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2.2: Seasonal Plants - Biology

2.2: Seasonal Plants - Biology



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Learning Objectives

  • Describe seasonal plants common to the horticulture industry.

Planning combinations of woody and herbaceous plants with different life cycles and high visual impact generates year round interest in exterior and interior plantings. When visual interest is planned for one period such as early summer, borders and containers can have a poor appearance the rest of the year. Optimizing the use of grasses, bulbs, perennials, annuals, biennials, shrubs, climbers, and trees can provide a succession of plant forms, colours, textures, and habits throughout the seasons. In temperate regions, year round interest is maximized by selecting plants with at least two, and even three or four seasons of interest.

Conifers and broadleaf evergreens shrubs are often used for year round colour and spatial structure. For example, Taxus cuspidata ‘Capitata’ (upright yew) provides reliable winter colour and a framework that can be enhanced with other shapes, textures, and colours. On the other hand, a planting of broadleaf evergreens such as Skimmia japonica (Japanese skimmia) offers winter colour and structure as well as showy spring flowers and colourful fruit in the autumn. Distinctive plant shapes and the bark of trees such as Cryptomeria japonica (Japanese cedar) and Morus alba ‘Pendula’ or species with persistent fruit like Sorbus aucuparia (European mountain ash) also contribute structure and winter interest.

Practice: Recognize woody plants for winter interest.

A link to an interactive elements can be found at the bottom of this page.

Some deciduous shrubs and trees like Caryopteris x clandonensis (bluebeard), Cercidiphyllum japonicum (katsura), and Rhus typhina (staghorn sumac) have interesting branching patterns throughout all seasons. The bark and buds of Ribes sanguineum (flowering currant, winter currant), Magnolia x soulangeana (saucer magnolia), Liriodendron tulipifera, and Styrax japonicus (Japanese snowbell, Japanese snowcone) provide winter interest and interesting buds forecast the appearance of foliage and flowers. Climbers with variegated or textured foliage and colourful flowers like Actinidia kolomikta (actinitdia) and Campsis radicans (trumpet vine) also contribute vertical structure. View the images seasonal plant characteristics available at this link to the KPU Plant Database [New Tab][1]

The appearance of plants before, during, and after flowering is an important consideration for planning seasonal interest. For example, the herbaceous specimen plant Gunnera manicata (gunnera, giant rhubarb) provides a bold shape and texture for at least half to perhaps three quarters of the year. With planning, the eye catching winter stems and seed heads of grasses and perennial species such as Pennisetum alopecuroides (fountain grass), Pennisetum setaceum ‘Rubrum’ (red fountain grass), and Perovskia atriplicifolia (Russian sage) can serve as distractions from seasonal voids. Layering various heights of ground covers, bulbs, annuals and perennials under and around woody shrubs and trees allows a succession of foliage shapes, sizes, textures, and colours to become prominent as the year progresses. In this way, emphasis is placed on year round interest and not only the seasonal show of flowers. A planting calendar is a useful tool for working out the succession of flowers and colour palettes as well as other planting design features. Figure 8.1 shows an example of a basic planting calendar that allows the planner to visualize the times of the year that are most colourful and interesting and those that could use additional development.

Figure 8.1 Sample planting calendar

As the succession of spring bulbs like Anemone blanda (Greek windflower, blue wood) and Hyacinthus cvs. (hyacinth) finish flowering and foliage fades, deciduous shrubs such as Spiraea x vanhouttei (bridal wreath spirea) and an array of herbaceous annuals, biennials and perennials come into flower in early and mid spring. Examples of spring blooming perennials include Aubrieta x cultorum (common rock cress), Brunnera macrophylla (Siberian bugloss), Papaver orientale (oriental poppy), Pulmonaria saccharata (lungwort), and Dicentra spectabilis (bleeding heart). From late spring and early to mid summer, the flowers and foliage of broadleaf evergreen shrubs such as Daphne cneorum (garland daphne) and herbaceous species like Thymus pseudolanuginosus (woolly thyme), Heuchera cvs. (coralbells, alumroot), and Phlox paniculata (common phlox) take prominence. The progression of seasonal foliage and bloom continues in mid to late summer and through autumn with perennials such as Actaea simplex Atropurpurea Group (cimicifuga), Aster spp. (common aster), Astrantia major (masterwort, astrantia), Coreopsis spp. & cvs. ( coreopsis), Geranium spp. (geranium), and Gaillardia cvs. (blanket flower). The texture and seed heads of perennials like Hylotelephium spectabile (autumn joy sedum, stonecrop), and grasses such as Andropogon gerardii (big bluestem), Calamagrostis x acutiflora (feather reed grass), and Molinia arundinacea ‘Skyracer’ (tall moor grass) extend the visual interest from late autumn into winter. Year round interest is fulfilled by evergreens and the flowers of winter blooming shrubs and perennials. View images of the seasonal plant characteristics available at this link to the KPU Plant Database [New Tab][2]. Read more about seasonal plant combinations at this link to Gardenia Seasonal Garden Ideas [New Tab][3].

Practice: Recognize plants for seasonal interest.

A link to an interactive elements can be found at the bottom of this page.



26.4 The Role of Seed Plants

By the end of this section, you will be able to do the following:

  • Explain how angiosperm diversity is due, in part, to multiple complex interactions with animals
  • Describe ways in which pollination occurs
  • Discuss the roles that plants play in ecosystems and how deforestation threatens plant biodiversity

Without seed plants, life as we know it would not be possible. Plants play a key role in the maintenance of terrestrial ecosystems through the stabilization of soils, cycling of carbon, and climate moderation. Large tropical forests release oxygen and act as carbon dioxide “sinks.” Seed plants provide shelter to many life forms, as well as food for herbivores, thereby indirectly feeding carnivores. Plant secondary metabolites are used for medicinal purposes and industrial production. Virtually all animal life is dependent on plants for survival.

Animals and Plants: Herbivory

Coevolution of flowering plants and insects is a hypothesis that has received much attention and support, especially because both angiosperms and insects diversified at about the same time in the middle Mesozoic. Many authors have attributed the diversity of plants and insects to both pollination and herbivory , or the consumption of plants by insects and other animals. Herbivory is believed to have been as much a driving force as pollination. Coevolution of herbivores and plant defenses is easily and commonly observed in nature. Unlike animals, most plants cannot outrun predators or use mimicry to hide from hungry animals (although mimicry has been used to entice pollinators). A sort of arms race exists between plants and herbivores. To “combat” herbivores, some plant seeds—such as acorn and unripened persimmon—are high in alkaloids and therefore unsavory to some animals. Other plants are protected by bark, although some animals developed specialized mouth pieces to tear and chew vegetal material. Spines and thorns (Figure 26.20) deter most animals, except for mammals with thick fur, and some birds have specialized beaks to get past such defenses.

Herbivory has been exploited by seed plants for their own benefit. The dispersal of fruits by herbivorous animals is a striking example of mutualistic relationships. The plant offers to the herbivore a nutritious source of food in return for spreading the plant’s genetic material to a wider area.

