Heat and desiccation tolerances predict bee abundance under climate change

Climate change could pose an urgent threat to pollinators, with critical ecological and economic consequences. However, for most insect pollinator species, we lack the long-term data and mechanistic evidence that are necessary to identify climate-driven declines and predict future trends. Here we document 16 years of abundance patterns for a hyper-diverse bee assemblage1 in a warming and drying region2, link bee declines with experimentally determined heat and desiccation tolerances, and use climate sensitivity models to project bee communities into the future. Aridity strongly predicted bee abundance for 71% of 665 bee populations (species × ecosystem combinations). Bee taxa that best tolerated heat and desiccation increased the most over time. Models forecasted declines for 46% of species and predicted more homogeneous communities dominated by drought-tolerant taxa, even while total bee abundance may remain unchanged. Such community reordering could reduce pollination services, because diverse bee assemblages typically maximize pollination for plant communities3. Larger-bodied bees also dominated under intermediate to high aridity, identifying body size as a valuable trait for understanding how climate-driven shifts in bee communities influence pollination4. We provide evidence that climate change directly threatens bee diversity, indicating that bee conservation efforts should account for the stress of aridity on bee physiology.

As above, not so below: Long-term dynamics of net primary production across a dryland transition zone

Drylands are key contributors to interannual variation in the terrestrial carbon sink, which has been attributed primarily to broad-scale climatic anomalies that disproportionately affect net primary production (NPP) in these ecosystems. Current knowledge around the patterns and controls of NPP is based largely on measurements of aboveground net primary production (ANPP), particularly in the context of altered precipitation regimes. Limited evidence suggests belowground net primary production (BNPP), a major input to the terrestrial carbon pool, may respond differently than ANPP to precipitation, as well as other drivers of environmental change, such as nitrogen deposition and fire. Yet long-term measurements of BNPP are rare, contributing to uncertainty in carbon cycle assessments. Here, we used 16 years of annual NPP measurements to investigate responses of ANPP and BNPP to several environmental change drivers across a grassland-shrubland transition zone in the northern Chihuahuan Desert. ANPP was positively correlated with annual precipitation across this landscape; however, this relationship was weaker within sites. BNPP, on the other hand, was weakly correlated with precipitation only in Chihuahuan Desert shrubland. Although NPP generally exhibited similar trends among sites, temporal correlations between ANPP and BNPP within sites were weak. We found chronic nitrogen enrichment stimulated ANPP, whereas a one-time prescribed burn reduced ANPP for nearly a decade. Surprisingly, BNPP was largely unaffected by these factors. Together, our results suggest that BNPP is driven by a different set of controls than ANPP. Furthermore, our findings imply belowground production cannot be inferred from aboveground measurements in dryland ecosystems. Improving understanding around the patterns and controls of dryland NPP at interannual to decadal scales is fundamentally important because of their measurable impact on the global carbon cycle. This study underscores the need for more long-term measurements of BNPP to improve assessments of the terrestrial carbon sink, particularly in the context of ongoing environmental change.

Measuring change in biological communities: multivariate analysis approaches for temporal datasets with low sample size

Effective and robust ways to describe, quantify, analyse, and test for change in the structure of biological communities over time are essential if ecological research is to contribute substantively towards understanding and managing responses to ongoing environmental changes. Structural changes reflect population dynamics, changes in biomass and relative abundances of taxa, and colonisation and extinction events observed in samples collected through time. Most previous studies of temporal changes in the multivariate datasets that characterise biological communities are based on short time series that are not amenable to data-hungry methods such as multivariate generalised linear models. Here, we present a roadmap for the analysis of temporal change in short-time-series, multivariate, ecological datasets. We discuss appropriate methods and important considerations for using them such as sample size, assumptions, and statistical power. We illustrate these methods with four case-studies analysed using the R data analysis environment.

Changes in the analysis of temporal community dynamics data: a 29-year literature review

BACKGROUND

Understanding how biological communities change over time is of increasing importance as Earth moves into the Anthropocene. A wide variety of methods are used for multivariate community analysis and are variously applied to research that aims to characterise temporal dynamics in community composition. Understanding these methods and how they are applied is useful for determining best practice in community ecology.

