Reintroducing bison results in long-running and resilient increases in grassland diversity.

The widespread extirpation of megafauna may have destabilized ecosystems and altered biodiversity globally. Most megafauna extinctions occurred before the modern record, leaving it unclear how their loss impacts current biodiversity. We report the long-term effects of reintroducing plains bison (Bison bison) in a tallgrass prairie versus two land uses that commonly occur in many North American grasslands: 1) no grazing and 2) intensive growing-season grazing by domesticated cattle (Bos taurus). Compared to ungrazed areas, reintroducing bison increased native plant species richness by 103% at local scales (10 m2) and 86% at the catchment scale. Gains in richness continued for 29 y and were resilient to the most extreme drought in four decades. These gains are now among the largest recorded increases in species richness due to grazing in grasslands globally. Grazing by domestic cattle also increased native plant species richness, but by less than half as much as bison. This study indicates that some ecosystems maintain a latent potential for increased native plant species richness following the reintroduction of native herbivores, which was unmatched by domesticated grazers. Native-grazer gains in richness were resilient to an extreme drought, a pressure likely to become more common under future global environmental change.

The long shadow of woody encroachment: An integrated approach to modeling grassland songbird habitat.

Animals must track resources over relatively fine spatial and temporal scales, particularly in disturbance-mediated systems like grasslands. Grassland birds respond to habitat heterogeneity by dispersing among sites within and between years, yet we know little about how they make post-dispersal settlement decisions. Many methods exist to quantify the resource selection of mobile taxa, but the habitat data used in these models are frequently not collected at the same location or time that individuals were present. This spatiotemporal misalignment may lead to incorrect interpretations and adverse conservation outcomes, particularly in dynamic systems. To investigate the extent to which spatially and temporally dynamic vegetation conditions and topography drive grassland bird settlement decisions, we integrated multiple data sources from our study site to predict slope, vegetation height, and multiple metrics of vegetation cover at any point in space and time within the temporal and spatial scope of our study. We paired these predictions with avian mark-resight data for 8 years at the Konza Prairie Biological Station in NE Kansas to evaluate territory selection for Grasshopper Sparrows (Ammodramus savannarum), Dickcissels (Spiza americana), and Eastern Meadowlarks (Sturnella magna). Each species selected different types and amounts of herbaceous vegetation cover, but all three species preferred relatively flat areas with less than 6% shrub cover and less than 1% tree cover. We evaluated several scenarios of woody vegetation removal and found that, with a targeted approach, the simulated removal of just one isolated tree in the uplands created up to 14 ha of grassland bird habitat. This study supports growing evidence that small amounts of woody encroachment can fragment landscapes, augmenting conservation threats to grassland systems. Conversely, these results demonstrate that drastic increases in bird habitat area could be achieved through relatively efficient management interventions. The results and approaches reported pave the way for more efficient conservation efforts in grasslands and other systems through spatiotemporal alignment of habitat with animal behaviors and simulated impacts of management interventions.

Trajectories and state changes of a grassland stream and riparian zone after a decade of woody vegetation removal.

Riparian zones and the streams they border provide vital habitat for organisms, water quality protection, and other important ecosystem services. These areas are under pressure from local (land use/land cover change) to global (climate change) processes. Woody vegetation is expanding in grassland riparian zones worldwide. Here we report on a decade-long watershed-scale mechanical removal of woody riparian vegetation along 4.5 km of stream channel in a before-after control impact experiment. Prior to this removal, woody plants had expanded into grassy riparian areas, associated with a decline in streamflow, loss of grassy plant species, and other ecosystem-scale impacts. We confirmed some expected responses, including rapid increases in stream nutrients and sediments, disappearance of stream mosses, and decreased organic inputs to streams via riparian leaves. We were surprised that nutrient and sediment increases were transient for 3 years, that there was no recovery of stream discharge, and that areas with woody removal did not shift back to a grassland state, even when reseeded with grassland species. Rapid expansion of shrubs (Cornus drummondii, Prunus americana) in the areas where trees were removed allowed woody vegetation to remain dominant despite repeating the cutting every 2 years. Our results suggest woody expansion can fundamentally alter terrestrial and aquatic habitat connections in grasslands, resulting in inexorable movement toward a new ecosystem state. Human pressures, such as climate change, atmospheric CO2 increases, and elevated atmospheric nitrogen deposition, could continue to push the ecosystem along a trajectory that is difficult to change. Our results suggest that predicting relationships between riparian zones and the streams they border could be difficult in the face of global change in all biomes, even in well-studied sites.