An extreme example of coevolution (discovered by Daniel Janzen) between an animal and a plant is exemplified by Mexican acacia trees and their attendant acacia ants Pseudomyrmex spp. (this is termed myrmecophytism). The trees support the ants with shelter and food: The ants nest in the hollows of large thorns produced by the tree and feed on sugary secretions produced at the ends of the leaves. The sugar pellets also help to keep the ants from interfering with insect pollinators. In return, ants discourage herbivores, both invertebrates and vertebrates, by stinging and attacking leaf-eaters and insects ovipositing on the plants. The ants also help to remove potential plant pathogens, such as fungal growths. Another case of insect-plant coevolution is found in bracken fern (Pteridium aquinilum), whose subspecies are found throughout the world. Bracken ferns produce a number of “secondary plant compounds” in their adult fronds that serve as defensive compounds against nonadapted insect attack (these compounds include cyanogenic glucosides, tannins, and phenolics). However, during the “fiddlehead” or crozier stage, bracken secretes nutritious sugary and proteinaceous compounds from special “nectaries” that attract ants and even species of jumping spiders, all of which defend the plant’s croziers until they are fully unfolded. These opportunistic groups of protective arthropods greatly reduce the damage that otherwise would occur during the early stages of growth.

Animals and Plants: Pollination

Flowers pollinated by wind are usually small, feathery, and visually inconspicuous. Grasses are a successful group of flowering plants that are wind pollinated. They produce large amounts of powdery pollen carried over large distances by the wind. Some large trees such as oaks, maples, and birches are also wind pollinated.

Link to Learning

Explore this website for additional information on pollinators.

More than 80 percent of angiosperms depend on animals for pollination (technically the transfer of pollen from the anther to the stigma). Consequently, plants have developed many adaptations to attract pollinators. With over 200,000 different plants dependent on animal pollination, the plant needs to advertise to its pollinators with some specificity. The specificity of specialized plant structures that target animals can be very surprising. It is possible, for example, to determine the general type of pollinators favored by a plant by observing the flower’s physical characteristics. Many bird or insect-pollinated flowers secrete nectar, which is a sugary liquid. They also produce both fertile pollen, for reproduction, and sterile pollen rich in nutrients for birds and insects. Many butterflies and bees can detect ultraviolet light, and flowers that attract these pollinators usually display a pattern of ultraviolet reflectance that helps them quickly locate the flower's center. In this manner, pollinating insects collect nectar while at the same time are dusted with pollen (Figure 26.21). Large, red flowers with little smell and a long funnel shape are preferred by hummingbirds, who have good color perception, a poor sense of smell, and need a strong perch. White flowers that open at night attract moths. Other animals—such as bats, lemurs, and lizards—can also act as pollinating agents. Any disruption to these interactions, such as the disappearance of bees, for example as a consequence of colony collapse disorders, can lead to disaster for agricultural industries that depend heavily on pollinated crops.

Scientific Method Connection

Testing Attraction of Flies by Rotting Flesh Smell

Question: Will flowers that offer cues to bees attract carrion flies if sprayed with compounds that smell like rotten flesh?

Background: Visitation of flowers by pollinating flies is a function mostly of smell. Flies are attracted by rotting flesh and carrions. The putrid odor seems to be the major attractant. The polyamines putrescine and cadaverine, which are the products of protein breakdown after animal death, are the source of the pungent smell of decaying meat. Some plants strategically attract flies by synthesizing polyamines similar to those generated by decaying flesh and thereby attract carrion flies.

Flies seek out dead animals because they normally lay their eggs on them and their maggots feed on the decaying flesh. Interestingly, time of death can be determined by a forensic entomologist based on the stages and type of maggots recovered from cadavers.

Hypothesis: Because flies are drawn to other organisms based on smell and not sight, a flower that is normally attractive to bees because of its colors will attract flies if it is sprayed with polyamines similar to those generated by decaying flesh.

Test the hypothesis:

  1. Select flowers usually pollinated by bees. White petunia may be a good choice.
  2. Divide the flowers into two groups, and while wearing eye protection and gloves, spray one group with a solution of either putrescine or cadaverine. (Putrescine dihydrochloride is typically available in 98 percent concentration this can be diluted to approximately 50 percent for this experiment.)
  3. Place the flowers in a location where flies are present, keeping the sprayed and unsprayed flowers separated.
  4. Observe the movement of the flies for one hour. Record the number of visits to the flowers using a table similar to Table 26.2. Given the rapid movement of flies, it may be beneficial to use a video camera to record the fly–flower interaction. Replay the video in slow motion to obtain an accurate record of the number of fly visits to the flowers.
  5. Repeat the experiment four more times with the same species of flower, but using different specimens.
  6. Repeat the entire experiment with a different type of flower that is normally pollinated by bees.

Analyze your data: Review the data you have recorded. Average the number of visits that flies made to sprayed flowers over the course of the five trials (on the first flower type) and compare and contrast them to the average number of visits that flies made to the unsprayed/control flowers. Can you draw any conclusions regarding the attraction of the flies to the sprayed flowers?

For the second flower type used, average the number of visits that flies made to sprayed flowers over the course of the five trials and compare and contrast them to the average number of visits that flies made to the unsprayed/control flowers. Can you draw any conclusions regarding the attraction of the flies to the sprayed flowers?

Compare and contrast the average number of visits that flies made to the two flower types. Can you draw any conclusions about whether the appearance of the flower had any impact on the attraction of flies? Did smell override any appearance differences, or were the flies attracted to one flower type more than another?

Form a conclusion: Do the results support the hypothesis? If not, how can your observations be explained?

The Importance of Seed Plants in Human Life

Seed plants are the foundation of human diets across the world (Figure 26.22). Many societies eat almost exclusively vegetarian fare and depend solely on seed plants for their nutritional needs. A few crops (rice, wheat, and potatoes) dominate the agricultural landscape. Many crops were developed during the agricultural revolution, when human societies made the transition from nomadic hunter–gatherers to horticulture and agriculture. Cereals, rich in carbohydrates, provide the staple of many human diets. Beans and nuts supply proteins. Fats are derived from crushed seeds, as is the case for peanut and rapeseed (canola) oils, or fruits such as olives. Animal husbandry also consumes large quantities of crop plants.

Staple crops are not the only food derived from seed plants. Various fruits and vegetables provide nutrient macromolecules, vitamins, minerals, and fiber. Sugar, to sweeten dishes, is produced from the monocot sugarcane and the eudicot sugar beet. Drinks are made from infusions of tea leaves, chamomile flowers, crushed coffee beans, or powdered cocoa beans. Spices come from many different plant parts: saffron and cloves are stamens and buds, black pepper and vanilla are seeds, the bark of a bush in the Laurales family supplies cinnamon, and the herbs that flavor many dishes come from dried leaves and fruit, such as the pungent red chili pepper. The volatile oils of a number of flowers and bark provide the scent of perfumes.

Additionally, no discussion of seed plant contribution to human diet would be complete without the mention of alcohol. Fermentation of plant-derived sugars and starches is used to produce alcoholic beverages in all societies. In some cases, the beverages are derived from the fermentation of sugars from fruit, as with wines and, in other cases, from the fermentation of carbohydrates derived from seeds, as with beers. The sharing of foods and beverages also contributes to human social ritual.

Seed plants have many other uses, including providing wood as a source of timber for construction, fuel, and material to build furniture. Most paper is derived from the pulp of coniferous trees. Fibers of seed plants such as cotton, flax, and hemp are woven into cloth. Textile dyes, such as indigo, were mostly of plant origin until the advent of synthetic chemical dyes.

Lastly, it is more difficult to quantify the benefits of ornamental seed plants. These grace private and public spaces, adding beauty and serenity to human lives and inspiring painters and poets alike.

