Ecosphere

Future disruptions to fire activity will threaten ecosystems and human well‐being throughout the world, yet there are few fire projections at global scales and almost none from a broad range of global climate models (GCMs). Here we integrate global fire datasets and environmental covariates to build spatial statistical models of fire probability at a 0.5° resolution and examine environmental controls on fire activity. Fire models are driven by climate norms from 16 GCMs (A2 emissions scenario) to assess the magnitude and direction of change over two time periods, 2010–2039 and 2070–2099. From the ensemble results, we identify areas of consensus for increases or decreases in fire activity, as well as areas where GCMs disagree. Although certain biomes are sensitive to constraints on biomass productivity and others to atmospheric conditions promoting combustion, substantial and rapid shifts are projected for future fire activity across vast portions of the globe. In the near term, the most consistent increases in fire activity occur in biomes with already somewhat warm climates; decreases are less pronounced and concentrated primarily in a few tropical and subtropical biomes. However, models do not agree on the direction of near‐term changes across more than 50% of terrestrial lands, highlighting major uncertainties in the next few decades. By the end of the century, the magnitude and the agreement in direction of change are projected to increase substantially. Most far‐term model agreement on increasing fire probabilities (∼62%) occurs at mid‐ to high‐latitudes, while agreement on decreasing probabilities (∼20%) is mainly in the tropics. Although our global models demonstrate that long‐term environmental norms are very successful at capturing chronic fire probability patterns, future work is necessary to assess how much more explanatory power would be added through interannual variation in climate variables. This study provides a first examination of global disruptions to fire activity using an empirically based statistical framework and a multi‐model ensemble of GCM projections, an important step toward assessing fire‐related vulnerabilities to humans and the ecosystems upon which they depend.

Salinization, a widespread threat to the structure and ecological functioning of inland and coastal wetlands, is currently occurring at an unprecedented rate and geographic scale. The causes of salinization are diverse and include alterations to freshwater flows, land‐clearance, irrigation, disposal of wastewater effluent, sea level rise, storm surges, and applications of de‐icing salts. Climate change and anthropogenic modifications to the hydrologic cycle are expected to further increase the extent and severity of wetland salinization. Salinization alters the fundamental physicochemical nature of the soil‐water environment, increasing ionic concentrations and altering chemical equilibria and mineral solubility. Increased concentrations of solutes, especially sulfate, alter the biogeochemical cycling of major elements including carbon, nitrogen, phosphorus, sulfur, iron, and silica. The effects of salinization on wetland biogeochemistry typically include decreased inorganic nitrogen removal (with implications for water quality and climate regulation), decreased carbon storage (with implications for climate regulation and wetland accretion), and increased generation of toxic sulfides (with implications for nutrient cycling and the health/functioning of wetland biota). Indeed, increased salt and sulfide concentrations induce physiological stress in wetland biota and ultimately can result in large shifts in wetland communities and their associated ecosystem functions. The productivity and composition of freshwater species assemblages will be highly altered, and there is a high potential for the disruption of existing interspecific interactions. Although there is a wealth of information on how salinization impacts individual ecosystem components, relatively few studies have addressed the complex and often non‐linear feedbacks that determine ecosystem‐scale responses or considered how wetland salinization will affect landscape‐level processes. Although the salinization of wetlands may be unavoidable in many cases, these systems may also prove to be a fertile testing ground for broader ecological theories including (but not limited to): investigations into alternative stable states and tipping points, trophic cascades, disturbance‐recovery processes, and the role of historical events and landscape context in driving community response to disturbance.

Extensively managed grasslands are recognized globally for their high biodiversity and their social and cultural values. However, their capacity to deliver multiple ecosystem services (ES) as parts of agricultural systems is surprisingly understudied compared to other production systems. We undertook a comprehensive overview of ES provided by natural and semi‐natural grasslands, using southern Africa (SA) and northwest Europe as case studies, respectively. We show that these grasslands can supply additional non‐agricultural services, such as water supply and flow regulation, carbon storage, erosion control, climate mitigation, pollination, and cultural ES. While demand for ecosystems services seems to balance supply in natural grasslands of SA, the smaller areas of semi‐natural grasslands in Europe appear to not meet the demand for many services. We identified three bundles of related ES from grasslands: water ES including fodder production, cultural ES connected to livestock production, and population‐based regulating services (e.g., pollination and biological control), which also linked to biodiversity. Greenhouse gas emission mitigation seemed unrelated to the three bundles. The similarities among the bundles in SA and northwestern Europe suggest that there are generalities in ES relations among natural and semi‐natural grassland areas. We assessed trade‐offs and synergies among services in relation to management practices and found that although some trade‐offs are inevitable, appropriate management may create synergies and avoid trade‐offs among many services. We argue that ecosystem service and food security research and policy should give higher priority to how grasslands can be managed for fodder and meat production alongside other ES. By integrating grasslands into agricultural production systems and land‐use decisions locally and regionally, their potential to contribute to functional landscapes and to food security and sustainable livelihoods can be greatly enhanced.

