丹霞地貌生境中铁皮石斛的繁殖生物学研究

目的:揭示丹霞地貌生境中铁皮石斛的繁育系统及濒危机制.方法:对该地区铁皮石斛的生境、生长特性、开花物候、繁殖特性以及资源破坏状况等进行了调查.结果:丹霞地貌铁皮石斛生长环境恶劣,春季为其生长高峰;2～3年生茎开花,花后及时授粉,结实率较高;授粉后4～5 d子房开始膨大,果实成熟期为185 d左右;自然有性繁殖的结实率(0.31%)极低;无性克隆繁殖1丛仅1年生1茎.结论:丹霞地貌生境下铁皮石斛群体自然更新主要是通过分蘖繁殖实现的;人为掠夺性采集是该地区铁皮石斛野生资源濒危的主要因素.     

Climate change and decadal shifts in the phenology of larval fishes in the California Current ecosystem

Climate change has prompted an earlier arrival of spring in numerous ecosystems. It is uncertain whether such changes are occurring in Eastern Boundary Current Upwelling ecosystems, because these regions are subject to natural decadal climate variability, and regional climate models predict seasonal delays in upwelling. To answer this question, the phenology of 43 species of larval fishes was investigated between 1951 and 2008 off southern California. Ordination of the fish community showed earlier phenological progression in more recent years. Thirty-nine percent of seasonal peaks in larval abundance occurred earlier in the year, whereas 18% were delayed. The species whose phenology became earlier were characterized by an offshore, pelagic distribution, whereas species with delayed phenology were more likely to reside in coastal, demersal habitats. Phenological changes were more closely associated with a trend toward earlier warming of surface waters rather than decadal climate cycles, such as the Pacific Decadal Oscillation and North Pacific Gyre Oscillation. Species with long-term advances and delays in phenology reacted similarly to warming at the interannual time scale as demonstrated by responses to the El Niño Southern Oscillation. The trend toward earlier spawning was correlated with changes in sea surface temperature (SST) and mesozooplankton displacement volume, but not coastal upwelling. SST and upwelling were correlated with delays in fish phenology. For species with 20th century advances in phenology, future projections indicate that current trends will continue unabated. The fate of species with delayed phenology is less clear due to differences between Intergovernmental Panel on Climate Change models in projected upwelling trends.Phenology is the study of seasonal biological processes and how they are influenced by climate and weather. Because warmer temperatures are frequently associated with earlier phenological events, changes in phenology are common indicators of the effects of climate change on ecological communities. Meta-analyses have shown that phenological events have advanced at mean rates of 2–5 d/decade relative to a historical baseline (1–5). Among species for which phenological changes were detected, >80% of these shifts occurred in a direction consistent with climate change (1, 2, 5).Despite the inclusion of hundreds of species in meta-analyses examining climate change effects on phenology, gaps in knowledge persist because most long-term studies of phenology have monitored spring events affecting terrestrial species residing in temperate habitats in the northern hemisphere (2, 4). Marine species are particularly underrepresented in these meta-analyses (6), although see recent work by Poloczanska et al. (5). Underrepresentation of marine species is problematic not only due to their ecological importance, but also because research suggests shifts in phenology may occur more rapidly in marine environments than terrestrial ecosystems (7, 8). Compared with other marine organisms, there is a longer history of studying the phenology of teleost fishes, because the seasonal coincidence between phytoplankton blooms and fish spawning can affect recruitment to commercial fisheries (9, 10). Nevertheless, little research has investigated the impact of anthropogenic climate change on fish phenology and, with a few exceptions (11, 12), studies have been limited to a small set of commercially fished species. To address this issue, the present study investigated the influence of local and basin-scale climatic and oceanic factors on the phenology of 43 fish species whose larval abundance has been monitored off southern California since 1951.In the California Current Ecosystem (CCE), wind-driven upwelling is one of the predominant physical processes regulating the seasonal cycle of primary and secondary productivity. The seasonal onset of upwelling, referred to as the “spring transition,” is associated with the commencement of southward, alongshore winds that induce offshore Ekman transport of coastal waters (13). This process coincides with a decrease in coastal sea surface temperature (SST) by 1.5–4 °C, the development of a nearshore, southward oceanic jet, and an increase in chlorophyll a in the coastal zone (14). In the central and northern CCE (>35°N), upwelling intensifies through summer until the wind direction reverses in the fall. In the southern CCE (<35°N), upwelling is observed in all seasons, but its intensity diminishes in fall and winter (15, 16). This pattern leads to a spring maximum in chlorophyll concentration occurring between March and May in the southern CCE (17, 18). The peak in phytoplankton is followed by a summer maximum in mesozooplankton displacement volume between May and July (19). Fishes spawn in the southern CCE year round, although most species exhibit distinct seasonal patterns of larval abundance (20).There is increasing evidence that seasonal cycles of temperature, sea surface height (SSH), and chlorophyll concentration may not be stationary in the CCE (21, 22). Empirical observations and regional climate models suggest that climate change is leading to