100% Original, Plagiarism Free, Tailored to your instructions

Order Now!

Investigation of the role of intraspecific variability in three functional traits
Contents page:
1)    Abstract
2)    Introduction
3)    Literature review
4)    Methodology
5)    Findings
6)    Discussion
7)    Conclusion
8)    Acknowledgement
9)    References
An enormous diversity of species on Earth has experienced high rates of decline on a global scale. The decrease in global biodiversity occurs because of economic growth and different anthropogenic activities, that have led subsequently to numerous global changes. These changes are habitat change due to agriculture; excessive land use; deforestation and overexploitation of natural resources; redistribution of invasive species; climate change due to pollution; and shifts in the atmospheric composition (Gren 2016). These changes have put extreme pressure on global ecosystem processes, and thus possibly of failure of the integrity of ecosystem services, which are so valuable for the livelihood human beings (Pimm 2014, Gren 2016).
Many studies confirm this statement (Gren 2016) including scientific papers showing the influence humans have on nature when military actions take place (Conteh 2016, Gren 2016).
The anthropogenic factors affecting nature are numerous finding links between data that could predict future species responses to the alternation of surrounding environment are vital for the ecology. A cornerstone of finding those type of data is to know the inter- and intraspecific interactions.
This research work undertaken will investigate the links between and within species trait variations and more specific will investigate the relationships between plant trait data and trait diversity and how species richness influences functional diversity.

To what extent community weighted means (CWM) affect the Functional Diversity on a species level?
To what extent functional richness (FRic) affect the Functional Diversity on a community level?


To investigate and analyse the relationship between CWM and functional diversity
To investigate and analyse the relationship between FRic and functional diversity

