Study sites
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His previous appointment was as researcher in School of Civil & Environmental Engineering of Nanyang Technological University of Singapore where he studied for his PhD during 2008-2011. His research is predominantly focused on hydrological modeling and flood forecasting using artificial intelligence techniques. Most recently, he has been also involved in research projects dealing with sustainable urban water management. To date, he has published over 50 articles in reputable journals and international conference proceedings. He has supervised several PhD and Master students and won the Supervisor of the Year Award in Monash University Malaysia in 2017. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"878",title:"Phytochemicals",subtitle:"A Global Perspective of Their Role in Nutrition and Health",isOpenForSubmission:!1,hash:"ec77671f63975ef2d16192897deb6835",slug:"phytochemicals-a-global-perspective-of-their-role-in-nutrition-and-health",bookSignature:"Venketeshwer Rao",coverURL:"https://cdn.intechopen.com/books/images_new/878.jpg",editedByType:"Edited by",editors:[{id:"82663",title:"Dr.",name:"Venketeshwer",surname:"Rao",slug:"venketeshwer-rao",fullName:"Venketeshwer Rao"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4816",title:"Face Recognition",subtitle:null,isOpenForSubmission:!1,hash:"146063b5359146b7718ea86bad47c8eb",slug:"face_recognition",bookSignature:"Kresimir Delac and Mislav Grgic",coverURL:"https://cdn.intechopen.com/books/images_new/4816.jpg",editedByType:"Edited by",editors:[{id:"528",title:"Dr.",name:"Kresimir",surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"41997",title:"Climate Change Impact on Tree Architectural Development and Leaf Area",doi:"10.5772/51510",slug:"climate-change-impact-on-tree-architectural-development-and-leaf-area",body:'The response of forests to the forecasted increase in climate stress occurrence is considered a key issue in climate change scenarios [1]. Although forest productivity increased in most ecosystems during the 20th century [2,3], a review by Allen et al. [4] underlined an emerging trend of heat and drought induced forest decline and dieback at global scale. Several and generally combined physical and biological causes contribute to observed tree decline or die-off [4-7]. Apart extensive insect outbreaks [8], understanding the respective role of hydraulic failure and carbon starvation due to excessive or long lasting water stress is one of the major research goal in order to predict forest response to climate change [9].
The consequences of climatic events on forest health can be immediate but are often delayed up to 5 to 10 years [5,10], and may be significant for decades and sometimes irreversible on tree growth [11]. Recent studies on tree architectural development and primary growth suggested that the long lasting impact of repeated droughts on tree crown development could be one of the causes of these delayed effects [12-14].
Primary growth corresponds to the creation of new tissues outside existing organs, and includes bole, branch and root length growth, branching (birth of new branches or roots), creation and growth of leaves or needles and rootlets, flowering and fruiting [15,16]. It is therefore fully linked to plant architectural development patterns and processes. In contrast, secondary growth for trees corresponds to the radial growth of existing branches, bole and roots. In single trees and forests, although secondary growth usually exceeds primary growth and leaf production [17], the total amount of biomass allocated to primary growth may be very important [18]. As an example, leaf and fruit production measured through litter bags in French adult broadleaved stands (mainly beech and oak) reached 20 to 40% of wood production by stems [19]. The relative allocation to new shoots was not correctly assessed up to now but it can be inferred from leaf production and the leaf mass fraction (LMF), ratio between leaves and whole twig mass. In a recent study, twig wood/leaf biomass ratio was found to reach from 25 to 50% and from 50 to 75% during respectively dry and humid years for Pinus halepensis [20] which means low LMF values (25 to 75%). However, LMF was generally higher on dry sites in south eastern France: 40-70% for Abies alba [21], 70-80% for Quercus ilex [22]. It was found to vary between 80 and 90% for 107 Chinese species at various elevations [23]. As a whole, primary growth may represent between 25 and 70% of secondary growth. But except for tree height growth, scant literature exists on the relationship between tree primary growth processes and climate change or accidents, whatever the species, and plant architecture is commonly neglected in climate change impact studies.