The medicinal properties of plants have been known to human societies since ancient times. There are references to the use of plants’ curative properties in Egyptian, Babylonian, and Chinese writings from 5,000 years ago. Many modern synthetic therapeutic drugs are derived or synthesized de novo from plant secondary metabolites. It is important to note that the same plant extract can be a therapeutic remedy at low concentrations, become an addictive drug at higher doses, and can potentially kill at high concentrations. Table 26.3 presents a few drugs, their plants of origin, and their medicinal applications.

Plant Compound Application
Deadly nightshade (Atropa belladonna ) Atropine Dilate eye pupils for eye exams
Foxglove (Digitalis purpurea) Digitalis Heart disease, stimulates heart beat
Yam (Dioscorea spp.) Steroids Steroid hormones: contraceptive pill and cortisone
Ephedra (Ephedra spp.) Ephedrine Decongestant and bronchiole dilator
Pacific yew (Taxus brevifolia) Taxol Cancer chemotherapy inhibits mitosis
Opium poppy (Papaver somniferum) Opioids Analgesic (reduces pain without loss of consciousness) and narcotic (reduces pain with drowsiness and loss of consciousness) in higher doses
Quinine tree (Cinchona spp.) Quinine Antipyretic (lowers body temperature) and antimalarial
Willow (Salix spp.) Salicylic acid (aspirin) Analgesic and antipyretic

Career Connection

Ethnobotanist

The relatively new field of ethnobotany studies the interaction between a particular culture and the plants native to the region. Seed plants have a large influence on day-to-day human life. Not only are plants the major source of food and medicine, they also influence many other aspects of society, from clothing to industry. The medicinal properties of plants were recognized early on in human cultures. From the mid-1900s, synthetic chemicals began to supplant plant-based remedies.

Pharmacognosy is the branch of pharmacology that focuses on medicines derived from natural sources. With massive globalization and industrialization, it is possible that much human knowledge of plants and their medicinal purposes will disappear with the cultures that fostered them. This is where ethnobotanists come in. To learn about and understand the use of plants in a particular culture, an ethnobotanist must bring in knowledge of plant life and an understanding and appreciation of diverse cultures and traditions. The Amazon forest is home to an incredible diversity of vegetation and is considered an untapped resource of medicinal plants yet, both the ecosystem and its indigenous cultures are threatened with extinction.

To become an ethnobotanist, a person must acquire a broad knowledge of plant biology, ecology, and sociology. Not only are the plant specimens studied and collected, but also the stories, recipes, and traditions that are linked to them. For ethnobotanists, plants are not viewed solely as biological organisms to be studied in a laboratory, but as an integral part of human culture. The convergence of molecular biology, anthropology, and ecology make the field of ethnobotany a truly multidisciplinary science.

Biodiversity of Plants

Biodiversity ensures a resource for new food crops and medicines. Plant life balances ecosystems, protects watersheds, mitigates erosion, moderates our climate, and provides shelter for many animal species. Threats to plant diversity, however, come from many sources. The explosion of the human population, especially in tropical countries where birth rates are highest and economic development is in full swing, is leading to devastating human encroachment into forested areas. To feed the growing population, humans need to obtain arable land, so there has been and continues to be massive clearing of trees. The need for more energy to power larger cities and economic growth therein leads to the construction of dams, the consequent flooding of ecosystems, and increased emissions of pollutants. Other threats to tropical forests come from poachers, who log trees for their precious wood. Ebony and Brazilian rosewood, both on the endangered list, are examples of tree species driven almost to extinction by indiscriminate logging. This unfortunate practice continues unabated today largely due to lack of population control and political willpower.

The number of plant species becoming extinct is increasing at an alarming rate. Because ecosystems are in a delicate balance, and seed plants maintain close symbiotic relationships with animals—whether predators or pollinators—the disappearance of a single plant can lead to the extinction of connected animal species. A real and pressing issue is that many plant species have not yet been catalogued, and so their place in the ecosystem is unknown. These unknown species are threatened by logging, habitat destruction, and loss of pollinators. They may become extinct before we have the chance to begin to understand the possible impacts from their disappearance. Efforts to preserve biodiversity take several lines of action, from preserving heirloom seeds to barcoding species. Heirloom seeds come from plants that were traditionally grown in human populations, as opposed to the seeds used for large-scale agricultural production. Barcoding is a technique in which one or more short gene sequences, taken from a well-characterized portion of DNA found in most genomes, are used to identify a species through DNA analysis.


Results

Untargeted metabolite profiling the metabolomes of different Taxus species

To explore the comprehensive variations in metabolomes of different Taxus species, an untargeted approach (15 repeats for each group) was applied, identifying 2246 metabolites from 8712 ions with a relative standard deviation < 30% (Additional file 1). Similar to the differences in twig morphology, variations in the metabolomes among different Taxus species were also observed (Fig. 1a). For quality checking, total ion chromatograms were generated, suggesting that the sample preparation met the common standards (Additional file 2). To produce an overview of the metabolic variations, a PCA was performed, and the percentages of explained value in the metabolome analysis of PC1 and PC2 were 25.01 and 31.24%, respectively. The PCA data showed three clearly separated sample groups, indicating separations among the three different species (Fig. 1b). Based on their KEGG annotations, 747 metabolites were predicted to be involved in various primary metabolic pathways, including the amino acid-, carbohydrate-, cofactor and vitamin-, energy-, lipid-, nucleotide-, secondary metabolite-, and terpenoid-related pathways (Fig. 1c and Additional file 3).

Untargeted metabolite profiling identifies the metabolites in the tested Taxus trees. a A picture of T. media, T. mairei and T. cuspidata under greenhouse condition. Fresh twigs were harvested from three cultivated Taxus species. b The PCA data of the samples from three different species. The red spots indicated the samples from T. cuspidata the green spots indicated the samples from T. media and the blue spots indicated the samples from T. mairei. c A heatmap of the metabolites grouped by Kyoto Encyclopedia of Genes and Genomes pathway found in the metabolomes of the three Taxus species (n = 15). The heatmap scale ranges from − 4 to + 4 on a log2 scale

Clustering of differential accumulated metabolites

All annotated metabolites were clustered to identify the differential accumulated metabolites (DAMs) among three Taxus species (Fig. 2a). All DAMs were grouped into three Clusters: I, II and III. The T. media predominantly accumulated metabolites were grouped into Cluster I (358 metabolites), the T. cuspidata predominantly accumulated metabolites were grouped into Cluster II (220 metabolites), and the T. mairei predominantly accumulated metabolites were grouped into Cluster III (169 metabolites) (Fig. 2b). Our data showed that the DAMs belonging to the ‘secondary metabolites’, ‘lipids’, ‘cofactors and vitamins’, ‘carbohydrate’ and ‘amino acid’ categories were predominantly accumulated in T. media (Fig. 2c). The Cluster I (T. media predominantly accumulated) consisted of 117 secondary metabolites, 91 amino acids, 51 cofactors and vitamins, 48 carbohydrates, 32 lipids, 17 nucleotides and 2 energy-related metabolites the Cluster II consisted of 80 secondary metabolites, 53 amino acids, 25 cofactors and vitamins, 23 carbohydrates, 18 lipids, 19 nucleotides and 2 energy-related metabolites and the Cluster III consisted of 71 secondary metabolites, 32 amino acids, 30 cofactors and vitamins, 13 carbohydrates, 11 lipids, 10 nucleotides and 2 energy-related metabolites (Fig. 2c).