Three types of functional features examined the intraspecific genetic diversity. Such as this could give a better estimation of changes related to this diversity, for example, population stability and productivity and ecosystem processes (Bolnick 2011).
Literature Review
Biodiversity has usually been described as “variability among living organisms from all sources including, inter alia, terrestrial, marine and other aquatic ecosystems and the ecological complexes of which they are part, this includes diversity within species, between species of ecosystems” according to the Convention on Biological Diversity from 1992 (United Nations 1992). However, it is hard to define and measure, due to its intrinsic complexity.  Biodiversity provides a base for all ecosystem services that are inevitably connected to the human survival and development (Reid 2005; Carpenter 2009; Butchart 2010; Perreira & Leadley 2010; Bullock 2011; Perreira & Navaro 2012). The species composition (including their genotypes and functional types) and their number in a given system are what scientists agreed to call biodiversity (Diaz and Cabido 2001).
Many factors influence the biodiversity of our planet. One hypothesis suggests that we are in the middle of the Sixth mass extinction caused by modern humans’ activities (Ceballos 2015). The loss of biodiversity becomes of the most crucial environmental problems of our time (Ceballos 2015).
Central questions of ecology are assembly of biodiversity congregation within communities (Gravel 2006) and the impact on ecosystem functioning (Naeem and Wright 2003, Hooper 2005. To give answers to those questions requires a different approach focused on the biological characteristic of species, and that goes beyond their taxonomical identity (Albert 2011).
Functional diversity definition as per Tilman (2001) is widely cited and is “the value and range of the functional traits of the organisms in a given ecosystem” (Tilman 2001). Functional diversity (FD) metrics are simply a measure of trait diversity.
In the ecological community, many propositions on the importance of trait diversity have been published throughout the years. (Diaz and Cadibo 2001, Geber and Griffen 2003, Hooper 2005, Mason 2005, McGill 2006, Diaz and Lavorel 2007, Violle 2007, Berg 2010, Jung 2010, Albert and Grassein 2011, Violle 2012, Laforest-Lapointe 2014, Alofs 2016, Chalmandrier 2017 and others). Some of them claim the diversity of traits in each community could enable the rate of prediction and reliability of different processes of the ecosystem (Hooper 2005, Mason 2005, McGill 2006). Another different state variability within trait data of species could have an influence on the predictions of features and inferences scientists make when using trait data. (Alofs 2016). However, in general, ecology community overlooked the trait variance and its importance for the environment (Violle 2012).
Predictions of community ecology’s structure and different dynamics of processes of organisms might be done by studying the four classes of processes: selection, speciation, drift and dispersal, thus understanding how organisms can co-occur within time and place (Vellend 2010).
The variance of intraspecific traits and means of interspecific species have been necessary for the theoretical study of coexistence (Violle 2012). A study such as this one of MacArtur and Levins (1967) can give a solution of the Gause’s Principle’s paradox which states the same niche cannot be shared by two species.
Nowadays dominant theories of evolutionary ecology show neglection on intraspecific variation in the study of different communities (Violle 2012). Those are principles such as community assembly and rules of assembly (Weiher 2011).
In the field of ecology community, phylogenetics studies are orientated only between species variations and ignore within-species variations, where this is another proof of the neglection of intraspecific trait differences (Cavender-Bares 2009).
In community ecology, the trait-based approach adopted a mean field theory that focuses on co-occurring species and their differences (Weiher 2011, McGill 2006). An individual organism of an assembly can respond via phenotypic plasticity of the presence of different direct neighbours (Arseen 1983, Ashton 2010).
The immediate neighbours of a particular species are “the ones directly involved in species interactions” (Aarseen 1983, Whitlock 2011).
To measure intraspecific variability an ecologist, have two different approaches both of which “cause similar effects in ecological communities”. The first is Phenotypic plasticity and the second is genetic variability (Hughes 2008, Berg 2010, Ashton 2010, Violle 2012).
The most profound insight of Charles Darwin was his deeper view of differences amongst individuals of the same species.  Differences which are unique to each organism such as behaviour and shape. Those traits combined with the visible ones could increase or decrease the survival rate of plants. If there is a decrease, the evolution will remove this trait and replace it with another, more adaptable, which prolonged the life of the species. Darwin made a highly significant push into the ecology and biology science back in the 19th century. In his research, he said and proved that organisms could acquire trait which enables them to adapt and survive.
At an individual level, any measurable feature that could have a direct or indirect result of the fitness of the species or influence their ecological processes such as competition, predation, and habitat filtering, or alters the properties of communities and ecosystems is called a functional trait. (Naeem and Wright 2003; Hooper 2005; Mason 2005; Violle 2007) Functional traits of organisms influence the functional attributes in a community which includes range and relative abundance.  The functional attributes of a community most possibly will have affected the functional traits (such as relative abundance and range).