Fire frequency, state change and hysteresis in tallgrass prairie.

Hysteresis is a fundamental characteristic of alternative stable state theory, yet evidence of hysteresis is rare. In mesic grasslands, fire frequency regulates transition from grass- to shrub-dominated system states. It is uncertain, however, if increasing fire frequency can reverse shrub expansion, or if grass-shrub dynamics exhibit hysteresis. We implemented annual burning in two infrequently burned grasslands and ceased burning in two grasslands burned annually. With annual fires, grassland composition converged on that of long-term annually burned vegetation due to rapid recovery of grass cover, although shrubs persisted. When annual burning ceased, shrub cover increased, but community composition did not converge with a long-term infrequently burned reference site because of stochastic and lagged dispersal by shrubs, reflecting hysteresis. Our results demonstrated that annual burning can slow, but not reverse, shrub encroachment. In addition, reversing fire frequencies resulted in hysteresis because vegetation trajectories from grassland to shrubland differed from those of shrubland to grassland.

Widespread regeneration failure in forests of Greater Yellowstone under scenarios of future climate and fire.

Changing climate and disturbance regimes are increasingly challenging the resilience of forest ecosystems around the globe. A powerful indicator for the loss of resilience is regeneration failure, that is, the inability of the prevailing tree species to regenerate after disturbance. Regeneration failure can result from the interplay among disturbance changes (e.g., larger and more frequent fires), altered climate conditions (e.g., increased drought), and functional traits (e.g., method of seed dispersal). This complexity makes projections of regeneration failure challenging. Here we applied a novel simulation approach assimilating data-driven fire projections with vegetation responses from process modeling by means of deep neural networks. We (i) quantified the future probability of regeneration failure; (ii) identified spatial hotspots of regeneration failure; and (iii) assessed how current forest types differ in their ability to regenerate under future climate and fire. We focused on the Greater Yellowstone Ecosystem (2.9 × 106  ha of forest) in the Rocky Mountains of the USA, which has experienced large wildfires in the past and is expected to undergo drastic changes in climate and fire in the future. We simulated four climate scenarios until 2100 at a fine spatial grain (100 m). Both wildfire activity and unstocked forest area increased substantially throughout the 21st century in all simulated scenarios. By 2100, between 28% and 59% of the forested area failed to regenerate, indicating considerable loss of resilience. Areas disproportionally at risk occurred where fires are not constrained by topography and in valleys aligned with predominant winds. High-elevation forest types not adapted to fire (i.e., Picea engelmannii-Abies lasiocarpa as well as non-serotinous Pinus contorta var. latifolia forests) were especially vulnerable to regeneration failure. We conclude that changing climate and fire could exceed the resilience of forests in a substantial portion of Greater Yellowstone, with profound implications for carbon, biodiversity, and recreation.

Simulating forest resilience: A review.