intensification of upwelling during spring and/or summer months but not other seasons (15, 23, 24). A model simulation that doubled atmospheric CO₂ indicated that upwelling off northern California is likely to increase during July–October, but decrease in April–May, resulting in a 1-mo delay in the spring transition (15). When climate feedbacks due to changes in land cover were accounted for in this model, similar results were obtained for the northern CCE, but model predictions suggested that the southern CCE would experience an increase in early-season upwelling and decreased peak and late-season upwelling (24). This change could cause an advance in the seasonal cycle of southern CCE upwelling, as well as potentially dampen its seasonal amplitude. Empirical observations of ocean temperature and the Bakun upwelling index validate these model results, indicating delays in the onset and peak of upwelling, particularly in the northern CCE (21, 25). In accordance with model predictions of earlier upwelling in the southern CCE, phytoplankton blooms were observed 1–2 mo earlier in the late 1990s in this region compared with previous years (18).In addition to anthropogenic climate change, oceanography in the CCE is affected by climate oscillations with interannual-to-decadal periods, including El Niño-Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), and the North Pacific Gyre Oscillation (NPGO). El Niño is frequently accompanied by delays in seasonal upwelling (25), although lower frequency modes of climate variability, such as the PDO, do not have as pronounced of an effect on upwelling seasonality (19, 25). Due to delayed and reduced upwelling, El Niño is associated with later spring phytoplankton blooms in certain regions (26). Although little research has examined PDO effects on bloom timing in the CCE, this mode of climate variability influences phytoplankton phenology elsewhere in the North Pacific (27). Among zooplankton in the CCE, the 1977 change from a negative to a positive PDO coincided with a 2-mo shift toward earlier maximum displacement volume of zooplankton (19). At the next trophic level, El Niño influences the spawning phenology of northern anchovy (Engraulis mordax) (28). Also, early spawning migrations of chinook salmon (Oncorhynchus tshawytscha) are weakly correlated with warm PDO anomalies (29). The NPGO is a more recently defined climate oscillation based on the second mode of SSH variability in the Northeast Pacific (30). In the southern CCE, the NPGO is more closely correlated to variations in upwelling, salinity, nutrients, and chlorophyll than the PDO. Whether this mode of climate variability has an impact on the phenology of marine organisms is a subject yet to be investigated.The match-mismatch hypothesis provides a mechanism explaining how climate-induced changes in fish and plankton phenology could potentially alter the abundance of fish stocks (9). This hypothesis proposes that fishes spawn during peak seasonal plankton production, which increases the likelihood that their larvae will encounter sufficient prey. However, due to interannual variability in the timing of plankton production and fish spawning, these events do not always coincide. During such mismatches, first-feeding larvae may experience increased vulnerability to starvation or slower growth, which can heighten susceptibility to predation (31). Poor larval survival can result in reduced recruitment and decreased fishery landings in subsequent years. Although many other processes during the early life history of fishes influence recruitment (32), variations in plankton phenology can result in order-of-magnitude changes in the recruitment and survival of commercially important fishes (33, 34). Coastal upwelling in the CCE complicates mismatch dynamics, because upwelling simultaneously provides nutrients for planktonic production while advecting fish larvae away from coastal habitats. Due to these opposing influences on larval survival and growth, many fishes in Eastern Boundary Current Upwelling (EBCU) systems spawn at low-to-moderate rates of upwelling (9, 35).Climate change could increase phenological mismatches through two mechanisms. First, certain seasonal cues, such as day length, will not be affected by global warming, whereas other seasonal processes will exhibit differing rates of change (e.g., surface vs. bottom temperatures) (36, 37). Because predators and prey may use different environmental factors as signals to initiate seasonal behaviors, this discrepancy can lead to a higher frequency of mismatches if these indicators become decoupled (10, 36). Second, individual species inevitably have distinct climate sensitivities that result in differing rates of phenological response to climate change. These differences can lead to situations where even small changes in climate can upset seasonal, interspecific interactions (10).This study examined decadal changes in the phenology of 43 species of fish larvae off California. The objectives were to (i) determine whether phenological changes were correlated with variations in regional climate indices and the seasonality of SST, coastal upwelling, and zooplankton displacement volume; (ii) assess whether life history characteristics of fishes are linked to changes in phenology, and (iii) forecast 21st century changes in fish phenology based on predicted changes in seasonal SST and coastal upwelling.Several hypotheses can be proposed regarding how fish phenology has changed since 1951 when ichthyoplankton surveys began in the southern CCE:

