Time-lagged effects of weather on plant demography: drought and Astragalus scaphoides

Canopy cover and soil moisture influence forest understory plant responses to experimental summer drought

Extreme droughts are globally increasing in frequency and severity. Most research on drought in forests focuses on the response of trees, while less is known about the impacts of drought on forest understory species and how these effects are moderated by the local environment. We assessed the impacts of a 45-day experimental summer drought on the performance of six boreal forest understory plants, using a transplant experiment with rainout shelters replicated across 25 sites. We recorded growth, vitality and reproduction immediately, 2 months, and 1 year after the simulated drought, and examined how differences in ambient soil moisture and canopy cover among sites influenced the effects of drought on the performance of each species. Drought negatively affected the growth and/or vitality of all species, but the effects were stronger and more persistent in the bryophytes than in the vascular plants. The two species associated with older forests, the moss Hylocomiastrum umbratum and the orchid Goodyera repens, suffered larger effects than the more generalist species included in the experiment. The drought reduced reproductive output in the moss Hylocomium splendens in the next growing season, but increased reproduction in the graminoid Luzula pilosa. Higher ambient soil moisture reduced some negative effects of drought on vascular plants. Both denser canopy cover and higher soil moisture alleviated drought effects on bryophytes, likely through alleviating cellular damage. Our experiment shows that boreal understory species can be adversely affected by drought and that effects might be stronger for bryophytes and species associated with older forests. Our results indicate that the effects of drought can vary over small spatial scales and that forest landscapes can be actively managed to alleviate drought effects on boreal forest biodiversity. For example, by managing the tree canopy and protecting hydrological networks.

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

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

Inclusive Fitness May Explain Some but Not All Benefits Derived from Helping Behavior in a Cooperatively Breeding Bird

AbstractIn cooperative breeding systems, inclusive fitness theory predicts that nonbreeding helpers more closely related to the breeders should be more willing to provide costly alloparental care and thus have more impact on breeder fitness. In the red-cockaded woodpecker (Dryobates borealis), most helpers are the breeders' earlier offspring, but helpers do vary within groups in both relatedness to the breeders (some even being unrelated) and sex, and it can be difficult to parse their separate impacts on breeder fitness. Moreover, most support for inclusive fitness theory has been positive associations between relatedness and behavior rather than actual fitness consequences. We used functional linear models to evaluate the per capita effects of helpers of different relatedness on eight breeder fitness components measured for up to 41 years at three sites. In support of inclusive fitness theory, helpers more related to the breeding pair made greater contributions to six fitness components. However, male helpers made equal contributions to increasing prefledging survival regardless of relatedness. These findings suggest that both inclusive fitness benefits and other direct benefits may underlie helping behaviors in the red-cockaded woodpecker. Our results also demonstrate the application of an underused statistical approach to disentangle a complex ecological phenomenon.

Study on the driving mechanism of lagged effects based on different time scales in a karst drainage basin in South China

Compared to earthquakes and volcanoes, drought is one of the most damaging natural disasters and is mainly affected by rainfall losses, especially by the runoff regulation ability of the underlying watershed surface. Based on monthly rainfall runoff data recorded from 1980 to 2020, in this study, the distributed lag regression model is used to simulate the rainfall-runoff process in the karst distribution region of South China, and a time series of watershed lagged-flow volumes is calculated. The watershed lagged effect is analyzed by four distribution models, and the joint probability between the lagged intensity and frequency is simulated by the copula function family. The results show that (1) the watershed lagged effects simulated by the normal, log-normal, P-III and log-logistic distribution models in the karst drainage basin are particularly significant, with small mean square errors (MSEs) and significant time-scale characteristics. (2) Affected by spatiotemporal distribution differences in rainfall and the impacts of different basin media and structures, the lag response of runoff to rainfall differs significantly among different time scales. Especially at the 1-, 3- and 12-month scales, the coefficient of variation (C_v) of the watershed lagged intensity is greater than 1, while it is less than 1 at the 6- and 9-month scales. (3) The lagged frequencies simulated by the log-normal, P-III and log-logistic distribution models are relatively high (with medium, medium-high and high frequencies, respectively), while that simulated by the normal distribution is relatively low (medium-low and low frequencies). (4) There is a significant negative correlation (R < - 0.8, Sig. < 0.01) between the watershed lagged intensity and frequency. For the joint probability simulation, the fitting effect of the gumbel Copula is the best, followed by the Clayton and Frank-1 copulas, and while that of the Frank-2 copula is relatively weak. Consequently, the propagation mechanism from meteorological drought to agricultural or hydrological drought and the conversion mechanism between agricultural and hydrological drought are effectively revealed in this study, thereby providing a scientific basis for the rational utilization of water resources and drought resistance and disaster relief in karst areas.

