Macroscale controls determine the recovery of river ecosystem productivity following flood disturbances.

River ecosystem function depends on flow regimes that are increasingly modified by changes in climate, land use, water extraction, and flow regulation. Given the wide range of variation in flow regime modifications and autotrophic communities in rivers, it has been challenging to predict which rivers will be more resilient to flow disturbances. To better understand how river productivity is disturbed by and recovers from high-flow disturbance events, we used a continental-scale dataset of daily gross primary production time series from 143 rivers to estimate growth of autotrophic biomass and ecologically relevant flow disturbance thresholds using a modified population model. We compared biomass recovery rates across hydroclimatic gradients and catchment characteristics to evaluate macroscale controls on ecosystem recovery. Estimated biomass accrual (i.e., recovery) was fastest in wider rivers with less regulated flow regimes and more frequent instances of biomass removal during high flows. Although disturbance flow thresholds routinely fell below the estimated bankfull flood (i.e., the 2-y flood), a direct comparison of disturbance flows estimated by our biomass model and a geomorphic model revealed that biomass disturbance thresholds were usually greater than bed disturbance thresholds. We suggest that primary producers in rivers vary widely in their capacity to recover following flow disturbances, and multiple, interacting macroscale factors control productivity recovery rates, although river width had the strongest overall effect. Biomass disturbance flow thresholds varied as a function of geomorphology, highlighting the need for data such as bed slope and grain size to predict how river ecosystems will respond to changing flow regimes.

Models of underlying autotrophic biomass dynamics fit to daily river ecosystem productivity estimates improve understanding of ecosystem disturbance and resilience.

Directly observing autotrophic biomass at ecologically relevant frequencies is difficult in many ecosystems, hampering our ability to predict productivity through time. Since disturbances can impart distinct reductions in river productivity through time by modifying underlying standing stocks of biomass, mechanistic models fit to productivity time series can infer underlying biomass dynamics. We incorporated biomass dynamics into a river ecosystem productivity model for six rivers to identify disturbance flow thresholds and understand the resilience of primary producers. The magnitude of flood necessary to disturb biomass and thereby reduce ecosystem productivity was consistently lower than the more commonly used disturbance flow threshold of the flood magnitude necessary to mobilize river bed sediment. The estimated daily maximum percent increase in biomass (a proxy for resilience) ranged from 5% to 42% across rivers. Our latent biomass model improves understanding of disturbance thresholds and recovery patterns of autotrophic biomass within river ecosystems.

Where can managers effectively resist climate-driven ecological transformation in pinyon-juniper woodlands of the US Southwest?

Pinyon-juniper (PJ) woodlands are an important component of dryland ecosystems across the US West and are potentially susceptible to ecological transformation. However, predicting woodland futures is complicated by species-specific strategies for persisting and reproducing under drought conditions, uncertainty in future climate, and limitations to inferring demographic rates from forest inventory data. Here, we leverage new demographic models to quantify how climate change is expected to alter population demographics in five PJ tree species in the US West and place our results in the context of a climate adaptation framework to resist, accept, or direct ecological transformation. Two of five study species, Pinus edulis and Juniperus monosperma, are projected to experience population declines, driven by both rising mortality and decreasing recruitment rates. These declines are reasonably consistent across various climate futures, and the magnitude of uncertainty in population growth due to future climate is less than uncertainty due to how demographic rates will respond to changing climate. We assess the effectiveness of management to reduce tree density and mitigate competition, and use the results to classify southwest woodlands into areas where transformation is (a) unlikely and can be passively resisted, (b) likely but may be resisted by active management, and (c) likely unavoidable, requiring managers to accept or direct the trajectory. Population declines are projected to promote ecological transformation in the warmer and drier PJ communities of the southwest, encompassing 37.1%-81.1% of our sites, depending on future climate scenarios. Less than 20% of sites expected to transform away from PJ have potential to retain existing tree composition by density reduction. Our results inform where this adaptation strategy could successfully resist ecological transformation in coming decades and allow for a portfolio design approach across the geographic range of PJ woodlands.