The variations in the metabolites among three Taxus species. a A heatmap of the relative amounts of DAMs from the three different species. b Clustering of the DAMs into three Clusters. Red cycles indicated the species specific accumulated metabolites. c These DAMs were also assigned into various primary metabolic categories

To get a comprehensive overview of variations, all DAMs were classified into different known metabolic pathways. In total, 32, 29, and 38 major pathways were enriched in the T. mairei vs T. cuspidata (Additional file 4), T. media vs T. mairei (Additional file 5), and T. media vs T. cuspidata (Additional file 6) comparisons. Interestingly, the largest number of DAMs in each comparison were enriched in the ‘diterpenoid biosynthesis’ pathway.

Variations in the abundance levels of taxoids among three Taxus species

Paclitaxel biosynthesis is an intricate metabolic pathway that involves a number of precursors, intermediates, and derivatives [5, 30]. By searching the metabolite pool, seven precursors from the MEP pathway, nine intermediates and derivatives, two side chain products, and paclitaxel were detected (Fig. 3a). For the MEP pathway, several precursors, such as D-glyceraldehyde 3-phosphate, 1-deoxy-D-xylulose 5-phosphate, and 2-C-methyl-D-erythritol 4-phosphate, were predominantly accumulated in T. mairei. Two precursors, 4-hydroxy-3-methyl-but-2-enyl diphosphate and 2-C-methyl-D-erythritol 2,4-cyclodiphosphate, were significantly accumulated in T. cuspidata. For the intermediate and derivative products, GGPP, Taxa-4(20),11(12)-dien-5α-ol, and Taxa-4(20),11(12)-dien-5α,13α-diol were predominantly accumulated in T. mairei Taxa-4(20),11(12)-dien-5α cetoxy-10β ol, 10-Deacetyl-2-debenzoylbaccatin III, 10-Deacetylbaccatin III, and Baccatin III were highest in T. mairei and T. media and 3′-N-Debenzoyl-2′-deoxytaxol, 3′-N-Debenzoyltaxol, and Paclitaxel were predominantly accumulated in T. cuspidata. For the side chain products, β-Phenylalanine was highly accumulated in T. media and β-Phenylalanoyl baccatin III was greatly accumulated in T. mairei (Fig. 3b). The complete biosynthetic pathway, including the elucidated and putative steps, was summarized in Fig. 4. All the taxane precursors that has been determined in our study were highlighted.

Analysis of the relative amounts of taxoids in the Taxus metabolomes from the three different species. (a) Overview of the taxol biosynthesis pathway. (b) The relative accumulation of taxoids, intermediates and derivatives in the three different species. The heatmap scale ranges from -4 to +4 on a log2 scale

The complete biosynthetic pathway of taxol. The red font indicated the taxane precursors whose structure has been determined in the present study

Variations in the abundance levels of flavonoids among three Taxus species

For flavonoid biosynthesis pathway, five intermediate products synthesized by chalcone synthase (CHS), six intermediate products synthesized by chalcone isomerase (CHI), five intermediate products synthesized by flavanone 3-hydroxylase (F3H), and four intermediate products synthesized by flavonol synthase (FLS) were identified (Fig. 5a). For the CHS-synthesized flavonoids, pinocembrin chalcone was highly accumulated in T. mairei, isoliquiritigenin, butein and homoeriodictyol chalcone were predominantly accumulated in T. media, and naringenin chalcone was greatly accumulated in both T. media and T. cuspidata. For the CHI-synthesized flavonoids, only pinocembrin was highly accumulated in T. mairei, eriodictyol and butin were largely accumulated in both T. media, and naringenin, pinostrobin and dihydrotricetin were predominantly accumulated in both T. media and T. cuspidata. Most of the F3H-synthesized flavonoids were predominantly accumulated in T. media, except for dihydroquercetin. For the FLS-synthesized flavonoids, 5-deoxyleucopelargonidin, deoxyleucocyanidin, and leucopelargonidin were highly accumulated in T. media, and leucocyanidin was greatly accumulated in T. mairei (Fig. 5b).

Analysis of the relative amounts of flavonoid in the Taxus metabolomes from the three different species. (a) Overview of the flavonoid biosynthesis pathway. (b) The accumulation levels of intermediate products synthesized by CHS, CHI, and F3H were showed by heatmaps. The heatmap scale ranges from -4 to +4 on a log2 scale

Confirmation of the variations in paclitaxel and its derivatives using a targeted approach

To determine more precisely the differences in taxoids among the three Taxus species, a targeted approach was used to measure the concentrations of paclitaxel, 10-DAB III, baccatin III, and 10-DAP (Additional file 7). The untargeted metabolomics analysis indicated that T. cuspidata and T. mairei contained the highest and the lowest levels of paclitaxel, respectively. The direct quantification with an authentic paclitaxel standard showed that T. cuspidata, T. media, and T. mairei contained 1.67 mg.g − 1 , 1.22 mg.g − 1 , and 0.66 mg.g − 1 of paclitaxel, respectively (Fig. 6a). The order of the paclitaxel contents was in good agreement with the untargeted metabolome results. For other taxoids, the highest levels of baccatin III and 10-DAP were accumulated in T. cuspidata (0.65 mg.g − 1 and 0.80 mg.g − 1 , respectively), and the highest level of 10-DAB III was detected in T. mairei (0.85 mg.g − 1 ) (Fig. 6b-d). To assess variability in taxoid level among different species of the genus Taxus, another three Taxus species, including T. chinensis, T. fuana and T. yunnanensis, have been collected. A more exhaustive profile of taxoids in the genus has been showed in Additional file 8.

Variation of the contents of several selected taxoids and flavonoids among three different Taxus species. The contents of paclitaxel (a) and three intermediates, including baccatin III (b), 10-DAP (c), and 10-DAB III (d), were quantified by HPLC-MS/MS method. The contents of amentoflavone (e), ginkgetin (f), quercetin (g), and luteolin (h), were quantified by HPLC-MS/MS method. A P value < 0.05 was considered to be statistically significant and indicated by “b” and P < 0.01 was indicated by “a”

Confirmation of the variations in flavonoids using a targeted approach

To determine more precisely the differences in flavonoids among the three Taxus species, a targeted approach was used to measure the concentrations of amentoflavone, ginkgetin, quercetin and luteolin (Additional file 9). Our data showed that amentoflavone highly accumulated in T. cuspidata (0.14 mg.g − 1 ) and lowly accumulated in T. media (0.024 mg.g − 1 ) (Fig. 6e). Interestingly, ginkgetin, quercetin and luteolin were greatly accumulated in T. mairei rather than the other two taxus trees (Fig. 6f-h).

Systematic correlativity analysis identifies a number of metabolites associated with key metabolites of paclitaxel biosynthesis

An analysis of metabolite–metabolite interaction networks contributed to the understanding of functional relationships and the identification of new compounds associated with key metabolites of paclitaxel biosynthesis. In our study, an interaction network based on the differentially accumulated metabolites was constructed. Furthermore, the taxoid-related networks were divided into three clusters surrounding paclitaxel, baccatin III, and 10-DAB III (Additional file 10). The interaction networks suggested that nine classes of metabolites, phenylpropanoids, flavonoids, alkaloids, carboxylic acid derivatives, quinones, glycosides, saccharides, steroids and terpenoids, may also contribute to the variations in taxoid accumulation in different species (Fig. 7). However, the mechanisms underlying the interactions of these potential new metabolites need to be investigated.