Fire is one of the most important natural disturbance processes in the western United States and ecosystems differ markedly with respect to their ecological and evolutionary relationships with fire. Reference fire regimes in forested ecosystems can be categorized along a gradient ranging from “fuel‐limited” to “climate‐limited” where the former types are often characterized by frequent, lower‐severity wildfires and the latter by infrequent, more severe wildfires. Using spatial data on fire severity from 1984–2011 and metrics related to fire frequency, we tested how divergence from historic (pre‐Euroamerican settlement) fire frequencies due to a century of fire suppression influences rates of high‐severity fire in five forest types in California. With some variation among bioregions, our results suggest that fires in forest types characterized by fuel‐limited fire regimes (e.g., yellow pine and mixed conifer forest) tend to burn with greater proportions of high‐severity fire as either time since last fire or the mean modern fire return interval (FRI) increases. Two intermediate fire regime types (mixed evergreen and bigcone Douglas‐fir) showed a similar relationship between fire frequency and fire severity. However, red fir and redwood forests, which are characterized by more climate‐limited fire regimes, did not show significant positive relationships between FRI and fire severity. This analysis provides strong evidence that for fuel‐limited fire regimes, lack of fire leads to increasing rates of high‐severity burning. Our study also substantiates the general validity of “fuel‐limited” vs. “climate‐limited” explanations of differing patterns of fire effects and response in forest types of the western US.

Climate‐induced vegetation change may be delayed in the absence of disturbance catalysts. However, increases in wildfire activity may accelerate these transitions in many areas, including the western boreal region of Canada. To better understand factors influencing decadal‐scale changes in upland boreal forest vegetation, we developed a hybrid modeling approach that constrains projections of climate‐driven vegetation change based on topo‐edaphic conditions coupled with weather‐ and fuel‐based simulations of future wildfires using Burn‐P3, a spatial fire simulation model. We evaluated eighteen scenarios based on all possible combinations of three fuel assumptions (static, fire‐mediated, and climate‐driven), two fire‐regime assumptions (constrained and unconstrained), and three global climate models. We simulated scenarios of fire‐mediated change in forest composition over the next century, concluding that, even under conservative assumptions about future fire regimes, wildfire activity could hasten the conversion of approximately half of Alberta's upland mixedwood and conifer forest to more climatically suited deciduous woodland and grassland by 2100. When fire‐regime parameter inputs (number of fire ignitions and duration of burning) were modified based on future fire weather projections, the simulated area burned was almost enough to facilitate a complete transition to climate‐predicted vegetation types. However, when fire‐regime parameters were held constant at their current values, the rate of increase in fire probability diminished, suggesting a negative feedback by which a short‐term increase in less‐flammable deciduous forest leads to a long‐term reduction in area burned. Our spatially explicit simulations of fire‐mediated vegetation change provide managers with scenarios that can be used to plan for a range of alternative landscape conditions.

Invasion by non‐native plants may fundamentally restructure the soil fungal community. The invasive plant, Alliaria petiolata, produces secondary compounds suppressive to mycorrhizal fungi and may therefore be expected to have generally negative effects on other components of the fungal community. Here, we compared fungal biomass, diversity, community composition, and the relative abundance of fungal trophic guilds, along with edaphic properties of soils collected from uninvaded and invaded plots across six temperate forests. Invaded plots were differentiated from uninvaded plots by lower variation in fungal community composition (beta diversity) and soil properties, higher fungal richness and community evenness (alpha diversity), and a suite of novel saprotrophic and pathotrophic fungi that were consistently present across the invaded landscape and absent from uninvaded forest patches. Invaded plots also had lower ectomycorrhizal but higher saprotrophic and pathotrophic relative abundance, despite there being no difference in fungal biomass between invasion statuses. We hypothesize that shifts in the fungal community with invasion may directly impact plant disease response, soil nutrient cycling processes, and plant performance of the invasive and native plant communities.

Soil microbial communities contribute to ecosystem function and structure plant communities, but are altered by anthropogenic disturbance. Successful restoration may require microbial community restoration. Inoculation of plants with arbuscular mycorrhizal fungi (AMF) may improve ecological restoration, but AMF species that are locally adapted to native plant communities are often unavailable and commercially propagated AMF are not necessarily locally adapted to the desired plant community target. The disconnect between readily available commercial fungi and later‐successional plants may inhibit successful establishment of the restoration. We tested this concept using four mid‐ to late successional prairie plant species planted with one of three inoculum sources: a locally adapted AMF mix cultured from native prairie, a non‐locally adapted commercial AMF product, or a sterilized background soil control. The inoculated plants (termed nurse plants) were planted in the middle of field plots. In each plot, uninoculated plants (test plants) were planted at 0.5, 1, and 2 m from the nurse plants in order to test whether growth and survival of test plants could be affected by inoculum source. Generally, plants grew larger when inoculated with native AMF compared to commercial inoculum or the control. Later successional species responded most positively to native AMF. Benefits of inoculation also spread to neighbors, as uninoculated late successional test plant, Sporobolus heterolepis, grew larger when its' neighbors were inoculated with native AMF than with commercial AMF or the control. Due to an unanticipated herbivory event, we also assessed the degree to which rate of herbivory or plant tolerance to herbivory is affected by inoculum source. The mid‐ successional nurse plant, Ratibida pinnata, received the majority of the herbivore damage, and when it was inoculated with commercial AMF, it experienced significantly more herbivory than plants inoculated with native AMF or the control. R. pinnata inoculated with native AMF grew significantly larger one month following herbivory, though there was no significant difference in growth in the second year of sampling. This study suggests that native, locally adapted AMF can improve restoration of prairie plant species and these benefits can extend to neighbors up to two meters from the inoculation point.