Climate disequilibrium dominates uncertainty in long-term projections of primary productivity.

Rapid climate change may exceed ecosystems' capacities to respond through processes including phenotypic plasticity, compositional turnover and evolutionary adaption. However, consequences of the resulting climate disequilibria for ecosystem functioning are rarely considered in projections of climate change impacts. Combining statistical models fit to historical climate data and remotely-sensed estimates of herbaceous net primary productivity with an ensemble of climate models, we demonstrate that assumptions concerning the magnitude of climate disequilibrium are a dominant source of uncertainty: models assuming maximum disequilibrium project widespread decreases in productivity in the western US by 2100, while models assuming minimal disequilibrium project productivity increases. Uncertainty related to climate disequilibrium is larger than uncertainties from variation among climate models or emissions pathways. A better understanding of processes that regulate climate disequilibria is essential for improving long-term projections of ecological responses and informing management to maintain ecosystem functioning at historical baselines.

Quantifying the demographic vulnerabilities of dry woodlands to climate and competition using rangewide monitoring data.

Climate change is expected to alter the distribution and abundance of tree species, impacting ecosystem structure and function. Yet, anticipating where this will occur is often hampered by a lack of understanding of how demographic rates, most notably recruitment, vary in response to climate and competition across a species range. Using large-scale monitoring data on two dry woodland tree species (Pinus edulis and Juniperus osteosperma), we develop an approach to infer recruitment, survival, and growth of both species across their range. In doing so, we account for ecological and statistical dependencies inherent in large-scale monitoring data. We find that drying and warming conditions generally lead to declines in recruitment and survival, but the strength of responses varied between species. These climate conditions point to geographic regions of high vulnerability for particular species, such as Pinus edulis in northern Arizona, where both survival and recruitment are low. Our approach provides a path forward for leveraging emerging large-scale monitoring and remotely sensed data to anticipate the impacts of global change on species distributions.

Biotic vs abiotic controls on temporal sensitivity of primary production to precipitation across North American drylands.

Dryland net primary productivity (NPP) is sensitive to temporal variation in precipitation (PPT), but the magnitude of this 'temporal sensitivity' varies spatially. Hypotheses for spatial variation in temporal sensitivity have often emphasized abiotic factors, such as moisture limitation, while overlooking biotic factors, such as vegetation structure. We tested these hypotheses using spatiotemporal models fit to remote-sensing data sets to assess how vegetation structure and climate influence temporal sensitivity across five dryland ecoregions of the western USA. Temporal sensitivity was higher in locations and ecoregions dominated by herbaceous vegetation. By contrast, much less spatial variation in temporal sensitivity was explained by mean annual PPT. In fact, ecoregion-specific models showed inconsistent associations of sensitivity and PPT; whereas sensitivity decreased with increasing mean annual PPT in most ecoregions, it increased with mean annual PPT in the most arid ecoregion, the hot deserts. The strong, positive influence of herbaceous vegetation on temporal sensitivity indicates that herbaceous-dominated drylands will be particularly sensitive to future increases in precipitation variability and that dramatic changes in cover type caused by invasions or shrub encroachment will lead to changes in dryland NPP dynamics, perhaps independent of changes in precipitation.

Latitudinal gradients in population growth do not reflect demographic responses to climate.

Spatial gradients in population growth, such as across latitudinal or elevational gradients, are often assumed to primarily be driven by variation in climate, and are frequently used to infer species' responses to climate change. Here, we use a novel demographic, mixed-model approach to dissect the contributions of climate variables vs. other latitudinal or local site effects on spatiotemporal variation in population performance in three perennial bunchgrasses. For all three species, we find that performance of local populations decreases with warmer and drier conditions, despite latitudinal trends of decreasing population growth toward the cooler and wetter northern portion of each species' range. Thus, latitudinal gradients in performance are not predictive of either local or species-wide responses to climate. This pattern could be common, as many environmental drivers, such as habitat quality or species' interactions, are likely to vary with latitude or elevation, and thus influence or oppose climate responses.