• • H₀: The phenology of larval fishes will remain constant regardless of variations in seasonal oceanographic conditions.
• • H_A1: Fish larvae will uniformly occur earlier during periods with warmer temperature, reflecting earlier spawning. This change could arise due to accelerated oocyte development under warmer temperatures (38–40) or the tendency of spawning to track phytoplankton blooms, which have occurred earlier in the southern CCE in recent years (18).
• • H_A2: Spring-spawning fishes will exhibit earlier larval phenology during periods with warmer temperatures, whereas fall-spawning species will exhibit delayed phenology, reflecting a later onset of cooler, fall conditions.
• • H_A3: Delays in upwelling will lead to later spawning and occurrence of larvae.
• • H_A4: The phenology of larval fishes will display interannual-to-decadal variability synchronous with climate oscillations, such as ENSO, PDO, and/or NPGO.

To examine these hypotheses, data on the abundance of larval fishes from California Cooperative Oceanic Fisheries Investigations (CalCOFI) were used. CalCOFI has surveyed larvae between 1951 and 2008 on a monthly-to-quarterly basis (with some gaps between 1967 and 1983) (20, 41). The region most consistently surveyed by CalCOFI includes the Southern California Bight (SCB), the area offshore of the SCB, and Point Conception (Fig. S1).Open in a separate windowFig. S1.Sites where larval fish abundance was sampled. The rectangular box in the inset map shows the location of the study region relative to the West Coast of North America.Monthly abundance of 43 fish species was calculated by decadally averaging data from quarterly surveys conducted in different months in successive years. This step was undertaken to achieve the minimum of a monthly sampling resolution needed for examining phenological trends. Eight species exhibited two peaks in larval abundance each year (7, 12, 42). Because calculating CT relative to decadal means led to a small sample size for each phenophase (n = 6) and reduced statistical power, this study did not focus on species-level changes in phenology. Instead, each phenophase was treated as a replicate for examining assemblage-wide patterns. Variations in CT were treated as a proxy for spawning time, because CalCOFI mainly collects young, preflexion larvae (43, 44), and the egg stage of many species lasts 2–4 d at temperatures in the southern CCE (45). Depending on the species and temperature, flexion occurs between 3 and 25 d after hatching (45–47).

Table S1.

Ecological characteristics of larval fish species

Extraordinary long life spans in fruit-feeding butterflies can provide window on evolution of life span and aging

Information on the life span of organisms in the field is essential for elucidating the evolution of life span and aging. We present mark-recapture data (>30,000 marked individuals, >4000 recaptured at least once) on 47 species of fruit-feeding butterflies in a tropical forest in Uganda. The data reveal adult life spans in the field for several species that are significantly longer than previously recorded in Lepidoptera (butterflies and moths). Longevity records for species of which more than 100 individuals were recaptured ranged from 67 (Bicyclus auricruda) to 293 days (Euphaedra medon). In contrast to the majority of Lepidoptera which are short-lived, these all show exceptionally long life spans, and may thus help to better identify factors that affect aging, particularly when combined with information on temporal patterns in reproduction, strategies to avoid predation, and nutritional ecology. These key traits are readily measurable in butterflies and thus studies on fruit-feeding butterflies have much potential for gaining insight into the evolution of life span and aging, especially given the tradition of field-research on butterflies.     

