Acknowledgements
A great number of people contributed to this final work, and to let their contributions go without mentioning would be unthinkable.
Firstly, I cannot express how much I owe to my Supervisor, Dr. João Tereso. Not only was he extremely supportive of my pursuit of this theme, he was a constant presence throughout my whole thesis, providing valuable input whenever requested, guidance where necessary and much silliness whenever the mood needed lightening. I could truly not ask for a better supervisor, and would do it all over again if given the chance. To my Co-supervisor, Dr. Rubim Almeida I also owe a great deal. His classes on plant biology and taxonomy were quite decisive in determining my choice of scientifical area, and even today I look back on them fondly. It was also he who introduced me to my supervisor and in this sense was the driving force that ultimately led to this thesis. To Cláudia Oliveira, Cristiana Maia and Paula Portela I also have to give my thanks. It was thanks to their earnest enthusiasm and mostly to a quiet informal chat one lazy summer afternoon that I chose this course at all. Without their input I might have ended up in a completely different course altogether. Remember, if it weren’t for you I might well be stuck in a molecular sciences laboratory somewhere!
To my colleagues in the MEAT, who interspersed these last two years with moments of fun, camaraderie and madness. We could have been strangers, instead we were comrades, brothers-in-arms, Tasqueiros. Thanks to you all.
I extend my thanks to those that had the willingness and patience to accompany and assist me on my field trips. Ana Luísa Ramos, Cláudia Oliveira, Filipe Vaz, João Tereso, Juliana Monteiro, Paula Portela. There was hard and sometimes difficult work but also very good moments and I am only sorry that we couldn’t have gone out more often.
A number of people also provided helpful input, in particular Dr. José Pissarra who gratiously provided practical advice as well as a borer for use in field work and Carlos Vila-Viçosa who provided input on sampling points. To them I am grateful also. To those above and also to Ana Jesus, Cristiana Vieira, Ginevra Coradeschi , Helena Hespanhol, Joana Marques, Luís Carlos Seabra, Maria Martín-Seijo, Valentina Bellavia and all others who contributed to a good work environment and provided fond
memories of the last two years. No matter where we are we will always be the group from lab 1.36.
Ana Luísa Ramos, you were a great companion and a valuable friend throughout all of this. Even if the vicissitudes of life meant that we weren’t together as much in these last months, you never ceased to be supportive and present whenever needed and I shall never forget that.
Cláudia Oliveira, your input and advice contributed a good deal to this thesis and our chats about various and diverse subjects, ranging from the taxonomy of “higher” plants to XX century history, or computer memory hierarchy always managed to cheer up even the gloomiest of days. I am truly thankful for everything.
To my mother Conceição and father Carlos, for raising me and helping me these long years, and providing me with an environment where I was free to explore and inquire, and for supporting my choice to become a scientist. I love you dearly.
To my brother Rodrigo and my sister Priscila, for putting up with me and my (often) incoherent babbling about some scientifical subject or other. You are both extremely annoying. I love you.
To Patrícia Martins, missing in action in faraway Britain, but never more distant than a keyboard stroke. Although in all likelihood you will not be able to attend this thesis defence, know that I consider you to be there in spirit. I hope we can be together again soon.
Ana Maria de Melo and Pedro Emanuel da Silva. What can I say. You two are the best Friends I could have ever had and your companionship over the last 24 years has been a blessing. Thank you for your friendship, support, patience, affection and mostly, for being the wonderful people that you are. This thesis is dedicated to you both. Let’s spend many more decades exploring this wonderful world!
Abstract
The wood of the Maloideae has long frustrated those that attempted to study it anatomically. Previous literature has been inconsistent in its treatment of the group, particularly as to the level of identification possible. In this work we perform a wide survey of the wood of three common Portuguese Maloideae: Crataegus monogyna,
Pyrus cordata and Pyrus bourgaeana. They are compared in terms of commonly used
wood anatomical characters in order to determine if an identification using these characters is indeed possible. We conclude that using only these traditional characters, it is not possible to distinguish the wood of these three species from one another. Furthermore, we compared the obtained anatomical characters with the growing environment of our specimens. A few expected and unexpected trends appeared. Notably, we report the appearance of scalariform perforation plates on some individuals of Pyrus cordata, a character that to our knowledge was previously undescribed for this species. We also conclude that enough data has been collected to suggest that ray-size might be a good indicator of environmental conditions, at least in
this group.
Keywords: Wood anatomy, Maloideae, Ecological gradients
Resumo
A anatomia da madeira das Maloideae há muito que é um tema de estudo frustrante. A literatura existente trata a anatomia das Maloideae de forma algo inconsistente no que diz respeito ao nível de detalhe taxonómico que é passível de ser obtido. Neste trabalho executamos uma pesquisa abrangente das madeiras de três espécies de Maloideae: Crataegus monogyna, Pyrus cordata e Pyrus bourgaeana. Comparamos as suas madeiras usando os caracteres anatómicos mais comummente usados de forma a determinar a possibilidade de uma identificação com base neste critério. Concluímos que com base nestes caracteres não é possível distinguir a madeira destas três espécies. Comparámos também os caracteres analisados com as condições ambientais. Assinalámos a presença de placas de perfuração escalariformes em indivíduos de Pyrus cordata, um carácter previamente inédito nesta espécie. Concluímos também que os dados recolhidos são suficientes para sugerir que o tamanho dos raios poderá ser um bom indicador de condições ambientais, pelo menos
neste grupo.
Table of contents
Aknowledgements ··· 4
Abstract ··· 7
Table of contents ··· 9
State of the art ··· 11
Materials and methods ··· 16
Field Sampling ··· 16
Laboratory work – preparation of specimens and slides ··· 18
Laboratory work – observation and analysis of slides ··· 20
Data analyses ··· 25
Results ··· 27
Sampling sites – environmental characteristics ··· 27
Anatomical characteristics of the species ··· 35
Anatomical characteristics and environmental factors··· 46
Discussion ··· 57
Anatomical characters of note ··· 57
Suitability of wood anatomical characters for differentiation between Crataegus monogyna, Pyrus cordata and Pyrus bourgaeana.··· 62
Closing remarks ··· 65 References ··· 67 Annex 01 ··· 72 Annex 02 ··· 79 Annex 03 ··· 81 Annex 04 ··· 83
State of the art
Wood is a biological material, produced by higher plants as a complex interaction of molecular building blocks and microstructural organization. It is a fibrous substance whose main building blocks are lignin polymers, as well as cellulose, hemicellulose and residual amounts of other materials, arranged in the cell walls of the xylem of woody plants (mostly Gymnosperms and Dicotyledons) (Forest products laboratory 1987). These cells are arranged in turn in complex patterns which are mainly responsible for the wide variety of properties exhibited by different types of wood. Wood, taken as a whole, is therefore an extremely versatile raw material, finding use as a construction material (both in structures and in ships), tools, furniture, musical and sports material, as well as fuel both processed and not. Despite having been used as a raw material by
humanity since prehistoric times, wood continues to be in high demand in the 21st
century, in applications where by local absence of technological infrastructure, lack of suitable cost-effective alternatives, or merely by the status it confers see its continued use.