The mediterranean climate is characterized by high temperatures associated with low rainfall in summer, drought being the main environmental constraint for vegetation growth [24]. For the 21st century, climatic models forecast that the Mediterranean basin will be prone to a faster warming than most other continental areas over the world, associated with a reduction of rainfall during the growth season [1,25]. Therefore, this area is a good place to detect and model any climate change impact on vegetation, all the more since a rapid decline in precipitation and higher temperatures were already noticeable in parts of this basin [26,27]. In Southeastern France, the period 1998-2007 was characterized by mean annual temperature and mean summer temperature 0.9°C and 1.3°C above the 30-year average (figure 1) Moreover, eight to ten of the twelve hottest years since 1850 were recorded during this time lapse [28] which give a foretaste of the climate forecasted for the next decades. In addition strong climatic events also recently occurred such as the 2003 heat
Average annual precipitations (grey bars) and temperatures (black line) in Font-Blanche since 1995. Horizontal lines are 1961–2010 average, grey line = mean rainfall, dotted black line = mean temperature.
wave which significantly impacted French Mediterranean forests as well as most of Europe [29]. Such extreme climatic events are likely to become frequent with global warming [1,30]. Scorching heat had direct and delayed negative effects on tree growth, especially on pine species [31]. The resulting increase in summer and spring water stress may reduce tree growth in Mediterranean areas [32-35]. Raising temperature may also lead to phenological lags [36], particularly in the beginning and end of the growth season, with direct consequences on some primary growth processes and architectural development such as polycyclisme and branching rates [37,38].
This study aimed at quantifying the influence of recent climatic trend and events, particularly intense heat and drought, on the primary growth and architectural development of six conifers and one broadleaved species growing in Mediterranean plains (Pinus halepensis, P. pinea, P. pinaster, Quercus ilex) and mountains (P. nigra, P.silvestris, Abies alba). The three last ones are at the lower limit of their distribution area in southern France. One of the final goals was to model the direct and delayed effects of climatic accidents on tree leaf area in order to help assessing the resulting risk in terms of decline and die-back.
The study area included 8 sites distributed between 80 and 1400 m of elevation, from the coast to hinterland mountains of Provence-Alpes-Côte d\'Azur region in south-eastern France (figure 2).
Study area and studied sites.
Nearly 5150 twigs from 1050 branches of 210 trees and 7 species were sampled between 2005 and 2011 (Table 1). Their architectural development was retrospectively measured from morphological markers (figure 3) over a period of 15 to 25 years. For each tree, the sampling design considered separately three thirds of the crown (top, middle and base), branch orientation (north and south), but also branch hierarchy (principal or secondary axis – figure 4) and branch vigor. Secondary axes were chosen according to their relative vigor (strong vs weak axes) within the branch they belong to (figure 4). Twig absolute vigor for each species was later split in three groups of equal number (vigorous, medium, frail) according to their total length growth in the last three years before sampling date.
Site name | Species (number of trees) | Altitude (m) | exposition | Dates of mesures |
Saint Mitre | PH (11) QI (6) | 80 | Flat | 2008-2009 |
Font-Blanche | PH (58) QI (34) | 420 | Flat | 2005-2011 |
Siou Blanc | PH (11) QI (6) | 650 | Flat | 2008-2009 |
Sainte Baume | PS (5+5+5), PM (5) | 950 | North | 2005-2006 |
Sainte Victoire 1 | PS (5); PN (5) | 650 | North | 2009-2010 |
Sainte Victoire 2 | PM (5); PP (5) | 500 | Flat | 2010 |
Trigance | PS (5) | 1000 | Flat | 2005-2006 |
Courchons | PS (5) | 1350 | North-east | 2005-2006 |
Ventoux | PS (5), PN (10), AA (19) | 1100 to 1400m | North | 2009-2010 |
Study sites
When present, 5 to 10 needles were randomly chosen from the base to the end of each twig and all around it to measure their length and width. Needle number per twig was counted on a subsample of twigs (1/3) with consideration of missing needles which were counted using their scars on the twig. As needles are lined up in three to five lines or spirals along the shoot, counting needles along one or two of these lines or spirals and then bulking up the count proved to be a very reliable assessment (error < 5%)
In order to bridge primary and secondary growth, ring width was measured for all studied trees. Two cores per tree were collected perpendicularly at 1.3 m height. Ring widths of each core were measured using a micrometer (±0.002 mm, Velmex Inc., Bloomfield, NY). Some trees were also logged for stem analysis and rings were counted along 4 perpendicular directions. Ring width series were firstly cross-dated and standardized with the classical methods of dendroecology, to remove age-related tendencies from the growth curve and to obtain a homogenised variance. Then elementary raw and detrended series were respectively averaged for each tree and master chronologies were constructed for each species and for each plot by averaging tree series.
For Pinus halepensis and Quercus ilex, a follow-up of phenology and architectural development was performed twice a month from 2008 to 2011 on one site (Font-Blanche) to understand their relationship with climate and their interrelations. Branches and twigs were chosen following the same protocols than for architectural studies.
