands?

Ancient semi-natural grasslands in Europe are important for ecosystem service (ES) provision. Often, the surrounding matrix contains 'Grassland Green Infrastructure' (GGI) that contain grassland species which have the potential to supplement grassland ES provision across the landscape. Here we investigate the potential for GGI to deliver a set of complementary ES, driven by plant composition.We surveyed 36 landscapes across three European countries comprising core grasslands and their surrounding GGI. We calculated community-level values of plant species characteristics to provide indicators for four ES: nature conservation value, pollination, carbon storage and aesthetic appeal.Inferred ES delivery for GGI was substantially lower than in core grasslands for conservation, pollination and aesthetic appeal indicators, but not for carbon storage. These differences were driven by the GGI having 17% fewer plant species, and compositional differences, with 61% of species unique to the core grasslands. In addition, connectivity to the core, the amount of GGI and inferred seed dispersal distances by livestock, were strongly positively correlated with conservation value, pollination and aesthetic indicators. All ES indicators showed similar responses to the GGI spatial structure and distance to the core, suggesting robust effects of these drivers on ES. We projected that improved landscape-wide delivery of nature conservation value and pollination could be achieved through targeted GGI management. Reductions in the distances seeds would need to disperse, more GGI, along with a diversification of the GGI elements, were predicted to enhance service credits.We conclude that for vegetation-related ES, species surveys can be employed to assess potential ES delivery. Creating and enhancing GGI is a useful landscape management strategy to supplement the ES delivered by ancient grasslands.

Soil multifunctionality and drought resistance are determined by plant structural traits in restoring grassland.

It is increasingly recognized that belowground responses to vegetation change are closely linked to plant functional traits. However, our understanding is limited concerning the relative importance of different plant traits for soil functions and of the mechanisms by which traits influence soil properties in the real world. Here we test the hypothesis that taller species, or those with complex rooting structures, are associated with high rates of nutrient and carbon (C) cycling in grassland. We further hypothesized that communities dominated by species with deeper roots may be more resilient to drought. These hypotheses were tested in a 3-yr grassland restoration experiment on degraded ex-arable land in southern England. We sowed three trait-based plant functional groups, assembled using database derived values of plant traits, and their combinations into bare soil. This formed a range of plant trait syndromes onto which we superimposed a simulated drought 2 yr after initial establishment. We found strong evidence that community weighted mean (CWM) of plant height is negatively associated with soil nitrogen cycling and availability and soil multifunctionality. We propose that this was due to an exploitative resource capture strategy that was inappropriate in shallow chalk soils. Further, complexity of root architecture was positively related to soil multifunctionality throughout the season, with fine fibrous roots being associated with greater rates of nutrient cycling. Drought resistance of soil functions including ecosystem respiration, mineralization, and nitrification were positively related to functional divergence of rooting depth, indicating that, in shallow chalk soils, a range of water capture strategies is necessary to maintain functions. Finally, after 3 yr of the experiment, we did not detect any links between the plant traits and microbial communities, supporting the finding that traits based on plant structure and resource foraging capacity are the main variables driving soil function in the early years of grassland conversion. We suggest that screening recently restored grassland communities for potential soil multifunctionality and drought resilience may be possible based on rooting architecture and plant height. These results indicate that informed assembly of plant communities based on plant traits could aid in the restoration of functioning in degraded soil.

Drought reduces floral resources for pollinators.

Climate change is predicted to result in increased occurrence and intensity of drought in many regions worldwide. By increasing plant physiological stress, drought is likely to affect the floral resources (flowers, nectar and pollen) that are available to pollinators. However, little is known about impacts of drought at the community level, nor whether plant community functional composition influences these impacts. To address these knowledge gaps, we investigated the impacts of drought on floral resources in calcareous grassland. Drought was simulated using rain shelters and the impacts were explored at multiple scales and on four different experimental plant communities varying in functional trait composition. First, we investigated the effects of drought on nectar production of three common wildflower species (Lathyrus pratensis, Onobrychis viciifolia and Prunella vulgaris). In the drought treatment, L. pratensis and P. vulgaris had a lower proportion of flowers containing nectar and O. viciifolia had fewer flowers per raceme. Second, we measured the effects of drought on the diversity and abundance of floral resources across plant communities. Drought reduced the abundance of floral units for all plant communities, irrespective of functional composition, and reduced floral species richness for two of the communities. Functional diversity did not confer greater resistance to drought in terms of maintaining floral resources, probably because the effects of drought were ubiquitous across component plant communities. The findings indicate that drought has a substantial impact on the availability of floral resources in calcareous grassland, which will have consequences for pollinator behaviour and populations.