Apart from its uses in manufacture and industry, wood can also be used as a window to the past. While the principle of using tree rings to assess the age of a given tree has been well known since at least the Renaissance, one can also combine this information with other characters present in wood in order to extract past environmental information from a given tree (Schweingruber 1996). One can, for example, track the occurrence of drought years, or unusually harsh winters, or even episodic events such as avalanches by the signatures they leave on tree rings. By cross dating several trees, it is even possible to create a continuous history of a regions climate (Douglass 1941). In recent decades, tree ring research has also aided studies in climate change (Dittmar, Zech & Elling 2003; Di Filippo et al. 2010), and the study of preserved wood remains (waterlogged, charred, desiccated or fossil) has been successfully used in archaeology
in order to help reconstruct past customs, practices and environments (Lev-Yadun
2007; Marguerie & Hunot 2007;Martín Seijo et al. 2011).
Tree rings, however, are at their most visible in regions with temperate climates. In tropical climates, tree rings become fainter due to the lesser degree of seasonal variability, whilst in regions with more extreme climates, tree rings become too narrow to be distinguished without the aid of a microscope (Schweingruber 1996). This means that the main thrust of dendroecological research has so far been primarily on the wood
of temperate regions. Traditionally, studies have focused on sites with either stable precipitation (where most variability is therefore attributable to temperature) or stable temperatures (with variability attributed to precipitation), with studies then proceeding to temperate regions, where growth is affected by both temperature and precipitation (Campbell 1949; Von Jazewitsch 1961; Schweingruber 1996). Wood growth also varies from species to species within the same region (Büntgen et al. 2007). As a result, in cases where wood cannot be primarily ascribed to a species, it is essential to be able to reliably identify the wood to the lowest taxonomical level possible.
In the case of many European woods, existing literature allows a reliable identification down to genus, or even species level (Schweingruber 1990; Vernet et al. 2001; Akkemik & Yaman 2012). Multimedia tools are also available that can assist in the identification of many taxa, such as Delta Intkey (Dallwitz, Paine & Zurcher 1993) or the Inside Wood database (Wheeler 2011), provided that proper diagnosis characters are
on-hand. The science of identifying wood down to a specific taxon relies on the
microscopic observation of three diagnostic sections. These rely on the axial-radial alignment of the xylemic structures in order to allow a clear visualization of wood microstructure. The three sections are: Transverse, Longitudinal Radial and Longitudinal Tangential. If correctly obtained, these allow one to visualize such characters as: size and arrangement of pores, disposition of parenchyma, ray size and composition, presence of helical thickenings and/or crystals, among several others.
Fig. 01 – The three diagnostic sections of wood. From left to right: Transverse (Ficus carica, large pores), Tangential (Pistacia terebinthus, wide rays from head-on), Radial (Pistacia terebinthus, heterogeneous rays in profile).
The significance given to precise numerical measurements of these characters varies:
Both Vernet et al. (2001) and Akkemik & Yaman (2012) make note of pore average
diameter in their descriptions, while Schweingruber (1990) mentions only proportions or
certain plant groups cannot be reliably identified down to a fine level. Family Fabaceae and subfamily Maloideae are two such examples. In these cases, wood variability is so large that a large sampling of individuals would be required in order to reliably ascribe diagnosis characters to species (Schweingruber 1990). This is particularly unfortunate in the case of the Maloideae.
Subfamily Maloideae, of the Family Rosacea, includes a series of economically relevant species. These include: Pyrus communis L. (Pear), Malus domestica (Borkh.) Borkh. (Apple), Cydonia oblonga Mill. (Quince) and Eriobotrya japonica (Thunb.) Lindl. (Loquat). Most of these species have been cultivated since ancient times (4000-3000 BCE) (Janick 2005). Nearly all members of this subfamily are edible, either raw or cooked (e.g. Pyrus, Cydonia), although some are unpalatable and considered famine foods (e.g. Crataegus). Additionally, a wide range of its members are cultivated as ornamentals and fragrants (e.g. Sorbus, Crataegus), and a few for their timber (e.g.
Malus) (Hummer & Janick 2009). Several species play an important ecological role. Therefore, it is considerably unfortunate that the wood of these species is generally considered undistinguishable according to the current state-of-the-art.
The taxon has undergone a number of revisions in recent times, thanks to the widespread availability of molecular typing methods that has allowed a more
phylogenetic approach to this group’s classification (Potter et al. 2007; Hummer &
Janick 2009). Most revisions group members of subfamily Spiraeoideae closely with members of this taxon. In the work by Potter et al. (2007), subtribe Pyrinae is made part of subfamily Spiraeoideae (Amygdaloideae as of 2011), and now corresponds to former subfamily Maloideae, now also including the former Prunoideae. However, since wood science still mostly follows the Maloideae as a subfamily, in part due to it mapping nicely to economically important species, we shall be using the subfamily such as defined by Schulze-Menz (Engler & Melchior 1967) in this work.
In a preliminary exploration of which characters would be most helpful in a putative attempt to distinguish between wood of members of subfamily Maloideae, as well as of those that would be most affected by environmental factors, a large sampling was taken of three members of this taxon: Crataegus monogyna, Pyrus cordata and Pyrus
bourgaeana. These species were selected on the basis of their ease of identification in
the field, and their widespread nature, both in geography and in the environment.
According to Akkemik & Yaman (2012) members of eastern mediterranean Maloideae can be distinguished by their simple perforation plates, possessing fibres with distinctively bordered pits, exclusively solitary pores, and rays between 1-3 cells wide. They further suggest that Crataegus can be distinguished from Pyrus by the presence of helical thickenings in the narrow vessels of the former, and libriform fibers in the latter. Vernet et al. (2001) provide a key where Pyrus is distinguished from Crataegus.
Pyrus is characterized as having isolated pores in the latewood 10 to 40 micrometers
wide, as well as narrow heterogeneous rays 1-2 cells wide and up to 20-25 cells high. Its ray-vessel pits are un-bordered. Crataegus is characterized as having latewood pores isolated or in groups of two, 15-60 micrometers wide, with homogeneous or heterogeneous rays 1-4 cells wide and up to 35 cells high. They do however, add the caveat that distinguishing between Maloideae is difficult. Schweingruber (1999) notes the Maloideae as being distinguished by their relatively small, isolated and regularly distributed pores, thick walled fibres, and homogeneous to slightly heterogeneous rays 1-4 cells wide and averaging 15 cells in height. Both Vernet et al. and Schweingruber note no libriform fibers in their studied species of Maloideae. It should be noted that the studied species of Crataegus and Pyrus varied between authors and may in part justify discrepancies in these works (Table 01).
Table 01 – Maloideae species mentioned in the anatomical studies cited. *Malus communis in the original source.
Anatomical atlas: Species of Maloideae mentioned:
Akkemik & Yaman (2012) Crataegus aronia (L.) Bosc. ex. DC.; Crataegus
monogyna Jacq.; Pyrus serikensis Güner & Duman; Pyrus syriaca Boiss.; Sorbus torminalis (L.) Crantz.