METHODOLOGY

We reviewed the ecological literature from 1990 to 2018 that used multivariate methods to address questions of temporal community dynamics. For each paper that fulfilled our search criteria, we recorded the types of multivariate analysis used to characterise temporal community dynamics in addition to the research aim, habitat type, location, taxon and the experimental design.

RESULTS

Most studies had relatively few temporal replicates; the median number was seven time points. Nearly 70% of studies applied more than one analysis method; descriptive methods such as bar graphs and ordination were the most commonly applied methods. Surprisingly, the types of analyses used were only related to the number of temporal replicates, but not to research aim or any other aspects of experimental design such as taxon, or habitat or year of study.

CONCLUSIONS

This review reveals that most studies interested in understanding community dynamics use relatively short time series meaning that several, more sophisticated, temporal analyses are not widely applicable. However, newer methods using multivariate dissimilarities are growing in popularity and many can be applied to time series of any length.

Introduced ecological engineers drive behavioral changes of grasshoppers, consequently linking to its abundance in two grassland plant communities

Introduced ecosystem engineers are expected to have extensive ecological impacts on a broad range of resident biota by altering the physical-chemical structure of ecosystems. Livestock that are potentially important introduced ecosystem engineers in grassland systems could create and/or modify habitats for native plant-dwelling insects. Yet, there is little knowledge of how insects respond to engineering effects of introduced livestock. To bridge this gap, we tested how domestic sheep affects the behavior and abundance of a native grasshopper Euchorthippus unicolor at both low (11.8 ± 0.4 plant species per plot) and high (19.8 ± 0.5 plant species per plot) diversity sites. Results found grasshoppers shifted their resting and feeding locations from the upper to the intermediate or low layers of vegetation, and fed on more plants species following livestock engineering effects. In the low plant diversity habitats, grazing caused grasshoppers to increase switching frequency, spend more time searching for host plants, and reduce time spent feeding, but had opposite effects on all the three behaviors in the high-diversity habitats. Moreover, grazing engineering effects on behavioral changes of grasshoppers were potentially related to their abundance. Overall, this study highlights native insect species' behavior and abundance in responses to introduced ecological engineers, and suggests that ecosystem engineers of non-native species have strong and important impacts extending beyond their often most obvious and frequently documented direct ecological effects.

Predicting changes in bee assemblages following state transitions at North American dryland ecotones

Drylands worldwide are experiencing ecosystem state transitions: the expansion of some ecosystem types at the expense of others. Bees in drylands are particularly abundant and diverse, with potential for large compositional differences and seasonal turnover across ecotones. To better understand how future ecosystem state transitions may influence bees, we compared bee assemblages and their seasonality among sites at the Sevilleta National Wildlife Refuge (NM, USA) that represent three dryland ecosystem types (and two ecotones) of the southwestern U.S. (Plains grassland, Chihuahuan Desert grassland, and Chihuahuan Desert shrubland). Using passive traps, we caught bees during two-week intervals from March–October, 2002–2014. The resulting dataset included 302 bee species and 56 genera. Bee abundance, composition, and diversity differed among ecosystems, indicating that future state transitions could alter bee assemblage composition in our system. We found strong seasonal bee species turnover, suggesting that bee phenological shifts may accompany state transitions. Common species drove the observed trends, and both specialist and generalist bee species were indicators of ecosystem types or months; these species could be sentinels of community-wide responses to future shifts. Our work suggests that predicting the consequences of global change for bee assemblages requires accounting for both within-year and among-ecosystem variation.

Divergence in Diversity and Composition of Root-Associated Fungi Between Greenhouse and Field Studies in a Semiarid Grassland