Driving Climatic Factors at Critical Plant Developmental Stages for Qinghai–Tibet Plateau Alpine Grassland Productivity

Determining the driving climatic factors at critical periods and potential legacy effects is crucial for grassland productivity predictions on the Qinghai–Tibet Plateau (QTP). However, studies with limited and ex situ ground samples from highly heterogeneous alpine meadows brought great uncertainties. This study determined the key climatic factors at critical plant developmental stages and the impact of previous plant growth status for interannual aboveground net primary productivity (ANPP) variations in different QTP grassland types. We hypothesize that the impact of climatic factors on grassland productivity varies in different periods and different vegetation types, while its legacy effects are not great. Pixel-based partial least squares regression was used to associate interannual ANPP with precipitation and air temperature at different developmental stages and prior-year ANPP from 2000 to 2019 using remote sensing techniques. Results indicated different findings from previous studies. Precipitation at the reproductive stage (July–August) was the most prominent controlling factor for ANPP which was also significantly affected by precipitation and temperature at the withering (September–October) and dormant stage (November–February), respectively. The influence of precipitation was more significant in alpine meadows than in alpine steppes, while the differentiated responses to climatic factors were attributed to differences in water consumption at different developmental stages induced by leaf area changes, bud sprouting, growth, and protection from frost damage. The prior-year ANPP showed a non-significant impact on ANPP of current year, except for alpine steppes, and this impact was much less than that of current-year climatic factors, which may be attributed to the reduced annual ANPP variations related to the inter-annual carbon circulation of alpine perennial herbaceous plants and diverse root/shoot ratios in different vegetation types. These findings can assist in improving the interannual ANPP predictions on the QTP under global climate change.

The contribution of plant spatial arrangement to bumble bee flower constancy

Floral constancy of foraging bees influences plant reproduction. Constancy as observed in nature arises from at least four distinct mechanisms frequently confounded in the literature: context-independent preferences for particular plant species, preferential visitation to the same species as the previous plant visited (simple constancy), the spatial arrangement of plants, and the relative abundances of co-flowering species. To disentangle these mechanisms, we followed individual bee flight paths within patches where all flowering plants were mapped, and we used step selection models to estimate how each mechanism influences the probability of selecting any particular plant given the available plants in a multi-species community. We found that simple constancy was positive: bees preferred to visit the same species sequentially. In addition, bees preferred to travel short distances and maintain their direction of travel between plants. After accounting for distance, we found no significant effect of site-level plant relative abundances on bee foraging choices. To explore the importance of the spatial arrangement of plants for bee foraging choices, we compared our full model containing all parameters to one with spatial arrangement removed. Due to bees' tendency to select nearby plants, combined with strong intraspecific plant clumping, spatial arrangement was responsible for about 50% of the total observed constancy. Our results suggest that floral constancy may be overestimated in studies that do not account for the spatial arrangement of plants, especially in systems with intraspecific plant clumping. Plant spatial patterns at within-site scales are important for pollinator foraging behavior and pollination success.