Vernet et al. (2001) Amelanchier ovalis Medik. ; Crataegus sp.; Cotoneaster
nebrodensis (Guss.) C.Koch; Cotoneaster tomentosus
Lindl.; Cotoneaster integerrimus Medik.; Cotoneaster
vulgaris Lindl.; Pyrus amygdalus Vill.; Pyrus communis
L.; Sorbus aria (L.) Crantz; S.domestica L.; S.torminalis (L.) Crantz; S.aucuparia L.; Malus domestica Borkh*
Schweingruber (1999) Amelanchier ovalis Medik.; Cotoneaster granatensis
Boiss; Cotoneaster integerrimus Medik. ; Cotoneaster
nebrodensis (Guss.) C.Koch; Cotoneaster nummularia
Fischer & C.A. Meyer; Crataegus calycina Peterm.;
Crataegus laciniata Ucria ;Crataegus monogyna Jacq.; Crataegus pycnoloba Boiss. & Heldr. ; Cydonia oblonga
Miller; Eriobotrya japonica (Thunb.) Lindley; Malus
domestica Borkh.; Malus sylvestris Miller; Mespilus germanica L.; Pyracantha coccinea M.J. Roemer; Pyrus amygdaliformis Vill. ; Pyrus communis L.; Pyrus pyraster Burgsd.; Sorbus aria (L.) Crantz; S. aucuparia
It is the objective of this work to attempt to exhaustively characterise the wood anatomy of three Portuguese Maloideae: Crataegus monogyna, Pyrus cordata, and Pyrus
bourgaeana. It will then attempt to discern which differences (if any) between
anatomical characters can be ascribed to the plants taxon, and which are mainly ascribed to environmental factors. It is hoped such a study will provide a solid basis for discussion on the status of wood identification and interpretation in subfamily Maloideae.
Fig. 02 – From left to right: Crataegus monogyna, Pyrus cordata, Pyrus bourgaeana.
Materials and methods
Field Sampling
In order to retrieve sufficient material to permit a study of the different ecological trends, it was decided to do the widest sampling possible within the temporal and budgetary constraints available. The species in this study were selected partially due to their presence in a wide array of environments as well as for their general ease of field identification and their widespread occurrence. C. monogyna, P. bourgaeana and P.
cordata are all found in forest margins, in a wide variety of soils (Castroviejo
1986-2012), simplifying their search in the field
.
As a starting point, the herbarium of theUniversity of Porto (PO) and the herbarium of the University of Trás-os-montes e Alto Douro (HVR) were parsed in search of previously collected specimens to which geographical data could be ascribed. After eliminating those specimens whose
geographical data was exceedingly poor, 22 usable points were found for C. monogyna, 12 for P. bourgaeana and 9 for P. cordata. In addition to these, two points were added for P. bourgaeana and one for P. cordata by referencing the Biodiversity4all database. The coordinates for 6 additional P. bourgaeana points were courtesy of Carlos Vila-Viçosa, who obtained them in the course of his post-graduate work. In all, 52 points were identified for sampling. Additional areas of interest, which might yield additional specimens, were identified based on the Flora-on and Anthos databases.
Sampling was carried out in the course of 8 field trips occurring in the period between August 7 and November 7, 2015. Trees identified in the field were assigned a specimen code, had their GPS coordinates marked, some basic local environmental data noted, and core and wood samples extracted. A total of 120 points were sampled, spread across continental Portugal. 32 of these points fell within the Atlantic
biogeographical region and 88 in the Mediterranean region. (European Environment
Agency 2016). There was a northernly bias to the sampling effort, due both to the proximity to the University of Porto and the available geographical information in planning field excursions. The precise location of each point can be found in Fig. 06 and annex 01.
Some environmental data was retrieved in the field by empirical observation concurrently with the sampling effort: Sampling point altitude, Shade density (Three classes), Light direction (Four classes), Soil abundance (Three classes) and Terrain slope (Three classes). Estimated tree height was also recorded.
Table 02 – Environmental characters registered at the sampling location.
Variable Classes
Altitude a.s.l. (meters) Quantitative
Shade Full sun, partial shade, full
shade
Light direction North, East, South, West
Soil abundance Residual, Sparse, Abundant
Terrain slope Negligible, moderate, high.
Height (meters) Quantitative
Core samples were taken using a Haglöf 4.3x400mm two-threaded Pressler increment borer, with the sample extracted at chest height whenever possible, and at the highest practical accessible point whenever not. The drill bit was removed once the borer
reached the midway point of the trees diameter and the extracted core transferred to a polypropylene straight drinking straw for safekeeping. For larger core samples, two straws were taped end-to-end.
Wood samples were removed by selecting an adequately sized (more than 5 cm in diameter) main branch, and extracting an approximately 50mm long section from the branch. The specimen code was recorded on the sample and a botanical sample was taken from the plant for addition to the Herbarium of the University of Porto. These were taken to serve as vouchers for the specimens so that their identification could be authenticated by later researchers.
As a result of these field sampling expeditions, 120 specimens were retrieved for this dissertation. These 120 specimens comprised: 58 C. monogyna, 24 P. bourgaeana, 21
P. cordata, 7 P. communis and 10 Pyrus sp.. The decision to take samples from P. communis was made in the field due to its relative abundance and the contrast it would
provide with non-domesticated Pyrus. All samples of P. communis were either wild or escaped specimens, with the exception of 4 cultivated individuals in Alentejo. The 10
Pyrus sp. samples correspond to individuals who presented neither fruiting structures
nor their remains, and whose leaves were too intermediate in character to reliably ascribe to any of the Portuguese Pyrus species. A list of sampled individuals and their geographical coordinates is available in annex 01.
Laboratory work – preparation of specimens and slides
The extracted wood samples were left to air-dry until they reached moisture equilibrium with the atmosphere. This method was preferred to kiln drying, both due to its allowing of a slower drying (minimizing radial deformation), and to the lack of a kiln at the storage and analysis area, which would severely complicate the logistics of one’s use. Larger and moister samples, where it was felt air drying would be too slow or leave them at risk of fungal attack, were instead immersed in 96% alcohol and left to dry. Alcohol replaces the water inside xylem cells and cell walls, and upon evaporation causes less deformation upon the wood samples, due to its weaker polarity, and
therefore swell ability, when compared to water (Stamm 1935). The immersion and
saturation of the wood using PEG 1500 (Polyethyleneglycol) was considered (Mitchell 1972), both to prevent deformation and to stabilize the wood during later microtome
sectioning, but was ultimately rejected, due to the large number of steps required, increasing both time and effort required for each sample. Linseed oil was applied to the exposed surfaces of the dried wood samples to reduce re-hydration while they waited further processing.