Investigations of plant-soil feedbacks (PSF) and plant-microbe interactions often rely exclusively on greenhouse experiments, yet we have little understanding of how, and when, results can be extrapolated to explain phenomena in nature. A systematic comparison of microbial communities using the same host species across study environments can inform the generalizability of such experiments. We used Illumina MiSeq sequencing to characterize the root-associated fungi of two foundation grasses from a greenhouse PSF experiment, a field PSF experiment, field monoculture stands, and naturally occurring resident plants in the field. A core community consisting < 10% of total fungal OTU richness but > 50% of total sequence abundance occurred in plants from all study types, demonstrating the ability of field and greenhouse experiments to capture the dominant component of natural communities. Fungal communities were plant species-specific across the study types, with the core community showing stronger host specificity than peripheral taxa. Roots from the greenhouse and field PSF experiments had lower among sample variability in community composition and higher diversity than those from naturally occurring, or planted monoculture plants from the field. Core and total fungal composition differed substantially across study types, and dissimilarity between fungal communities did not predict plant-soil feedbacks measured in experiments. These results suggest that rhizobiome assembly mechanisms in nature differ from the dynamics of short-term, inoculation studies. Our results validate the efficacy of common PSF experiment designs to test soil inoculum effects, and highlight the challenges of scaling the underlying microbial mechanisms of plant responses from whole-community inoculation experiments to natural ecosystems.

Experimental drought reduces genetic diversity in the grassland foundation species Bouteloua eriopoda

Understanding the resistance and resilience of foundation plant species to climate change is a critical issue because the loss of these species would fundamentally reshape communities and ecosystem processes. High levels of population genetic diversity may buffer foundation species against climate disruptions, but the strong selective pressures associated with climatic shifts may also rapidly reduce such diversity. We characterized genetic diversity and its responsiveness to experimental drought in the foundation plant, black grama grass (Bouteloua eriopoda), which dominates many western North American grasslands and shrublands. Previous studies suggested that in arid ecosystems, black grama reproduces largely asexually via stolons, and thus is likely to have low genetic variability, which might limit its potential to respond to climate disruptions. Using genotyping-by-sequencing, we demonstrated unexpectedly high genetic variability among black grama plants in a 1 ha site within the Sevilleta National Wildlife Refuge in central New Mexico, suggesting some level of sexual reproduction. Three years of experimental, growing season drought reduced black grama survival and biomass (the latter by 96%), with clear genetic differentiation (higher F_ST) between plants succumbing to drought and those remaining alive. Reduced genetic variability in the surviving plants in drought plots indicated that the experimental drought had forced black grama populations through selection bottlenecks. These results suggest that foundation grass species, such as black grama, may experience rapid evolutionary change if future climates include more severe droughts.

Change in dominance determines herbivore effects on plant biodiversity

Herbivores alter plant biodiversity (species richness) in many of the world's ecosystems, but the magnitude and the direction of herbivore effects on biodiversity vary widely within and among ecosystems. One current theory predicts that herbivores enhance plant biodiversity at high productivity but have the opposite effect at low productivity. Yet, empirical support for the importance of site productivity as a mediator of these herbivore impacts is equivocal. Here, we synthesize data from 252 large-herbivore exclusion studies, spanning a 20-fold range in site productivity, to test an alternative hypothesis-that herbivore-induced changes in the competitive environment determine the response of plant biodiversity to herbivory irrespective of productivity. Under this hypothesis, when herbivores reduce the abundance (biomass, cover) of dominant species (for example, because the dominant plant is palatable), additional resources become available to support new species, thereby increasing biodiversity. By contrast, if herbivores promote high dominance by increasing the abundance of herbivory-resistant, unpalatable species, then resource availability for other species decreases reducing biodiversity. We show that herbivore-induced change in dominance, independent of site productivity or precipitation (a proxy for productivity), is the best predictor of herbivore effects on biodiversity in grassland and savannah sites. Given that most herbaceous ecosystems are dominated by one or a few species, altering the competitive environment via herbivores or by other means may be an effective strategy for conserving biodiversity in grasslands and savannahs globally.

Chronic nitrogen addition induces a cascade of plant community responses with both seasonal and progressive dynamics