Delayed effects of climate on vital rates lead to demographic divergence in Amazonian forest fragments

Deforestation often results in landscapes where remaining forest habitat is highly fragmented, with remnants of different sizes embedded in an often highly contrasting matrix. Local extinction of species from individual fragments is common, but the demographic mechanisms underlying these extinctions are poorly understood. It is often hypothesized that altered environmental conditions in fragments drive declines in reproduction, recruitment, or survivorship. The Amazon basin, in addition to experiencing continuing fragmentation, is experiencing climate change-related increases in the frequency and intensity of droughts and unusually wet periods. Whether plant populations in tropical forest fragments are particularly susceptible to extremes in precipitation remains unclear. Most studies of plants in fragments are relatively short (1-6 years), focus on a single life-history stage, and often do not compare to populations in continuous forest. Even fewer studies consider delayed effects of climate on demographic vital rates despite the importance of delayed effects in studies that consider them. Using a decade of demographic and climate data from an experimentally fragmented landscape in the Central Amazon, we assess the effects of climate on populations of an understory herb (Heliconia acuminata, Heliconiaceae). We used distributed lag nonlinear models to understand the delayed effects of climate (measured as standardized precipitation evapotranspiration index, SPEI) on survival, growth, and flowering. We detected delayed effects of climate up to 36 months. Extremes in SPEI in the previous year reduced survival, drought in the wet season 8-11 months prior to the February census increased growth, and drought two dry seasons prior increased flowering probability. Effects of extremes in precipitation on survival and growth were more pronounced in forest fragments compared to continuous forest. The complex delayed effects of climate and habitat fragmentation in our study point to the importance of long-term demography experiments in understanding the effects of anthropogenic change on plant populations.

Is the Life History Flexibility of Cold Desert Annuals Broad Enough to Cope with Predicted Climate Change? The Case of Erodium oxyrhinchum in Central Asia

Interannual seasonal variability in precipitation may strongly affect the life history and growth of desert annual plants. We compared the effects of dry and wet springs and dry and wet autumns on growth and F2 seed dormancy of plants from spring (SG)- and autumn (AG)-germinated seeds of the cold desert annual Erodium oxyrhinchum. Vegetative and reproductive growth and F2 seed dormancy and germination were monitored from September 2016 to November 2020 in the sandy Gurbantunggut Desert in NW China in Central Asia. Dry autumns decreased the density of AG plants, and dry springs decreased the density of SG plants and growth of SG and AG plants. In dry springs, SG plants were more sensitive to precipitation than AG plants, while in wet springs SG and AG plants had similar responses to precipitation. During growth in both dry and wet springs, most morphological characters of SG and AG plants initially increased rapidly in size/number and then plateaued or decreased, except for SG plants in dry springs. In dry springs, most morphological characters of AG plants were larger or more numerous than those of SG plants, and they were larger/more numerous for SG plants in wet than in dry springs. The percentage biomass allocated to reproduction in SG plants was slightly higher in a wet than in a dry spring. A much higher proportion of dormant seeds was produced by AG plants in a wet spring than in a dry spring. Projected changes in precipitation due to climate change in NW China are not likely to have much of an effect on the biology of this common desert annual plant.

Lagged and dormant season climate better predict plant vital rates than climate during the growing season

Understanding the effects of climate on the vital rates (e.g., survival, development, reproduction) and dynamics of natural populations is a long-standing quest in ecology, with ever-increasing relevance in the face of climate change. However, linking climate drivers to demographic processes requires identifying the appropriate time windows during which climate influences vital rates. Researchers often do not have access to the long-term data required to test a large number of windows, and are thus forced to make a priori choices. In this study, we first synthesize the literature to assess current a priori choices employed in studies performed on 104 plant species that link climate drivers with demographic responses. Second, we use a sliding-window approach to investigate which combination of climate drivers and temporal window have the best predictive ability for vital rates of four perennial plant species that each have over a decade of demographic data (Helianthella quinquenervis, Frasera speciosa, Cylindriopuntia imbricata, and Cryptantha flava). Our literature review shows that most studies consider time windows in only the year preceding the measurement of the vital rate(s) of interest, and focus on annual or growing season temporal scales. In contrast, our sliding-window analysis shows that in only four out of 13 vital rates the selected climate drivers have time windows that align with, or are similar to, the growing season. For many vital rates, the best window lagged more than 1 year and up to 4 years before the measurement of the vital rate. Our results demonstrate that for the vital rates of these four species, climate drivers that are lagged or outside of the growing season are the norm. Our study suggests that considering climatic predictors that fall outside of the most recent growing season will improve our understanding of how climate affects population dynamics.

