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Mean plant length (height) ± standard error of each treatment combination over the course of the spring growing season. Ambient plots are in yellow, white-gravel in blue, and black-gravel in red, with high density plantings represented by filled circles, and low-density planting represented by open squares. Harvest occurred on the final sampling date which was June 8th at the Boise, and July 22nd at the Cheyenne site
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Purpose
The sensitivity of wildland plants to temperature can be directly measured using experimental manipulations of temperature in situ. We show that soil surface temperature and plant density (per square meter) have a significant impact on the germination, growth, and phenology of Bromus tectorum L., cheatgrass, a short-statured invasive winter...
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Sowing is a well‐established restoration technique to overcome dispersal limitation. Seed mixtures adapted to certain environmental conditions, like substrate or microclimate, are most effective to achieve functional communities. This is especially important if the restored vegetation has to protect critical infrastructure like roadsides and dikes....
Citations
... B. tectorum exhibits considerable phenotypic plasticity, allowing it to acclimate to short-term shifts in its environment, and substantial genetic and phenotypic variation both within and across its introduced populations (reviewed in Hufft & Zelikova, 2016;Leger et al., 2009;Rice & Mack, 1991a), despite primarily self-pollinating (Novak et al., 1991). Previous work on B. tectorum phenology suggests that flowering timing has a strong genetic component (Revolinski et al., 2023;Rice & Mack, 1991b), and also that flowering time can meaningfully shift in response to warming over the course of a year to a decade (Howell et al., 2020;Maxwell et al., 2023;Prevéy et al., 2024). ...
... At each common garden site in fall 2021, we planted seeds 1 cm below the soil surface in a gridded design in two density treatments (low-density treatment = 100 seeds planted in a grid across a 1-m 2 area; high-density treatment = 100 seeds planted in a grid across a 0.04-m 2 area; Figure 1a) and under two temperature treatments (black gravel = higher soil surface temperature; white gravel = lower soil surface temperature; Figure 1a; Appendix S1: Table S1, Figure S2). We note that our study design follows that of Maxwell et al. (2023) closely, which was a pilot study that used similar gravel and seeding techniques to manipulate surface albedo and intraspecific density but was limited in replication and geographic scope and did not include multiple genotypes. The gravel treatments used here meaningfully alter soil surface temperatures in this system (refer to Boyd et al., 2017;Maxwell et al., 2023 for details) and in this experiment, resulted in a 2.1 C difference between treatments on average (range across common garden sites = [1.5-2.8 ...
... We note that our study design follows that of Maxwell et al. (2023) closely, which was a pilot study that used similar gravel and seeding techniques to manipulate surface albedo and intraspecific density but was limited in replication and geographic scope and did not include multiple genotypes. The gravel treatments used here meaningfully alter soil surface temperatures in this system (refer to Boyd et al., 2017;Maxwell et al., 2023 for details) and in this experiment, resulted in a 2.1 C difference between treatments on average (range across common garden sites = [1.5-2.8 C]). ...
Plants respond to their environment with both short‐term, within‐generation trait plasticity, and long‐term, between‐generation evolutionary changes. However, the relative magnitude of plant responses to short‐ and long‐term changes in the environment remains poorly understood. Shifts in phenological traits can serve as harbingers for responses to environmental change, and both a plant's current and source (i.e., genotype origin) environment can affect plant phenology via plasticity and local adaptation, respectively. To assess the role of current and source environments in explaining variation in flowering phenology of Bromus tectorum, an invasive annual grass, we conducted a replicated common garden experiment using 92 genotypes collected across western North America. Replicates of each genotype were planted in two densities (low = 100 seeds/1 m², high = 100 seeds/0.04 m²) under two different temperature treatments (low = white gravel; high = black gravel; 2.1°C average difference) in a factorial design, replicated across four common garden locations in Idaho and Wyoming, USA. We tested for the effect of current environment (i.e., density treatment, temperature treatment, and common garden location), source environment (i.e., genotype source climate), and their interaction on each plant's flowering phenology. Flowering timing was strongly influenced by a plant's current environment, with plants that experienced warmer current climates and higher densities flowering earlier than those that experienced cooler current climates and lower densities. Genotypes from hot and dry source climates flowered consistently earlier than those from cool and wet source climates, even after accounting for genotype relatedness, suggesting that this genetically based climate cline is a product of natural selection. We found minimal evidence of interactions between current and source environments or genotype‐by‐environment interactions. Phenology was more sensitive to variation in the current climate than to variation in source climate. These results indicate that cheatgrass phenology reflects high levels of plasticity as well as rapid local adaptation. Both processes likely contribute to its current success as a biological invader and its capacity to respond to future environmental change.