Analysis of metabolite-metabolite interaction networks. The taxoid-related networks were divided into three clusters surrounding paclitaxel, baccatin III and 10-DAB III, respectively. Nine major classes of metabolites grouped into various dotted circles with different color


2 MATERIALS AND METHODS

To examine spatiotemporal patterns of flowering abundance, phenology, and interspecific overlap, we targeted sites along an elevational gradient in a high arctic system: the Zackenberg valley in NE Greenland (74°28′N, 20°34′W). At each site, we monitored the abundance of flowers at weekly intervals. To relate these flower abundances to interspecific competition for pollinators, we monitored multiple stages of the pollination process (Ne'eman, Jürgens, Newstrom-Lloyd, Potts, & Dafni, 2010 ) among the dominant flowering plant species: insect visitation rates (i.e., pollinator visits per flower and time unit), pollen transport (i.e., the representation of the species in pollen loads carried by pollinating flies), and seed set success (i.e., the proportion of inflorescences setting seed). We then searched for climatic imprints on relative species phenology along the elevational gradient (representing current climatic variation, with elevation as a space-for-time surrogate for climate change e.g., Benadi et al., 2014 Elmendorf et al., 2015 Hoiss, Krauss, & Steffan-Dewenter, 2015 Kearns, 1992 Körner, 2007 ).

2.1 Study species

To characterize variation in the phenology of flowering and competition for pollinators among plant species, we counted inflorescences of all flowering species. Six species emerged as quantitatively dominant in the local flora: Cassiope tetragona Ericaceae, D. integrifolia × octopetala Rosaceae, Papaver radicatum Papaveraceae, Salix arctica Salicaceae, Saxifraga oppositifolia Saxifragaceae, or S. acaulis Caryophyllaceae. These species are all abundant and widely distributed across the Arctic (Walker et al., 2005 ).

2.2 Study sites

We recorded the flowering of plants and flower visitor abundance at 24 study sites (50 m × 50 m each) from late June to early August in 2016. In order to track the effects of the local variation in climate along the elevation gradient on plant–pollinator interactions in a space-for-time experiment, we chose eight study sites in each of three zones along an elevation gradient (0–60, 60–240, and 240–480 m above sea level, 3 × 8 = 24 sites total see Figure S1). To characterize temperature conditions across the gradient, we drew on records from another study (Kankaanpää, 2020 ), with data presented in Figure S2. To minimize the generally large effects of changing plant community on pollination along the elevation gradient (Simanonok & Burkle, 2014 ), each of the sites represented the same vegetation type, Dryas heath. This vegetation type is abundant and widespread at all elevations considered (Bay, 1998 ). To avoid effects caused by spatial variation in the timing of snow-melt (Kankaanpää et al., 2018 Kudo & Hirao, 2006 ), the study sites were established in areas at the same phenophase, that is, when the first flowers opened. The study sites were separated by distances of at least 250 m, a scale over which we assumed few arctic insects to move during their daily foraging. Thus, the sites were considered at least semi-independent in terms of their insect populations. Within each of the 24 study sites, we marked 10 study plots (circular, radius 50 cm) with small flags to locate them later.

2.3 Phenological variation in flower densities and insect visitation

Once a week, we recorded the local, instantaneous density of all flowering plant species at two spatial scales: at the level of the study site and at the level of the study plot. The rate with which different insects visited flowers as a function of contemporary flower densities was scored twice a week by visual observation. During each visit, we walked up to a distance of 2 m from the plot and recorded all visitors on the flowers (thus scoring a snapshot of arthropod abundances present on the flowers upon the observer's arrival). This was, on average, achieved in just some minute per site. The radius of the area for visitor inspection equaled two visual fields of the binoculars used (Ibis, model 10 × 42 Kite), that is 50 cm, with the mark flag held at the center of the circle. Within this area, we recorded all flower visitors at the family level. Flower visitation observations were done mainly between 10:00 and 18:00 and only if the weather conditions were suitable for flower visitors (no rain or heavy wind).

2.4 Pollen transport by flies

To establish the impacts of flower densities on pollen transport (i.e., the representation of pollen from focal flower species in pollen carried by insects), we focused on pollen loads on flies in family Muscidae. This taxon was chosen for being the presumptively most important pollinators in the area (and many other arctic and alpine areas as well Kearns, 1992 Kevan, 1972 Pont, 1993 Tiusanen, Hebert, Schmidt, & Roslin, 2016 ), and the numerically dominant fly taxon of the High Arctic (Böcher, Kristensen, Pape, & Vilhelmsen, 2015 Loboda et al., 2017 ).

With the aim of examining how the pollen loads reflected plant species-specific flower densities and relative flowering phenology, we captured 10 fly individuals at each of the study sites every week. The flies were individually caught with an insect net while they were basking on vegetation or soil on the study sites. To avoid interfering with local flower visitation patterns, and to prevent secondary contamination by pollen during handling, we explicitly avoided catching insects sitting on flowers. All flies caught were stored individually in ethanol-filled tubes.

To remove the pollen from the flies, we then vortexed the tubes (max rpm for 10 s, Vortex-Genie 2, Scientific Industries, Inc.). To concentrate the pollen in the bottom of the tube, the fly was removed, and the pollen suspension centrifuged at 3,000 g for 3 min (Sigma Laboratory centrifuges, model 4-15C). In order to count and identify the pollen, we evaporated the ethanol and cleaned the dry tube from pollen with the aid of agarose gel (15 ml glycerin, 25 ml water, 0.5 g agar, red food dye, Dr. Oetker), which was then poured onto a microscopy slide. The pollen samples were identified and counted with a microscope (CX41, Olympus). Due to the difficulty of identifying the muscid flies in the field, we stayed with family-level identification.

2.5 Proportion of inflorescences setting seed

To estimate the impact of competition on the seed set of plants, we chose two abundant and widely distributed species: D. integrifolia × octopetala, henceforth Dryas for brevity, and S. acaulis. Of these, Dryas was selected as a particularly dominant species in the plant community with a need for pollinators for optimal seed set (Tiusanen et al., 2016 ) and S. acaulis is a plant with a particularly high demand for pollen transport services: S. acaulis is gynodioecious, with some plants being hermaphrodites and others female only (Kevan, 1972 Shykoff, 1992 ). Thus, in S. acaulis, we used female-only plants with an obligate need for pollinators to score whether they got successfully pollinated or not. For this purpose, we targeted a subset of study sites with sufficient abundances (>500 flowers per site) of these flowering species (14 and 10 sites for Dryas and S. acaulis, respectively). To keep track of spatiotemporal variation in the seed production, we marked 10 flowers per species (female-only individuals of S. acaulis) at each targeted site each week. All the marked flowers were recently opened (no more than 24 hr old). During the first visit to the study sites, we also found Dryas flowers, which were already senescent (at 14 of the sites) and withered (at 13 of the sites). At each of these sites, we marked 10 old and 10 withered flowers (in addition to freshly opened flowers). Reflecting the average flowering time of Dryas (M. Tiusanen, personal observation, June–July, 2016), we subsequently treated them as if they had first opened 2 or 6 days, respectively, before our visit.