AIM: Simulation models are important tools for quantifying the resilience (i.e., persistence under changed environmental conditions) of forest ecosystems to global change. We synthesized the modelling literature on forest resilience, summarizing common models and applications in resilience research, and scrutinizing the implementation of important resilience mechanisms in these models. Models applied to assess resilience are highly diverse, and our goal was to assess how well they account for important resilience mechanisms identified in experimental and empirical research. LOCATION: Global. TIME PERIOD: 1994 to 2019. MAJOR TAXA STUDIED: Trees. METHODS: We reviewed the forest resilience literature using online databases, selecting 119 simulation modelling studies for further analysis. We identified a set of resilience mechanisms from the general resilience literature and analysed models for their representation of these mechanisms. Analyses were grouped by investigated drivers (resilience to what) and responses (resilience of what), as well as by the type of model being used. RESULTS: Models used to study forest resilience varied widely, from analytical approaches to complex landscape simulators. The most commonly addressed questions were associated with resilience of forest cover to fire. Important resilience mechanisms pertaining to regeneration, soil processes, and disturbance legacies were explicitly simulated in only 34 to 46% of the model applications. MAIN CONCLUSIONS: We found a large gap between processes identified as underpinning forest resilience in the theoretical and empirical literature, and those represented in models used to assess forest resilience. Contemporary forest models developed for other goals may be poorly suited for studying forest resilience during an era of accelerating change. Our results highlight the need for a new wave of model development to enhance understanding of and management for resilient forests.

Integrating Subjective and Objective Dimensions of Resilience in Fire-Prone Landscapes.

Resilience has become a common goal for science-based natural resource management, particularly in the context of changing climate and disturbance regimes. Integrating varying perspectives and definitions of resilience is a complex and often unrecognized challenge to applying resilience concepts to social-ecological systems (SESs) management. Using wildfire as an example, we develop a framework to expose and separate two important dimensions of resilience: the inherent properties that maintain structure, function, or states of an SES and the human perceptions of desirable or valued components of an SES. In doing so, the framework distinguishes between value-free and human-derived, value-explicit dimensions of resilience. Four archetypal scenarios highlight that ecological resilience and human values do not always align and that recognizing and anticipating potential misalignment is critical for developing effective management goals. Our framework clarifies existing resilience theory, connects literature across disciplines, and facilitates use of the resilience concept in research and land-management applications.

Beyond arctic and alpine: the influence of winter climate on temperate ecosystems.

Winter climate is expected to change under future climate scenarios, yet the majority of winter ecology research is focused in cold-climate ecosystems. In many temperate systems, it is unclear how winter climate relates to biotic responses during the growing season. The objective of this study was to examine how winter weather relates to plant and animal communities in a variety of terrestrial ecosystems ranging from warm deserts to alpine tundra. Specifically, we examined the association between winter weather and plant phenology, plant species richness, consumer abundance, and consumer richness in 11 terrestrial ecosystems associated with the U.S. Long-Term Ecological Research (LTER) Network. To varying degrees, winter precipitation and temperature were correlated with all biotic response variables. Bud break was tightly aligned with end of winter temperatures. For half the sites, winter weather was a better predictor of plant species richness than growing season weather. Warmer winters were correlated with lower consumer abundances in both temperate and alpine systems. Our findings suggest winter weather may have a strong influence on biotic activity during the growing season and should be considered in future studies investigating the effects of climate change on both alpine and temperate systems.

Tight coupling of leaf area index to canopy nitrogen and phosphorus across heterogeneous tallgrass prairie communities.

Nitrogen (N) and phosphorus (P) are limiting nutrients for many plant communities worldwide. Foliar N and P along with leaf area are among the most important controls on photosynthesis and hence productivity. However, foliar N and P are typically assessed as species level traits, whereas productivity is often measured at the community scale. Here, we compared the community-level traits of leaf area index (LAI) to total foliar nitrogen (TFN) and total foliar phosphorus (TFP) across nearly three orders of magnitude LAI in grazed and ungrazed tallgrass prairie in north-eastern Kansas, USA. LAI was strongly correlated with both TFN and TFP across communities, and also within plant functional types (grass, forb, woody, and sedge) and grazing treatments (bison or cattle, and ungrazed). Across almost the entire range of LAI values and contrasting communities, TFN:TFP ratios indicated co-limitation by N and P in almost all communities; this may further indicate a community scale trend of an optimal N and P allocation per unit leaf area for growth. Previously, results from the arctic showed similar tight relationships between LAI:TFN, suggesting N is supplied to canopies to maximize photosynthesis per unit leaf area. This tight coupling between LAI, N, and P in tallgrass prairie suggests a process of optimal allocation of N and P, wherein LAI remains similarly constrained by N and P despite differences in species composition, grazing, and canopy density.