... They surmised that the warming decreased the temperature limitation on recruitment and growth, since cheatgrass germinates in the fall or early spring, depending on precipitation and matures in late spring. Maxwell et al. (2023) manipulated surface albedo at two sites (Boise, ID and Cheyenne, WY) using white gravel to reduce net radiation and thereby cool the surface or black gravel to increase net radiation and thereby warm the surface. At both locations, the black gravel treatment significantly advanced cheatgrass phenology relative to the white gravel treatment. ...
Inquiry into the phenologies of grasslands and grasses in North America has progressed substantially over the past decade. This chapter highlights five prominent themes from the recent phenological research on grasses and grasslands: (1) phenologies and invasion in grasslands, (2) exploring invasive grass phenologies with experimental manipulations, (3) remote sensing of invasive grass phenologies, (4) phenologies associated with flowering in grasslands, and (5) modeling and grassland phenologies.
... Understanding how precipitation changes will impact brome abundances will require determining if positive current-spring effects override negative subsequent-spring effects. Finally, brome responses to experimental warming have been inconsistent, being negative in one study (Larson et al., 2017) and neutral (Maxwell et al., 2023), mixed (Compagnoni & Adler, 2014;Zelikova et al., 2013), and positive (Blumenthal et al., 2016) in other studies. Studies that jointly consider precipitation and temperature indicate precipitation is the more important of the two drivers (Blumenthal et al., 2016;Bradley, 2009;Howell et al., 2020). ...
... We resist assigning a high level of confidence to this estimate because changes to precipitation are uncertain (Bradford et al., 2020). Additionally, although temperature was not a significant predictor in our study, water availability declines with increasing temperature (Blumenthal et al., 2016;Bradford et al., 2020;Maxwell et al., 2023), so effects of increased fall temperature could override effects of increased fall precipitation. Compared with increased precipitation, increased temperature is more assured in the coming decades (Marvel et al., 2023). ...
In arid and semiarid systems of western North America, the most damaging invasive plants are winter annuals. These plants are destroying wildlife habitat, reducing livestock production, and increasing wildfires. Monitoring these plants for lasting population changes is challenging because their abundances vary widely from year to year. Some of this variation is due to weather, and quantifying effects of weather is important for distinguishing transcient from lasting population changes and understanding effects of climate change. Fall and spring weather affect germination and seed production of the current generation of plants and, therefore, impact population sizes of subsequent generations of plants. Extensive data are required to estimate effects of fall and spring weather on multiple generations of plants. We used Bayesian statistics to integrate experimental and long‐term (31 years) monitoring data and quantify invasive annual grass [downy brome (Bromus tectorum L.) and Japanese brome (Bromus japonicus Thunb.)] responses to weather. Bromes ranged from nearly absent to comprising half of total biomass depending on three previous years of weather. Brome biomass increased with precipitation one, two, and three falls prior to measurement. Fall precipitation is projected to increase, and a mere 6.5 mm increase, which is just 2% of mean annual precipitation, would increase brome biomass 40% (28%, 54%) (mean [95% CI]) according to our model. Increased fall precipitation could favor many invasive winter annual grasses and forbs. Dry spring conditions reduced brome biomass the current year but increased brome biomass one and likely two (p = 0.08) years later, perhaps because dry conditions weakened perennial competitors. This finding casts doubt on several one‐year precipitation experiments that concluded drier spring weather would reduce brome abundances. Integrating short‐term experiments and long‐term monitoring is useful for estimating invasive plant responses to the weather and characterizing their responses to climate change. Our research provides predictions of brome abundances that could improve monitoring efforts by helping land managers interpret population dynamics in the context of seasonal precipitation patterns.
... However, it is important to time management activities correctly; for example, livestock will preferentially choose invasive brome species when the plants are in their early growth stages yet avoid them as they dry out and produce spiky seeds. Timing phenology-based management can be difficult, as these invasive grasses have been shown to have high phenotypic plasticity, are very responsive to weather variability, and will flower and produce seeds much earlier in some years than others (Howell et al., 2020;Hufft & Zelikova, 2016;Maxwell et al., 2023). ...
... Previous studies on cheatgrass phenology revealed variation associated with genetic differences, experimental warming, and increased precipitation, and with increased vernalization time (Howell et al., 2020;Maxwell et al., 2023;Meyer et al., 2004;Zelikova et al., 2013). However, to our knowledge there has been only one study parameterizing a phenology model for cheatgrass reproduction (Ball et al., 2004), and no studies creating process-based phenology models for red brome. ...