Once adequately dried, each sample was processed from its raw state into a rectangular cuboid with dimensions 20x20x40mm. The faces of these cuboids were oriented such as to coincide with the three diagnostic sections of wood anatomy. The cuboid dimensions were sufficient to obtain adequately sized slices from a microtome, with a healthy margin of error, while being small enough to unobtrusively store in the space available in the herbarium of the University of Porto. Unprocessed samples were mounted on a 75mm forged steel vise, and cutting planes were carefully marked before being cut close to the reference size with a hacksaw. The cut surfaces were then adjusted by abrasion using aluminium oxide sandpaper with increasingly finer grits, these being in order: p220, p320, p400, p500 and p600. In practice, it was quickly ascertained that only the two coarser grits were necessary to obtain an adequate surface for the microtome, since the microtome’s blade by its own action would polish the cutting surface. However, the surfaces polished up to the finest grit (p600) did present a very high contrast with sufficient detail to visualize anatomical structures when viewed under a stereomicroscope, so it might be worthwhile to pursue finer abrasion when producing show- and educational pieces.
It is intended for these samples to enhance and modernize the wood reference collection (xylarium), at the University of Porto. The size of the cuboids is also sufficient to allow standardised physical tests to be carried out if desired, i.e., specific gravity (UNE 56531), Hygroscopicity (UNE 56532) and volumetric shrinkage (UNE 56533). Non-standardised tests other than bending stress tests could also be carried out on these cuboids (Kasal & Anthony 2004).
Once the cuboids were obtained, they were mounted on an Ulbrecht-Reichert sliding
sledge microtome to obtain 20 m thick wood slices of the tree diagnostic sections. An
initial slice was made to expose fresh wood, and then 3-4 slices were obtained from one of the surfaces, and gently brushed onto a duly identified petri dish. The cuboid was then repositioned on the jig, and the process was repeated. This continued until all three planes were sampled. These then proceeded directly to staining.
The detailed staining protocol can be found in annex 02. In short, samples were stained in Alcian blue and Safranine, then dehydrated and transferred to Xylene before permanent mounting in Canada balsam. After staining, sections were observed under a Nikon SMZ 2 stereomicroscope to evaluate if they had properly taken up the stain and if they had any remaining water. In some cases, quality justifying, duplicates or triplicates were retained. Slides were identified with specimen codes and anatomical section, and stored pending analysis.
Laboratory work – observation and analysis of slides
Slides were imaged under a NIKON Eclipse 50i compound microscope using transmitted light and no special filters. Images were acquired using a Nikon DS-Fi1 digital camera and associated NIS-Elements F image capture software. Images were recorded from the three diagnosis sections. When recording images from the tangential section, care was taken to image the areas where the rays appeared head-on, as opposed to the edges of the slice, where due to the geometry of the wood, they could appear slightly edge-on, distorting measurements.
The images were analyzed using the public domain ImageJ 1.45 (Rasband 1997-2016) software, with select quantitative and qualitative characteristics noted, as presented on table 03. Areas were calculated by the use of threshold functions to select only those areas of interest. Counting of objects was done using the particle analysis function. Distances were measured using the line tool. Aspect ratios, averages, maximums and minimums were obtained by using the inbuilt tools in the measurement command. For all quantitative measurements, a 10x objective was used, corresponding to a 100x total magnification. When taking into account the cameras narrow aperture, this resulted in a
field of view featuring an area of 750000 m2. Qualitative measurements were obtained
Table 03 – Wood anatomical characteristics selected for imaging, and corresponding diagnosis section.* Homogeneous rays are those composed solely of procumbent cells. Heterogeneous type I rays have one row of upright cells in their periphery, Heterogeneous type II rays have interspersed rows of upright and procumbent cells.
Character Description Diagnosis section
evaluated
Number of pores Total number of pores
visible in field.
Transverse
Pore grouping Whether pores are
exclusively solitary, or appear in clusters.
Transverse
Maximum number of pores per cluster
The maximum number of pores observed in a single cluster.
Transverse
Pore cluster orientation Whether pore clusters
are oriented according
to the tangential
direction, radial
direction, or neither.
Transverse
Total number of pore clusters Total number of
clusters visible in field.
Transverse
Total pore area (m2) The sum total of the
area of all pores.
Transverse
Area of smallest pore (m2) Area of the smallest
pore visible
Area of largest pore (m2) Area of the largest pore visible
Transverse
Average pore area (m2) Average area of all
pores.
Transverse
Average pore aspect ratio The average of the ratio
between the long axis and the short axis.
Transverse
Direction of semi-major axis Whether the
semi-major axis has a radial
or a tangential
orientation.
Transverse
Height of tallest ray (m) The height from top cell
to bottom cell of the tallest ray visible.
Tangential
Height of shortest ray (m) The height from top cell
to bottom cell of the shortest ray visible.
Tangential
Average ray height (m) The average height of
all rays visible in field
Tangential
Number of rays/mm2 The total number or
rays visible in the field, divided by field area.
Tangential
Width of widest ray ( No. cells)
The number of cells at the widest point of the widest ray visible.
Width of narrowest ray (No. cells)
The number of cells at the widest point of the narrowest ray visible.
Tangential
Height of tallest ray (No. of cells)
The number of cells
from bottommost to
topmost, in the tallest
ray visible. When
different cell columns would yield different results, the one with the greater number of cells was counted.
Tangential
Height of shortest ray (No. of cells)
The number of cells
from bottommost to
topmost, in the shortest
ray visible. When
different cell columns would yield different results, the one with the greater number of cells was counted.
Tangential
Presence of two distinct ray sizes
Whether the rays
visible form two distinct populations or not.
Tangential
Type of vessel perforations Whether the vessel
perforations observed
were simple,
scalariform, or both.
Ray heterogeneity Whether the rays were
homogeneous or
heterogeneous.
Radial
Presence of crystals Whether crystals of any
type were present.
Radial
Presence of helical
thickenings
Whether helical
thickenings were
present in the xylem
(Excluding primary
xylem)
Radial
The selection of these characters for analysis was based mostly on their use in wood
anatomy atlases to distinguish between different taxa (Schweingruber 1990; Vernet et
al. 2001; Akkemik & Yaman 2012). A few were added due to the ease of their recording (The command that returns the average pore area also allows the return of its maximum and minimum values.) to evaluate their potential to provide relevant information. Although not generally considered a diagnostic character, pore eccentricity data was included since its collection did not add any significant extra effort to the analysis, and a measurement tool was readily available.
Fig. 03 – Crataegus monogyna. From left to right: Transverse section, Tangential section, Radial section.
Fig. 04 – Pyrus cordata. From left to right: Transverse section, Tangential section, Radial section.
Fig. 05 – Pyrus bourgaeana. From left to right: Transverse section, Tangential section, Radial section.
Data analyses
After anatomical data was collected, efforts turned to geospatial analysis. Field coordinates (Taken from GPS using ETRF 89 reference data) were entered into ArcMap 10.2. These were then superposed over environmental data shapefiles obtained from Atlas do Ambiente (Agência Portuguesa do Ambiente 2011). The list of shapefiles used can be found on table 04. For each point, the polygon in each shapefile to which it belonged was obtained, and the data registered.
Table 04 – Shapefiles used for spatial analysis. *Time period information unavailable.