Those different dimensions are acknowledged in the ecology as ‘functional diversity’(FD or trait diversity) (Mason 2005, Diaz 2007, Albert 2011), and those dimensions could be measured by associated metrics of different components (Pavoine and Bonsall 2011).
Functional diversity is all functional attributes of a community of species and several different structural aspects. They are mediated in each community by their relative abundance, different range, and kind. All those different measures are known collectively as trait diversity (Diaz and Cabido 2001, Mason 2005, Albert 2011), and their associated components and metrics can quantify them.
The trait diversity can be disintegrated into two components according to Mouillot (2005). The first component is functional richness (FRic) and this is what is used as a measure of trait diversity in this dissertation. The definition of FRic as per Mouillot (2005) is “the amount of niche space occupied by the species within a community may be used as a richness measure – functional richness” (Mouillot 2005).
The second component is functional evenness but it will not be investigated because those two components vary of each other independently and they both relate to species (the same entities). Also, the evenness of abundance distribution is orthogonal and this why only one metric of trait diversity (FRic) has been used for quantification (Mouillot 2005).
From another side a characterisation of a community’s trait diversity is done by its dominant trait values which are estimated by a community-weighted mean trait (CWM) value (mean of trait values weighted to calculate species abundance, Garnier 2004).
So, going back to functional traits is good to understand approaches based on functional traits and types, and species richness turned out to be very productive for the last decade, but a connection between their findings have not been established so often as it should. Those two different approaches if gained together (cross-fertilized) can give excellent results in gaining mechanistic insight into the connections between and within plant diversity and ecosystem processes, boosting the practical management of biodiversity conservation and ecosystem processes (Diaz and Cabido 2001).
In 2004 a problem with the precise definition of traits and their mixture on an individual level and environmental factors (Petchley 2004, Eviner 2004, Violle 2007) had shown to the ecologists that one definition must be adopted to quantify and classify data correctly and interpret the results. This one definition was proposed by Violle in 2007 and underlined the importance of positives of adoption and the negatives of unproductive confusion with terms. This definition states that trait could be any morphological, physiological or phenological feature that can be measured at the level of an individual (Violle 2007, Perez-Harguindeguy 2013). Any trait that affects the fitness of an individual directly or indirectly it is a functional trait (Violle 2007, Albert 2011). Those traits characterise the biological activity of different species and ecological processes influenced directly like habitat filtering, predation, competition, and mutualism; Also, all properties of diverse communities and ecosystems characterise (Neaeem and Wright 2003, Hooper 2005).
Trait-based researchers are widely used in the scientific society and helped Darwin to write his Natural selection book and published it in 1859. Darwin proposition stated that traits (only gained ones) could be used as different proxies for the tracing of organismal performance (Violle 2007, Ha M. 2014).
In the last three decades after development in the community (Petchey and Gaston 2002, Mcgill 2006) and ecology (Grime 1997), the definition of a trait has adopted wider concept in the research field. Nowadays the term has been used in trait-based approaches ranging from the level of an organism to the degree of an ecosystem (Violle 2007).
The immediate way how we can deduce the functions of an organism: The leaf shape maximises the light interception and reduces the water loss from the plant through transpiration. This example provides information about the structure that can be assessed of how well contributes to the organismic system of which part the ultimate sense of judgment of those traits is the Darwinian fitness – the impact of those traits on survivorship, fecundity and development rates (Calow 1987).
According to the traits they have, the species are filtered by the conditions of the environment (Weiher & Keddy 1995).
It is known that intraspecific trait variations have significant effects in ecology and evolution (Bolnick 2011, Alofs 2016). Those changes must be integrated into the trait-based analysis because they could influence the truthfulness of “predictions in community ecology” (Albert 2012, Violle 2012, Alofs 2016).
The importance of intraspecific variation is distinctly stated in an increasing number of studies examined different ecological and evolutionary processes.  Also, the traditional ecological theory has emphasised the significance of interspecific differences. By going beyond the traditional studies and analysing the various structures of intraspecific variability in real communities because of past community assembly processes will enhance the predicting capabilities of trait-based studies for community ecology. Theories and models based on population averages predict lower local diversity than those theories and models incorporated in intraspecific variability. Therefore, species’ trait variance has to be included in predictions of the changes of species and functional diversity to environmental changes and their consequences for the functioning of an ecosystem. This will assist the progress of shifting from species-based to individual-based ecology of communities and inevitably lead to a much more productive theory in ecology (Violle 2012).