Differences in spatial versus temporal reaction norms for spring and autumn phenological events

For species to stay temporally tuned to their environment, they use cues such as the accumulation of degree-days. The relationships between the timing of a phenological event in a population and its environmental cue can be described by a population-level reaction norm. Variation in reaction norms along environmental gradients may either intensify the environmental effects on timing (cogradient variation) or attenuate the effects (countergradient variation). To resolve spatial and seasonal variation in species’ response, we use a unique dataset of 91 taxa and 178 phenological events observed across a network of 472 monitoring sites, spread across the nations of the former Soviet Union. We show that compared to local rates of advancement of phenological events with the advancement of temperature-related cues (i.e., variation within site over years), spatial variation in reaction norms tend to accentuate responses in spring (cogradient variation) and attenuate them in autumn (countergradient variation). As a result, among-population variation in the timing of events is greater in spring and less in autumn than if all populations followed the same reaction norm regardless of location. Despite such signs of local adaptation, overall phenotypic plasticity was not sufficient for phenological events to keep exact pace with their cues—the earlier the year, the more did the timing of the phenological event lag behind the timing of the cue. Overall, these patterns suggest that differences in the spatial versus temporal reaction norms will affect species’ response to climate change in opposite ways in spring and autumn.

To stay tuned to their environment, species need to respond to both short- and long-term variation in climatic conditions. In temperate regions, favorable abiotic conditions, key resources, and major enemies may all occur early in a warm year, whereas they may occur late in a cold year. Coinciding with such factors may thus come with pronounced effects on individual fitness and population-level performance (1–4). As phenological traits also show substantial variability within and among populations, they can be subject to selection in nature (5–7), potentially resulting in patterns of local adaptation (8–10).At present, the rapid rate of global change is causing shifts in species phenology across the globe (11–13). Of acute interest is the extent to which different events are shifting in unison or not, sometimes creating seasonal mismatches and functionally disruptive asynchrony (3, 14–16). If much of the temporal and spatial variation in seasonal timing is a product of phenotypic plasticity, then changes can be instant, and sustained synchrony among interaction partners will depend on the extent to which different species react similarly to short-term variation in climatic conditions. If geographic variation in phenology reflects local adaptive evolutionary differentiation, then, in the short term, as climate changes, phenological interactions may be disrupted due to the lag as adaptation tries to catch up (17–19). By assuming that space can substitute time, it is possible to make inference about the role that adaptation to climate may play. How well species stay in synchrony will then depend on the extent to which local selective forces act similarly or differently on different species and events.Local adaptation in phenology may take two forms. 1) The magnitude of phenological change might vary along environmental gradients in ways that intensify the environmental effects on phenological traits, a process known as cogradient variation (Fig. 1B). In such a case, the covariance between the genetic influences on phenological traits and the environmental influences is positive. Under this scenario, the effect of environmental variation over space and time will be larger than if all populations were to follow the same reaction norm regardless of location. 2) Genotypes might counteract environmental effects, thereby diminishing the change in mean trait expression across the environmental gradient. In such a case, the effect of environmental variation over space and time will be smaller than if all populations were to follow the same reaction norm regardless of location. This latter scenario, termed countergradient variation, occurs when genetic and environmental influences on phenotypic traits oppose one another (Fig. 1C) (20, 21).Open in a separate windowFig. 1.Schematic illustration showing slopes of phenology on temperature. Adapted with permission from ref. 30. A corresponds to phenological plasticity with respect to temperature and no local adaptation. B reveals phenological plasticity with respect to temperature plus cogradient local adaptation. C reveals phenological plasticity with respect to temperature plus countergradient local adaptation. For each scenario, we have included two examples of events showing this type of pattern in our data. For the exact climatic cues related to these biotic events, see SI Appendix, Table S1. In each plot, the red lines correspond to the within-population reaction norms through time (i.e., temporal slopes within locations), and the blue line corresponds to the between-population reaction norm (i.e., spatial slopes). If all populations respond alike, then the same reaction norm will apply across all locations, and individuals