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At least 253 records · Page 14Linked to original sources
USGS2022

Phylogenetic risk assessment is robust for forecasting the impact of European insects on North American conifers

Some introduced species cause severe damage, although the majority have little impact. Robust predictions of which species are most likely to cause substantial impacts could focus efforts to mitigate those impacts or prevent certain invasions entirely. Introduced herbivorous insects can reduce crop yield, fundamentally alter natural and managed forest ecosystems, and are unique among invasive species in that they require certain host plants to succeed. Recent studies have demonstrated that understanding the evolutionary history of introduced herbivores and their host plants can provide robust predictions of impact. Specifically, divergence times between hosts in the native and introduced ranges of a nonnative insect can be used to predict the potential impact of the insect should it establish in a novel ecosystem. However, divergence time estimates vary among published phylogenetic datasets, making it crucial to understand if and how the choice of phylogeny affects prediction of impact. Here, we tested the robustness of impact prediction to variation in host phylogeny by using insects that feed on conifers and predicting the likelihood of high impact using four different published phylogenies. Our analyses ranked 62 insects that are not established in North America and 47 North American conifer species according to overall risk and vulnerability, respectively. We found that results were robust to the choice of phylogeny. Although published vascular plant phylogenies continue to be refined, our analysis indicates that those differences are not substantial enough to alter the predictions of invader impact. Our results can assist in focusing biosecurity programs for conifer pests and can be more generally applied to nonnative insects and their potential hosts by prioritizing surveillance for those insects most likely to be damaging invaders.

Ecological Applications↗
USGS2022

Integrating principles and tools of decision science into value-driven watershed planning for compensatory mitigation

Several environmental policies strive to restore impaired ecosystems and could benefit from a consistent and transparent process — co-developed with key stakeholders — to prioritize impaired ecosystems for restoration activities. The Clean Water Act, for example, establishes reallocation mechanisms to transfer ecosystem services from sites of disturbance to compensation sites to offset aquatic resource functions that are unavoidably lost through land development. However, planning for the prioritization of compensatory mitigation areas is often hampered by decision-making processes that fall into a myopic decision frame because they are not co-produced with stakeholders. In this study, we partnered with domain experts from the North Carolina Division of Mitigation Services (NCDMS) to co-develop a real-world decision framework to prioritize catchments by potential for the development of mitigation projects following principles of a structured decision-making process and knowledge co-production. Following an iterative decision analysis cycle, domain experts revised foundational components of the decision framework and progressively added complexity and realism as they gained additional insights or more information became available. Through the course of facilitated in-person and remote interactions, the co-development of a decision framework produced three main ‘breakthroughs’ from the perspective of the stakeholder group: a) recognition of the problem as a multi-objective decision driven by several values in addition to biogeophysical goals (e.g., functional uplift; restoring or enhancing lost functionality of ecosystems), b) that the decision comprises a linked and sequential planning-to-implementation process, and c) future risk associated with land-use and climate change must be considered. We also present an interactive tool for ‘on-the-fly’ assessment of alternatives and tradeoff analysis, allowing domain experts to quickly test, react to, and revise prioritization strategies. The decision framework described in this study is not limited to the prioritization of compensatory mitigation activities across North Carolina, but rather serves as a framework to prioritize a wide range of restoration, conservation, and resource allocation activities in similar environmental contexts across the nation.

Ecological Applications↗
USGS2023

Empirical evidence for effects of invasive American Bullfrogs on occurrence of native amphibians and emerging pathogens