Filling in the gaps in survival analysis: using field data to infer plant responses to environmental stressors.

Elucidating how organismal survival depends on the environment is a core component of ecological and evolutionary research. To reconcile high-frequency covariates with lower-frequency demographic censuses, many statistical tools involve aggregating environmental conditions over long periods, potentially obscuring the importance of fluctuating conditions in driving mortality. Here, we introduce a flexible model designed to infer how survival probabilities depend on changing environmental covariates. Specifically, the model (1) quantifies effects of environmental covariates at a higher frequency than the census intervals, and (2) allows partitioning of environmental drivers of individual survival into acute (short-term) and chronic (accumulated) effects. By applying our method to a long-term observational data set of eight annual plant species, we show we can accurately infer daily survival probabilities as temperature and moisture levels change. Next, we show that a species' water use efficiency, known to mediate annual plant population dynamics, is positively correlated with the importance of "chronic stress" inferred by the model. This suggests that model parameters can reflect underlying physiological mechanisms. This method is also applicable to other binary responses (hatching, phenology) or systems (insects, nestlings). Once known, environmental sensitivities can be used for ecological forecasting even when the frequency or variability of environments are changing.

Transient population dynamics impede restoration and may promote ecosystem transformation after disturbance.

The apparent failure of ecosystems to recover from increasingly widespread disturbance is a global concern. Despite growing focus on factors inhibiting resilience and restoration, we still know very little about how demographic and population processes influence recovery. Using inverse and forward demographic modelling of 531 post-fire sagebrush populations across the western US, we show that demographic processes during recovery from seeds do not initially lead to population growth but rather to years of population decline, low density, and risk of extirpation after disturbance and restoration, even at sites with potential to support long-term, stable populations. Changes in population structure, and resulting transient population dynamics, lead to a > 50% decline in population growth rate after disturbance and significant reductions in population density. Our results indicate that demographic processes influence the recovery of ecosystems from disturbance and that demographic analyses can be used by resource managers to anticipate ecological transformation risk.

Adapting management to a changing world: Warm temperatures, dry soil, and interannual variability limit restoration success of a dominant woody shrub in temperate drylands.

Restoration and rehabilitation of native vegetation in dryland ecosystems, which encompass over 40% of terrestrial ecosystems, is a common challenge that continues to grow as wildfire and biological invasions transform dryland plant communities. The difficulty in part stems from low and variable precipitation, combined with limited understanding about how weather conditions influence restoration outcomes, and increasing recognition that one-time seeding approaches can fail if they do not occur during appropriate plant establishment conditions. The sagebrush biome, which once covered over 620,000 km2 of western North America, is a prime example of a pressing dryland restoration challenge for which restoration success has been variable. We analyzed field data on Artemisia tridentata (big sagebrush) restoration collected at 771 plots in 177 wildfire sites across its western range, and used process-based ecohydrological modeling to identify factors leading to its establishment. Our results indicate big sagebrush occurrence is most strongly associated with relatively cool temperatures and wet soils in the first spring after seeding. In particular, the amount of winter snowpack, but not total precipitation, helped explain the availability of spring soil moisture and restoration success. We also find considerable interannual variability in the probability of sagebrush establishment. Adaptive management strategies that target seeding during cool, wet years or mitigate effects of variability through repeated seeding may improve the likelihood of successful restoration in dryland ecosystems. Given consistent projections of increasing temperatures, declining snowpack, and increasing weather variability throughout midlatitude drylands, weather-centric adaptive management approaches to restoration will be increasingly important for dryland restoration success.

Rainfall variability and fine-scale life history tradeoffs help drive niche partitioning in a desert annual plant community.