Short-lived herbaceous plants provide a useful model to rapidly reveal how multiple generations of plants in natural plant communities of sensitive desert ecosystems will be affected by N deposition. We monitored dynamic responses of community structure, richness, evenness, density and biomass of herbaceous plants to experimental N addition (2:1 NH₄⁺:NO₃^- added at 0, 0.5, 1, 3, 6 and 24gNm^-2a^-1) in three seasons in each of three years in the Gurbantunggut desert, a typical temperate desert of central Asia. We found clear rate-dependent and season-dependent effects of N deposition on each of these variables, in most cases becoming more obvious through time. N addition reduced plant richness, leading to a loss of about half of the species after three generations in the highest N application level. Evenness and density were relatively insensitive to all but the greatest levels of N addition for two generations, but negative effects emerged in the third generation. Biomass, both above and below ground, was non-linearly affected by N deposition. Low and intermediate levels of N deposition often increased biomass, whereas the highest level suppressed biomass. Stimulatory effects of intermediate N addition disappeared in the third generation. All of these responses are strongly interrelated in a cascade of changes. Notably, changes in biomass due to N deposition were mediated by declines in richness and evenness, and other changes in community structure, rather than solely being the direct outcome of release from limitation. The interrelationships between N deposition and the different plant community attributes change not only seasonally, but also progressively change through time. These temporal changes appear to be largely independent of interannual or seasonal climatic conditions.

Novel fine-scale aerial mapping approach quantifies grassland weed cover dynamics and response to management

Invasive weeds threaten the biodiversity and forage productivity of grasslands worldwide. However, management of these weeds is constrained by the practical difficulty of detecting small-scale infestations across large landscapes and by limits in understanding of landscape-scale invasion dynamics, including mechanisms that enable patches to expand, contract, or remain stable. While high-end hyperspectral remote sensing systems can effectively map vegetation cover, these systems are currently too costly and limited in availability for most land managers. We demonstrate application of a more accessible and cost-effective remote sensing approach, based on simple aerial imagery, for quantifying weed cover dynamics over time. In California annual grasslands, the target communities of interest include invasive weedy grasses (Aegilops triuncialis and Elymus caput-medusae) and desirable forage grass species (primarily Avena spp. and Bromus spp.). Detecting invasion of annual grasses into an annual-dominated community is particularly challenging, but we were able to consistently characterize these two communities based on their phenological differences in peak growth and senescence using maximum likelihood supervised classification of imagery acquired twice per year (in mid- and end-of season). This approach permitted us to map weed-dominated cover at a 1-m scale (correctly detecting 93% of weed patches across the landscape) and to evaluate weed cover change over time. We found that weed cover was more pervasive and persistent in management units that had no significant grazing for several years than in those that were grazed, whereas forage cover was more abundant and stable in the grazed units. This application demonstrates the power of this method for assessing fine-scale vegetation transitions across heterogeneous landscapes. It thus provides means for small-scale early detection of invasive species and for testing fundamental questions about landscape dynamics.

Quantifying long-term plant community dynamics with movement models: implications for ecological resilience

Quantification of rates and patterns of community dynamics is central for understanding the organization and function of ecosystems. These insights may support a greater empirical understanding of ecological resilience, and the application of resilience concepts toward ecosystem management. Distinct types of dynamics in natural communities can be used to interpret and apply resilience concepts, but quantitative methods that can systematically distinguish among them are needed. We develop a quantitative method to analyze long-term records of plant community dynamics using principles of movement ecology. We analyzed dissimilarity of species composition through time with linear and nonlinear statistical models to assign community change to four classes of movement trajectories. Compositional change in each sampled plot through time was classified into four classes, stability, abrupt nonlinear change, transient reversible change, and gradual linear drift, each representing a different aspect of ecological resilience. These competing models were evaluated based on estimated coefficients, goodness of fit, and parsimony. We tested our method's accuracy and robustness through simulations, or the ability to distinguish among trajectories and classify them correctly. We simulated 16,000 trajectories of four types, of which 94-100% were correctly classified. Next, we analyzed 13 long-term vegetation records from North American grasslands (annual grasslands with warm-season and cool-season communities, shortgrass, mixedgrass, and tallgrass prairies, and sagebrush steppe), and a record of primary succession at Mt. St. Helens volcano. Collectively, we analyzed 14,647 observations from 775 plots, between 1915 and 2012. Dynamics could be reliably assigned for 705 plots (91%), and overall statistical fit was high (goodness of fit, 0.77 ± 0.15 SD). Among the perennial grasslands, stability was most common (44% of all plots), followed by gradual linear (22%), abrupt nonlinear (17%), and reversible (6%) change. Among annual grasslands, abrupt nonlinear shifts (33%) were more common in the warm-season community than in the cool-season (20%). As expected, abrupt nonlinear change was common during primary succession (51%) while reversible change was rare (3%). Generally, reversible dynamics often required 2-3 decades. Analysis of long-term community change, or trajectories, with principles of movement ecology provides a quantitative basis to compare and interpret ecological resilience within and among ecosystems.