Invasive species and emerging infectious diseases are two of the greatest threats to biodiversity. American Bullfrogs ( Rana [ Lithobates ] catesbeiana ), which have been introduced to many parts of the world, are often linked with declines of native amphibians via predation and spreading emerging pathogens such as amphibian chytrid fungus ( Batrachochytrium dendrobatidis [Bd]) and ranaviruses. Although many studies have investigated the potential role of bullfrogs in declines of native amphibians, analyses that account for shared habitat affinities and imperfect detection have found limited support for clear effects. Similarly, the role of bullfrogs in shaping the patch-level distribution of pathogens is unclear. We used eDNA methods to sample 233 sites in the southwestern USA and Sonora, Mexico (2016–2018) to estimate how presence of bullfrogs affects occurrence of 4 native amphibians, Bd, and ranaviruses. Based on 2-species, dominant-subordinate occupancy models fitted in a Bayesian context, federally threatened Chiricahua Leopard Frogs ( R. chiricahuensis ) and Western Tiger Salamanders ( Ambystoma mavortium ) were 8 times (32% vs. 4%) and 2 times (36% vs. 18%), respectively, less likely to occur at sites where bullfrogs occurred. Evidence for negative effects of bullfrogs on Lowland Leopard Frogs ( R. yavapaiensis ) and Northern Leopard Frogs ( R. pipiens ) was less clear, possibly because of smaller numbers of sites where these native species still occur and because bullfrogs often occur at lower densities in streams, the primary habitat for Lowland Leopard Frogs. At the community level, Bd was most likely to occur where bullfrogs co-occurred with native amphibians, which could increase risk to native species. Ranaviruses were estimated to occur at 33% of bullfrog-only sites, 10% of sites where bullfrogs and native amphibians co-occurred, and only 3% of sites where only native amphibians occurred. Of the 85 sites where we did not detect any of the 5 target amphibian species, we also did not detect Bd or ranaviruses; this suggests other hosts do not drive the distribution of these pathogens in our study area. Our results provide landscape-scale evidence that bullfrogs reduce occurrence of native amphibians and increase occurrence of pathogens, information that can clarify risks and aid the prioritization of conservation actions.

Ecological Applications↗
USGS2023

Combining local, landscape, and regional geographies to assess plant community vulnerability to invasion impact

Invasive species science has focused heavily on the invasive agent. However, management to protect native species also requires a proactive approach focused on resident communities and the features affecting their vulnerability to invasion impacts. Vulnerability is likely the result of factors acting across spatial scales, from local to regional, and it is the combined effects of these factors that will determine the magnitude of vulnerability. Here, we introduce an analytical framework that quantifies the scale-dependent impact of biological invasions on native richness from the shape of the native species–area relationship (SAR). We leveraged newly available, biogeographically extensive vegetation data from the U.S. National Ecological Observatory Network to assess plant community vulnerability to invasion impact as a function of factors acting across scales. We analyzed more than 1000 SARs widely distributed across the USA along environmental gradients and under different levels of non-native plant cover. Decreases in native richness were consistently associated with non-native species cover, but native richness was compromised only at relatively high levels of non-native cover. After accounting for variation in baseline ecosystem diversity, net primary productivity, and human modification, ecoregions that were colder and wetter were most vulnerable to losses of native plant species at the local level, while warmer and wetter areas were most susceptible at the landscape level. We also document how the combined effects of cross-scale factors result in a heterogeneous spatial pattern of vulnerability. This pattern could not be predicted by analyses at any single scale, underscoring the importance of accounting for factors acting across scales. Simultaneously assessing differences in vulnerability between distinct plant communities at local, landscape, and regional scales provided outputs that can be used to inform policy and management aimed at reducing vulnerability to the impact of plant invasions.

Ecological Applications↗
USGS2023

Qualitative value of information provides a transparent and repeatable method for identifying critical uncertainty

Conservation decisions are often made in the face of uncertainty because the urgency to act can preclude delaying management while uncertainty is resolved. In this context, adaptive management is attractive, allowing simultaneous management and learning. An adaptive program design requires the identification of critical uncertainties that impede the choice of management action. Quantitative evaluation of critical uncertainty, using the expected value of information, may require more resources than are available in the early stages of conservation planning. Here, we demonstrate the use of a qualitative index to the value of information (QVoI) to prioritize which sources of uncertainty to reduce regarding the use of prescribed fire to benefit Eastern Black Rails ( Laterallus jamaicensis jamaicensis ), Yellow Rails ( Coterminous noveboracensis ), and Mottled Ducks ( Anas fulvigula ; hereafter, focal species) in high marshes of the U.S. Gulf of Mexico. Prescribed fire has been used as a management tool in Gulf of Mexico high marshes throughout the last 30+ years; however, effects of periodic burning on the focal species and the optimal conditions for burning marshes to improve habitat remain unknown. We followed a structured decision-making framework to develop conceptual models, which we then used to identify sources of uncertainty and articulate alternative hypotheses about prescribed fire in high marshes. We used QVoI to evaluate the sources of uncertainty based on their magnitude, relevance for decision making, and reducibility. We found that hypotheses related to the optimal fire return interval and season were the highest priorities for study, whereas hypotheses related to predation rates and interactions among management techniques were lowest. These results suggest that learning about the optimal fire frequency and season to benefit the focal species might produce the greatest management benefit. In this case study, we demonstrate that QVoI can help managers decide where to apply limited resources to learn which specific actions will result in a higher likelihood of achieving the desired management objectives. Further, we summarize the strengths and limitations of QVoI and outline recommendations for its future use for prioritizing research to reduce uncertainty about system dynamics and the effects of management actions.