will respond in the same way to the cue no matter where they were, and no matter whether we examine responses within or between locations. If this was the case, then the reaction norm would be the same within (red lines) and between locations, and the blue and the red slopes would be parallel (i.e., their slopes identical). This scenario is depicted in A. What we use as our estimate of local adaptation is the difference between the two, i.e., whether the slope of reaction norms within populations differs from that across populations. If the temporal slopes are estimated at a relatively short time scale (as compared to the generation length of the focal organisms), then we can assume that within-location variation in the timing of the event reflects phenotypic responses alone, not evolutionary change over time. This component is then, per definition, due to phenotypic plasticity as such, i.e., to how individuals of a constant genetic makeup respond to annual variation in their environment. By comparison, the spatial slope (i.e., the blue line) is a sum of two parts: first, it reflects the mean of how individuals of a constant genetic makeup respond to annual variation in their environment, i.e., the temporal reaction norm defined above. These means are shown by the red dots in A–C. However, second, if populations differentiate across sites, then we will see variation in their response to long-term conditions, with an added element in the spatial slope reflecting mean plasticity plus local adaptation. Therefore, if the spatial slope differs from the temporal slope, this reveals local adaptation (see Materials and Methods for further details). Such local adaptation in phenological response may take two forms. 1) The magnitude of phenological change might vary along environmental gradients in ways that intensify the environmental effects on phenological traits, a process known as cogradient variation (Fig. 1B). In such a case, the covariance between the genetic influences on phenological traits and the environmental influences is positive. Under this scenario, variation in the environmental cue over space and time will cause larger variation in phenological timing than if all populations were to follow the same reaction norm regardless of location. 2) Genotypes might counteract environmental effects, thereby diminishing the change in mean trait expression across the environmental gradient. In such a case, the effect of variation in the environmental cue over space and time will be smaller than if all populations were to follow the same reaction norm regardless of location. This latter scenario, termed countergradient variation, occurs when genetic and environmental influences on phenotypic traits oppose one another (C).For phenology, the overall prevalence of co- versus countergradient patterns is crucial, as it will dictate the extent to which local adaptation will either accentuate or attenuate phenological responses to temporal shifts in climate (10). Across environmental gradients in space, the relative prevalence of counter- versus cogradient variation in spring versus autumn will critically modify how climatic variation affects the length of the activity period of the entire ecological community. Overall, geographic variation in the activity period will be maximized when events in autumn and spring differ in terms of whether they adhere to patterns of co- or countergradient variation.Although the study of individual species and local species communities has revealed fine-tuning of species to local conditions (22), and a wealth of studies report shifts in phenology worldwide (23), we still lack a general understanding of how the two tie together: how strong is local adaptation in the timing of events, and how do they vary across the season? Here, a major hurdle to progress has been a skew in the focus of past studies: our current understanding of climatic effects on phenology has been colored by springtime events (24–26), whereas events with a mean occurrence later in the season have been disproportionately neglected (27). To achieve satisfactory insight into how climate and its change affect the timing of biological activity across the season, we should thus ask how strongly phenology is influenced by climatic variation, what part of this response reflects phenotypic plasticity and what part evolutionary differentiation, and how the relative imprint of the two varies across the season. Addressing these pertinent questions is logistically challenging (e.g., ref. 28). Therefore, few studies have tackled them outside of the laboratory (29).Phillimore and coworkers (10, 30) proposed an elegant technique for identifying the relative roles of plasticity and local adaptation in generating spatiotemporal patterns of phenological variation. The rationale is to use a space versus time comparison (10, 30) (but see ref. 31 for criticism), drawing on the realization that at any one site, local conditions will vary between years. To be active at the right time, species will thus need to respond to temporal variation in climatic conditions. Let us assume that a focal species times some aspect of its annual activity (a species-specific “phenological event”) by reacting to a single environmental cue (e.g., the crossing of a given temperature sum). Now, if there were no differentiation between populations and all populations followed the same reaction norm, then with variation in the