Regeneration strategies and forest resilience to changing fire regimes: Insights from a Goldilocks model.

Disturbances are ubiquitous in ecological systems, and species have evolved a range of strategies to resist or rebound following disturbance. Understanding how the presence and complementarity of regeneration traits will affect community responses to disturbance is increasingly urgent as disturbance regimes shift beyond their historical ranges of variability. We define "disturbance niche" as a species' fitness across a range of disturbance sizes and frequencies that can reflect the fundamental or realized niche, that is, whether the species occurs alone or with other species. We developed a model of intermediate complexity (i.e., a Goldilocks model) to infer the disturbance niche. We parameterized the model for subalpine forests in Yellowstone National Park (USA) adapted to infrequent stand-replacing fires and included the three major tree-regeneration strategies: (1) obligate seeders that rely on ex situ seeding into burned areas (non-serotinous lodgepole pine, Pinus contorta var. latifola), (2) obligate seeders that depend on in situ seedbanks (serotinous lodgepole pine, Pinus contorta var. latifola), and (3) species that can resprout from surviving roots following fire (quaking aspen, Populus tremuloides). Our results showed which regeneration strategies increase or decrease in prevalence as fire rotation declines. Non-serotinous pines were extirpated when fire rotation was below 50 years in a monoculture and 100 years in a mixed forest; serotinous pines were extirpated when fire rotation was below 20 years; and aspen was extirpated when fire rotation fell below 6 years. The fundamental and realized disturbance niches pinpointed the key mechanisms limiting regeneration for each strategy, namely, increasing fire size for non-serotinous pine (ex situ seeders), decreasing fire frequency for serotinous pine (in situ seeders), and interspecific competition for aspen (resprouters). In a mixed forest, the three regeneration strategies were complementary and each dominated at different combinations of fire size and frequency. Consequently, diversity of regeneration strategies enhanced forest resilience to declining fire rotations. Despite its simplicity, our Goldilocks model produced realistic dynamics and could be readily adapted to other disturbance-prone ecosystems to explore the generality of these results. The disturbance niche is a key concept for anticipating community resilience to changing disturbance regimes.

Climate change, ecosystems and abrupt change: science priorities.

Ecologists have long studied patterns, directions and tempos of change, but there is a pressing need to extend current understanding to empirical observations of abrupt changes as climate warming accelerates. Abrupt changes in ecological systems (ACES)-changes that are fast in time or fast relative to their drivers-are ubiquitous and increasing in frequency. Powerful theoretical frameworks exist, yet applications in real-world landscapes to detect, explain and anticipate ACES have lagged. We highlight five insights emerging from empirical studies of ACES across diverse ecosystems: (i) ecological systems show ACES in some dimensions but not others; (ii) climate extremes may be more important than mean climate in generating ACES; (iii) interactions among multiple drivers often produce ACES; (iv) contingencies, such as ecological memory, frequency and sequence of disturbances, and spatial context are important; and (v) tipping points are often (but not always) associated with ACES. We suggest research priorities to advance understanding of ACES in the face of climate change. Progress in understanding ACES requires strong integration of scientific approaches (theory, observations, experiments and process-based models) and high-quality empirical data drawn from a diverse array of ecosystems. This article is part of the theme issue 'Climate change and ecosystems: threats, opportunities and solutions'.

Abrupt Change in Ecological Systems: Inference and Diagnosis.