Ecological Applications↗
USGS2023

A big data–model integration approach for predicting epizootics and population recovery in a keystone species

Infectious diseases pose a significant threat to global health and biodiversity. Yet, predicting the spatiotemporal dynamics of wildlife epizootics remains challenging. Disease outbreaks result from complex nonlinear interactions among a large collection of variables that rarely adhere to the assumptions of parametric regression modeling. We adopted a nonparametric machine learning approach to model wildlife epizootics and population recovery, using the disease system of colonial black-tailed prairie dogs (BTPD, Cynomys ludovicianus ) and sylvatic plague as an example. We synthesized colony data between 2001 and 2020 from eight USDA Forest Service National Grasslands across the range of BTPDs in central North America. We then modeled extinctions due to plague and colony recovery of BTPDs in relation to complex interactions among climate, topoedaphic variables, colony characteristics, and disease history. Extinctions due to plague occurred more frequently when BTPD colonies were spatially clustered, in closer proximity to colonies decimated by plague during the previous year, following cooler than average temperatures the previous summer, and when wetter winter/springs were preceded by drier summers/falls. Rigorous cross-validations and spatial predictions indicated that our final models predicted plague outbreaks and colony recovery in BTPD with high accuracy (e.g., AUC generally >0.80). Thus, these spatially explicit models can reliably predict the spatial and temporal dynamics of wildlife epizootics and subsequent population recovery in a highly complex host–pathogen system. Our models can be used to support strategic management planning (e.g., plague mitigation) to optimize benefits of this keystone species to associated wildlife communities and ecosystem functioning. This optimization can reduce conflicts among different landowners and resource managers, as well as economic losses to the ranching industry. More broadly, our big data–model integration approach provides a general framework for spatially explicit forecasting of disease-induced population fluctuations for use in natural resource management decision-making.

Arizona, Colorado, Kansas, Montana, Nebraska, New ↗
USGS2023

Crossing the threshold: Invasive grasses inhibit forest restoration on Hawaiian islands

Forest removal for livestock grazing is a striking example of human-caused state change leading to a stable, undesirable invasive grass system that is resistant to restoration efforts. Understanding which factors lead to resilience to the alternative grass state can greatly benefit managers when planning forest restoration. We address how thresholds of grass cover and seed rain might influence forest recovery in a restoration project on Hawaiʻi Island, USA. Since the 1980s, over 400,000 Acacia koa (koa) trees have been planted across degraded pasture, and invasive grasses still dominate the understory with no native woody-plant recruitment. Between this koa/grass matrix are remnant native Metrosideros polymorpha (ʻōhiʻa) trees beneath which native woody plants naturally recruit. We tested whether there were threshold levels of native woody understory that accelerate recruitment under both tree species by monitoring seed rain at 40 trees (20 koa and ʻōhiʻa) with a range of native woody understory basal area (BA). We found a positive relationship between total seed rain (but not bird-dispersed seed rain) and native woody BA and a negative relationship between native woody BA and grass cover, with no indication of threshold dynamics. We also experimentally combined grass removal levels with seed rain density (six levels) of two common understory species in plots under koa ( n = 9) and remnant ʻōhiʻa ( n = 9). Few seedlings emerged when no grass was removed despite adding seeds at densities two to 75 times higher than naturally occurring. However, seedling recruitment increased two to three times once at least 50% of grass was removed. Existing survey data of naturally occurring seedlings also supported a threshold of grass cover below which seedlings were able to establish. Thus, removal of all grasses is not necessary to achieve system responses: Even moderate reductions (~50%) can increase rates of native woody recruitment. The nonlinear thresholds found here highlight how incremental changes to an inhibitory factor lead to limited restoration success until a threshold is crossed. The resources needed to fully eradicate an invasive species may be unwarranted for state change, making understanding where thresholds lie of the utmost importance to prioritize resources.