Drought neutralises plant-soil feedback of two mesic grassland forbs.

Plant-soil feedbacks (PSFs) describe the effect of a plant species on soil properties, which affect the performance of future generations. Here we test the hypothesis that drought alters PSFs by reducing plant-microbe associations and nutrient uptake. We chose two grassland forb species, previously shown to respond differently to soil conditioning and drought, to test our hypothesis. We conditioned unsterilised grassland soil with one generation of each species, and left a third soil unconditioned. We grew a second generation consisting of each combination of plant species, soil, and drought in a full factorial design, and measured soil microbial community and nutrient availability. Scabiosa columbaria displayed negative PSF (smaller plants) under non-droughted conditions, but neutral under drought, suggesting that drought disrupts plant-soil interactions and can advantage the plant. Photosynthetic efficiency of S. columbaria was reduced under drought, but recovered on rewetting regardless of soil conditioning, indicating that PSFs do not impede resilience of this species. Sanguisorba minor showed positive PSFs (larger plants), probably due to an increase in soil N in conspecific soil, but neutral PSF under drought. PSF neutralisation appeared to occur through drought-induced change in the soil microbial community for this species. When S. minor was planted in conspecific soil, photosynthetic efficiency declined to almost zero, with no recovery following rewetting. We attributed this to increased demand for water through higher demand for nutrients with positive PSF. Here we show that drought neutralises PSFs of two grassland forbs, which could have implications for plant communities under climate change.

The importance of landscape characteristics for the delivery of cultural ecosystem services.

The importance of Cultural Ecosystem Services (CES) to human wellbeing is widely recognised. However, quantifying these non-material benefits is challenging and consequently they are often not assessed. Mapping approaches are increasingly being used to understand the spatial distribution of different CES and how this relates to landscape characteristics. This study uses an online Public Participation Geographic Information System (PPGIS) to elicit information on outdoor locations important to respondents in Wiltshire, a dynamic lowland landscape in southern England. We analysed these locations in a GIS with spatial datasets representing potential influential factors, including protected areas, land use, landform, and accessibility. We assess these characteristics at different spatial and visual scales for different types of cultural engagement. We find that areas that are accessible, near to urban centres, with larger views, and a high diversity of protected habitats, are important for the delivery of CES. Other characteristics including a larger area of woodland and the presence of sites of historic interest in the surrounding landscape were also influential. These findings have implications for land-use planning and the management of ecosystems, by demonstrating the benefits of high quality ecological sites near to towns. The importance of maintaining and restoring landscape features, such as woodlands, to enhance the delivery of CES were also highlighted.

Mechanistic species distribution modeling reveals a niche shift during invasion.

Niche shifts of nonnative plants can occur when they colonize novel climatic conditions. However, the mechanistic basis for niche shifts during invasion is poorly understood and has rarely been captured within species distribution models. We quantified the consequence of between-population variation in phenology for invasion of common ragweed (Ambrosia artemisiifolia L.) across Europe. Ragweed is of serious concern because of its harmful effects as a crop weed and because of its impact on public health as a major aeroallergen. We developed a forward mechanistic species distribution model based on responses of ragweed development rates to temperature and photoperiod. The model was parameterized and validated from the literature and by reanalyzing data from a reciprocal common garden experiment in which native and invasive populations were grown within and beyond the current invaded range. It could therefore accommodate between-population variation in the physiological requirements for flowering, and predict the potentially invaded ranges of individual populations. Northern-origin populations that were established outside the generally accepted climate envelope of the species had lower thermal requirements for bud development, suggesting local adaptation of phenology had occurred during the invasion. The model predicts that this will extend the potentially invaded range northward and increase the average suitability across Europe by 90% in the current climate and 20% in the future climate. Therefore, trait variation observed at the population scale can trigger a climatic niche shift at the biogeographic scale. For ragweed, earlier flowering phenology in established northern populations could allow the species to spread beyond its current invasive range, substantially increasing its risk to agriculture and public health. Mechanistic species distribution models offer the possibility to represent niche shifts by varying the traits and niche responses of individual populations. Ignoring such effects could substantially underestimate the extent and impact of invasions.

Impacts of invasive plants on carbon pools depend on both species' traits and local climate.