relative timing of the cue over time, all populations would react in the same way to the same cue regardless of spatial location (Fig. 1A). At the level of population means across space (blue line in Fig. 1A), we would then see a relationship between phenological event and cue timing identical to year-to-year variation within locations (red lines in Fig. 1A). However, if populations differentiate across sites, then we will see an added component in the spatial slope, reflecting the contribution of local adaptation to the mean phenology of the populations. By subtracting the within-population temporal slope from the spatial slope, we will thus achieve a direct measure of local adaptation (10), henceforth called Δb (30).Importantly, the temporal slope (i.e., the local phenological response to local year-to-year variation in the cue) can be either steeper or more shallow than the spatial slope (Fig. 1B vs. Fig. 1C)—the former being a sign of countergradient local adaptation, the latter of cogradient local adaptation (20, 21, 32). For a worked-through example of how this methodology is applied to the current data, see SI Appendix, Text S1.Here, we adopt temperature sums as widely used predictors of phenological events (33–35) and treat the difference between the spatial and temporal slopes of phenological events on such sums as our estimates of local adaptation in reaction norms (SI Appendix, Text S1). Pinpointing the relative roles of plasticity and microevolution from spatiotemporal observations in the absence of direct measures of fitness will, per necessity, rely on several assumptions (for a full discussion, see ref. 36). However, given the adequate precaution, such quantification allows a tractable way toward estimating local adaption on a large scale (8, 10, 30, 36–38).A key requirement for the successful application of this approach to resolving patterns across events of different relative timing is the existence of abundant data covering a large geographic area (30, 36). The extensive phenological data-collection scheme implemented at hundreds of nature reserves and other monitoring sites within the area of the former Soviet Union offers unique opportunities for addressing community-level phenology across a large space and long time (39). From this comprehensive dataset spanning 472 monitoring sites, 510,165 events and a time series of up to 118 y (Fig. 2 and ref. 39), we selected those 178 phenological events for which we have at least 100 data points that represent at least 10 locations (SI Appendix, Table S1). These events concerned 91 distinct taxa (SI Appendix, Table S1).Open in a separate windowFig. 2.Study sites and spatiotemporal patterns in climatic and phenological data. A shows the depth of the data and the spatial distribution of monitoring sites, with the size of the symbol proportional to the number of events scored locally. Since the selection of sites differed between events (39), in A, we have pooled sites located within 300 km from each other for illustration purposes. B shows the mean timing (day of year) of a phenological event: the onset of blooming in dandelion (Taraxacum officinale). C shows the mean timing (day of year) of a climatic event: the day of the year when the temperature sum providing the highest temporal slope for the onset of blooming in dandelion was first exceeded, computed as the mean over the years considered in B. For a worked-through example estimating reaction norms and metrics of local adaptation (Δb) for this species, see SI Appendix, Text S1.To express data on species phenology and abiotic conditions in the same currency, we related the dates of the phenological events (e.g., the first observation of an animal, or first flowering time of a plant species; SI Appendix, Fig. S1) to the dates when a given thermal sum (34, 35) was first exceeded. This choice of units has a convenient consequence in terms of the interpretation of slope values: if the date of phenology changes follows one-to-one the date of attaining a given temperature sum, then the slope will be one—an assumption frequently made but rarely tested in studies based on growth-degree days. The observed reaction norms can then be compared to this value. A value below 1 will signal undercompensation, i.e., that the earlier the cue, the larger the relative delay of the phenological event compared to its cue. By contrast, a value larger than 1 would signal overcompensation, i.e., that with an advancement of the cue, the timing of the phenological event will be advanced even more.Since thermal sums can be formed using a variety of thresholds, we used a generic approach and considered dates for exceeding a wide range of both heating and chilling degree-day sums (34, 35) (see Material and Methods for more information). As there is also evidence that sensitivity to temperature arises after a certain time point (13, 36), we calculated each heating and chilling degree-days sum for a range of starting dates. For each of the resulting 2,926 events, we then picked the variable that offered the highest temporal slope estimate, i.e., the largest within-location change in the timing of the event with a change in the timing of the cue (see Material and Methods for more information). Following the rationale outline above, this will be the most appropriate optimization criterion, since it selects the cue to which the phenological event responds the strongest to over time.     