Shapefile
Description
AtAmb_1001111_Insolacao_Cont
Average No. of hours of sunlight
per annum. 1931-1960.
AtAmb_1002111_Temperatura_Cont
Annual average of daily mean air
temperature. 1931-1960.
AtAmb_1003111_RadiacaoSolar_Cont
Solar irradiance. 1938-1970
AtAmb_1009111_EvapotranspiracaoReal_Cont
Real evapotranspiration.*
AtAmb_1013111_CLitologica_Cont
Lithological map.
AtAmb_1041111_Precipitacao_NrDiasAno_Cont Average No. of rain days per
annum. 1931-1960.
AtAmb_1042111_Precipitacao_QuantTotal_Cont Average total annual rainfall.
1931-1961.
AtAmb_1052111_GeadaNrDiasAno_Cont
Average No. of frost days per
annum. 1941-1960.
AtAmb_3001111_CSolos_Cont
Soil map.
Having collected all the data, it was then organized into an Excel spreadsheet (Microsoft Office Excel 14.0) that collated the specimen code, species, Geographical coordinates, anatomical data, site environmental data, and GIS-derived environmental
data. In order to prepare the data for statistical analysis, non-binary quantitative information was transformed using equation 01. The transformed data had values between 0 and 1.
𝑿𝒏 =
𝑿 − 𝑿𝒎𝒊𝒏
𝑿𝒎𝒂𝒙 − 𝑿𝒎𝒊𝒏
Equation 01 – Where X is the value of the individual entries, Xmin and Xmax are the minimum and maximum of the entire value range and Xn is the normalized output of the equation.
In order to search for correlations between the gathered characters, statistical analysis was performed using the past 3.0 free software program (Hammer, Harper & Ryan 2001). Species and sites were entered into the program as group type data, all others as generic data types. Spearman correlation analysis was performed in an attempt to find which characters exhibited a significant taxonomical or environmental signal. Cluster analysis was performed using the neighbor-joining algorithm with a bootstrap value of 10000 to try to understand if the species and/or sites clustered naturally according to the studied characters. A Betula pendula sample analyzed in the same manner as the other species was used to root the dendrogram. Principal component analysis was performed to attempt to visualize any explainable trends in the variance of the data.
Results
Sampling sites – environmental characteristics
A nested percentage table (table 05) summarizes the environmental variables collected
in situ. Not all possible combinations appear in this table since some of these (e.g.
abundant soil in high terrain slope) are far less likely to occur than others. As for the
various classes; 62.5% of the points sampled belonged to the “abundant” soil
abundance class, 60.8% to the “negligible” terrain slope class and 60% to the “full sun” shade class. This is hardly surprising, reflecting better odds of finding the target
vegetation when the site is favorable to plant growth. Somewhat surprisingly, of the trees under some degree of shade, 42.6% belonged to the “North” light direction class, in spite of Portugal’s location in the Northern hemisphere ensuring that southerly facing surfaces receive, a priori, more sunlight. The collected environmental data can be found in annex 03.
Typically, most sampled sites possessed only one of each species under study, although the sites near Portel and Montemor-o-Novo (Évora district, Baixo Alentejo) yielded both Crataegus monogyna and Pyrus bourgaeana, and the site near Miradouro da Boneca (Braga district, Minho) yielded Crataegus monogyna and Pyrus cordata. Over half the sampled C. monogyna came from north of the river Douro, with 26 individuals proceeding from the Minho region, and 6 from the Trás-os-montes region. Of the remainder, 8 individuals came from the Beira Litoral, 5 from the Beira Alta and 13 were sampled in the Alentejo. P. cordata and P. bourgaeana were rather more restricted in their sampling distribution. P. cordata was sampled only once south of the Douro, in Alentejo. P. bourgaeana was sampled in Alentejo almost exclusively, again with a single exception, an individual sampled in Minho. This mutually exclusive distribution was already evident from the distribution data available from various sources (Flora-on: Flora de Portugal Interactiva. 2014; Anthos. Information System of the plants of Spain. 2011; Castroviejo 1986-2012). It was initially hoped that individuals could be collected along the boundaries of these two species’ distribution area, which would have allowed a more precise understanding of the presence of a gradient in their anatomical characters, however poor data on sampling points in this area, together with time constraints prevented this.
Pyrus communis was found almost always in close proximity to P. cordata or P. bourgaeana, and it often exhibited signs of grafting. In the Alentejo region at least,
exchanges with local inhabitants revealed that such grafting is apparently a cultural practice, performed almost as if to “tame” wild pear trees, with the result that the ancestry of some of the trees is potentially problematic. These were nevertheless still included in the final analysis, under the assumption that they would present either environmental or anatomical differences that would make them useful as a control
Table 05 – Nested percentages of qualitative environmental data Full shade 19,17% Abundant 14,17% Moderate 5,83% Negligible 8,33% Residual 1,67% High 1,67% Sparse 3,33% High 0,83% Moderate 0,83% Negligible 1,67% Full sun 60,00% Abundant 30,83% High 0,83% Moderate 2,50% Negligible 27,50% Residual 10,00% High 1,67% Moderate 2,50% Negligible 5,83% Sparse 19,17% High 5,83% Moderate 5,00% Negligible 8,33% Partial shade 20,83% Abundant 17,50% High 2,50% Moderate 6,67% Negligible 8,33% Sparse 3,33% High 1,67% Moderate 0,83% Negligible 0,83% Total 100,00%
A summary of the spatial analysis is provided in figures 07-14. The analysis revealed that 40% of the samples fell within the cambisol soil class, with 77.5% of these being humic cambisols. This could be due to the northernly bias in the sampling effort, Northern Portugal being particularly rich in Humic Cambisols. As an exercise, removing all sites to the north of the Douro river results in 50% of the remaining sites falling into
the Lithosol category
.
As for soil lithology, it was mostly granitic or schistose. Togetherthese two lithologies represented 66.66% of all sites.
The sampling sites fell within three different rainfall categories: 50-75, 75-100 and >100 days, being roughly well represented in all three categories (37.50%, 22.50% and 40.00% respectively), but when taking into account rainfall amount the largest class was actually 600 to 700 mm (with 25%), a rather moderate amount.
The abundance of sampling sites at the extreme values of evapotranspiration decreased sharply, as it likewise did for increasing duration of frost. Again, this is likely a result of the greater abundance of vegetation at the more favorable conditions. A local maximum at frost levels of 20-30 days corresponds to sampling performed in moderately well-conserved mountainous regions, the more frost-free lowlands being under greater anthropic pressure.
Solar radiation was significantly more well represented at the >140 Kcal/cm2 class.
Since northern Portugal is more homogenous in terms of received solar radiation than the south (Agência Portuguesa do Ambiente 2011) this may reflect a sampling bias. Amount of sunlight hours was much more evenly distributed, northern Portugal’s geography allowing a greater amount of variation than the relatively flat Alentejo.
Fig. 07 – Percentage of sites sampled in each Soil class.
Fig. 09 – Percentage of sites sampled in each Total Rainfall class.