To resolve the effect of pollinator availability on the seed set of Dryas, and to probe for differences in seed set over time, we excluded pollinators from accessing some of the flowers. We did so by covering 10 unopened buds with plastic cups (Iisi, 0.25 L, Nupik International). To minimize the effects of the treatment on temperature and moisture, the bottom of which had been replaced with a mesh (mesh size 0.3 mm × 0.3 mm, Yleistylli, pehmeä, Eurokangas). Wherever possible, we chose flowers on the same tussocks as the flowers monitored for seed set in the presence of pollinators. For S. acaulis, we relied on the self-sterility of the female-only individuals targeted (see above). Seed set by such individuals reflects successful pollen transport from another individual. Given the spatial distribution of plants in the study system, it will almost invariably require an insect vector.

At the end of the season, we investigated seed set success of Dryas and S. acaulis (i.e., whether the flower had produced seeds or not) of the marked flowers, and—for Dryas—of the flowers from which pollinators had been excluded.

2.6 Statistical methods

2.6.1 Relative phenology of flowering species

To describe phenological patterns in the flowering of different plant species, we calculated the mean date of flowering for each of the flowering species at each of the study sites as the mean occurrence of open flowers , expressed as day of year, DOY. The overall DOY of the mean flowering of a plant species was calculated as the average of all the site-specific values.

To examine how the relative timing of flowering in other plant species along the elevational gradient, we fitted generalized linear models (GLMs) in R (The R Core Team, 2016 ) to phenological data. Since Dryas emerged as the most attractive species (see Section 3) we used the difference of the date of mean flowering between Dryas and the focal species (C. tetragona, P. radicatum, S. arctica, S. oppositifolia, or S. acaulis) as the response variable and elevation as an explanatory variable. Sites with observations of a species flowering only on 1 day were excluded from the species-specific analyses, as offering records with disproportionately low precision.

Notably, the key interest here relates to the interaction “plant species” × “overall annual phenology.” A significant interaction will reveal differential responses in different species, and the slope estimates will indicate the extent to which flowering in different species gets compressed or spread aside by variation in the relative earliness of the year. In other words, the interaction will quantify the impact of climate on the overlap in timing among competing species. To account for environmental variation causing site-to-site differences in flowering time, we used study plot as a random effect. The model was fitted with package lme4 (Bates et al., 2017 ) in R (The R Core Team, 2016 ).

To further examine the potential for competition between the plant species, we characterized the site-specific temporal niche overlap in flowering between Dryas and other species with Schoener's index (SI, Schoener, 1970 ). , where pxi and pyi are the normalized flower abundances of species x and y on day i, respectively (SI gets values between 0 and 1, with higher values indicating larger overlap). To test for a change in niche overlap with Dryas along the elevation gradient, we modeled the SI between Dryas and the focal taxon (C. tetragona, P. radicatum, S. arctica, S. oppositifolia, S. acaulis or the average of SI of all species) as a function of elevation. These GLMs were fitted in R (The R Core Team, 2016 ). Sites with observations of a species flowering only on one day were excluded from the species-specific analyses, as offering records with disproportionately low precision.

2.6.2 Visitation rate as a function of flower densities

If with more flowers of the most attractive species (Dryas), there would be no signs of less visitors per flower, then one might hardly argue that pollinators in this system are in limited supply. Therefore, we tested whether intensified competition with increasing flower densities was evident as reduced visits per flower, focusing on the most highly visited plant, Dryas. To account for a high number of zero observations, we fitted a hurdle model to the counts of flower visitors as a function of Dryas flower abundance on the respective study plot. The number of Dryas flowers was used as an offset in the model. For the count model, we assumed a Poisson distribution and a log-link function, and for the zero model we used a binomial distribution with a logit-link function. The model was fitted with package pscl (Jackman et al., 2017 ) in R (The R Core Team, 2016 ).

2.6.3 Pollen transport by flies

Since Dryas attracted the vast majority of flower visits (Figure 1), we chose to focus on the effect of Dryas flower densities on the transport of conspecific and heterospecific pollen. These analyses were focused on S. acaulis, as the species with the highest level of co-occurrence of pollen with Dryas in space (across sites) and time. For other plant species, the overall incidence of pollen transport by muscids proved too low and/or spatiotemporal co-occurrence with Dryas too scarce to allow meaningful analyses (see Figure 1 for a visual representation of the dominance of Dryas). To test whether high densities of Dryas flowers affect pollen transport by muscid flies, we modeled fly transport of Dryas and S. acaulis pollen, respectively, by generalized linear mixed effect models (GLMMs) fitted separately to data on each plant species. The presence or absence (1/0) of Dryas pollen on individual flies (one observation per fly) was modeled as a function of the day- and site-specific abundance of Dryas flowers and S. acaulis flowers on the study sites (treated as continuous, fixed effects the model was fitted for the presence or absence of the pollen instead of actual pollen counts to avoid overdispersion). The flower abundances on specific DOYs were acquired from field observations (see above) or—where the abundance was not recorded on the specific date—by linearly interpolating missing values between observed ones.

To capture competition of a form where increasing abundances of flowers of a species results in a decreasing probability of flies carrying heterospecific pollen (as a sign of competition for pollinators), we included the interaction between Dryas and S. acaulis flower abundances. Because the effect of the local flower abundance on pollen loads carried by flower visitors can be expected to saturate (a flower visitor cannot carry an unlimited amount of pollen or visit all the flowers), flower abundances were log10(n + 1)-transformed. To account for site-to-site differences in pollen loads, we included study site as a random effect. Since the dependent variable was a proportion of events, we assumed a logit-link function and binomially distributed errors. The presence or absence (1/0) of S. acaulis pollen was then modeled by an equivalent GLMM. The models were fitted package lme4 (Bates et al., 2017 ) in R (The R Core Team, 2016 ). Because monitoring of study sites V, W, and X (see Figure S1) did not start from the beginning of the season, they were excluded from the analyses.

2.6.4 Seed set by inflorescences

To resolve temporal patterns in seed set, we used GLMMs of the fraction of Dryas and S. acaulis inflorescences, respectively, producing seeds as a function of DOY. Because Dryas attracts a majority of flower visits, high densities of Dryas could potentially reduce the seed set of other flowers. Therefore, we also modeled the seed sets of Dryas and S. acaulis as a function of the local abundance of open Dryas flowers on the study site. The Dryas abundances on specific DOYs were acquired from field observations or—where the abundance was not recorded on the specific date—by linearly interpolating missing values between observed ones. To account for environmental variation causing site-to-site differences in average seed set, we included study site as a random effect. To clarify the role of pollinators on the seed set of Dryas and to test for experimental artifacts induced by seasonal changes in seed set unrelated to pollinators, we modeled the fraction of inflorescences producing seeds as a function of the exclusion treatment, DOY, and their interaction. To account for environmental variation causing site-to-site differences in average seed set, we included study site as a random effect. The models were fitted package lme4 (Bates et al., 2017 ) in R (The R Core Team, 2016 ). Because the dependent variable was a proportion of events, we assumed a logit-link function and binomially distributed errors.


High Temperature Stress in Plants

In this article we will discuss about High Temperature Stress in Plants. After reading this article you will learn about: 1. Subject-Matter of High Temperature Stress 2. Effects of High Temperature Stress.

Subject-Matter of High Temperature Stress:

All the living organisms, either plants or animals, are adapted to grow within a narrow range of temperature limits. Temperatures within the range influence metabolism by its effect on chemical reactions, which are catalysed by enzymes.

A slight increase in temperature even for a short duration, may affect the physiological and biochemical processes of plants. At extremely high temperature beyond the limit of survival life is destroyed by losing control on chemical reactions, proteins undergo denaturation along with physical changes detrimental to the organism.