Hawaii↗
USGS2023

Climate change mitigation potential of Louisiana's coastal area: Current estimates and future projections

Coastal habitats can play an important role in climate change mitigation. As Louisiana implements its climate action plan and the restoration and risk-reduction projects outlined in its 2017 Louisiana Coastal Master Plan, it is critical to consider potential greenhouse gas (GHG) fluxes in coastal habitats. This study estimated the potential climate mitigation role of existing, converted, and restored coastal habitats for years 2005, 2020, 2025, 2030, and 2050, which align with the Governor of Louisiana's GHG reduction targets. An analytical framework was developed that considered (1) available scientific data on net ecosystem carbon balance fluxes per habitat and (2) habitat areas projected from modeling efforts used for the 2017 Louisiana Coastal Master Plan to estimate the net GHG flux of coastal area. The coastal area was estimated as net GHG sinks of −38.4 ± 10.6 and −43.2 ± 12.0 Tg CO 2 equivalents (CO 2 e) in 2005 and 2020, respectively. The coastal area was projected to remain a net GHG sink in 2025 and 2030, both with and without the implementation of Coastal Master Plan projects (means ranged from −25.3 to −34.2 Tg CO 2 e). By 2050, with model-projected wetland loss and conversion of coastal habitats to open water due to coastal erosion and relative sea level rise, Louisiana's coastal area was projected to become a net source of GHG emissions both with and without the Coastal Master Plan projects. However, in the year 2050, the Louisiana Coastal Master Plan project implementation was projected to avoid the release of +8.8 ± 1.3 Tg CO 2 e compared with an alternative with no action. Reduction in current and future stressors to coastal habitats, including impacts from sea level rise, as well as the implementation of restoration projects could help to ensure coastal areas remain a natural climate solution.

Louisiana↗
USGS2023

Modeling impacts of saltwater intrusion on methane and nitrous oxide emissions in tidal forested wetlands

Emissions of methane (CH 4 ) and nitrous oxide (N 2 O) from soils to the atmosphere can offset the benefits of carbon sequestration for climate change mitigation. While past study has suggested that both CH 4 and N 2 O emissions from tidal freshwater forested wetlands (TFFW) are generally low, the impacts of coastal droughts and drought-induced saltwater intrusion on CH 4 and N 2 O emissions remain unclear. In this study, a process-driven biogeochemistry model, Tidal Freshwater Wetland DeNitrification-DeComposition (TFW-DNDC) was applied to examine the responses of CH 4 and N 2 O emissions to episodic drought-induced saltwater intrusion in TFFW along the Waccamaw River and Savannah River, USA. These sites encompass landscape gradients of both surface and porewater salinity as influenced by Atlantic Ocean tides superimposed on periodic droughts. Surprisingly, CH 4 and N 2 O emission responsiveness to coastal droughts and drought-induced saltwater intrusion varied greatly between river systems and among local geomorphologic settings. This reflected the complexity of wetland CH 4 and N 2 O emissions and suggests that simple linkages to salinity may not always be relevant, as non-linear relationships dominated our simulations. Along the Savannah River, N 2 O emissions in the moderate-oligohaline tidal forest site tended to increase dramatically under the drought condition, while CH 4 emission decreased. For the Waccamaw River, emissions of both CH 4 and N 2 O in the moderate-oligohaline tidal forest site tended to decrease under the drought condition, but the capacity of the moderate-oligohaline tidal forest to serve as a carbon sink was substantially reduced due to significant declines in net primary productivity and soil organic carbon sequestration rates as salinity killed the dominant freshwater vegetation. These changes in fluxes of CH 4 and N 2 O reflect crucial synergistic effects of soil salinity and water level on C and N dynamics in TFFW due to drought-induced seawater intrusion.