Morphological markers used for twig growth reconstruction in conifers. All growth units start by sterile scales, small and clustered on the first one, larger and spaced out on the following ones in case of polycyclisme (mainly Pinus halepensis and P. pinaster). Male flowering (left): male flowers appear at the base of the first annual growth unit over sterile scales for pines. The scars they left on the twig are generally different from needle scars. Female flowering (right): cones (with very few exceptions) appear at the top of the first annual growth unit. For pines, cones or their peduncles remain a long time on the branch or leave a specific scar. The presence of at least one branch or of a whorl indicates the limit of a growth unit for pines, but some growth units may be branchless. For firs and oaks, intermediate branches may appear, during all the branch life. A given pine twig never bears male and female flowers the same year. For Quercus ilex, a pseudo-whorl of branches indicates the limit between two annual shoots. The retrospective analysis of branch growth is far more difficult than for conifers.
The observed variations of architectural parameters, needle number and needle size were integrated into a 2D-model of pine branch architectural development to simulate the impact of climate on pine total leaf area (figure 5c). We designed the model for the more complex of studied conifers: Aleppo pine (Pinus halepensis). Aleppo pine gives potentially the higher number of growth units per year, so that the model can easily be simplified for other species. In a first attempt we considered medium vigor branches located in the middle part of the crown as representative of the average branch of a tree. Parameters for each twig category (principal and secondary axes, vigor, medium and frail axes) were implemented according to scenarios of successive years considered as "normal" or "bad" (defined afterwards;\n\t\t\t\t\t\tfigure 5 a -b, table 2). As pine architectural development for a given year is partly to fully pre-determined by the climate of the previous year, the impact of bad years on polycyclism and the number of needles are delayed compared to the impact on leaf size.
Twig sampling. Five axes are measured on each branch: the principal axis and two pairs of secondary axes one weak and one strong by pair five years-old and 10 years-old. The classes "weak" and "strong" are relative to each other in the concerned pair and their absolute vigour depends on branch vigour.
Example of the development of a medium vigor secondary axis of Pinus halepensis without (a) or with (b) 1 to 3 bad years. Example of a middle crown / medium vigor branch (principal and secondary axes) and development after 7 years with 4 successive bad years. The model includes strong and weak secondary axes and 3 classes of twig vigor. Color changes each year along each axis: blue and green for good years, orange and red for bad years.
At each step of branch development and at the end of each year, active twigs (with needles) could be counted and sorted by vigor. The number and size of needles per active twig was set according to table 2. Total needle surface (length*width*needle number) was calculated for each twig and bulked up for the whole branch.
This model was used to simulate branch growth for 10 years, as all parameters for secondary axes were obtained for this time span. For longer periods, the interaction and competition with neighboring branches, twig self pruning, branch aging and accidents may significantly change these parameters, so that a 3D model taking these interactions into account is necessary.
For Abies alba, some specific sampling and analyses were made to compare trunk, lateral axes and ring width responses to climate. Trees were sampled at 3 different elevations (1150, 1250 and 1350m) [26]. For 14 trees, annual shoot length was measured on the trunk. Laterals axis sampling and measurements followed the same protocol as other species.
As most architectural and growth parameters slowly evolve with branch aging, it was necessary to remove this natural trend. This was systematically done for each parameter using the difference measured at equal cambial age for branches of respectively top vs middle and middle vs base of the crown, for the period 1995-2000 considered as accident-free (figure 8, method in references [12,37]).
To quantify inter-annual variability between traits, an individual detrended coefficient of variation (dCV), for the period 1990-2010, was computed, for each trait of each tree, as follow: (i) individual trend was removed by taking the residuals of the linear or non-linear model with time as explanatory variable and (ii) the standard deviation of the detrended sequence was divided by the raw sequence mean (i.e. the mean trait value for each tree).
Thus, the detrended coefficient of variation of trait j for tree i can be written:
For a global assessment of the relationship between growth, architectural parameters and climate, a Principal Component Analysis (PCA) was performed considering years as observations and all detrended architectural and growth parameters as variables, species by species. PCA was also used to help sorting good years (favorable climate for tree growth) and bad years (figure 7). As some parameters were not common to all species (polycyclism, male flowering, needle number), each PCA was performed with and without these variables to check the stability of years and variables in PCA planes. Needle length was not always available for the same period than other factors. Thus each PCA was also performed with needle length for available years and without needle length on the whole studied period (1995-2010).
All growth and architectural variables were averaged per species for bad and normal years. Bad years were defined as the four worst years in the 2003-2008 period for each individual variable. All other years were merged to compute the data for "normal years": as exceptionally low values due to repeated severe drought were excluded, we considered other data as normally good, mean or bad, representative of the normal interannual variability.