Time lags and the invasion debt in plant naturalisations

Ecological processes often exhibit time lags. For plant invasions, lags of decades to centuries between species' introduction and establishment in the wild (naturalisation) are common, leading to the idea of an invasion debt: accelerating rates of introduction result in an expanding pool of introduced species that will naturalise in the future. Here, I show how a concept from survival analysis, the hazard function, provides an intuitive way to understand and forecast time lags. For plant naturalisation, theoretical arguments predict that lags between introduction and naturalisation will have a unimodal distribution, and that increasing horticultural activity will cause the mean and variance of lag times to decline over time. These predictions were supported by data on introduction and naturalisation dates for plant species introduced to Britain. While increasing trade and horticultural activity can generate an invasion debt by accelerating introductions, the same processes could lower that debt by reducing lag times.

Larger workers outperform smaller workers across resource environments: An evaluation of demographic data using functional linear models

Behavior and organization of social groups is thought to be vital to the functioning of societies, yet the contributions of various roles within social groups toward population growth and dynamics have been difficult to quantify. A common approach to quantifying these role-based contributions is evaluating the number of individuals conducting certain roles, which ignores how behavior might scale up to effects at the population-level. Manipulative experiments are another common approach to determine population-level effects, but they often ignore potential feedbacks associated with these various roles.Here, we evaluate the effects of worker size distribution in bumblebee colonies on worker production in 24 observational colonies across three environments, using functional linear models. Functional linear models are an underused correlative technique that has been used to assess lag effects of environmental drivers on plant performance. We demonstrate potential applications of this technique for exploring high-dimensional ecological systems, such as the contributions of individuals with different traits to colony dynamics.We found that more larger workers had mostly positive effects and more smaller workers had negative effects on worker production. Most of these effects were only detected under low or fluctuating resource environments suggesting that the advantage of colonies with larger-bodied workers becomes more apparent under stressful conditions.We also demonstrate the wider ecological application of functional linear models. We highlight the advantages and limitations when considering these models, and how they are a valuable complement to many of these performance-based and manipulative experiments.

Demographic effects of interacting species: exploring stable coexistence under increased climatic variability in a semiarid shrub community

Population persistence is strongly determined by climatic variability. Changes in the patterns of climatic events linked to global warming may alter population dynamics, but their effects may be strongly modulated by biotic interactions. Plant populations interact with each other in such a way that responses to climate of a single population may impact the dynamics of the whole community. In this study, we assess how climate variability affects persistence and coexistence of two dominant plant species in a semiarid shrub community on gypsum soils. We use 9 years of demographic data to parameterize demographic models and to simulate population dynamics under different climatic and ecological scenarios. We observe that populations of both coexisting species may respond to common climatic fluctuations both similarly and in idiosyncratic ways, depending on the yearly combination of climatic factors. Biotic interactions (both within and among species) modulate some of their vital rates, but their effects on population dynamics highly depend on climatic fluctuations. Our results indicate that increased levels of climatic variability may alter interspecific relationships. These alterations might potentially affect species coexistence, disrupting competitive hierarchies and ultimately leading to abrupt changes in community composition.

A native annual forb locally excludes a closely related introduced species that co-occurs in oak-savanna habitat remnants

Despite the ubiquity of introduced species, their long-term impacts on native plant abundance and diversity remain poorly understood. Coexistence theory offers a tool for advancing this understanding by providing a framework to link short-term individual measurements with long-term population dynamics by directly quantifying the niche and average fitness differences between species. We observed that a pair of closely related and functionally similar annual plants with different origins-native Plectritis congesta and introduced Valerianella locusta-co-occur at the community scale but rarely at the local scale of direct interaction. To test whether niche and/or fitness differences preclude local-scale long-term coexistence, we parameterized models of competitor dynamics with results from a controlled outdoor pot experiment, where we manipulated densities of each species. To evaluate the hypothesis that niche and fitness differences exhibit environmental dependency, leading to community-scale coexistence despite local competitive exclusion, we replicated this experiment with a water availability treatment to determine if this key limiting resource alters the long-term prediction. Water availability impacted population vital rates and intensities of intraspecific versus interspecific competition between P. congesta and V. locusta. Despite environmental influence on competition our model predicts that native P. congesta competitively excludes introduced V. locusta in direct competition across water availability conditions because of an absence of stabilizing niche differences combined with a difference in average fitness, although this advantage weakens in drier conditions. Further, field data demonstrated that P. congesta densities have a negative effect on V. locusta seed prediction. We conclude that native P. congesta limits abundances of introduced V. locusta at the direct-interaction scale, and we posit that V. locusta may rely on spatially dependent coexistence mechanisms to maintain coexistence at the site scale. In quantifying this competitive outcome our study demonstrates mechanistically how a native species may limit the abundance of an introduced invader.