Tradeoffs have long been an essential part of the canon explaining the maintenance of species diversity. Despite the intuitive appeal of the idea that no species can be a master of all trades, there has been a scarcity of linked demographic and physiological evidence to support the role of resource use tradeoffs in natural systems. Using five species of Chihuahuan desert summer annual plants, I show that demographic tradeoffs driven by short-term soil moisture variation act as a mechanism to allow multiple species to partition a limiting resource. Specifically, by achieving highest fitness in either rainfall pulse or interpulse periods, variability reduces fitness differences through time that could promote coexistence on a limiting resource. Differences in fitness are explained in part by the response of photosynthesis to changing soil moisture. My results suggest that increasing weather variability, as predicted under climate change, could increase the opportunity for coexistence in this community.

Elephants in the understory: opposing direct and indirect effects of consumption and ecosystem engineering by megaherbivores.

Positive indirect effects of consumers on their resources can stabilize food webs by preventing overexploitation, but the coupling of trophic and non-trophic interactions remains poorly integrated into our understanding of community dynamics. Elephants engineer African savanna ecosystems by toppling trees and breaking branches, and although their negative effects on trees are well documented, their effects on small-statured plants remain poorly understood. Using data on 117 understory plant taxa collected over 7 yr within 36 1-ha experimental plots in a semi-arid Kenyan savanna, we measured the strength and direction of elephant impacts on understory vegetation. We found that elephants had neutral effects on most (83-89%) species, with a similar frequency of positive and negative responses among the remainder. Overall, estimated understory biomass was 5-14% greater in the presence of elephants across a range of rainfall levels. Whereas direct consumption likely accounts for the negative effects, positive effects are presumably indirect. We hypothesized that elephants create associational refuges for understory plants by damaging tree canopies in ways that physically inhibit feeding by other large herbivores. As predicted, understory biomass and species richness beneath elephant-damaged trees were 55% and 21% greater, respectively, than under undamaged trees. Experimentally simulated elephant damage increased understory biomass by 37% and species richness by 49% after 1 yr. Conversely, experimentally removing elephant damaged branches decreased understory biomass by 39% and richness by 30% relative to sham-manipulated trees. Camera-trap surveys revealed that elephant damage reduced the frequency of herbivory by 71%, whereas we detected no significant effect of damage on temperature, light, or soil moisture. We conclude that elephants locally facilitate understory plants by creating refuges from herbivory, which countervails the direct negative effects of consumption and enhances larger-scale biomass and diversity by promoting the persistence of rare and palatable species. Our results offer a counterpoint to concerns about the deleterious impacts of elephant "overpopulation" that should be considered in debates over wildlife management in African protected areas: understory species comprise the bulk of savanna plant biodiversity, and their responses to elephants are buffered by the interplay of opposing consumptive and non-consumptive interactions.

Comparative demography of an epiphytic lichen: support for general life history patterns and solutions to common problems in demographic parameter estimation.

Lichens are major components in many terrestrial ecosystems, yet their population ecology is at best only poorly understood. Few studies have fully quantified the life history or demographic patterns of any lichen, with particularly little attention to epiphytic species. We conducted a 6-year demographic study of Vulpicida pinastri, an epiphytic foliose lichen, in south-central Alaska. After testing multiple size-structured functions to describe patterns in each V. pinastri demographic rate, we used the resulting estimates to construct a stochastic demographic model for the species. This model development led us to propose solutions to two general problems in construction of demographic models for many taxa: how to simply but accurately characterize highly skewed growth rates, and how to estimate recruitment rates that are exceptionally difficult to directly observe. Our results show that V. pinastri has rapid and variable growth and, for small individuals, low and variable survival, but that these traits are coupled with considerable longevity (e.g., >50 years mean future life span for a 4-cm(2) thallus) and little deviation of the stochastic population growth rate from the deterministic expectation. Comparisons of the demographic patterns we found with those of other lichen studies suggest that their relatively simple architecture may allow clearer generalities about growth patterns for lichens than for other taxa, and that the expected pattern of faster growth rates for epiphytic species is substantiated.