Fig. 11 – Percentage of sites sampled in each Frost class.
Fig. 13 – Percentage of sites sampled in each Sunlight class.
Fig. 14 – Percentage of sites sampled in each Temperature class.
Anatomical characteristics of the species
The anatomical characters observed showed some interesting trends. C. monogyna showed less variation than other species for a number of characters, despite having the greatest number of specimens and being sampled across a greater range of sites. Despite being typical of regions with higher levels of rainfall, P. cordata showed a mean average pore area lower than that of P. bourgaeana, a species more typical of areas
0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00% 35.00% 7.5-10 10-12.5 12.5-15 15-16 16-17.5 >17.5 Per ce n t to tal Average temperature; ºC
Temperature
were water stress is a greater concern. This is the opposite of what was expected and might be connected to frost resistance strategies as discussed in the next chapter. A greater occurrence of pore clusters in P. bourgaeana was also noted.
Pore aspect ratio measurements were notably clustered, with the semi major axis tending to be approximately twice the length of the semi minor axis. Outliers could be explained by sections in which the pores were at a degree to the normal. Ray density in P. communis was notably higher than any of the other species. Despite the small sample number, the magnitude of the difference was still notable.
Most of the specimens retrieved showed two distinct types of ray sizes, one tall and narrow, the other short and narrow. This was expected since it is a commonly described anatomical feature of the Maloideae (Schweingruber 1990). Those that did not show two clearly distinct classes did so by having more intermediate sizes of rays that blurred the line between classes, and not due to a lack of short rays.
Much more surprising was the presence of scalariform perforation plates in the vessels of a number of P. cordata specimens (figure 45). Although a small sample, this was completely unexpected since one of the anatomical features of the Maloideae are their simple perforation plates (Schweingruber 1990), and to our knowledge, scalariform plates have not been previously described in a member of this group. The specimens with this character were all sampled from the same site, (Corno de Bico, Viana do Castelo district, Minho) and it might represent an environmental adaption to frost, discussed in the next chapter.
Type I heterogeneous rays were the most common ray type. Type II and homogenous rays were less frequent but nonetheless present, and Type III heterogeneous were completely absent (as expected). Prismatic crystals were present in about a quarter of the samples, but relative proportions varied greatly, in C. monogyna being present in one-fifth of the samples and in P. bourgaeana in three quarters. When present, crystals were located in the axial elements i.e. no crystals were found in the ray cells. Helical thickenings were imaged in 4 of the specimens, an unexpectedly low amount. Anatomical atlases indicate that the presence of this character in Maloideae wood is variable (Schweingruber 1990; Akkemik & Yaman 2012), but personal experience indicated that its presence was substantially more frequent than 4/121.
Except for one individual (MI1 5.7), all specimens presented their pores with the semi major axis in the radial direction. Direction of semi major axis was thus dropped as a variable from further analysis.
Fig. 15 – Boxplot showing the distribution of the Number of pores variable, grouped by taxon.
Fig. 16 –Boxplot showing the distribution of the Total number of pore clusters variable, grouped by taxon.
Fig. 17 – Boxplot showing the distribution of the Maximum number of pores per cluster variable, grouped by taxon. Note that only individuals who had pore clusters present were accounted for in this graph.
Fig. 19– Boxplot showing the distribution of the Total pore area variable, grouped by taxon.
Fig. 20 – Boxplot showing the distribution of the Area of smallest pore variable, grouped by taxon.
Fig. 21 – Boxplot showing the distribution of the Area of largest pore variable, grouped by taxon.
Fig. 22 – Boxplot showing the distribution of the Average pore area variable, grouped by taxon.
Fig. 23 – Boxplot showing the distribution of the Average pore aspect ratios variable, grouped by taxon.
Fig. 25 – Boxplot showing the Distribution of the Height of shortest ray in micrometers variable, grouped by taxon.
Fig. 26 – Boxplot showing the distribution of the Height of tallest ray variable, grouped by taxon.
Fig. 27 – Boxplot showing the distribution of the Number of rays per square millimeter variable, grouped by taxon.
Fig. 29 – Boxplot showing the distribution of the Height of tallest ray in number of cells variable, grouped by taxon.
Fig. 30 – Boxplot showing the distribution of the Height of shortest ray in number of cells variable, grouped by taxon.
Fig. 31 – Bar graph showing the Presence of two distinct ray sizes, grouped by taxon.
Fig. 32– Bar graph showing the Vessel perforation type, percent of each taxon’s abundance.
Fig. 34– Bar graph showing the Presence of crystals, grouped by taxon.
Fig. 35 – Bar graph showing the Presence of helical thickenings, grouped by taxon.
Anatomical characteristics and environmental factors
Principal component analysis (PCA) on the anatomical characters failed to reveal any significant clustering of data. The first component accounted for merely 16.15% of the total variance of the dataset, while the second accounted for 13.4%. The first four components when taken together accounted for 49.1%. An alternate approach using log transformation of the original data had little effect on either the explained variance, or the distribution of the samples on the plot. It thus proved impossible to use the PCA to produce clusters or to reduce the number of variables under analysis.
Analysis of similarities (ANOSIM) performed using the 5 species as groups showed high similarity between all groups for all anatomical characteristics. The highest R value was that obtained for the Rays per square mm character, with a value of 0.138.
Six characters (Total pore area, Height of tallest ray (m), Average ray height, Width of
widest ray, Height of tallest ray (cells) and Presence of helical thickenings) displayed a negative R value, suggesting that differences were larger within groups than between them.
The dendrogram produced by the neighbor-joining algorithm reinforced this notion, with no discernible clusters emerging from the tree, and with several of the nodes showing 0% support after 10000 bootstrap replicates.
ANOSIM was then performed against the environmental variables, again using the 5 species as groups. Overall R values were again low, however pairwise comparison of the groups did show some trends. P. cordata and P. bourgaeana showed marked dissimilarity on the following variables: Altitude (R:0.8574 ; P:0.0001), Soil class (R:0.5706 ; P: 0.0001), No. days rainfall (R:0.6580 ; P:0.0001), Lithology (R:0.5948 ; P:0.0001), Evapotranspiration (R:0.5639 ; P:0.0001), Solar radiation (R:0.7070 ; P:0.0001), Mean temperature (R:0.7519 ; P:0.0001), Hours sunshine (R:0.7734 ; P:0.0001) and Total rainfall (R:0.7130 ; P:0.0001). These differences are quite possibly the result of the North Portugal/South Portugal divide in the distribution of these two species. Significant differences were also returned for the Crataegus monogyna/Pyrus
cordata combination for the following variables: Mean temperature (R:0.7519 ; P:
0.0001) and Total rainfall (R:0.6319 ; P:0.0001).