Explaining the persistence of mutualism remains a challenge in ecology and evolutionary biology. The evolutionary stability of arbuscular mycorrhiza, a most widespread and ancient mutualistic association, is particularly intriguing because plants lack apparent mechanisms to prevent cheaters from gaining competitive advantages over cooperators. We developed a triple isotopic labeling method (¹⁴C, ³²P, and ³³P) within a split‐root design to measure the exchange of carbon (C) and phosphorus (P) between the host plant and two mycorrhizal partners across a soil P gradient. Host plant preferentially allocated more C to the roots associated with the fungus delivering higher P per unit plant C, and the strength of preferential allocation decreased with increasing soil P availability. The host plant received more P per unit of allocated C from the better fungus and this advantageous exchange rate did not depend upon P availability. As a result, the level of preferential allocation was correlated with the differential delivery of P from the two fungi. Our findings suggest that plant preferential allocation to better mutualists can stabilize mutualisms in environments limiting in the traded resource, but as the availability of this resource increases, plant preferential allocation declines. This environmental dependence of preferential allocation generates predictions of declining levels in relative abundance of mutualistic fungi in high‐resource environments.

Ongoing forest restoration on public lands in the western US is a concerted effort to counter the growing incidence of uncharacteristic wildfire in fire‐adapted ecosystems. Restoration projects cover 725,000 ha annually, and include thinning and underburning to remove ladder and surface fuel, and seeding of fire‐adapted native grasses and shrubs. The backlog of areas in need of restoration combined with limited budgets requires that projects are implemented according to a prioritization system. The current system uses a stand‐scale metric that measures ecological departure from pre‐settlement conditions. Although conceptually appealing, the approach does not consider important spatial factors that influence both the efficiency and feasibility of managing future fire in the post‐treatment landscape. To address this gap, we developed a spatial model that can be used to explore different landscape treatment configurations and identify optimal project parameters that maximize restoration goals. We tested the model on a 245,000 ha forest and analyzed tradeoffs among treatment strategies as defined by fire behavior thresholds, total area treated, and the proportion of the project area treated. We assumed the primary goal as the protection and conservation of old growth ponderosa pine trees from potential wildfire loss. The model located optimal project areas for restoration and identified treatment areas within them, although the location was dependent on assumptions about acceptable fire intensity within restored landscapes, and the total treated area per project. When a high percentage of stands was treated (e.g., >80%), the resulting project area was relatively small, leaving the surrounding landscape at risk for fire. Conversely, treating only a few stands with extreme fire behavior (<20%) created larger projects, but substantial old growth forests remained susceptible to wildfire mortality within the project area. Intermediate treatment densities (35%) were optimal in terms of the overall reduction in the potential wildfire mortality of old growth. The current work expands the application in spatial optimization to the problem of dry forest restoration, and demonstrates a decision support protocol to prioritize landscapes and specific areas to treat within them. The concepts and model can be applied to similar problems in spatial ecology.

High‐resolution characterizations and predictions are a grand challenge for ecohydrology. Recent advances in flight control, robotics and miniaturized sensors using unmanned aerial vehicles (UAVs) provide an unprecedented opportunity for characterizing, monitoring and modeling ecohydrologic systems at high‐resolution (<1 m) over a range of scales. How can the ecologic and hydrologic communities most effectively use UAVs for advancing the state of the art? This Innovative Viewpoints paper introduces the utility of two classes of UAVs for ecohydrologic investigations in two semiarid rangelands of the southwestern U.S. through two useful examples. We discuss the UAV deployments, the derived image, terrain and vegetation products and their usefulness for ecohydrologic studies at two different scales. Within a land‐atmosphere interaction study, we utilize high‐resolution imagery products from a rotary‐wing UAV to characterize an eddy covariance footprint and scale up environmental sensor network observations to match the time‐varying sampling area. Subsequently, in a surface and subsurface interaction study within a small watershed, we demonstrate the use of a fixed‐wing UAV to characterize the spatial distribution of terrain attributes and vegetation conditions which serve as input to a distributed ecohydrologic model whose predictions compared well with an environmental sensor network. We also point to several challenges in performing ecohydrology with UAVs with the intent of promoting this new self‐service (do‐it‐yourself) model for high‐resolution image acquisition over many scales. We believe unmanned aerial vehicles can fundamentally change how ecohydrologic science is conducted and offer ways to merge remote sensing, environmental sensor networks and numerical models.