Effects of competition on induction of crassulacean acid metabolism in a facultative CAM plant

Abiotic drivers of environmental stress have been found to induce CAM expression (nocturnal carboxylation) in facultative CAM species such as Mesembryanthemum crystallinum. The role played by biotic factors such as competition with non-CAM species in affecting CAM expression, however, remains largely understudied. This research investigated the effects of salt and water conditions on the competition between M. crystallinum and the C₃ grass Bromus mollis with which it is found to coexist in California's coastal grasslands. We also investigated the extent to which CAM expression in M. crystallinum was affected by the intensity of the competition with B. mollis. We found that M. crystallinum had a competitive advantage over B. mollis in drought and saline conditions, while B. mollis exerted strong competitive effects on M. crystallinum in access to light and soil nutrients in high water conditions. This strong competitive effect even outweighed the favorable effects of salt or water additions in increasing the biomass and productivity of M. crystallinum in mixture. Regardless of salt conditions, M. crystallinum did not switch to CAM photosynthesis in response to this strong competitive effect from B. mollis. Disturbance (i.e., grass cutting) reduced the competitive pressure by B. mollis and allowed for CAM expression in M. crystallinum when it was grown mixed with B. mollis. We suggest that moderate competition with other functional groups can enhance CAM expression in M. crystallinum, thereby affecting its plasticity and ability to cope with biological stress.

Press-pulse interactions: effects of warming, N deposition, altered winter precipitation, and fire on desert grassland community structure and dynamics

Global environmental change is altering temperature, precipitation patterns, resource availability, and disturbance regimes. Theory predicts that ecological presses will interact with pulse events to alter ecosystem structure and function. In 2006, we established a long-term, multifactor global change experiment to determine the interactive effects of nighttime warming, increased atmospheric nitrogen (N) deposition, and increased winter precipitation on plant community structure and aboveground net primary production (ANPP) in a northern Chihuahuan Desert grassland. In 2009, a lightning-caused wildfire burned through the experiment. Here, we report on the interactive effects of these global change drivers on pre- and postfire grassland community structure and ANPP. Our nighttime warming treatment increased winter nighttime air temperatures by an average of 1.1 °C and summer nighttime air temperature by 1.5 °C. Soil N availability was 2.5 times higher in fertilized compared with control plots. Average soil volumetric water content (VWC) in winter was slightly but significantly higher (13.0% vs. 11.0%) in plots receiving added winter rain relative to controls, and VWC was slightly higher in warmed (14.5%) compared with control (13.5%) plots during the growing season even though surface soil temperatures were significantly higher in warmed plots. Despite these significant treatment effects, ANPP and plant community structure were highly resistant to these global change drivers prior to the fire. Burning reduced the cover of the dominant grasses by more than 75%. Following the fire, forb species richness and biomass increased significantly, particularly in warmed, fertilized plots that received additional winter precipitation. Thus, although unburned grassland showed little initial response to multiple ecological presses, our results demonstrate how a single pulse disturbance can interact with chronic alterations in resource availability to increase ecosystem sensitivity to multiple drivers of global environmental change.

Plant-soil feedbacks promote negative frequency dependence in the coexistence of two aridland grasses

Understanding the mechanisms of species coexistence is key to predicting patterns of species diversity. Historically, the ecological paradigm has been that species coexist by partitioning resources: as a species increases in abundance, self-limitation kicks in, because species-specific resources decline. However, determining coexistence mechanisms has been a particular puzzle for sedentary organisms with high overlap in their resource requirements, such as plants. Recent evidence suggests that plant-associated microbes could generate the stabilizing self-limitation (negative frequency dependence) that is required for species coexistence. Here, we test the key assumption that plant-microbe feedbacks cause such self-limitation. We used competition experiments and modelling to evaluate how two common groups of soil microbes (rhizospheric microbes and biological soil crusts) influenced the self-limitation of two competing desert grass species. Negative feedbacks between the dominant plant competitor and its rhizospheric microbes magnified self-limitation, whereas beneficial interactions between both plant species and biological soil crusts partly counteracted this stabilizing effect. Plant-microbe interactions have received relatively little attention as drivers of vegetation dynamics in dry land ecosystems. Our results suggest that microbial mechanisms can contribute to patterns of plant coexistence in arid grasslands.