Also, it is nice to understand a critical part such as intraspecific trait variability shows the species ecological plasticity and niche breadth, also an excellent point to underline that implications for community and also functional ecology have not been explored in details (Laforest-Lapointe 2014). It is certain that the functional traits of different species show important morphological, physiological and phenological features (Perez-Harquindeguy ). Studies are focusing on plant community and the importance of their functional traits, with their help researchers could make a significant change of approaching the ecology of a given community (McGill 2006, Keraney M. & Porter 2006). Another adamant statement written as an answer to McGill’s work is that an ecological niche can be modelled only entirely by plant functional traits of three models: modelling of energy and mass budgets – DEB Theory; the geometric framework and the nutritional niche; biophysical ecology and the climatic niche. All of them are based on the first law of thermodynamics (conservation of mass and energy and homoeostasis’ principle) and though them a hypothesis of the development of a functional trait-based approach around the concept of the niche has been established. (Kearney & Simpson 2010).
One of the scientific researches of Geber and Griffen in 2003 was to review patterns of how specific functional traits are selected and assessing general questions for evolution and also about selection & heritability for different classes of traits. In this study, they examined in details the processes and conclusion; they stated functional traits are both heritable and simultaneously with this under selection. The enormous pressure of natural selection is applied by both – biotic and abiotic factors.
Fascinating is the study of Bolnick 2011“Why intraspecific trait variation matters in community ecology”, where he makes a table with six different intraspecific trait variation that could alter dynamics of a community or its structure.
Looking from a methodological point of view the last ten years have been very productive with the establishment of different criteria on multi-levels of selection of efficient trait diversity indicators for various research questions (Petchey and Gaston 2002). Trait diversity is a very complex concept, and for now, no consensus has been reached on the most efficient way of measurements or its influence on community assembly and ecosystem functioning.  One of the biggest problems of when and how to account for intraspecific trait variability is a discrepancy of assessment of trait diversity (Mason 2005, Albert 2011).
Community’s trait diversity is a major component of biological assemblages as proposed by Mason (2005) in “Functional richness, functional evenness, and functional divergence”. There he tells the trait diversity could enable the rate of prediction and reliability of different processes of ecosystems (“i.e. ecosystem function and ecosystem reliability”). And more precisely the dominant trait values could make a general description of a community’s trait diversity. Especially those estimated by CWM (species abundances weighted by trait value means, Garnier et al. 2004) and by species richness, species evenness, and species divergence (Mouillot 2005; Albert 2011). The most various treatments having a greater probability dominating within the productive species inside of the whole species pool named “Selection Probability effect” (Wardle 1999).
The sixth intraspecific trait variation is “TRAIT SAMPLING”. This one can alter the average fitness of a community or the strength of interaction within the community. Occurs when “Small population size permits stochastic sampling from trait distributions” (reference).
(need to connect lit review with methodology)
The following method can be divided into three main sections: Study Location and Types of Species; Leaf trait Measurements and Statistical Analysis.
The methods adopted for this dissertation includes trait-based sampling, laboratory work and research.
This study was conducted in Woodwalthon, Cambridgeshire, United Kingdom
The precise location of the fen is Lat, Long 52.44628001980083,-0.19071578979492188
Alternatively, 52 degrees, 26 minutes and 46.608 seconds North,
0 degrees, 11 minutes and 26.576 second West.
This precise location is characterised as part of a vast wetland area. Woodwalton Fen is only a small fragment of a massive restoration project (the largest one in Europe of this type) named “Great Fen Project” (www.greatfen.org.uk). Wetland in the United Kingdom and all around the world are precious for both people and wildlife. They provide different habitats (wet woodland, scrub, open water, reedbeds, real fen habitat and wet and dry meadows) for various species such as breeding birds, wintering birds, bats, water voles, small mammals, deer, otters, aquatic invertebrates, soil invertebrates, earthworms, butterflies, dragonflies and damselflies, true flies, moths, ground beetles, amphibians and reptiles. Also, many species of plants such as Ragged Robin, Marsh Pea, Purple Loosestrife, Purple Moor Grass, Great Water Dock, Meadow Rue and rare Bog Myrtle, Water Violet and Bladderwort (Great Fen Project).
Apart of the species richness of wetlands they also provide the ecosystem service so valuable for people which are the primary source of drinking water for wildlife and people (JNCC, WWT).
The species included in this study have different and very specific characteristics.
The information for the plants is derived from Online Atlas of British and Irish Flora and Royal Horticultural Society.