Invasive plants can alter ecosystem properties, leading to changes in the ecosystem services on which humans depend. However, generalizing about these effects is difficult because invasive plants represent a wide range of life forms, and invaded ecosystems differ in their plant communities and abiotic conditions. We hypothesize that differences in traits between the invader and native species can be used to predict impacts and so aid generalization. We further hypothesize that environmental conditions at invaded sites modify the effect of trait differences and so combine with traits to predict invasion impacts. To test these hypotheses, we used systematic review to compile data on changes in aboveground and soil carbon pools following non-native plant invasion from studies across the World. Maximum potential height (Hmax ) of each species was drawn from trait databases and other sources. We used meta-regression to assess which of invasive species' Hmax , differences in this height trait between native and invasive plants, and climatic water deficit, a measure of water stress, were good predictors of changes in carbon pools following invasion. We found that aboveground biomass in invaded ecosystems relative to uninvaded ones increased as the value of Hmax of invasive relative to native species increased, but that this effect was reduced in more water stressed ecosystems. Changes in soil carbon pools were also positively correlated with the relative Hmax of invasive species, but were not altered by water stress. This study is one of the first to show quantitatively that the impact of invasive species on an ecosystem may depend on differences in invasive and native species' traits, rather than solely the traits of invasive species. Our study is also the first to show that the influence of trait differences can be altered by climate. Further developing our understanding of the impacts of invasive species using this framework could help researchers to identify not only potentially dangerous invasive species, but also the ecosystems where impacts are likely to be greatest.

A trait-based approach for predicting species responses to environmental change from sparse data: how well might terrestrial mammals track climate change?

Estimating population spread rates across multiple species is vital for projecting biodiversity responses to climate change. A major challenge is to parameterise spread models for many species. We introduce an approach that addresses this challenge, coupling a trait-based analysis with spatial population modelling to project spread rates for 15 000 virtual mammals with life histories that reflect those seen in the real world. Covariances among life-history traits are estimated from an extensive terrestrial mammal data set using Bayesian inference. We elucidate the relative roles of different life-history traits in driving modelled spread rates, demonstrating that any one alone will be a poor predictor. We also estimate that around 30% of mammal species have potential spread rates slower than the global mean velocity of climate change. This novel trait-space-demographic modelling approach has broad applicability for tackling many key ecological questions for which we have the models but are hindered by data availability.

Modelling the introduction and spread of non-native species: international trade and climate change drive ragweed invasion.

Biological invasions are a major driver of global change, for which models can attribute causes, assess impacts and guide management. However, invasion models typically focus on spread from known introduction points or non-native distributions and ignore the transport processes by which species arrive. Here, we developed a simulation model to understand and describe plant invasion at a continental scale, integrating repeated transport through trade pathways, unintentional release events and the population dynamics and local anthropogenic dispersal that drive subsequent spread. We used the model to simulate the invasion of Europe by common ragweed (Ambrosia artemisiifolia), a globally invasive plant that causes serious harm as an aeroallergen and crop weed. Simulations starting in 1950 accurately reproduced ragweed's current distribution, including the presence of records in climatically unsuitable areas as a result of repeated introduction. Furthermore, the model outputs were strongly correlated with spatial and temporal patterns of ragweed pollen concentrations, which are fully independent of the calibration data. The model suggests that recent trends for warmer summers and increased volumes of international trade have accelerated the ragweed invasion. For the latter, long distance dispersal because of trade within the invaded continent is highlighted as a key invasion process, in addition to import from the native range. Biosecurity simulations, whereby transport through trade pathways is halted, showed that effective control is only achieved by early action targeting all relevant pathways. We conclude that invasion models would benefit from integrating introduction processes (transport and release) with spread dynamics, to better represent propagule pressure from native sources as well as mechanisms for long-distance dispersal within invaded continents. Ultimately, such integration may facilitate better prediction of spatial and temporal variation in invasion risk and provide useful guidance for management strategies to reduce the impacts of invasion.

Wildlife-friendly farming increases crop yield: evidence for ecological intensification.