... T A B L E 1 List of data sources used for training and testing models for flowering and senescence of cheatgrass and red brome, the number of observations per source, and the range in years and day of year (DOY) of phenological stages. Research from manipulative field studies have shown that warmer temperatures are associated with earlier phenology of cheatgrass (Howell et al., 2020;Maxwell et al., 2023). Some studies have found that phenology of another annual grass species, winter wheat, can be predicted by accumulated growing degree days, or forcing sums, in addition to photoperiod (Heuer et al., 1978) while other studies have found that using both forcing sums and photoperiod as drivers provided more accurate phenological predictions for winter wheat (Grant, 1964;Hänsel, 1953). ...
Non‐native annual grasses can dramatically alter fire frequency and reduce forage quality and biodiversity in the ecosystems they invade. Effective management techniques are needed to reduce these undesirable invasive species and maintain ecosystem services. Well‐timed management strategies, such as grazing, that are applied when invasive grasses are active prior to native plants can control invasive species spread and reduce their impact; however, anticipating the timing of key phenological stages that are susceptible to management over vast landscapes is difficult, as the phenology of these species can vary greatly over time and space. To address this challenge, we created range‐wide phenology forecasts for two problematic invasive annual grasses: cheatgrass (Bromus tectorum), and red brome (Bromus rubens). We tested a suite of 18 mechanistic phenology models using observations from monitoring experiments, volunteer science, herbarium records, timelapse camera imagery, and downscaled gridded climate data to identify the models that best predicted the dates of flowering and senescence of the two invasive grass species. We found that the timing of flowering and senescence of cheatgrass and red brome were best predicted by photothermal time models that had been adjusted for topography using gridded continuous heat‐insolation load index values. Phenology forecasts based on these models can help managers make decisions about when to schedule management actions such as grazing to reduce undesirable invasive grasses and promote forage production, quality, and biodiversity in grasslands; to predict the timing of greatest fire risk after annual grasses dry out; and to select remote sensing imagery to accurately map invasive grasses across topographic and latitudinal gradients. These phenology models also have the potential to be operationalized for within‐season or within‐year decision support.
... -Ramirez et al., 2016). Greater fire heat under shrubs might also kill existing native seed banks and thereby provide both fertile and vacant hotspots for IAGs invading the burned area (Hoover & Germino, 2012;Rau et al., 2014;Boyd et al., 2017;Maxwell et al., 2023). Thus, managing for invasion resistance may require a better understanding of the spatial structure of fuels and land management activities that promote native bunchgrasses within the interspaces of shrubs (Hulet et al., 2015). ...
Aims
Invasion by annual grasses (IAGs) and concomitant increases in wildfire are impacting many drylands globally, and an understanding of factors that contribute to or detract from community resistance to IAGs is needed to inform postfire restoration interventions. Prefire vegetation condition is often unknown in rangelands but it likely affects variation in postfire invasion resistance across large burned scars. Whether satellite‐derived products like the Rangeland Analysis Platform (RAP) can fulfill prefire information needs and be used to parametrize models of fire recovery to inform postfire management of IAGs is a key question.
Methods
We used random forests to ask how IAG abundances in 669 field plots measured in the 2‐3 years following megafires in sagebrush steppe rangelands of western USA responded to RAP estimates of annual:perennial prefire vegetation cover, the effects of elevation, heat load, postfire treatments, soil moisture–temperature regimes, and land‐agency ratings of ecosystem resistance to invasion and resilience to disturbance.
Results
Postfire IAG cover measured in the field was % and RAP‐estimated prefire annual herbaceous cover was %. The random forest model had an R ² of 0.36 and a root‐mean‐squared error (RMSE) of 4.41. Elevation, postfire herbicide treatment, and prefire estimates from RAP for the ratio of annual:perennial and shrub cover were the most important predictors of postfire IAG cover. Threshold‐like relationships between postfire IAG cover and the predictors indicate that maintaining annual:perennial cover below 0.4 and shrub cover below <10% prior to wildfire would decrease invasion, at low elevations below 1400 m above sea level.
Conclusion
Despite known differences between RAP and field‐based estimates of vegetation cover, RAP was still a useful predictor of variation in IAG abundances after fire. IAG management is oftentimes reactive, but our findings indicate impactful roles for more inclusively addressing the exotic annual community, and focusing on prefire maintenance of annual:perennial herbaceous and shrub cover at low elevations.