Ecological Applications↗
USGS2023

High resolution lidar data shed light on inter-island translocation of endangered bird species in the Hawaiian Islands

Translocation, often a management solution reserved for at-risk species, is a highly time-sensitive intervention in the face of a rapidly changing climate. The definition of abiotic and biotic habitat requirements is essential to the selection of appropriate release sites in novel environments. However, field-based approaches to gathering this information are often too time intensive, especially in areas of complex topography where common, coarse-scale climate models lack essential details. We apply a fine-scale remote sensing-based approach to study the 'akikiki ( Oreomystis bairdi ) and 'akeke'e ( Loxops caeruleirostris ), Hawaiian honeycreepers endemic to Kaua'i that are experiencing large-scale population declines due to warming-induced spread of invasive disease. We use habitat suitability modeling based on fine-scale light detection and ranging (lidar)-derived habitat structure metrics to refine coarse climate ranges for these species in candidate translocation areas on Maui. We found that canopy density was consistently the most important variable in defining habitat suitability for the two Kaua'i species. Our models also corroborated known habitat preferences and behavioral information for these species that are essential for informing translocation. We estimated a nesting habitat that will persist under future climate conditions on east Maui of 23.43 km 2 for 'akikiki, compared to the current Kaua'i range of 13.09 km 2 . In contrast, the novel nesting range for 'akeke'e in east Maui was smaller than its current range on Kaua'i (26.29 vs. 38.48 km 2 , respectively). We were also able to assess detailed novel competitive interactions at a fine scale using models of three endemic Maui species of conservation concern: 'ākohekohe ( Palmeria dolei ), Maui 'alauahio ( Paroreomyza montana ), and kiwikiu ( Pseudonestor xanthophrys ). Weighted overlap areas between the species from both islands were moderate (<12 km 2 ), and correlations between Maui and Kaua'i bird habitat were generally low, indicating limited potential for competition. Results indicate that translocation to east Maui could be a viable option for 'akikiki but would be more uncertain for 'akeke'e. Our novel multifaceted approach allows for the timely analysis of both climate and vegetation structure at informative scales for the effective selection of appropriate translocation sites for at-risk species.

Hawaii↗
USGS2023

Waterfowl show spatiotemporal trends in influenza A H5 and H7 infections but limited taxonomic variation

Influenza A viruses in wild birds pose threats to the poultry industry, wild birds, and human health under certain conditions. Of particular importance are wild waterfowl, which are the primary reservoir of low pathogenicity influenza viruses that ultimately cause high pathogenicity outbreaks in poultry farms. Despite much work on the drivers of influenza A virus prevalence, the underlying viral subtype dynamics are still mostly unexplored. Nevertheless, understanding these dynamics, particularly for the agriculturally significant H5 and H7 subtypes, is important for mitigating the risk of outbreaks in domestic poultry farms. Here, using an expansive surveillance database, we take a large-scale look at the spatial, temporal, and taxonomic drivers in the prevalence of these two subtypes among influenza A positive wild waterfowl. We document spatiotemporal trends that are consistent with past work, particularly an uptick in H5 viruses in late autumn and H7 viruses in spring. Interestingly, despite large species differences in temporal trends in overall influenza A virus prevalence, we document only modest differences in the relative abundance of these two subtypes and little, if any, temporal differences among species. As such, it appears that differences in species' phenology, physiology, and behaviors that influence overall susceptibility to influenza A viruses play a much lesser role in relative susceptibility to different subtypes. Instead, species likely freely pass viruses among each other regardless of subtype. Importantly, despite the similarities among species documented here, individual species still may play important roles in moving viruses across large geographic areas or sustaining local outbreaks through their different migratory behaviors.