Species and initials
Common Name
Native or Introduced

Calamagrostis canescens –
Purple small-reed
(Poaceae family)

Carex acutiformis
Lesser pond-sedge
Perennial herb (Cyperaceae family)

Galium aparine
Herbaceous annual herb (Rubiaceae family)

Glechoma hederacea
Perennial herb (Lumiaceae family)

Iris pseudacorus
Yellow Iris
Perennial herb (Iridaceae family)

Juncus effusus
(Juncaceae family)

Lychnis flos-cuculi
Perennial (Caryophyllaceae family)

Phragmites australis
Common Reed
Perennial grass (Poaceae family)

Quercus robur
Pedunculatee Oak
Deciduous tree (Fagaceae family)

Salix cinerea
Grey Willow
Deciduous shrub (Salicaceae family)

Urtica dioica
Common nettle

Betula pubescens

Alnus glutinosa

The sampling methods adopted in this dissertation are taken from “New handbook for standardised measurements of plant functional traits worldwide” written by a collective of authors Perez-Harguindeguy, Diaz, Garnier amd others in  2013.
Collection of raw data (leaf samples) from two fens in Cambridgeshire, UK was in May, June and July.  The location of the fens is as follow:
Latitude 52.44628001980083
Longitude -0.19071578979492188
The methodology adopted is for trait-based sampling – where the sample is a statistical tool and can give us inference to draw different conclusions about a population that.
Selection of species and different individuals as per Perez-Harguindeguy (2013). Per the Handbook (2013) the individuals chosen have to be healthy-looking unless another specific goal is not determined. Also, they need to be exposed to sunlight, species of plants have to be located an in lighted environment, without shades. This criterion does not make problems for sunny plants, but when there are true shades species the sample must be collected from not so shady places and they must still look healthy.
During May, June and July ten five individuals for each species were collected in the study area in Woodwalton. The selected individuals were collected from distant locations to reduce the likelihood of collection of individuals that are similar genetically. The collected leaf samples were fully exposed to sunlight leaves, all of them collected from outer canopy of plants. All species collected were placed and labelled immediately in transparent plastic bags, sprayed with water and additional wet tissue was added inside the plastic bag to prevent loss of moisture, and stored in a cool bag. After that the cool bag was stored in a fridge upon returning of the field prior the to start with the measurements.
Within 24 to 48 hours at most, the fresh mass (LW) of each leaf was measured with a scale (need to put the correct name here) at the laboratory at Kingston University. Leaf area of all samples was measured (LA) as well using a Portable Leaf Area Meter. After those measurements, all leaf samples were wrapped in a tin foil, labelled and then placed in an oven to dry for 72 hours at 70 degrees Celsius. On the third day, the Leaf Dry Mass Content (LDMC) was measured immediately after taking the leaf samples out of the drying oven.  Afterward the specific leaf area was calculated (SLA), as dividing the fresh leaf area by the final dry mass leaf area.
For this study, only SLA, LDMC and seed mass traits will be used.
Seed mass was weighted in the laboratory at Kingston University using Sartorius Scale BP615 with a maximum weighing of 61 grams. The samples were taken from Pollen laboratory after Professor Martyn Waller granted me a permission to use his personal collection of seeds to fulfil my purpose.
Measure of Functional diversity / trait diversity metrics using CWM.
The first goal of this study was to find all Community Weighted Means (CWM). For each individual, all samples of SLA, LDMC and seed mass measurements were summed up individually for each trait, and divided by the number of specific samples for individuals. This gave a single number for each species, and this number is a CWM, which will give a way to quantify the functional diversity of a community. CWM was done for all species.
Second goal was to find how CWM vary in different years between species. For this purpose, I plotted a graph on excel where I can compare results of species.
There are only four species for which the data was relevant and and can be compared for two years. Galium aparine, Phragmites australis , Urtica dioica – all of the samples are from Woodwalton Fen, and Alnus Glutinosa – where the first sample is from Charles Hill and the second one from Woodwalton.
Third goal of this study was to conclude how variance of three leaf functional traits studied (SLA, LDMC, seed mass) divided into parts across and within different species and individuals. For this purpose, a nested analysis of variance or ANOVA is used to calculate differences in the following levels: among species and among datasets. Those analyses were performed for all species.

CWM of Alnus Glutinosa

Interpretation of findings:

CWM of Galium aparine


CWM of Phragmites australis


CWM of Urtica dioica

Only those four species could be compared within the group of species.
Three of the species from the group did not have seed mass measurement because the seeds were too small to be measured and they are Carex acutiformis, Juncus effuses, Dryopteris dilatata
So, those three were not included in the SPSS analysis.
SPSS Analyses
For the descriptive statistic – 400 words at most
For the ANOVA – 800 words minimum