Partial least square (PLS) regressions were used to investigate relationships between architectural or growth parameters and climate. This method was chosen because it handles many variables with relatively few observations [39] and deals with correlated variables [40]. The number of significant PLS components was chosen by a permutation test [41] with a 5% threshold for the explained variance. Variables were tested with a 1000-step cross-validation [42]: they were retained only when the confidence interval (p<5%) for their partial correlation coefficient excluded zero. According to the phenology of the species in South-eastern France, climatic monthly parameters tested in each PLS were rainfall (P), maximum temperature (MaxT), minimum temperatures (MinT) and mean temperatures (MT) from January of previous year (n-1) to November of current year (n) over the period 1995–2010 [43,44]. The low number of observations (16) and high inter-annual variability of climate made grouping monthly climatic parameters necessary to obtain significant variables. We grouped the successive months having same signs for their individual partial correlation coefficients (sum of precipitations, average temperature). To compare exposition, position, status and vigour classes for each growth variable, normality was checked using a standard Shapiro-Wilks test. When the distribution was normal, a variance analysis and a multiple comparison test were performed to look for significant differences globally and further compare the different classes two by two. When the distribution was non-normal, these comparisons were performed respectively by a Kruskall-Wallis test and a Nemenyi test [45].
For all species, most growth and architectural variables showed decreasing values in the last 15 or 20 years, and also from the top to the base of the crown (figure 6.a). After detrending with the comparison between branch position in the 1995-2000 period (figure 6.b), their decreasing rate from 2000 was always faster than the natural trend and showed a deep trough lasting 2 to 5 years after 2003 or 2004 (figures 8-12 and\n\t\t\t\t14).
Pinus sylvestris annual branch length growth at Sainte Victoire for the top, middle and base of the crown (respective branch age 15, 25 and 35 years), for the same period (6.a) and with a 10-year shift (6.b) giving the natural trend of growth slowdown with age. Trees are approximately 60 year-old and measured branches are not competing with neighbouring trees.
Whatever the species and variables used, PCA axis 1 and 2 were dominant with respectively 50-70% and 17-32% of explained variance, far over Axis 3 (4-12%). PCA results were highly coherent between species for the distribution of years in 3 groups (figure 7): bad years (2004 to 2007) and good years (1995 to 1998) were stable across all analyses, other years being more variable, generally in intermediate situation but sometimes good or bad (2003 and 2008). Some variables were stable for most species: shoot length, polycyclism and needle number were correlated with Axis 1 and between each other. Fruiting rate and needle length were better correlated to axis 2. Male flowering was available for Pinus halepensis and P. sylvestris only and was linked to the occurrence of bad years. Ring width occupied a variable position between axis 1 and 2 according to species. No noticeable difference was observed in year ranking or inter-variable correlations for a given species when PCA was performed with a variable number of years to include needle length.
The period 2004-2007 was characterized by a reduction of all growth and architectural parameters: shoot length, ring widths, needle length and number, and branching rate (figures 6 and\n\t\t\t\t8 to 14). Production of female reproductive organs was also disfavored during this period while male flowering twigs were more numerous, particularly in the middle and top crown. This PCA approach indicated that most growth and architectural parameters were inter-correlated, but figure 8 shows time lags in the response to bad years and recovery. For example, the original position of 2007 in the PCA plane for Abies alba is due to the high value of needle length in 2007 (figure 8) while all other variables did not recover so fast, particularly branching rate.
PCA plane for Abies alba (left) and Pinus halepensis (right) with years and variables: SL = shoot length, NL = needle length, Ra = ramification (branching rate), Rw = ring width, GU = number of growth units (polycyclism), NN = needle number, Fr = fructification, MF = male flowers. In red: bad years, in blue, good years.
Evolution of detrended and standardized growth traits of Abies alba showing the consistent fall in the heart of the 2003-2007 climatic accident but time lags in their response to climatic variations and recovery after 2006.
Branching rate, one of the important architectural development indicator, is a good example of the common pattern between all species (figure 9). Differences were observed in the response to individual years and in the speed of recovery after the lower values, but the global trend was similar.
Branching rate (undetrended) on principal axes of the 6 studied conifers. PA = Pinus halepensis, PM = P. pinaster, PP = P. pinea, PN = P. nigra, PS = P. sylvestris, AA = Abies alba
Polycyclism, a fundamental growth trait for some pines species, confirmed this pattern (figure 10). It influences branching rate as each growth unit may give birth to new branches. This is why these two parameters are highly correlated (figures 9 and\n\t\t\t\t10).
Polycyclism rate of branch principal axes for the two polycyclic pines, P. halepensis (left scale) and P. pinaster (right scale)
All architectural variables were positively correlated to branch vigour. Figure 11 shows the example of needle number for P. halepensis according to branch vigour. The difference between the 3 classes of vigour was always significant all years in the aggregate, and also for most individual years.
Number of needles per annual shoot for Pinus halepensis according to twig vigour.