Ecological Applications↗
USGS2023

Testing the hierarchy of predictability in grassland restoration across a gradient of environmental severity

Ecological restoration is critical for recovering degraded ecosystems but is challenged by variable success and low predictability. Understanding which outcomes are more predictable and less variable following restoration can improve restoration effectiveness. Recent theory asserts that the predictability of outcomes would follow an order from most to least predictable from coarse to fine community properties (physical structure > taxonomic diversity > functional composition > taxonomic composition) and that predictability would increase with more severe environmental conditions constraining species establishment. We tested this “hierarchy of predictability” hypothesis by synthesizing outcomes along an aridity gradient with 11 grassland restoration projects across the United States. We used 1829 vegetation monitoring plots from 227 restoration treatments, spread across 52 sites. We fit generalized linear mixed-effects models to predict six indicators of restoration outcomes as a function of restoration characteristics (i.e., seed mixes, disturbance, management actions, time since restoration) and used variance explained by models and model residuals as proxies for restoration predictability. We did not find consistent support for our hypotheses. Physical structure was among the most predictable outcomes when the response variable was relative abundance of grasses, but unpredictable for total canopy cover. Similarly, one dimension of taxonomic composition related to species identities was unpredictable, but another dimension of taxonomic composition indicating whether exotic or native species dominated the community was highly predictable. Taxonomic diversity (i.e., species richness) and functional composition (i.e., mean trait values) were intermittently predictable. Predictability also did not increase consistently with aridity. The dimension of taxonomic composition related to the identity of species in restored communities was more predictable (i.e., smaller residuals) in more arid sites, but functional composition was less predictable (i.e., larger residuals), and other outcomes showed no significant trend. Restoration outcomes were most predictable when they related to variation in dominant species, while those responding to rare species were harder to predict, indicating a potential role of scale in restoration predictability. Overall, our results highlight additional factors that might influence restoration predictability and add support to the importance of continuous monitoring and active management beyond one-time seed addition for successful grassland restoration in the United States.

Continental United States↗
USGS2023

Effects of vehicle traffic on space use and road crossings of caribou in the Arctic

Assessing the effects of industrial development on wildlife is a key objective of managers and conservation practitioners. However, wildlife responses are often only investigated with respect to the footprint of infrastructure, even though human activity can strongly mediate development impacts. In Arctic Alaska, there is substantial interest in expanding energy development, raising concerns about the potential effects on barren-ground caribou ( Rangifer tarandus granti ). While caribou generally avoid industrial infrastructure, little is known about the role of human activity in moderating their responses, and whether managing activity levels could minimize development effects. To address this uncertainty, we examined the influence of traffic volume on caribou summer space use and road crossings in the Central Arctic Herd within the Kuparuk and Milne Point oil fields on the North Slope of Alaska. We first modeled spatiotemporal variation in hourly traffic volumes across the road system from traffic counter data using gradient-boosted regression trees. We then used generalized additive models to estimate nonlinear step selection functions and road-crossing probabilities from collared female caribou during the post-calving and insect harassment seasons, when they primarily interact with roads. Step selection analyses revealed that caribou selected areas further from roads (~1–3 km) during the post-calving and mosquito seasons and selected areas with lower traffic volumes during all seasons, with selection probabilities peaking when traffic was <5 vehicles/h. Using road-crossing models, we found that caribou were less likely to cross roads during the insect seasons as traffic increased, but that response dissipated as insect harassment became more severe. Past studies suggested that caribou exhibit behavioral responses when traffic exceeds 15 vehicles/h, but our results demonstrate behavioral responses at much lower traffic levels. Our results illustrate that vehicle activity mediates caribou responses to road infrastructure, information that can be used in future land-use planning to minimize the behavioral responses of caribou to industrial development in sensitive Arctic landscapes.

Alaska↗
USGS2024

Cross-scale analysis reveals interacting predictors of annual and perennial cover in Northern Great Basin rangelands