When comparing variables among themselves using Spearman correlation, several showed a p value under 0.01. These included several that correlated with latitude and/or longitude, which might go a long way to explain pairwise correlation detected between several of the environmental variables, since in most cases these have a stronger correlation with geodata than with each other. When looking at correlations between environmental and anatomical variables, the following correlations show up as highly significant: Pore numbers correlated with seven soil classes, but otherwise showed only a weaker (P=0.0266) correlation with solar radiation; Of the three Pore cluster orientation classes, Random cluster orientation showed a strong correlation with
Full shade (0.00891); Both the Area of smallest pore and the Average pore area
respectively); The height of shortest ray in m correlated with No. days rainfall (0.00574) and Evapotranspiration (0.00728); Average ray height correlated with No. days rainfall (0.000696), Evapotranspiration (0.000933), Solar radiation (0.00225), Mean temperature (0.00674), Hours sunshine (0.00232) and Total rainfall (0.00446); the Number of rays per square mm correlated with the Residual soil abundance class (0.00575) and with Solar radiation (0.00725); Height of tallest ray correlated with Full
shade (0.000601);The Type of vessel perforations correlated with full shade (3.18x10-5)
and with Evapotranspiration (0.000921); Heterogeneous Type I rays were correlated with partial shade (0.00791) while Heterogeneous type II were correlated with the
Residual soil abundance class (3.53x10-5), No. days rainfall (0.00467),
Evapotranspiration (0.00276) and Solar radiation (0.00360). Homogeneous rays also
correlated with No. days rainfall and Solar radiation (0.00734 and 3.23x10-5
respectively) but also showed correlation with Mean temperature (0.00116), Hours sunshine (0.000531) and Total rainfall (0.00674). Fifty-four other variable combinations showed a lesser degree of correlation (0.01 < p < 0.05). These can be visualized in the table in annex 04.
Several soil and lithology classes presented strong correlations with one or more anatomical characters. However two classes dominated the sampling for both variables (Humic cambisols for soils and Granites for lithology), which as discussed earlier is most likely an artifact of the sampling effort. Furthermore since these variables were broken up into multiple classes (19 soil classes and 11 lithology classes) many of these ended up having only a handful of samples. On that basis they are presented here separately. Of the soils: Humic cambisols correlated with Number of pores (P =
0.00267), Average ray height in m (0.00203), Type of vessel perforation (0.00241)
and Heterogeneous type II rays (0.00421). Schist associated cambisols correlated with total pore area (0.00193), Area of largest pore (0.00500) and Average pore area (0.00314). Chromic cambisols correlated with width of widest ray (0.00402) and presence of helical thickenings (0.000222). Eutric lithosols correlated with
homogeneous rays (2.44x10-7) and Heterogeneous type I rays (0.000715). These exact
same correlations repeated themselves in the Luvisol associated eutric lithosols soil class. Eutric fluvisols correlated with the number of rays per square mm. Orthic luvisols
correlated with pore grouping (4.92x10-6), Maximum number of pores per cluster
(0.00258), Total number of clusters (0.00325) and Average ray height in m (0.000225).
Albic luvisols correlated with the Maximum number of pores per cluster (0.00523), Random cluster orientation (0.00712), Width of widest ray (0.00174) and Presence of
crystals (0.00488). Chromic luvisols correlated with the Tangential cluster orientation (0.00440) and with Average pore area (0.00195). Distric regosols correlated with Total pore area (0.00293), Area of smallest pore (0.00879), Area of largest pore (0.0100) and average pore area (0.00410). Gleyic solonchaks correlated with pore cluster
orientation (0.00406). Orthic podzols correlated with width of narrowest ray (1.31x10-5)
and Homogeneous rays (0.000180).
As for lithology: Granite correlated with average Ray height (0.00401), Homogeneous rays (0.00677) and Heterogeneous type II rays (0.00341). Schist and greywacke correlated with Pore grouping (0.00893), Area of smallest pore (0.00320), Area of largest pore (0.00570) and Average pore area (0.000481). Schist, amphibolites, mica
schist, greywackes, quartzites and gneisses correlated with Height of tallest ray in m
(0.00189), Height of tallest ray in cells (0.000705) and Presence of helical thickenings
(2.88x10-5). Aeolian sands correlated with Total pore area (0.00293), Area of smallest
pore (0.00880), Area of largest pore (0.00985) and Average pore area (0.00410). Sands, pebble s, clays and weakly consolidated sandstone correlated with height of shortest ray (0.00581) and width of widest ray (0.00400). Sands, gravels, limestones and clays correlated with width of narrowest ray (0.000183), Homogeneous rays (0.000160) and Heterogeneous type I rays (0.00389). Finally, Shale, graywacke and sandstone correlated with average ray height (0.00682) and homogeneous rays
Fig.36 – PC1/PC2 scatter plot. Dots coloured as per species: Red, Crataegus monogyna; Blue, Pyrus cordata; Yellow, Pyrus bourgaeana; Violet, Pyrus communis; Black, Pyrus sp.
Fig. 37 – PC1/PC3 scatter plot. Dots coloured as per species: Red, Crataegus monogyna; Blue, Pyrus cordata; Yellow, Pyrus bourgaeana; Violet, Pyrus communis; Black, Pyrus sp.
Fig. 38 – PC1/PC4 scatter plot. Dots coloured as per species: Red, Crataegus monogyna; Blue, Pyrus cordata; Yellow, Pyrus bourgaeana; Violet, Pyrus communis; Black, Pyrus sp.
Fig. 39 – PC2/PC3 scatter plot. Dots coloured as per species: Red, Crataegus monogyna; Blue, Pyrus cordata; Yellow, Pyrus bourgaeana; Violet, Pyrus communis; Black, Pyrus sp.
Fig. 40 – PC2/PC4 scatter plot. Dots coloured as per species: Red, Crataegus monogyna; Blue, Pyrus cordata; Yellow, Pyrus bourgaeana; Violet, Pyrus communis; Black, Pyrus sp.
Fig. 41 – PC3/PC4 scatter plot. Dots coloured as per species: Red, Crataegus monogyna; Blue, Pyrus cordata; Yellow, Pyrus bourgaeana; Violet, Pyrus communis; Black, Pyrus sp.
Fig. 42 – Dendrogram constructed using neighbor-joining algorithm with 10000 bootstrap replicates. The numbers at each branch represent the percentage of replicates for which the node was still supported. Betula pendula was included to serve as a rooting point.
Discussion
Anatomical characters of note
The analysis performed on the wood anatomical characters of C. monogyna, P.
cordata and P. bourgaeana revealed a number of noteworthy facts that merit a more
in-depth discussion.
Fig. 43 – Transverse section of Pyrus cordata Mi1 5.12 (Left) and of Pyrus bourgaeana Aj4 4.1 (Right). Both images taken at 100x magnification.
As mentioned previously, despite being found mostly in moist northwestern Portugal, our samples of Pyrus cordata proved to have lower average pore areas than Pyrus
bourgaeana, which were sampled mostly in the drier Alentejo and Trás-os-montes
regions. This is somewhat peculiar, since as a general rule, plants tend to have
narrower pores in more arid conditions (Lovisolo & Schubert 1998;Carlquist 1966). In
terms of conductivity, larger pore diameters are more efficient than narrower ones, as a result of the Hagen-Poiseuille law:
𝚽 = 𝚷. 𝐑𝟒.∆ 𝐩
8L
Equation 02 – Where is the flow rate (volume), P is the pressure gradient between the ends of the vessel, is the viscosity of the fluid in the vessel and L is the length of the vessel.