Effects of High Temperature Stress:

i. Cellular Organisms:

High temperature stress adversely affects every physiological activity or metabolic process in plants. Land plants have to tolerate an environment of changing temperature, and such changes may diurnal or seasonal. The upper temperature limits at which the different organisms may grow and survive have been found to vary considerably.

A simple organism like heterotrophic bacteria can grow at 110°C, while photosynthetic bacteria are not found above 73°C and eukaryotes are able to live above 60°C. Although higher plants cannot withstand a temperature above 50°C for a long time, there are some flowering plants like cactus plants which can survive for quite some time at 55°C (day) and 45°C (night) temperatures.

Km for an enzyme represents the concentration of substrate required to half-saturate the enzyme. The value of Km indicates enzyme-substrate affinity. A higher Km reflects lower affinity of the enzyme for substrate. Conversely, a lower Km reflects higher affinity of the enzyme for substrate.

The temperature has large effects on enzyme-substrate affinities as shown by Km variations. This is because the specific shape of the active site is stabilized by temperature-sensitive interactions within enzyme protein, which in turn influence the attraction between enzyme and substrate.

Catalytic efficiency of an enzyme rises with increase of Vmax but falls with increase of Km and the ratio Vmax/Km is a measure of catalytic activity. At high temperatures within physiological limits, Vmax will rise and Km will decrease leading to increased activity. But at still higher temperatures, proteins will be denatured with loss in catalytic activity.

iii. Photosynthesis:

Photosynthesis represents an integration of photochemical as well as biochemical processes.

Thus, temperature will have a direct impact on photosynthesis through its effects on temperature- sensitive biochemical and physiological processes. It has been observed that exposure of leaves to elevated temperature (35 – 50°C) in the biologically relevant range, CO2 assimilation, O2 evolution and photophosphorylation are generally inhibited.

Chloroplast activities associated with thylakoids appear to be more heat-sensitive than those of the stroma, and PS II is the most heat-labile component of thylakoid membranes. Inactivation of PS II by high temperature is associated with denaturation of PS II polypeptides and the inhibition of the oxygen-evolving complex as a result of release of Mn 2+ ions.

It is to be noted that in contrast to PS II components, which are less stable to high temperature, PS I components are more thermos-table. Chloroplast biogenesis has been shown to be affected when plants are grown at high temperature. Chlorophyll content also declines and the leaf senescence process begins.

Photophosphorylation is one process that is inhibited by high temperature owing to thermal uncoupling. This will result in a decrease in the supply of ATP necessary for carbon assimilation.

In addition, damage to PS II at the level of O2 evolving complex or the destabilization of the light- harvesting chlorophyll binding complex (LHCP) associated with PS II will lead to the reduced supply of NADPH concerned in CO2 fixation as well as will result in decreased efficiency of the thioredoxin system responsible for the light activation of key enzymes of the Calvin cycle including Rubisco.

It has also been suggested that the decline in Rubisco activation may be due to an inhibition of Rubiscoactivase.

iv. Ultra-Structural :

The ultra-structures of cells undergo considerable changes when exposed to high temperature stress. It is generally observed that the cellular activities are always separated from outside environment by suitable barriers represented by membranes which very often lead to the formation of cellular compartments.

Heat stress has also been reported to cause prominent ultra-structural changes in nucleus, mitochondria, endoplasmic reticulum and plastids. In secretory cells of barley aleurone, amylase translation process is arrested by dissociation of lamellar structure.

During heat stress, fatty acids comprising the membrane lipids shift from long-chain unsaturated to short-chain saturated ones. It is possibly an adaptive change by which membrane with decreased level of fluidity is formed through a conversion of unsaturated to saturated state that will be able to maintain membrane integrity at high temperature.

v. Metabolism (Thermogenesis):

Several species belonging to family Araceae show a special kind of respiration that is cyanide resist ant and thermo-genic. These species have been found to heat their tissues much above the surrounding temperature. In this case, heat is produced by cyanide-resistant respiration in mitochondria of thermo-genic tissues of the inflorescence of such aroids.

The phosphorylation site of cyanide- resistant respiration is either one (in case of NAD-linked substrate) or zero (in case of succinate) in contrast to three present in normal, cyanide-sensitive respiratory chain. Since energy conservation is less, the tissue produces much waste heat as the energy that is not conserved as ATP.

The response to high temperature or heat shock is one of the very well-known environmental responses at the molecular level. When seedlings are shifted to temperatures five or more degrees above optimal growing temperature, synthesis of most normal proteins and mRNAs is repressed, and transcription and translation of a small set of “heat-shock proteins” (HSPs) is initiated. This was first discovered in Drosophila.

Several classes of HSPs have been described in eukaryotes including plants. They are designated by their approximate molecular weight in kDa as HSP 110, HSP 90, HSP 70, HSP 60 and low molecular weight (LMW) HSPs (15 – 20 kDa). In addition, ubiquitin is also referred to as an HSP because its synthesis increases during heat stress.

Ubiquitin is a highly conserved protein composed of 76 amino acids and conjugation of ubiquitin to various acceptor proteins in eukaryotic cells regulates a number of cellular processes. Ubiquitin has protease activity and it helps in removal of denatured or non-functional proteins. Thus, it prevents the accumulation of such proteins to toxic levels and recycles them as peptides or amino acids.

Heat-shock proteins have potential role in plant protection from high temperature stress. It is possible that HSPs contribute to an organism’s ability to survive at high temperature. The principal role of HSPs involves stabilization of proteins in a particular state of folding.

Through this mechanism, HSP 90, HSP 70 and HSP 60 facilitate many processes like protein folding, transport of proteins across membranes, assembly of oligomeric proteins, and modulation of receptor activities.

All these functions require alteration or maintenance of specific polypeptide conformations. Based on these activities, HSP 90, HSP 70 and HSP 60 have been termed “molecular chaperones”or “polypeptide chain binding proteins”.


Affiliations

Scotland’s Rural College (SRUC), Kings Buildings, West Mains Road, Edinburgh, EH9 3JG, UK

Chin Jian Yang, Wayne Powell & Ian Mackay

The James Hutton Institute, Invergowrie, Dundee, DD2 5DA, UK

Joanne Russell, Luke Ramsay & William Thomas

IMplant Consultancy Ltd., Chelmsford, UK

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Contributions

W.P. and I.M. proposed the research idea. C.J.Y. performed the data analysis. J.R., L.R., and W.T. provided the marker data. C.J.Y., W.P., and I.M. wrote and revised the manuscript. All authors read and approved the manuscript.

Corresponding author


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DISCUSSION

Both non-diapausing and diapausing females clearly avoided UV (Fig. 2C,D, Fig. 3). In contrast, only non-diapausing females were clearly attracted to VIS (Fig. 2E, Fig. 3). Our study is the first to investigate the negative and positive photo-orientation responses of terrestrial arthropods to UV and VIS in the same experimental system. Storz and Paul (Storz and Paul, 1998) showed similar opposite responses to UV and VIS in the water flea Daphnia magna (an aquatic arthropod), and suggested that the distribution of UV and VIS in different water layers was one of the factors that controlled the vertical position of D. magna in water.

