Análisis descriptivo de los datos de FIV/ICSI

Although woodlands in the UK are not faced with the same threats as many other regions of the world, such as large scale deforestation or wildfires, there are still many challenges that exist when attempting to sustainably manage such a significant resource. In light of the global concern for anthropogenic climate change, the UK Government issued a legally binding target to reduce the net UK carbon account by 80% in 2015 from the 1990 baseline (Climate Change Act, 2008). To assess these targets in a forestry context, and as a national response to the IPCC 4th Assessment Report, the Forestry Commission produced a UK based assessment compiled by leading experts in forestry and climate change chaired by Professor Sir David Read, commonly known as ‘The Read Report’ (Read et al., 2009). This independent assessment examined the potential of UK woodlands to mitigate and adapt to our changing climate, and described how the impacts of climate change are becoming apparent in UK woodlands with effects on productivity, tree condition, leaf emergence, soil function, fauna and flora, and forest hydrology. However, the report noted that there is uncertainty about the likely severity and extent of these impacts (Read et al., 2009). Several projected trends, supported by the UK Climate Projections by the Met

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Office (UKCP09) for the UK were identified which would impact woodland vegetation growth:

 Increased temperature, lengthening of growing seasons, and rising CO2

concentrations

 Increased precipitation in winter

 Increased frequency and severity of summer droughts  Pests and diseases of forest trees representing a major threat

The report concluded that “clear, robust, research programmes” will be required to

underpin the changes of forestry policy and practice to meet the challenges of the changing climate (Read et al., 2009). However, an extensive body of literature provides compelling evidence that the climate has already changed considerably over the past fifty years and has affected the timing of vegetation phenophases (IPCC, 2013). In temperate regions, air temperature is considered to be most closely related to the phenological shift of vegetation (Menzel et al., 2006).

Sparks and Gill (2002) report changes of spring activity of several plant and animal species advancing by up to a month, and more marked in the UK than elsewhere in Europe. The Read Report documented that in the UK the leafing date has advanced by two to three weeks since the 1950s (Read et al., 2009). The Forestry Commission confirm a clear temporal advancement in phenology for some species (Ray et al., 2010).

Figure 2.4 suggests that leafing of pedunculate oak trees in Surrey is now around 25 days earlier than in the 1950s and has advanced by approximately 6 days for every 1°C increase in spring temperature (Ray et al., 2010). However, the large variability in the data is clear and this may be attributed partly to the fact that the data is based on subjective visual observations. These studies highlight that spring phenology has responded to recent climate change in some measurable way, although large uncertainties remain as to how phenology will respond to projected future climate change such as scenarios depicted in UKCP09.

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Figure 2.4. First leafing date of pedunculate oak trees (Quercus robur) in Surrey (source:

Ray et al., 2010).

In the last decade the value of phenological data, particularly in climate change research, has been fully recognised. In 1999 (and reviewed in 2003), the timing of budburst of oak was identified as an official UK Government indicator of climate change (indicator 25 of 34) based on data from the UK Phenology Network (Cannell et al., 1999; Cannell et al., 2003). Climate science and the changes in vegetation phenology have entered more into public consciousness with the release of IPCC reports and media attention although the study of phenology has in fact a long history, in Europe dating back to early 1700s, with most developed countries having a recording scheme by 1850-1950 (Sparks & Menzel, 2002). This recent increase in public and scientific interest is marked by the emergence of a number of research and monitoring projects in the UK such as the UK Phenology Network (http://www.naturescalendar.org.uk/), the UK Environmental Change Network (http://www.ecn.ac.uk/), and the establishment of a UK-based International Phenology Garden (IPG) (http://www.forestry.gov.uk/fr/INFD-5ZZLRE). The IPG program was established in 1959 in Europe and the scheme uses cloned plants to minimise genetic variability (both within and among populations) to observe the timing of phenophases in a set of chosen species. An IPG site was established at Alice Holt Forest in Surrey, a long- term monitoring and experimental site of Forest Research UK, providing a useful international dataset. However, the scheme has received criticism for being unrepresentative of wild-grown native plants, which may be locally adapted to environmental conditions (Richardson et al., 2013).