The relative fall of growth and architectural variables after 2003 was generally more severe for vigorous and principal axes and at the top of the crown than on weaker and secondary axes and in the middle and bottom of the crown (figures 6, 11\n\t\t\t\tand\n\t\t\t\t12). Between 2004 and 2007, during 1 to 4 years according to species and variables, there were no longer significant differences according to branch vigour and hierarchy, and sometimes between positions in the crown. This higher relative sensitivity was also visible in a faster or better recovery: for most variables and all species, low and weak axes started recovering one or two years after top and vigorous ones and sometimes showed no significant increase up to 2010 (figure 11). However, the detrended coefficient of variation was not always significantly different between trunk and branch principal or secondary axes length growth, e.g. for Abies alba (figure 12). Ring width proved to be less variable than shoot length in Abies alba, but not in Pines, particularly because of their sharp decrease after 2003 and their high sensitivity to some accidents due to heavy snow falls.
a - Abies alba trunk and branch detrended length growth (LG). Each series starts with its first real value. b - Detrended coefficient of variation (dCV) “beanplot” of the mean value (black lines), the kernel density function (in grey) and the raw values (white lines with size proportional to the number of measurements stacked. Letters summarize the results of a pairwise comparisons using Wilcoxon rank sum tests (P=0.05).
Although branch vigour was correlated to branch hierarchy and position within the crown, each of these factors significantly influenced branch architectural development (figure 13). For the same vigour (same mean length growth during the last 3 years), a branch had higher values on branch principal axes than on secondary axes and on axes of following orders, and decreasing values from the top to the base of the crown. Vigour, hierarchy and position were always highly significant (P<0.01%). South-exposed branches had sometimes higher values than north-exposed ones, but the difference was rarely significant (P<5%) and always at the very limit.
Needle length was highly variable from one year to the other (figures 7 and\n\t\t\t\t14). It was severely affected by 2003 heat wave for all species, loosing from 25 to 45% on previous years average and recovered only slowly. According to species and sites, 4 to 8 years were necessary to regain normal values (mean of 1995-2002 values when available, or values from literature and herbariums: see reference [12]).
For Pinus nigra and Abies alba, 2006 and 2007 respectively were the first years after 2003 to reach normal values, but needle length further decreased again to significantly lower values. Pinus halepensis and Pinus sylvestris needles remained under normal values up to 2010.
Although we only have short series of data for Quercus ilex, it seems to follow the same trends as conifers (figure 15). Individual leaf area remained very low in 2009 compared to normal values for the French Mediterranean area, but inter-individual variability is very high and prevents assessing the normal values without older references on the same trees.
Mean relative weight of branch vigour, hierarchy (principal vs secondary), position (low, middle, top of the crown) and orientation (north vs south) in the determination of branching rate, polycyclism when relevant and needle number and length for the 6 studied conifers. The bars corresponds to the mean partial correlation coefficient of PLS regressions for each growth and architecture parameter and each species. Stars indicate the level of confidence: *** P<0.01%, * P<0.5%.
P. nigra needle length for branch principal axis in Mount Ventoux. Vertical bars indicate 2 standard deviation. Letters summarize the results of a Nemenyi test (P=0.05). Years sharing one letter are not significantly different. <2002 = mean values from all previous years (few samples) and from literature and herbariums for the study area.
Table 2 presents Pinus halepensis needle mean size and number according to axis vigour for good and bad years, and the resulting leaf area per twig. Leaf area for a given twig decreases with time due to accidents, parasites and aging. Survival rates measured in our plots (at the bottom of the table) varied according to twig vigour: needles remained longer on frail twigs than on vigorous ones.
These values were used to compute the total leaf area of a branch during 10 years with and without a 4-year accident, corresponding to the four worst years observed for many variables in this study (figure 6). According to the branch model, the deficit of active twigs (carrying needles) and of leaf area amounted respectively to 59 % and 78 % for Pinus halepensis compared to the values simulated with only normal years and average parameters (figure 16). This deficit was only slowly absorbed: it remained close to 30% and 40 % respectively two years after the end of the accident and disappeared only after 5 years.
Quercus ilex growth at Font-Blanche.
Axis vigor | vigorous | medium | frail |
needles number per twig | |||
normal year | 69 | 59 | 49 |
bad year | 52 | 38 | 28 |
needles length (mm) | |||
normal year | 81 | 71 | 65 |
bad year | 67 | 54 | 42 |
Needle width (mm) | |||
normal year | 0.9 | 0.8 | 0.6 |
bad year | 0.75 | 0.65 | 0.55 |
Needle surface (mm²) | |||
normal year | 72.9 | 56.8 | 39 |
bad year | 50.25 | 35.1 | 23.1 |
Leaf area per twig (mm²) | |||
normal year | 4995 | 3357 | 1919 |
bad year | 2601 | 1351 | 645 |
Needle number and size and leaf area according to twig vigor and climate for Pinus halepensis.