Ecological intensification has been promoted as a means to achieve environmentally sustainable increases in crop yields by enhancing ecosystem functions that regulate and support production. There is, however, little direct evidence of yield benefits from ecological intensification on commercial farms growing globally important foodstuffs (grains, oilseeds and pulses). We replicated two treatments removing 3 or 8% of land at the field edge from production to create wildlife habitat in 50-60 ha patches over a 900 ha commercial arable farm in central England, and compared these to a business as usual control (no land removed). In the control fields, crop yields were reduced by as much as 38% at the field edge. Habitat creation in these lower yielding areas led to increased yield in the cropped areas of the fields, and this positive effect became more pronounced over 6 years. As a consequence, yields at the field scale were maintained--and, indeed, enhanced for some crops--despite the loss of cropland for habitat creation. These results suggested that over a 5-year crop rotation, there would be no adverse impact on overall yield in terms of monetary value or nutritional energy. This study provides a clear demonstration that wildlife-friendly management which supports ecosystem services is compatible with, and can even increase, crop yields.

Seed bank dynamics govern persistence of Brassica hybrids in crop and natural habitats.

BACKGROUND AND AIMS: Gene flow from crops to their wild relatives has the potential to alter population growth rates and demography of hybrid populations, especially when a new crop has been genetically modified (GM). This study introduces a comprehensive approach to assess this potential for altered population fitness, and uses a combination of demographic data in two habitat types and mathematical (matrix) models that include crop rotations and outcrossing between parental species. METHODS: Full life-cycle demographic rates, including seed bank survival, of non-GM Brassica rapa × B. napus F1 hybrids and their parent species were estimated from experiments in both agricultural and semi-natural habitats. Altered fitness potential was modelled using periodic matrices including crop rotations and outcrossing between parent species. KEY RESULTS: The demographic vital rates (i.e. for major stage transitions) of the hybrid population were intermediate between or lower than both parental species. The population growth rate (λ) of hybrids indicated decreases in both habitat types, and in a semi-natural habitat hybrids became extinct at two sites. Elasticity analyses indicated that seed bank survival was the greatest contributor to λ. In agricultural habitats, hybrid populations were projected to decline, but with persistence times up to 20 years. The seed bank survival rate was the main driver determining persistence. It was found that λ of the hybrids was largely determined by parental seed bank survival and subsequent replenishment of the hybrid population through outcrossing of B. rapa with B. napus. CONCLUSIONS: Hybrid persistence was found to be highly dependent on the seed bank, suggesting that targeting hybrid seed survival could be an important management option in controlling hybrid persistence. For local risk mitigation, an increased focus on the wild parent is suggested. Management actions, such as control of B. rapa, could indirectly reduce hybrid populations by blocking hybrid replenishment.

Predicting species' maximum dispersal distances from simple plant traits.

Many studies have shown plant species' dispersal distances to be strongly related to life-history traits, but how well different traits can predict dispersal distances is not yet known. We used cross-validation techniques and a global data set (576 plant species) to measure the predictive power of simple plant traits to estimate species' maximum dispersal distances. Including dispersal syndrome (wind, animal, ant, ballistic, and no special syndrome), growth form (tree, shrub, herb), seed mass, seed release height, and terminal velocity in different combinations as explanatory variables we constructed models to explain variation in measured maximum dispersal distances and evaluated their power to predict maximum dispersal distances. Predictions are more accurate, but also limited to a particular set of species, if data on more specific traits, such as terminal velocity, are available. The best model (R2 = 0.60) included dispersal syndrome, growth form, and terminal velocity as fixed effects. Reasonable predictions of maximum dispersal distance (R2 = 0.53) are also possible when using only the simplest and most commonly measured traits; dispersal syndrome and growth form together with species taxonomy data. We provide a function (dispeRsal) to be run in the software package R. This enables researchers to estimate maximum dispersal distances with confidence intervals for plant species using measured traits as predictors. Easily obtainable trait data, such as dispersal syndrome (inferred from seed morphology) and growth form, enable predictions to be made for a large number of species.

Phenology predicts the native and invasive range limits of common ragweed.

Accurate models for species' distributions are needed to forecast the progress and impacts of alien invasive species and assess potential range-shifting driven by global change. Although this has traditionally been achieved through data-driven correlative modelling, robustly extrapolating these models into novel climatic conditions is challenging. Recently, a small number of process-based or mechanistic distribution models have been developed to complement the correlative approaches. However, tests of these models are lacking, and there are very few process-based models for invasive species. We develop a method for estimating the range of a globally invasive species, common ragweed (Ambrosia artemisiifolia L.), from a temperature- and photoperiod-driven phenology model. The model predicts the region in which ragweed can reach reproductive maturity before frost kills the adult plants in autumn. This aligns well with the poleward and high-elevation range limits in its native North America and in invaded Europe, clearly showing that phenological constraints determine the cold range margins of the species. Importantly, this is a 'forward' prediction made entirely independently of the distribution data. Therefore, it allows a confident and biologically informed forecasting of further invasion and range shifting driven by climate change. For ragweed, such forecasts are extremely important as the species is a serious crop weed and its airborne pollen is a major cause of allergy and asthma in humans. Our results show that phenology can be a key determinant of species' range margins, so integrating phenology into species distribution models offers great potential for the mechanistic modelling of range dynamics.