Sum of Squares
Mean Square

Between Groups

Within Groups


Between Groups

Within Groups


Between Groups

Within Groups


Aarseen L.(1983) “Ecological combining ability and competitive combining ability in plants: toward a general evolutionary theory of coexistence in systems of competition” [online] The American Naturalist, Volume 122, Issue 6, Pages: 707-731,
Albert C.H., Grassein F., Schurr F. M., (2011) “When and how should intraspecific variability be considered in trait-based plant ecology?” [online] Perspectives in Plant Ecology, Evolution and Systematics Journal, Volume 13, Issue 3, Pages 217-225
Albert C., De Bello (2011) “On the importance of intraspecific variability for the quantification of functional diversity” [online] Oikos Journal, Volume 121, Pages 116-126,
Alofs K.(2016) “The influence of variability in species trait data on community-level ecological prediction and inference”[online] Ecology and Evolution Journal, Volume 6, Issue 17, Pages 6345-6353,
Ashton I.(2010) “Niche complementarity due to plasticity in resource use: plant partitioning of chemical N forms”[online] Ecology – Ecological Society of America, Volume 91, Issue 11, Pages: 3252-3260
Berg M., Ellers J.(2010) “Trait plasticity in species interactions: a driving force of community dynamics”[online] Evolutionary Ecology, Volume 24, Issue 3, Pages: 617-629,
Bullock J.M., Aronson J.(2011) “Restoration of ecosystem services and biodiversity: conflicts and opportunities”[online] Trends in Ecology & Evolution, Volume 26, Issue 10, Pages: 541-549 [Peer Reviewed Journal],
Butchart S., Walpole M., Collen B. (2010)”Global Biodiversity: Indicators of recent declines”[online] Science, Volume 328, Issue 5982, Pages: 1164-1168,
Calow P.(1987)”Towards a Definition of Functional Ecology”[online] Functional Ecology Journal, Volume 1, Issue 1, Pages 57-61
Carpenter S., Mooney H. (2009) “Science for managing ecosystem services: Beyond the Millennium Ecosystem Assessment”[online] PNAS, Volume 106, Issue 5, Pages: 1305-1312,
Jung V., Violle C. (2010) “Instraspecfic variability and trait-based community assembly”[online] Journal of Ecology, Volume 98, Issue 5, Pages 1134-1140, Available at:
Laforest-Lapointe I., Martinez-Vilalta J. (2014) “Intraspecific variability in functional traits matters: case study of Scots pine” [online] Oecologia journal, Volume 175, Issue 4, Pages 1337-1348,
Lavorel S., McIntyre S., Landsberg J.(1997)”Plant functional classifications: from general groups to specific groups based on response to disturbance”[online] Trends in Ecology & Evolution, Volume 12, Issue 12, Pages 474-478
Mason N., Mouillot D. (2005) “Functional richness, functional eveness and functional divergence: the primary components of functional diversity”[online] Oikos, Volume 111, Issue 1, Pages 112-118
Perez-Harguindeguy N., Diaz S., Garnier E., (2013) “New handbook for standardised measurement of plant functional traits worldwide”[online] Australian Journal of Botany, Volume 61, Pages: 167-234,

Our Service Charter

  1. Excellent Quality / 100% Plagiarism-Free

    We employ a number of measures to ensure top quality essays. The papers go through a system of quality control prior to delivery. We run plagiarism checks on each paper to ensure that they will be 100% plagiarism-free. So, only clean copies hit customers’ emails. We also never resell the papers completed by our writers. So, once it is checked using a plagiarism checker, the paper will be unique. Speaking of the academic writing standards, we will stick to the assignment brief given by the customer and assign the perfect writer. By saying “the perfect writer” we mean the one having an academic degree in the customer’s study field and positive feedback from other customers.
  2. Free Revisions

    We keep the quality bar of all papers high. But in case you need some extra brilliance to the paper, here’s what to do. First of all, you can choose a top writer. It means that we will assign an expert with a degree in your subject. And secondly, you can rely on our editing services. Our editors will revise your papers, checking whether or not they comply with high standards of academic writing. In addition, editing entails adjusting content if it’s off the topic, adding more sources, refining the language style, and making sure the referencing style is followed.
  3. Confidentiality / 100% No Disclosure

    We make sure that clients’ personal data remains confidential and is not exploited for any purposes beyond those related to our services. We only ask you to provide us with the information that is required to produce the paper according to your writing needs. Please note that the payment info is protected as well. Feel free to refer to the support team for more information about our payment methods. The fact that you used our service is kept secret due to the advanced security standards. So, you can be sure that no one will find out that you got a paper from our writing service.
  4. Money Back Guarantee

    If the writer doesn’t address all the questions on your assignment brief or the delivered paper appears to be off the topic, you can ask for a refund. Or, if it is applicable, you can opt in for free revision within 14-30 days, depending on your paper’s length. The revision or refund request should be sent within 14 days after delivery. The customer gets 100% money-back in case they haven't downloaded the paper. All approved refunds will be returned to the customer’s credit card or Bonus Balance in a form of store credit. Take a note that we will send an extra compensation if the customers goes with a store credit.
  5. 24/7 Customer Support

    We have a support team working 24/7 ready to give your issue concerning the order their immediate attention. If you have any questions about the ordering process, communication with the writer, payment options, feel free to join live chat. Be sure to get a fast response. They can also give you the exact price quote, taking into account the timing, desired academic level of the paper, and the number of pages.

Excellent Quality
Zero Plagiarism
Expert Writers

Instant Quote

Single spaced
approx 275 words per page
Urgency (Less urgent, less costly):
Total Cost: NaN

Get 10% Off on your 1st order!