Evolution of the relative deficit of active twigs and total leaf area for a branch of Pinus halepensis submitted to a 4-year long climatic accident (2nd to 5th year), compared to a branch developing with mean climate parameters.
Ontogeny and axis morphogenetical gradients
Most of the studied morphological traits present a progressive decreasing trend along time (figures 6, 9, 10, 11 and 12). This decrease corresponds to a morphogenetical gradient named axis drift [15,46,47]. Morphological traits values are also driven by axis vigor, hierarchy and position within the crown (figure 13).
Theses endogenous constraints can be viewed as a variational module sensu Wagner et al. [48] that constraints any independent trait variations and thus partly explain the strong covariations found between morphological traits (figures 7 and\n\t\t\t\t\t8).
Pre-induction of the primary growth characteristics (and when relevant of several flushes) in buds induces a strong dependence of primary growth on the global health status of trees and branch vigour at the time of bud formation, i.e. in previous year. Except in case of successive intense stress or extreme events, tree vigour and health rarely sharply changes between two years as trees can use non-structural carbohydrates stored in the stem and branches for growth and respiration. Such an autocorrelation between growth units is well known in ring width series [5,49,50] and was logically found for primary growth in this study.
Climatic effect on primary and secondary growth\n\t\t\t\t
Climatic effect on tree growth are generally analyzed using classical dendroclimatic analyses based on tree-ring data [51]. They usually conclude that tree radial growth is affected by continuous changes in climatic conditions (trends) and by strong climatic events [3,26,52]. Height growth was more occasionally used as indicator due to time-consuming measurements in the field, but gave reliable results [53]. This study revealed that a temporal survey of branch elongation and architectural parameters is of interest to this aim.
The occurrence of successive drought years between 2003 and 2007 led to a clear fall in all growth and architectural parameters: branch length and tree height growth, branching rate and polycyclism, needle number and needle length reached very low values during two to five years. These reductions could be clearly attributed to climate as the natural trends induced by branch or tree aging were slower, and all parameters finally recovered, at least partly, with more favorable climatic conditions.
As an extreme event with deleterious effects on forest health and productivity throughout Europe [54] and on studied species in Southeastern France [13], the 2003 summer heat-wave was supposed to have deeply impacted tree architectural development and growth. The direct impact of 2003 was mainly visible on needle length and individual leaf area (figures 8 and\n\t\t\t\t\t14), on ring width and to a lesser extent on some parameters of Abies alba (figure 8). Leaf development and ring width were stopped very early at the end of spring due to extreme water stress. But for most other parameters and species (figures 8 to 12), 2003 was a normal or even a good year. The predetermination of most architectural parameters in the buds during 2002 which was a rainy year, and for polycyclic species the ability to add a new growth unit at the end of the year explain that 2003 impact is mainly visible from 2004. But our study cannot accurately assess this impact as 2003 was followed by several very dry years. However, the fact that some of the traits (Pinus halepensis and Pinus pinaster polycyclism and branch length growth, needle length for many species) started or completed their recovery in 2006 or 2007 (figures 8 to 10, 12\n\t\t\t\t\tand\n\t\t\t\t\t14) although they were extremely dry years, could be interpreted as the end of the delayed effects of 2003. This is consistent with the time necessary for all studied pine species to built up a full set of normal needles again after the loss of a large amount of old needles in summer 2003 [31], and to get read of the short needles of 2003. This time could have been also necessary to overcome the disorders caused by hydraulic failure in tree sapwood in summer 2003 [9,55,56].
Intra-specific variability in traits response to climate
All the traits did not respond similarly to climate variability and accidents (figures 8, 12, 15) for a species on a given site. Each of them is driven by many factors, related to climate or to functional relations between organs within a tree.
Needle length is mainly determined by the climate of the year of their development. For polycyclic species, needles of the later cycle can be very short when they lack time to complete their lengthening before the end of the growth season. Conversely, needle width and thickness mainly depend on twig diameter and vigour [57] and therefore, at tree level, on the climate of previous years and more generally on branch and tree health status. Although they are slightly sensitive to climate conditions of their growing year, they do not follow the rapid changes of needle length. Consequently, needle area is a compromise between its length and width which do not vary synchronously. Needle number and branching rate on a given twig are predetermined in the terminal bud of the twig. For monocyclic species, they are fully controlled by the climate of the previous year and by twig vigour. For polycyclic species, several growth units can be predetermined by previous year conditions but additional cycles may be formed later in the growing year according to climate and other constraints [15]. These new growth units can give birth to both needles and new branches, or only needles or branches. Branches are, however, also controlled by the climate of their first growth season: some of the preformed buds remain dormant and young shoots abort in case of unfavourable conditions. The total leaf area at branch level is thus complex to model due to the many factors at stake.