Altered rainfall patterns increase forb abundance and richness in native tallgrass prairie

Models predict that precipitation variability will increase with climate change. We used a 15-year precipitation manipulation experiment to determine if altering the timing and amount of growing season rainfall will impact plant community structure in annually burned, native tallgrass prairie. The altered precipitation treatment maintained the same total growing season precipitation as the ambient precipitation treatment, but received a rainfall regime of fewer, larger rain events, and longer intervals between events each growing season. Although this change in precipitation regime significantly lowered mean soil water content, overall this plant community was remarkably resistant to altered precipitation with species composition relatively stable over time. However, we found significantly higher forb cover and richness and slightly lower grass cover on average with altered precipitation, but the forb responses were manifest only after a ten-year lag period. Thus, although community structure in this grassland is relatively resistant to this type of altered precipitation regime, forb abundance in native tallgrass prairie may increase in a future characterized by increased growing season precipitation variability.

Hotspots of Community Change: Temporal Dynamics Are Spatially Variable in Understory Plant Composition of a California Oak Woodland

Community response to external drivers such climate and disturbance can lead to fluctuations in community composition, or to directional change. Temporal dynamics can be influenced by a combination of drivers operating at multiple spatial scales, including external landscape scale drivers, local abiotic conditions, and local species pools. We hypothesized that spatial variation in these factors can create heterogeneity in temporal dynamics within landscapes. We used understory plant species composition from an 11 year dataset from a California oak woodland to compare plots where disturbance was experimentally manipulated with the removal of livestock grazing and a prescribed burn. We quantified three properties of temporal variation: compositional change (reflecting the appearance and disappearance of species), temporal fluctuation, and directional change. Directional change was related most strongly to disturbance type, and was highest at plots where grazing was removed during the study. Temporal fluctuations, compositional change, and directional change were all related to intrinsic abiotic factors, suggesting that some locations are more responsive to external drivers than others. Temporal fluctuations and compositional change were linked to local functional composition, indicating that environmental filters can create subsets of the local species pool that do not respond in the same way to external drivers. Temporal dynamics are often assumed to be relatively static at the landscape scale, provided disturbance and climate are continuous. This study shows that local and landscape scale factors jointly influence temporal dynamics creating hotspots that are particularly responsive to climate and disturbance. Thus, adequate predictions of response to disturbance or to changing climate will only be achieved by considering how factors at multiple spatial scales influence community resilience and recovery.

Effects of monsoon precipitation variability on the physiological response of two dominant C₄ grasses across a semiarid ecotone

For the southwestern United States, climate models project an increase in extreme precipitation events and prolonged dry periods. While most studies emphasize plant functional type response to precipitation variability, it is also important to understand the physiological characteristics of dominant plant species that define plant community composition and, in part, regulate ecosystem response to climate change. We utilized rainout shelters to alter the magnitude and frequency of rainfall and measured the physiological response of the dominant C4 grasses, Bouteloua eriopoda and Bouteloua gracilis. We hypothesized that: (1) the more drought-adapted B. eriopoda would exhibit faster recovery and higher rates of leaf-level photosynthesis (A(net)) than B. gracilis, (2) A(net) would be greater under the higher average soil water content in plots receiving 30-mm rainfall events, (3) co-dominance of B. eriopoda and B. gracilis in the ecotone would lead to intra-specific differences from the performance of each species at the site where it was dominant. Throughout the study, soil moisture explained 40-70% of the variation in A(net). Consequently, differences in rainfall treatments were not evident from intra-specific physiological function without sufficient divergence in soil moisture. Under low frequency, larger rainfall events B. gracilis exhibited improved water status and longer periods of C gain than B. eriopoda. Results from this study indicate that less frequent and larger rainfall events could provide a competitive advantage to B. gracilis and influence species composition across this arid-semiarid grassland ecotone.