Exotic annual grass invasion is a widespread threat to the integrity of sagebrush ecosystems in Western North America. Although many predictors of annual grass prevalence and native perennial vegetation have been identified, there remains substantial uncertainty about how regional-scale and local-scale predictors interact to determine vegetation heterogeneity, and how associations between vegetation and cattle grazing vary with environmental context. Here, we conducted a regionally extensive, one-season field survey across burned and unburned, grazed, public lands in Oregon and Idaho, with plots stratified by aspect and distance to water within pastures to capture variation in environmental context and grazing intensity. We analyzed regional-scale and local-scale patterns of annual grass, perennial grass, and shrub cover, and examined to what extent plot-level variation was contingent on pasture-level predictions of site favorability. Annual grasses were widespread at burned and unburned sites alike, contrary to assumptions of annual grasses depending on fire, and more common at lower elevations and higher temperatures regionally, as well as on warmer slopes locally. Pasture-level grazing pressure interacted with temperature such that annual grass cover was associated positively with grazing pressure at higher temperatures but associated negatively with grazing pressure at lower temperatures. This suggests that pasture-level temperature and grazing relationships with annual grass abundance are complex and context dependent, although the causality of this relationship deserves further examination. At the plot-level within pastures, annual grass cover did not vary with grazing metrics, but perennial cover did; perennial grasses, for example, had lower cover closer to water sources, but higher cover at higher dung counts within a pasture, suggesting contrasting interpretations of these two grazing proxies. Importantly for predictions of ecosystem response to temperature change, we found that pasture-level and plot-level favorability interacted: perennial grasses had a higher plot-level cover on cooler slopes, and this difference across topography was starkest in pastures that were less favorable for perennial grasses regionally. Understanding the mechanisms behind cross-scale interactions and contingent responses of vegetation to grazing in these increasingly invaded ecosystems will be critical to land management in a changing world.

Ecological Applications↗
USGS2024

Multi-decadal vegetation transformations of a New Mexico ponderosa pine landscape after severe fires and aerial seeding

Wildfires and climate change are having transformative effects on vegetation composition and structure, and post-fire management may have long-lasting impacts on ecosystem reorganization. Post-fire aerial seeding treatments are commonly used to reduce runoff and soil erosion, but little is known about how seeding treatments affect native vegetation recovery over long periods of time, particularly in type-converted forests which have been dramatically transformed by the effects of repeated, high-severity fire. In this study, we analyze and report on a rare long-term (23-year) dataset that documents vegetation dynamics following a 1996 post-fire aerial seed treatment and subsequent 2011 high-severity reburn in a dry conifer forest of northern New Mexico in the southwestern United States. Repeated surveys between 1997 – 2019 of 49 permanent transects were used to test for differences in vegetation cover, richness, and diversity between seeded and unseeded areas, and to characterize the development of seeded and unseeded vegetation communities through time and across gradients of burn severity, elevation, and soil-available water capacity. Post-fire seeding led to a clear and sustained divergence in herbaceous community composition. Seeded plots had much higher cover of non-native graminoids, primarily Bromus inermis , a likely contaminant in the seed mix. High-severity reburning in all plots in 2011 reduced native graminoid cover by half at seeded plots compared to both pre-fire levels and to plots that were unseeded following the initial 1996 fire. In addition, increased fire severity was associated with increased non-native graminoid cover and reduced native graminoid cover, native species richness, and species diversity. This study documents a fire-driven ecosystem transformation from a former conifer forest into a shrub-grass system, reinforced by aerial seeding of grasses and high-severity reburning. This unique long-term dataset illustrates that post-fire seeding carries significant risk of unwanted non-native species invasions that persist through subsequent fires – indicating that alternative post-fire management actions merit consideration to better support native ecosystem resilience in the face of emergent climate change and increasing disturbance. Lastly, this study highlights the importance of long-term monitoring of post-fire vegetation dynamics, as short-term assessments will miss key elements of the full complexity of ecosystem responses to fire and post-fire management actions.

New Mexico↗
USGS2024

Scale‐dependent population drivers inform avian management in a declining saline lake ecosystem

Shrinking saline lakes provide irreplaceable habitat for waterbird species globally. Disentangling the effects of wetland habitat loss from other drivers of waterbird population dynamics is critical for protecting these species in the face of unprecedented changes to saline lake ecosystems, ideally through decision-making frameworks that identify effective management options and their potential outcomes. Here, we develop a framework to assess the effects of hypothesized population drivers and identify potential future outcomes of plausible management scenarios on a saline lake-reliant waterbird species. We use 36 years of monitoring data to quantify the effects of environmental conditions on the population size of a regionally important breeding colony of American white pelicans ( Pelecanus erythrorhynchos ) at Great Salt Lake, Utah, US, then forecast colony abundance under various management scenarios. We found that low lake levels, which allow terrestrial predators access to the colony, are probable drivers of recent colony declines. Without local management efforts, we predicted colony abundance could likely decline approximately 37.3% by 2040, although recent colony observations suggest population declines may be more extreme than predicted. Results from our population projection scenarios suggested that proactive approaches to preventing predator colony access and reversing saline lake declines are crucial for the persistence of the Great Salt Lake pelican colony. Increasing wetland habitat and preventing predator access to the colony together provided the most effective protection, increasing abundance 145.4% above projections where no management actions are taken, according to our population projection scenarios. Given the importance of water levels to the persistence of island-nesting colonial species, proactive approaches to reversing saline lake declines could likely benefit pelicans as well as other avian species reliant on these unique ecosystems.