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2.3.1 Vegetation phenological monitoring by visual observations

Traditional methods of phenological data collection involve direct human visual

observation of discrete phenological events, for instance, noting the date at which a certain tree shows the first sign of budburst. There are several accepted protocols available which provide guidance for observations (such as Koch et al., 2007, Miller-Rushing & Primack, 2008, and the IPG protocol). However, variations in definitions, criteria, sampling

methods, and frequencies, often make the data difficult to compare (Denny et al., 2014). More recent methods, such as the protocol employed in the National Phenology Network in America (USA-NPN) phenology observation program, Nature’s Notebook

(www.nn.usanpn.org), also include an intensity/abundance measure (e.g. percentage of buds open) (protocol described in Denny et al., 2014). However, estimating, or even being able to visualise, these fine scale changes in tall heavily occluded tree canopies poses obvious challenges.

Furthermore, all these methods are subject to the observer’s skills and experience and only representative of the specific organism observed in the local site conditions. The observer can change from year to year, as can the plants measured, the amount of occlusion of the canopy, and day of year surveyed. Despite these significant limitations, the method of visual observations is still commonly adopted today and has been used to provide evidence to the IPCC and Read Report (IPCC, 2007; 2013; Read et al., 2009).

The resultant data can best be described as a descriptive summary of phenological change and a requirement exists to quantify and gain more detailed information about vegetation growth dynamics to match the level of detail in carbon studies (such as Figures 2.2 and 2.3). This would ensure that these important interactions are accurately reproduced by models and further understood by forest managers, ecologists, and climate scientists.

2.3.2 Phenological modelling

There are two main model frameworks for phenological information: those that are used to predict the onset of a defined phenological event (usually budburst), and those that predict and analyse long term climatic data which incorporate phenology data as a primary input and/or a projected output.

The phenological stages of woodland phenology can be represented by a transitional date describing a discrete time where one phase ends and the next begins; for example budburst

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signals the break of dormancy and the onset of leaf expansion. Models have been developed to predict these dates based on climatic conditions in order to forecast (and recreate past events) large area climate change impacts on phenology (such as Morin et al., 2009) and to represent the seasonal course of foliage development and senescence, and associated physiological activity (Richardson et al., 2012). Numerous models exist for predicting the onset of budburst based on temperature, such as the Bud Dormancy Release Model by Seeley (1996). The Forestry Commission research branch, Forest Research UK, have developed a budburst model for oak using day length and temperature, based on Hänninen (1990); the model uses observational data collected at IPG sites. Good agreement has been found between predicted and observed dates when datasets from multiple sites are combined, although variations in “observer performance” are noted (Forest Research, 2013), highlighting the issues raised in Section 2.3.1.

Numerous complex and sophisticated climatic models exist that are used to predict future climate scenarios and project likely environmental impacts, such as the Atmosphere-Ocean General Circulation Models (AO-GCMs), which have formed the core of IPCC report climate projections (IPCC, 2013). However, many of the land-atmosphere interaction models do not place sufficient emphasis on accurately modelling vegetation phenology or the seasonality of ecosystem processes (Richardson et al., 2012); a factor that was reflected in the latest IPCC report for two key studies. Firstly, Pitman et al. (2009) compared the impact of land use change according to seven climate models which showed a wide range of results. It was reported that these discrepancies were “...mostly due to different

assumptions on ecosystem albedo, plant phenology and evapotranspiration” (IPCC, 2013 ch8 pp32). Secondly, a study by Schwalm et al. (2010) found a difference between observations and simulations of ten times the observational uncertainty when comparing 22 terrestrial carbon cycle models to simulate the seasonal dynamics of land-atmosphere CO2 fluxes from 44 eddy covariance towers. Again, poor simulation of spring phenology

was listed in the model shortcomings (IPCC, 2013).

In another example, three carbon-climate models were examined (HadCM3LC, IPSL- CM2-C, and IPSL-CM4-LOOP) against measured CO2 in the atmosphere to reproduce

global growth rate, seasonal cycle, and the El Niño–Southern Oscillation, it was found that two out of the three models generally underestimate seasonal amplitude and suggests uncertainty in describing vegetation phenology (Cadule et al., 2010). The Joint UK Land

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Environment Simulator (JULES) land surface model, developed using UKCP (2009), and the Met Office HadCM3, acknowledges vegetation phenology as an important factor (Clark et al., 2011). In the current JULES model, phenology is characterised by scaling the maximum annual LAI by a temperature factor. When compared to using daily MODIS LAI, only very small improvements were observed (Slevin et al., 2015).

An important consequence of the poor representation of phenology in model simulations is that phenology, particularly budburst, drives primary feedbacks to the climate systems between vegetation and the atmosphere, and therefore uncertainty in the prediction of these events can feed forward to generate uncertainty in estimates of carbon and water cycling (Migliavacca et al., 2012; Richardson et al., 2013).