Spreading speeds for plant populations in landscapes with low environmental variation.

Characterising the spread of biological populations is crucial in responding to both biological invasions and the shifting of habitat under climate change. Spreading speeds can be studied through mathematical models such as the discrete-time integro-difference equation (IDE) framework. The usual approach in implementing IDE models has been to ignore spatial variation in the demographic and dispersal parameters and to assume that these are spatially homogeneous. On the other hand, real landscapes are rarely spatially uniform with environmental variation being very important in determining biological spread. This raises the question of under what circumstances spatial structure need not be modelled explicitly. Recent work has shown that spatial variation can be ignored for the specific case where the scale of landscape variation is much smaller than the spreading population׳s dispersal scale. We consider more general types of landscape, where the spatial scales of environmental variation are arbitrarily large, but the maximum change in environmental parameters is relatively small. We find that the difference between the wave-speeds of populations spreading in a spatially structured periodic landscape and its homogenisation is, in general, proportional to ϵ(2), where ϵ governs the degree of environmental variation. For stochastically generated landscapes we numerically demonstrate that the error decays faster than ϵ. In both cases, this means that for sufficiently small ϵ, the homogeneous approximation is better than might be expected. Hence, in many situations, the precise details of the landscape can be ignored in favour of spatially homogeneous parameters. This means that field ecologists can use the homogeneous IDE as a relatively simple modelling tool--in terms of both measuring parameter values and doing the modelling itself. However, as ϵ increases, this homogeneous approximation loses its accuracy. The change in wave-speed due to the extrinsic (landscape) variation can be positive or negative, which is in contrast to the reduction in wave-speed caused by intrinsic stochasticity. To deal with the loss of accuracy as ϵ increases, we formulate a second-order approximation to the wave-speed for periodic landscapes and compare both approximations against the results of numerical simulation and show that they are both accurate for the range of landscapes considered.

Spreading speeds for stage structured plant populations in fragmented landscapes.

Landscape fragmentation has huge ecological and economic implications and affects the spatial dynamics of many plant species. Determining the speed of population spread in fragmented/heterogeneous landscapes is therefore of utmost importance to ecologists. Stage-structured integrodifference equations (IDEs) are deterministic models which accurately reflect the life cycles and dispersal patterns for numerous species. Existing approximations to wave-speeds consider only particular kernels, or landscapes in which the scale of variation is much smaller than the dispersal scale. We propose an analytical approximation to the wave-speeds of IDE solutions with periodic landscapes of alternating good and bad patches, where the dispersal scale is greater than the extent of each good patch and where the ratio of the demographic rates in the good and bad patches is given by a small parameter, denoted as ε. We formulate this approximation for the Gaussian and Laplace dispersal kernels and for stage structured and non-stage structured populations, and compare the results against numerical simulations. We find that the approximation is accurate for the landscapes considered, and that the type of dispersal kernel affects the relationship between landscape structure, as classified by landscape period and good patch size, and the spreading speed. This indicates that accurately fitting a kernel to data is important in determining the relationship between landscape structure and spreading speed.

Ecological restoration and rewilding: two approaches with complementary goals?

As we enter the UN Decade on Ecosystem Restoration (2021-2030) and address the urgent need to protect and restore ecosystems and their ecological functions at large scales, rewilding has been brought into the limelight. Interest in this discipline is thus increasing, with a large number of conceptual scientific papers published in recent years. Increasing enthusiasm has led to discussions and debates in the scientific community about the differences between ecological restoration and rewilding. The main goal of this review is to compare and clarify the position of each field. Our results show that despite some differences (e.g. top-down versus bottom-up and functional versus taxonomic approaches) and notably with distinct goals - recovery of a defined historically determined target ecosystem versus recovery of natural processes with often no target endpoint - ecological restoration and rewilding have a common scope: the recovery of ecosystems following anthropogenic degradation. The goals of ecological restoration and rewilding have expanded with the progress of each field. However, it is unclear whether there is a paradigm shift with ecological restoration moving towards rewilding or vice versa. We underline the complementarity in time and in space of ecological restoration and rewilding. To conclude, we argue that reconciliation of these two fields of nature conservation to ensure complementarity could create a synergy to achieve their common scope.