Abrupt ecological changes are, by definition, those that occur over short periods of time relative to typical rates of change for a given ecosystem. The potential for such changes is growing due to anthropogenic pressures, which challenges the resilience of societies and ecosystems. Abrupt ecological changes are difficult to diagnose because they can arise from a variety of circumstances, including rapid changes in external drivers (e.g., climate, or resource extraction), nonlinear responses to gradual changes in drivers, and interactions among multiple drivers and disturbances. We synthesize strategies for identifying causes of abrupt ecological change and highlight instances where abrupt changes are likely. Diagnosing abrupt changes and inferring causation are increasingly important as society seek to adapt to rapid, multifaceted environmental changes.

Resilience in the global food system.

Ensuring food security requires food production and distribution systems function throughout disruptions. Understanding the factors that contribute to the global food system's ability to respond and adapt to such disruptions (i.e. resilience) is critical for understanding the long-term sustainability of human populations. Variable impacts of production shocks on food supply between countries indicate a need for national-scale resilience indicators that can provide global comparisons. However, methods for tracking changes in resilience have had limited application to food systems. We developed an indicator-based analysis of food systems resilience for the years 1992-2011. Our approach is based on three dimensions of resilience: socio-economic access to food in terms of income of the poorest quintile relative to food prices, biophysical capacity to intensify or extensify food production, and the magnitude and diversity of current domestic food production. The socio-economic indicator has large variability, but with low values concentrated in Africa and Asia. The biophysical capacity indicator is highest in Africa and Eastern Europe, in part because of high potential for extensification of cropland and for yield gap closure in cultivated areas. However, the biophysical capacity indicator has declined globally in recent years. The production diversity indicator has increased slightly, with a relatively even geographic distribution. Few countries had exclusively high or low values for all indicators. Collectively, these results are the basis for global comparisons of resilience between nations, and provide necessary context for developing generalizations about the resilience in the global food system.

Evidence of physiological decoupling from grassland ecosystem drivers by an encroaching woody shrub.

Shrub encroachment of grasslands is a transformative ecological process by which native woody species increase in cover and frequency and replace the herbaceous community. Mechanisms of encroachment are typically assessed using temporal data or experimental manipulations, with few large spatial assessments of shrub physiology. In a mesic grassland in North America, we measured inter- and intra-annual variability in leaf δ(13)C in Cornus drummondii across a grassland landscape with varying fire frequency, presence of large grazers and topographic variability. This assessment of changes in individual shrub physiology is the largest spatial and temporal assessment recorded to date. Despite a doubling of annual rainfall (in 2008 versus 2011), leaf δ(13)C was statistically similar among and within years from 2008-11 (range of -28 to -27‰). A topography*grazing interaction was present, with higher leaf δ(13)C in locations that typically have more bare soil and higher sensible heat in the growing season (upland topographic positions and grazed grasslands). Leaf δ(13)C from slopes varied among grazing contrasts, with upland and slope leaf δ(13)C more similar in ungrazed locations, while slopes and lowlands were more similar in grazed locations. In 2011, canopy greenness (normalized difference vegetation index - NDVI) was assessed at the centroid of individual shrubs using high-resolution hyperspectral imagery. Canopy greenness was highest mid-summer, likely reflecting temporal periods when C assimilation rates were highest. Similar to patterns seen in leaf δ(13)C, NDVI was highest in locations that typically experience lowest sensible heat (lowlands and ungrazed). The ability of Cornus drummondii to decouple leaf physiological responses from climate variability and fire frequency is a likely contributor to the increase in cover and frequency of this shrub species in mesic grassland and may be generalizable to other grasslands undergoing woody encroachment.

Comment on "Global resilience of tropical forest and savanna to critical transitions".

Hirota et al. (Reports, 14 October 2011, p. 232) used spatial data to show that grasslands, savannas, and forests represent opposing stable states. Reanalyzing their data and drawing from temporal studies, we argue that spatial analyses underestimate the bistability of grasslands and savannas due to limitations of substituting space for time. We propose that temporal and spatial data are needed to predict critical transitions between grasslands and savannas.