The variable response of traits in time and intensity may also be linked with phenology: secondary growth occurs longer than shoot extension in monocyclic species [58], but the opposite is observed in some polycyclic species when shoot growth occurs late in autumn and even in winter without cambial activity [20]. Early or late climate-related stresses may not have the same impact.
Ring width seemed to present a reduced plasticity compared with annual shoot lengths for Abies alba (figure 12b). This result, poorly investigated in the literature, highlight the critical need of multi-traits approaches to assess the effect of climate change on trees and open questions about tree carbon allocation under stress conditions. Although ring width is known to present autocorrelated series, it was generally mainly driven by the climate of its growth season and the previous winter for studied sites and species [13,21,59].
Recently, Girard et al. [12] found a significant expanded influence of the previous year for Pinus halepensis ring width: rainfall from February to June and temperature from April to September. Moreover, Sarris et al. [60] showed the significant influence of cumulated rainfalls expanding from one to five previous years from the more humid to the driest area of this species distribution range. Thus, climate change should increase the autocorrelation in tree response to climate and make it far more complex in integrating medium term climate variations in each annual growth pattern. The slow response of many growth variables after the 2003-2007 droughts may be a normal adaptation to this arid period and globally to an exceptionally hot and dry climate during one decade in the study area [61].
The inertia of branching patterns, driving leaf number and total leaf area, may explain the increasing length of the integration period with climate aridity.
Inter-specific response variability
Although some differences can be observed in the response of species to inter-annual climate variability, this study showed globally consistent trends in time for all traits and all species (figures 7, 9\n\t\t\t\t\tand\n\t\t\t\t\t10). Discrepancies consist mainly in time lags of one or two years for the lower values in the 2003-2007 periods, and in the speed of recovery after 2007. In some cases, a significant decreasing trend was observed from 1998 or 2000 for some species, while in the same sites the other species showed no fall before 2003. Inter-specific differences seamed relatively higher before 2003 than during and after the crisis. This proves that species and traits varied resistance to drought or other stresses, which allowed these initial differences, was smoothed by the intensity of the crisis. This conclusion should be tempered as we only present measures for living trees: P. sylvestris and Abies alba mainly, P. nigra to a lesser extent, experienced high rates of die-back in the hinterland. Dead trees could have shown different response patterns.
As already stated, within the six studied conifers, only two (P. halepensis and P. pinaster) present frequent polycyclism that should contribute to a different response pattern to climate change. As illustrated by figure 10, the number of growth cycles within a year present huge inter-annual variations that are directly linked with climatic conditions [37]. Polycyclism can be viewed as a fast way to improve foraging abilities when growth conditions are favourable. On the other hand, late cycles induced by hot autumns and recently observed even in winter in the study area are detrimental to tree health and growth due to frost damages [38,62].
Leaf area deficit vs branching rate\n\t\t\t\t
Tree leaf area is the product of numerous architectural components. It is the result of the number and size of leaves per growth unit and the number of growth units per annual shoot and the branching rate. At tree level, it also depends on competition between branches and between trees, and on crown shape related to age and tree history. At all scales, it depends on twig, branch and tree vigour and health status, not to mention external factors as defoliators and diseases. Up to now, leaf area deficit and tree growth (radial, height, or volume) were the main factors used to quote tree health [63,64]. If leaf area deficit can initially occur as an avoidance mechanism to maintain a favorable water balance by reducing transpiration, it also induces a reduction in carbon assimilation [65]. Consequently leaf area deficit may be the early warning of a sequence leading to tree death [63,66], and could be used to predict tree mortality [67]. But this deficit was always assessed globally without desentangling its distinct causes. In this study, we quantified with our branch model an extreme leaf area real deficit, reaching nearly 80% after 4 very bad years (figure 16). This is far over the "leaf deficit" usually quoted by crown transparency, reaching such an extreme only for dying trees which is far from being the case in our plots. This discrepancy can be partly explained by the reduction of branch length growth and of the distance between leaves or needles along the twigs, which concentrates them in a smaller crown volume.
According to the branch model, during the two first bad years, branch deficit remained under 10% and could not explain the leaf area reduction which reached 35%. Thus, leaf number and size were the main factors at stake. With the lengthening of the drought period, the deficit in branch number became dominant, explaining most of the gap in total leaf area. Finally, during the recovery period after the end of bad years, branching shortage entirely matched leaf area deficit. This is consistent with figures 8 and\n\t\t\t\t\t9 showing that branching rate reached its minimum in 2007 or 2008, after the other variables, and particularly after needle length. Its recovery rate was slower than needle number (figure 11), which also showed a minimum in 2008 for Pinus halepensis. Finally, branching deficit during bad years is probably one of the key issues in leaf area long lasting deficit leading to forest decline.