Quantifying farm sustainability through the lens of ecological theory.

The achievements of the Green Revolution in meeting the nutritional needs of a growing global population have been won at the expense of unintended consequences for the environment. Some of these negative impacts are now threatening the sustainability of food production through the loss of pollinators and natural enemies of crop pests, the evolution of pesticide resistance, declining soil health and vulnerability to climate change. In the search for farming systems that are sustainable both agronomically and environmentally, alternative approaches have been proposed variously called 'agroecological', 'conservation agriculture', 'regenerative' and 'sustainable intensification'. While the widespread recognition of the need for more sustainable farming is to be welcomed, this has created etymological confusion that has the potential to become a barrier to transformation. There is a need, therefore, for objective criteria to evaluate alternative farming systems and to quantify farm sustainability against multiple outcomes. To help meet this challenge, we reviewed the ecological theories that explain variance in regulating and supporting ecosystem services delivered by biological communities in farmland to identify guiding principles for management change. For each theory, we identified associated system metrics that could be used as proxies for agroecosystem function. We identified five principles derived from ecological theory: (i) provide key habitats for ecosystem service providers; (ii) increase crop and non-crop habitat diversity; (iii) increase edge density: (iv) increase nutrient-use efficiency; and (v) avoid extremes of disturbance. By making published knowledge the foundation of the choice of associated metrics, our aim was to establish a broad consensus for their use in sustainability assessment frameworks. Further analysis of their association with farm-scale data on biological communities and/or ecosystem service delivery would provide additional validation for their selection and support for the underpinning theories.

Carbon pools recover more quickly than plant biodiversity in tropical secondary forests.

Although increasing efforts are being made to restore tropical forests, little information is available regarding the time scales required for carbon and plant biodiversity to recover to the values associated with undisturbed forests. To address this knowledge gap, we carried out a meta-analysis comparing data from more than 600 secondary tropical forest sites with nearby undisturbed reference forests. Above-ground biomass approached equivalence to reference values within 80 years since last disturbance, whereas below-ground biomass took longer to recover. Soil carbon content showed little relationship with time since disturbance. Tree species richness recovered after about 50 years. By contrast, epiphyte richness did not reach equivalence to undisturbed forests. The proportion of undisturbed forest trees and epiphyte species found in secondary forests was low and changed little over time. Our results indicate that carbon pools and biodiversity show different recovery rates under passive, secondary succession and that colonization by undisturbed forest plant species is slow. Initiatives such as the Convention on Biological Diversity and REDD+ should therefore encourage active management to help to achieve their aims of restoring both carbon and biodiversity in tropical forests.

Correlated biodiversity change between plant and insect assemblages resurveyed after 80 years across a dynamic habitat mosaic.

Historical data on co-occurring taxa are extremely rare. As such, the extent to which distinct co-occurring taxa experience similar long-term patterns in species richness and compositional change (e.g., when exposed to a changing environment) is not clear. Using data from a diverse ecological community surveyed in the 1930s and resurveyed in the 2010s, we investigated whether local plant and insect assemblages displayed cross-taxon congruence-that is, spatiotemporal correlation in species richness and compositional change-across six co-occurring taxa: vascular plants, non-vascular plants, grasshoppers and crickets (Orthoptera), ants (Hymenoptera: Formicinae), hoverflies (Diptera: Syrphidae), and dragonflies and damselflies (Odonata). All taxa exhibited high levels of turnover across the ca. 80-year time period. Despite minimal observed changes at the level of the whole study system, species richness displayed widespread cross-taxon congruence (i.e., correlated temporal change) across local assemblages within the study system. Hierarchical logistic regression models suggest a role for shared responses to environmental change underlying cross-taxon correlations and highlight stronger correlations between vascular plants and their direct consumers, suggesting a possible role for biotic interactions between these groups. These results provide an illustration of cross-taxon congruence in biodiversity change using data unique in its combination of temporal and taxonomic scope, and highlight the potential for cascading and comparable effects of environmental change (abiotic and biotic) on co-occurring plant and insect communities. However, analyses of historical resurveys based on currently available data come with inherent uncertainties. As such, this study highlights a need for well-designed experiments, and monitoring programs incorporating co-occurring taxa, to determine the underlying mechanisms and prevalence of congruent biodiversity change as anthropogenic environmental change accelerates apace.