Utah↗
USGS2024

Declining ecological resilience and invasion resistance under climate change in the sagebrush region, United States

In water-limited dryland ecosystems of the Western United States, climate change is intensifying the impacts of heat, drought, and wildfire. Disturbances often lead to increased abundance of invasive species, in part, because dryland restoration and rehabilitation are inhibited by limited moisture and infrequent plant recruitment events. Information on ecological resilience to disturbance (recovery potential) and resistance to invasive species can aid in addressing these challenges by informing long-term restoration and conservation planning. Here, we quantified the impacts of projected future climate on ecological resilience and invasion resistance (R&R) in the sagebrush region using novel algorithms based on ecologically relevant and climate-sensitive predictors of climate and ecological drought. We used a process-based ecohydrological model to project these predictor variables and resulting R&R indicators for two future climate scenarios and 20 climate models. Results suggested widespread future R&R decreases (24%–34% of the 1.16 million km 2 study area) that are generally consistent among climate models. Variables related to rising temperatures were most strongly linked to decreases in R&R indicators. New continuous R&R indices quantified responses to climate change; particularly useful for areas without projected change in the R&R category but where R&R still may decrease, for example, some of the areas with a historically low R&R category. Additionally, we found that areas currently characterized as having high sagebrush ecological integrity had the largest areal percentage with expected declines in R&R in the future, suggesting continuing declines in sagebrush ecosystems. One limitation of these R&R projections was relatively novel future climatic conditions in particularly hot and dry areas that were underrepresented in the training data. Including more data from these areas in future updates could further improve the reliability of the projections. Overall, these projected future declines in R&R highlight a growing challenge for natural resource managers in the region, and the resulting spatially explicit datasets provide information that can improve long-term risk assessments, prioritizations, and climate adaptation efforts.

western United States↗
USGS2024

Restoration treatments enhance tree growth and alter climatic constraints during extreme drought

The frequency and severity of drought events are predicted to increase due to anthropogenic climate change, with cascading effects across forested ecosystems. Management activities such as forest thinning and prescribed burning, which are often intended to mitigate fire hazard and restore ecosystem processes, may also help promote tree resistance to drought. However, it is unclear whether these treatments remain effective during the most severe drought conditions or whether their impacts differ across environmental gradients. We used tree-ring data from a system of replicated, long-term (>20 years) experiments in the southwestern United States to evaluate the effects of forest restoration treatments (i.e., evidence-based thinning and burning) on annual growth rates (i.e., basal area increment; BAI) of ponderosa pine ( Pinus ponderosa ), a broadly distributed and heavily managed species in western North America. The study sites were established at the onset of the most extreme drought event in at least 1200 years and span much of the climatic niche of Rocky Mountain ponderosa pine. Across sites, tree-level BAI increased due to treatment, where trees in treated units grew 133.1% faster than trees in paired, untreated units. Likewise, trees in treated units grew an average of 85.6% faster than their pre-treatment baseline levels (1985 to ca. 2000), despite warm, dry conditions in the post-treatment period (ca. 2000–2018). Variation in the local competitive environment promoted variation in BAI, and larger trees were the fastest-growing individuals, irrespective of treatment. Tree thinning and prescribed fire altered the climatic constraints on growth, decreasing the effects of belowground moisture availability and increasing the effects of atmospheric evaporative demand over multi-year timescales. Our results illustrate that restoration treatments can enhance tree-level growth across sites spanning ponderosa pine's climatic niche, even during recent, extreme drought events. However, shifting climatic constraints, combined with predicted increases in evaporative demand in the southwestern United States, suggest that the beneficial effects of such treatments on tree growth may wane over the upcoming decades.

Arizona, Colorado, Nevada, New Mexico, Texas↗