Action spectra for photo-orientation responses of Tetranychus urticae. The spectra are shown as relative sensitivities plotted against λmax of the LEDs. The sensitivity to red light is set as zero. Sensitivities (symbols with 95% fiducial intervals) were obtained by probit analysis of localization data used in Fig. 3. Although non-diapausing females showed very high sensitivity to UV-B (Fig. 3), the value is shown in parentheses because of difficulties in calculating the fiducial interval.

Action spectra for photo-orientation responses of Tetranychus urticae. The spectra are shown as relative sensitivities plotted against λmax of the LEDs. The sensitivity to red light is set as zero. Sensitivities (symbols with 95% fiducial intervals) were obtained by probit analysis of localization data used in Fig. 3. Although non-diapausing females showed very high sensitivity to UV-B (Fig. 3), the value is shown in parentheses because of difficulties in calculating the fiducial interval.

Plant leaves filter out UV from sunlight before it reaches the chloroplasts, while at the same time passing some photosynthetically active radiation (PAR 400–700 nm), which almost overlaps the range of wavelengths in VIS (Caldwell et al., 1983). Less than 5% of UV is reflected by the upper surface of a typical leaf, whereas 75 to 95% is absorbed by the epidermis, and the rest by the mesophyll, leading to little or no transmittance of UV through the leaf (Caldwell et al., 1983). Between 85 and 90% of PAR is absorbed by the leaf the rest (particularly green light) is either reflected at the leaf's upper surface or is transmitted through the leaf (Smith, 1986). Because non-diapausing T. urticae females were sensitive to UV in particular as well as to green light (Fig. 4), they may be able to sense differences in the distributions of these wavelengths between the two sides of a leaf and use them as a cue to locate the undersurface of the leaf, like the vertical positioning of D. magna (Storz and Paul, 1998). If non-diapausing females only avoid UV, it would be difficult for them to find the undersurface of leaves, and they might move into dark sites with increased risk of starvation. If mites were only attracted to VIS, they would have a high risk of UV damage (Barcelo, 1981 Ohtsuka and Osakabe, 2009 Sakai and Osakabe, 2010 Suzuki et al., 2009). Therefore, non-diapausing females need both UV avoidance and VIS attraction to successfully locate the undersurface of leaves.

Surprisingly, however, diapausing females showed no preference for VIS (Fig. 2F, Fig. 3). To our knowledge, ours is the first report of a lack of response to specific wavelengths during diapause. Although Hussey and Parr (Hussey and Parr, 1963) showed light avoidance in diapausing females of T. urticae, the light source (which they did not describe) would have included some UV if they used sunlight or fluorescent tubes thus, avoidance of UV would have been induced, as we observed here (Fig. 2D). Mori (Mori, 1962) showed that T. urticae females collected in late October (autumn) were less sensitive to light than those collected in summer in Sapporo, Japan (43°N). Although it is unclear whether the less sensitive females were true diapause forms, the result is comparable to the lack of response to VIS by our diapausing females (Fig. 2F), because Mori passed light from an incandescent bulb through a water bath and frosted glass, which would result in VIS alone. However, Mori did not take the result further to consider the winter habitat selection of T. urticae. Diapausing females overwinter in dark hibernacula (Veerman, 1985), which probably offer a refuge from UV as well thus, avoidance of UV is also an adaptive response for diapausing females. Moreover, if diapausing females were attracted to VIS, as in the case of non-diapausing females, they would risk exposure to the abundant UV in leafless trees in winter. Furthermore, a lack of preference for VIS may save energy that can be used to maintain the photoreceptors during diapause. Therefore, the absence of attraction to VIS is also a reasonable adaptation for diapausing females.

The mites showed much higher sensitivity to UV than to VIS (Fig. 4), as did D. magna (Storz and Paul, 1998). This difference and the lack of preference for VIS during diapause suggest that T. urticae has at least two types of photoreceptors. This mite has adjacent pairs of anterior and posterior eyes, on each side of the propodosoma (McEnroe, 1969 Mills, 1974), and both sets of eyes act as photoreceptors (Suski and Naegele, 1963b). McEnroe and Dronka (McEnroe and Dronka, 1969) suggested that the anterior eyes have photoreceptors for UV and VIS but the posterior eyes have photoreceptors only for UV. The hypothesis that photoreceptors for UV and VIS are independent was also proposed on the basis of electroretinogram analyses of the eyes of spiders (DeVoe, 1967) and scorpions (Machan, 1968).

In animals, the VIS-sensitive molecule rhodopsin and its relatives consist of an opsin and the chromophore retinal (Terakita, 2005). β-carotene, which is the precursor of retinal, is essential for the photoreception involved in the photoperiodic induction of diapause in the predacious mite Amblyseius potentillae (Van Zon et al., 1981), suggesting that opsin-based photoreceptors also function in mites. Diapausing T. urticae females feed only a little (Veerman, 1985), so the intake of plant carotenoids (e.g. β-carotene) likely decreases. Moreover, hydroxy-keto-carotenoids, which are not found in leaves but are converted from β-carotene, are present in greater quantities in diapausing females than in non-diapausing females, possibly because of the dissolution of these carotenoids in lipids or the lipid moiety of lipoproteins, which are present in increased amount in diapausing females, and consequently the mite's body is orange during diapause (Veerman, 1985) (see inset in Fig. 2). These facts suggest that β-carotene is insufficiently converted into retinal for use in opsin-based photoreceptors in diapausing females, which therefore become blind to VIS. However, sensitivity to UV was preserved even during diapause (Fig. 2D, Figs 3, 4), thus UV photoreceptors might be a non-opsin-based type such as cryptochrome, which is sensitive to short wavelengths, possesses the flavin chromophore, and acts as a photoreceptor in the circadian clock of plants and animals (Cashmore et al., 1999).

Further investigations will be needed to verify the hypotheses that non-diapausing females discriminate between the two sides of a leaf by sensing spatial differences in the distribution of UV and VIS that diapausing females select dark hibernacula by sensing spatial differences in the distribution of UV that T. urticae has independent UV and VIS photoreceptors and that the VIS photoreceptor ceases to function during diapause, probably owing to insufficient conversion of β-carotene to retinal. We anticipate that our findings will provide a basis for examining the role of light in the mites' habitat selection and the effect of seasonal changes in carotenoid metabolism on the photoreception systems.

Furthermore, T. urticae is a hard-to-control agricultural pest because of the rapid development of pesticide resistance. Our findings may contribute to the development of a lighting method that disturbs its behaviour using artificial light sources or reflective materials. To incorporate the lighting method into integrated pest management, further investigations of the photo-orientation behaviour of natural enemies will be needed. Interestingly, the predatory mite Typhlodromalus aripo hides in the apex of cassava during the day and emerges at night to forage for the herbivorous mite Mononychellus tanajoa on young leaves (Onzo et al., 2003 Onzo et al., 2009). Hiding in the apex during the day protects T. aripo against the deleterious effects of UV (Onzo et al., 2010). Therefore, providing UV cut-off materials to shelter UV-susceptible natural enemies may reinforce biological control measures.

This paper focuses exclusively on the seasonal change of photo-orientation responses of mites. Our results suggest that the mites compare the light intensities before and after they cross the boundary between light and dark patches because they cannot detect the direction of light in the horizontal plane with only overhead illumination. The abrupt self-steered turn triggered by the onset or cessation of light cues is likely to be the same response seen in klinokinesis and klinotaxis (Kennedy, 1978). Further path analysis (to be published elsewhere) will help to reveal the photo-orientation mechanisms causing localization of the mites under illumination.


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