Natal dispersal driven by environmental conditions interacting across the annual cycle of a migratory songbird

Natal dispersal, the process through which immature individuals permanently depart their natal area in search of new sites, is integral to the ecology and evolution of animals. Insights about the underlying causes of natal dispersal arise mainly from research on species whose short dispersal distances or restricted distributions make them relatively easy to track. However, for small migratory animals, the causes of natal dispersal remain poorly understood because individuals are nearly impossible to track by using conventional mark-recapture approaches. Using stable-hydrogen isotope ratios in feathers of American redstarts (Setophaga ruticilla) captured as immature birds and again as adults, we show that habitat use during the first tropical nonbreeding season appears to interact with latitudinal gradients in spring phenology on the temperate breeding grounds to influence the distance traveled on the initial spring migration and the direction of natal dispersal. In contrast, adult redstarts showed considerable site fidelity between breeding seasons, indicating that environmental conditions did not affect dispersal patterns after the first breeding attempt. Our findings suggest that habitat occupancy during the first nonbreeding season helps determine the latitude at which this species of Neotropical-Nearctic migratory bird breeds throughout its life and emphasize the need to understand how events throughout the annual cycle interact to shape fundamental biological processes.     

Timing outweighs magnitude of rainfall in shaping population dynamics of a small mammal species in steppe grassland

Climate change–induced shifts in species phenology differ widely across trophic levels, which may lead to consumer–resource mismatches with cascading population and ecosystem consequences. Here, we examined the effects of different rainfall patterns (i.e., timing and amount) on the phenological asynchrony of population of a generalist herbivore and their food sources in semiarid steppe grassland in Inner Mongolia. We conducted a 10-y (2010 to 2019) rainfall manipulation experiment in 12 0.48-ha field enclosures and found that moderate rainfall increases during the early rather than late growing season advanced the timing of peak reproduction and drove marked increases in population size through increasing the biomass of preferred plant species. By contrast, greatly increased rainfall produced no further increases in vole population growth due to the potential negative effect of the flooding of burrows. The increases in vole population size were more coupled with increased reproduction of overwintered voles and increased body mass of young-of-year than with better survival. Our results provide experimental evidence for the fitness consequences of phenological mismatches at the population level and highlight the importance of rainfall timing on the population dynamics of small herbivores in the steppe grassland environment.