A notable result of this equation is that if a plant were to shrink its pores to half their diameter (all other things being equal) it would now need 16 times as many pores to equal the same flow rate, even though these new pores would have a combined pore
area 4 times larger than the original. So long as a plant is capable of generating enough negative pressure in its vessels so as to maintain cohesion-tension, it would benefit from having the widest pores it can support. However wider pores have disadvantages. Larger pores are at greater risk of embolization (Zimmermann 1983; Sperry et al. 1994), and their presence is therefore a tradeoff between conductive efficiency and risk of hydraulic failure. Plants that live in conditions of water stress in general show a tendency to have smaller diameter pores than plants in more mesic conditions, and this is often interpreted as a response to increased embolism risk. The higher negative pressure maintained in the xylem under conditions of drought increases the probability of embolisms spreading via the air-seeding mechanism, where air from adjoining air-filled vessels gets aspirated into functional vessels (Sperry & Tyree 1988). However despite the smaller pores observed in P. cordata, this should not be taken to mean that the pores of P. bourgaeana are uncharacteristic of arid
climates. The mean pore area for this species was 792.9 m2 which for an ideal
circular pore translates into a diameter of 31.77m. This falls within the size range
typical of other published descriptions of Pyrus in Mediterranean habitats (Akkemik & Yaman 2012). What is peculiar is rather that P. cordata consistently shows smaller
values than its southerly counterpart (685.5m2 and 29.54m respectively). Since high
correlations were found between average pore area and full shade, one hypothesis is that the reduction in photosynthetic activity under conditions of shade has an even more drastic effect on pore size than water stress. The relative frequencies of occurrence of shade conditions (47.6% P. cordata under conditions of full shade versus 16.6% for P. bourgaeana) would seem to bear this out. The fact that there is only a weak inverse relationship between Number of pores and Maximum pore size, serves to reinforce the notion that reduced conductivity and not safety from embolism is the driving force behind pore size reduction.
Fig. 44 – Plot of Area of largest pore vs. Number of pores for Pyrus bourgaeana and Pyrus cordata.
In contrast, the greater occurrence of pore clusters observed in P. bourgaeana meshes correctly with the established literature, where greater occurrence of pore clustering has been likewise connected to greater water stress, the clusters being interpreted as offering greater hydraulic safety by creating “bypasses” around embolised vessel elements, and serving as a reservoir from where embolised pores can be refilled (Lindorf 1994; Lens et al. 2010; Rita et al. 2015). The fact that the relationship between greater clustering and aridity is maintained but that of average pore area is not reinforces the notion that and additional environmental variable is at work where pore area is concerned. A more directed study focusing solely on these characters might be warranted in order to better understand the relative response of Pyrus to light and water stress.
Most significant of all was the presence of scalariform perforation plates in the vessels of Pyrus cordata sampled at Corno de Bico, since according to the existing literature
(Schweingruber 1990; Vernet et al. 2001; Akkemik & Yaman 2012) one of the
diagnostic characters of the Maloideae is their simple perforation plates. In fact scalariform perforation plates are rare in the Rosaceae (Eyde 1975). In the sampled individuals, the perforation plates were exclusively scalariform (i.e. no simple perforation plates were observed), formed an angle of 10-23 degrees with the longitudinal axis and possessed 20-24 bars, at least some of which were forked.
Scalariform perforation plates (particularly those with large numbers of bars and low angles to the longitudinal) have been described as a primitive character, lost in favor of the derived simple perforation plates. They mostly persist in species characteristic of mesic habitats, the number of taxa possessing them increasing with latitude and
altitude (Carlquist 1975; Baas 1976; Lens et al. 2016). Scalariform perforation plates
have been described as having a resistivity-increasing effect on vessels, possibly to as high as double the value of the unobstructed vessel lumen. Furthermore, their resistivity seems to place an upper constraint on the diameter displayed by pores (Christman & Sperry 2010). It is thus argued that they are retained by taxa that are not faced with high selective pressure for conductive efficiency (Lens et al. 2016).
Fig. 45 – To the left: Scalariform perforation plate of a Pyrus cordata specimen sampled at Corno de Bico, Mi1 5.12. To the right: Simple perforation plate of another Pyrus cordata, Mi1 5.14, for comparison. Both images are at 500x
magnification.
Although Corno de Bico’s location in the Atlantic bioclimatic region, as well as its location between the Lima and Coura river valleys, place it as one of the most rainy sites in continental Portugal (Beja 2008), this alone does not explain the re-appearance of a presumed ancestral character in a species characterized by the presence of its more derived counterpart. Zimmerman (1983) suggested that the retention of
scalariform plates confers some sort of advantage to plants that must endure frost conditions (Zimmermann 1983). Low temperatures are known to be a risk factor for vessel embolism, with outgassing caused by the freezing of sap followed by gas bubble fusion following the re-establishment of negative xylem pressures once sap-flow is restored leading to vessel occlusion by vapor. It is theorized that scalariform plates provide plants with a mechanism to combat this phenomenon, either by trapping and/or splitting gas bubbles as they ascend, limiting their surface area and thus making it easier to redissolve them in the liquid (Zimmermann 1983), or by forcing subdivisions in gas bubbles, restricting them to the length a vessel element, simplifying vessel refilling. (Sperry 1986). Although the plants were in a relatively low temperature area (monthly
averages 8.6 – 21.4 ºC, reaching a minimum of -5ºC in the winter (Beja 2008)), with
moderate amounts of frost in winter (30-40 days (Agência Portuguesa do Ambiente 2011)), they were not the only individuals in such conditions and in fact several others were sampled in more extreme temperature and frost conditions without exhibiting scalariform perforation plates. However, they were the only ones that combined these factors with a high evapotranspiration rate (>800mm (Agência Portuguesa do Ambiente 2011)) and full shade.
Depending on which factor is considered dominant, one can be tempted to offer two potential explanations for the presence of scalariform plates. If evapotranspiration is considered the most significant factor, one could expect that the plant’s conductive fluids would be under a greater amount of negative xylem pressure, due to stomatal opening and decreased water potential at the plant’s leaves. This would then leave the plant at a greater risk of embolism, since the decreased pressure would make it easier for dissolved gasses to come out of solution, and conversely, more difficult for gas bubbles to dissolve back into the sap (Zimmermann 1983). This combined greater risk of embolism might be serious enough for the plant to sacrifice conductive efficiency in favor of greater safety from embolism. However we find this to be the less likely scenario: although the amount of plant cover means that transpiration is almost certainly an important contribution to total evapotranspiration, the sampled plants were all part of the understory, experiencing greater humidity and lower temperature conditions as well as greater protection from wind that would make transpiration less intense than the total average for the area would suggest.
If we consider shade conditions to be the driving factor, it can instead be argued that the reduced levels of photosynthesis results in a higher leaf water potential that in turn