Using Climate to Explain and Predict West Nile Virus Risk in Nebraska

We used monthly precipitation and temperature data to give early warning of years with higher West Nile Virus (WNV) risk in Nebraska. We used generalized additive models with a negative binomial distribution and smoothing curves to identify combinations of extremes and timing that had the most influence, experimenting with all combinations of temperature and drought data, lagged by 12, 18, 24, 30, and 36 months. We fit models on data from 2002 through 2011, used Akaike's Information Criterion (AIC) to select the best-fitting model, and used 2012 as out-of-sample data for prediction, and repeated this process for each successive year, ending with fitting models on 2002-2017 data and using 2018 for out-of-sample prediction. We found that warm temperatures and a dry year preceded by a wet year were the strongest predictors of cases of WNV. Our models did significantly better than random chance and better than an annual persistence naïve model at predicting which counties would have cases. Exploring different scenarios, the model predicted that without drought, there would have been 26% fewer cases of WNV in Nebraska through 2018; without warm temperatures, 29% fewer; and with neither drought nor warmth, 45% fewer. This method for assessing the influence of different combinations of extremes at different time intervals is likely applicable to diseases other than West Nile, and to other annual outcome variables such as crop yield.

Experimental migration upward in elevation is associated with strong selection on life history traits

One of the strongest biological impacts of climate change has been the movement of species poleward and upward in elevation. Yet, what is not clear is the extent to which the spatial distribution of locally adapted lineages and ecologically important traits may also shift with continued climate change. Here, we take advantage of a transplant experiment mimicking up-slope seed dispersal for a suite of ecologically diverse populations of yellow monkeyflower (Mimulus guttatus sensu lato) into a high-elevation common garden during an extreme drought period in the Sierra Nevada mountains, California, USA. We use a demographic approach to quantify fitness and test for selection on life history traits in local versus lower-elevation populations and in normal versus drought years to test the potential for up-slope migration and phenotypic selection to alter the distribution of key life history traits in montane environments. We find that lower-elevation populations tend to outperform local populations, confirming the potential for up-slope migration. Although selection generally favored some local montane traits, including larger flowers and larger stem size at flowering, drought conditions tended to select for earlier flowering typical of lower-elevation genotypes. Taken together, this suggests that monkeyflower lineages moving upward in elevation could experience selection for novel trait combinations, particularly under warmer and drier conditions that are predicted to occur with continued climate change.

Cumulative weather effects can impact across the whole life cycle

Predicting how species will be affected by future climatic change requires the underlying environmental drivers to be identified. As vital rates vary over the lifecycle, structured population models derived from statistical environment-demography relationships are often used to inform such predictions. Environmental drivers are typically identified independently for different vital rates and demographic classes. However, these rates often exhibit positive temporal covariance, suggesting that vital rates respond to common environmental drivers. Additionally, models often only incorporate average weather conditions during a single, a priori chosen time window (e.g. monthly means). Mismatches between these windows and the period when the vital rates are sensitive to variation in climate decrease the predictive performance of such approaches. We used a demographic structural equation model (SEM) to demonstrate that a single axis of environmental variation drives the majority of the (co)variation in survival, reproduction, and twinning across six age-sex classes in a Soay sheep population. This axis provides a simple target for the complex task of identifying the drivers of vital rate variation. We used functional linear models (FLMs) to determine the critical windows of three local climatic drivers, allowing the magnitude and direction of the climate effects to differ over time. Previously unidentified lagged climatic effects were detected in this well-studied population. The FLMs had a better predictive performance than selecting a critical window a priori, but not than a large-scale climate index. Positive covariance amongst vital rates and temporal variation in the effects of environmental drivers are common, suggesting our SEM-FLM approach is a widely applicable tool for exploring the joint responses of vital rates to environmental change.