The Earth is facing a great challenge from accelerated climate change. The global surface air temperature has increased by about 1° during the past century and is projected to exceed 1.5 to 2 °C by the end of the 21st century (1). Climate change has caused profound impacts on the Earth’s ecosystems, such as local extinctions (2), range shifts (3), and population fluctuations (4, 5) of many species. Many organisms have advanced the timing of phenological events in response to climate warming, such as earlier leaf-out in plants, earlier emergence of insects, or accelerated egg hatching dates for birds (6). For consumers, phenological events are timed to match peak food resources for breeding; however, the direction of consumer’s phenological response to climate change may differ from the response of species occupying lower trophic levels, leading to asynchrony between resources and consumers (7, 8). With respect to climate change, numerous studies have focused on the impact of temperature and its role in driving phenological asynchrony (9–11) since this is especially critical for species population dynamics and ecosystem functioning. However, relatively little is known about how rainfall mediates asynchrony between resources and consumers and its potential demographic consequences, especially in arid environments.Shifts in rainfall patterns have been greatly affected by climate warming (12) and play a key role in regulating vertebrate population dynamics (13), the species composition of communities, and ecosystem functions and services (14). Both the timing and the amount of rainfall are recognized as distinct but major components that synergistically influence the timing of vegetation phenology, e.g., the timing of plant germination and seed ripening (15, 16). However, it remains unclear whether changes in the timing or the amount of rainfall play the more dominant role in the processes of phenological asynchrony between interacting species despite their distinct effects on aboveground annual net primary productivity (17). It is therefore important to disentangle the independent effects of rainfall timing and amount if we are to predict responses of species’ populations and ecosystems to global climate change.Among small herbivores, rainfall is well recognized to induce a bottom-up increase in abundance via increasing food availability, as observed in Phyllotis darwini and Octodon degus in South America (18, 19), Pseudomys hermannsburgensis and Mus domesticus in Australia (20, 21), Spermophilus dauricus (22) and Cricetulus barabensis (23) in East Asia, Dipodomys merriami in North America (24), and Mastomys natalensis in Africa (25). However, these observations are all based on the correlation between rodent abundance and precipitation; the mechanism underlying the bottom-up effects of precipitation on rodents through plant productivity is often assumed but has been rarely investigated by manipulative experiments. While valuable in their own right, most previous studies have been unable to elucidate fully the role of rainfall as a potential proximate cue in regulating phenology. In natural environments, many biotic factors (e.g., predation and interspecific competition) and abiotic factors (e.g., flooding of burrows) may interact to influence how phenological processes can affect population dynamics. To understand the effects of rainfall on the role of phenological asynchrony in the population dynamics of target species, including the effects of rainfall amount and timing, it is therefore necessary to exclude or control for confounding factors. Conducting more tightly controlled manipulative experiments is a requirement when assessing the fitness consequences of phenological asynchrony (6, 7), although it is very challenging for small rodents owing to the need for large field enclosures that prevent immigration/emigration of individuals and impacts by predators.We conducted a 10-y, large-scale, manipulative experiment to examine the bottom-up effects of changes in rainfall regime (including timing and amount; SI Appendix, Fig. S1) on the phenological asynchrony between plants and herbivores, demographic parameters, and population dynamics of Brandt’s voles Lasiopodomys brandtii. In our study region in Inner Mongolia, an increase in annual rainfall, especially during the early growing season, can markedly enhance annual net primary productivity (26), with more rain increasing the biomass of rye grass Leymus chinensis (27, 28), a major and favored food source for Brandt’s voles (29). Additional rainfall in the early growing season can provide a match between the peak food resources and peak food requirements of young voles. Therefore, we hypothesized that rainfall would change the population density of voles by mediating the timing and peak amount of preferred foods and that rainfall timing (in the early growing season) would be of vital importance in triggering population increases, or outbreaks, of voles in arid steppe grassland.     

贵州仿野生栽培红天麻的生活史及物候期研究

为掌握仿野生栽培红天麻的生活史及物候期,在贵州大方县采用林下仿野生模式栽培红天麻,观察并记录其生长发育各阶段特征。整理的历时24个月的贵州仿野生栽培红天麻生活史,将贵州仿野生栽培红天麻无性繁殖与有性繁殖中箭麻繁育物候期各自划分出5个时期,并详述各期特点。其结果可明确贵州红天麻仿野生栽培流程,为仿野生栽培天麻技术标准的研究与制订提供理论支撑。     

Compounded effects of climate change and habitat alteration shift patterns of butterfly diversity

Climate change and habitat destruction have been linked to global declines in vertebrate biodiversity, including mammals, amphibians, birds, and fishes. However, invertebrates make up the vast majority of global species richness, and the combined effects of climate change and land use on invertebrates remain poorly understood. Here we present 35 years of data on 159 species of butterflies from 10 sites along an elevational gradient spanning 0–2,775 m in a biodiversity hotspot, the Sierra Nevada Mountains of Northern California. Species richness has declined at half of the sites, with the most severe reductions at the lowest elevations, where habitat destruction is greatest. At higher elevations, we observed clear upward shifts in the elevational ranges of species, consistent with the influence of global warming. Taken together, these long-term data reveal the interacting negative effects of human-induced changes on both the climate and habitat available to butterfly species in California. Furthermore, the decline of ruderal, disturbance-associated species indicates that the traditional focus of conservation efforts on more specialized and less dispersive species should be broadened to include entire faunas when estimating and predicting the effects of pervasive stressors.