Functional equilibrium
According to the concept of functional equilibrium [68,69] plants allocate biomass in priority to organs concerned by the most limiting factors [70]: roots if case of nutrients or water shortage, shoots and leaves when their environment is deficient in CO2 or light. Accordingly, plants show remarkable resilience when part of their leaves, branches or roots are destroyed or artificially removed. They generally recover a normal leaf area or root length and biomass in a few years [71]. This may be true when repeated or long lasting climatic stresses reduce first their aerial growth (shoot and needle length) (figures 8 and\n\t\t\t\t\t16), in order to maintain and develop the root system while limiting evapotranspiration. After the release of the stress, tree favors leaf production to reach the balanced level (figures 8 and\n\t\t\t\t\t14) as well as shoot length. This priority in resource allocation to primary growth seams to the expense of secondary growth as indicated by a slower recovery in ring width, as already described by Girard et al. [12] for Pinus halepensis.
Modeling tree responses to climate change and particularly dieback hazard is a key issue since strong changes in tree productivity, survival and recruitment were observed recently [4,63]. A main concern is the assessment of tree vulnerability to increasing drought periods. Empirical models based on statistical relationships are not reliable as they cannot accurately take thresholds and extreme events into account. In contrast, mechanistic models explicitly represent the processes by splitting them into different blocks, which describe the response of the process to some input variables. However the variability of architectural components is poorly represented up to now in process-based models of individual tree growth. Most of them ignore their spatial variations and differentiated temporal response according to axis position in the crown, hierarchy in the branch and vigour. Their improvement with these new findings is urgently needed.
Our analysis made on many sites and species in Southeastern France revealed common patterns of response of tree architectural development to climate change and accidents. The role of long lasting delayed consequences of climate accidents on branching rate, holding back the potential leaf area for years, is one of the key issues to be tackled. Low leaf area, through carbon shortage, may contribute to forest decline and die-back.
This study highlights the necessity of more thorough investigations, in terms of field work and modeling. Our preliminary results must be confirmed for new species and climates and with longer data series to disentangle the multiple and contradictory effects of climate change on tree architectural development.
We would like to thank Christian Ripert, Roland Estève, Willy Martin, Aminata N’Diaye Boucabar, Frédéric Faure-Brac, Maël Grauer, Hendrik Davi, Nicolas Mariotte, William Brunetto and Florence Courdier for their assistance in the field and laboratory work. This research was funded by the French National Research Agency (DROUGHT+ project N° ANR-06-VULN-003-04, and DRYADE project n° ANR-06-VULN-004), the French Ministry for Ecology, Energy and Sustainable Development (GICC–REFORME project, No MEED D4ECV05000007), the Conseil Général des Bouches-du-Rhône (CG13), ECCOREV Research Federation (FR3098), the ‘‘F-ORE-T’’ LTER network and Cemagref.
In delusional misidentification syndromes (DMSs), the individual everlastingly misidentifies persons, places, objects, or events. Capgras syndrome (CS) is the most common in the umbrella term DMS [1, 2]. Perhaps the best known form of DMS is the Capgras syndrome, originally described by Dr. Joseph Capgras and his colleague, J. Reboul-Lachaux, in the early twentieth century [3]. They first encounter this impressive phenomenon when their patient Madame M. insisted that all her friends, family, relatives, and neighbors were being replaced or constantly misperceived as being an imposter [4]. The term l’illusion des sosies (the illusion of doubles) was used to describe the case of a woman who strongly believes that various “doubles” had taken the place of people she knew [3]. It is an essential feature of the Capgras syndrome, the denial of identity of known persons and the delusional belief that this person has been substituted by a double [5].
CS is characterized by the delusional denial of identity of a significant other and the belief that they have been replaced by a double. Some patients with CS may deny the identity of the actual spouse and claim that there are two spouses, the actual and the imposter [6]. Therefore there are four conditions in patient with CS: the person is recognized, and the patient affirms the resemblance of the double to the misidentified significant other; no identity is attributed to the double, who has neither name nor existence; the double is an imposter, pretending to be the original they are replacing; the original has disappeared, his/her absence remaining unquestioned [7].
The rareness of CS, as well as its impressive clinical manifestation as a colorful syndrome, has caused most publications to present case descriptions as scientific curiosities [8, 9]. CS has also attracted the attention of novelists in fictional literature. Dostoevsky provided a dramatic description of the phenomenon in his novel, The Possessed [6]. Sociocultural factors essentially shape the phenomena and thus mightily influence the establishment of definitions of this disorder [11]. Therefore, it may be necessary to mention. The meaning given to the terms ‘change’ and ‘transformation’ of physical identity has been called ‘incarnations’ or ‘possessions’ of other bodies in some cultures [11]. Possessions by an evil spirit have early origins within Paganism, Wicca, Haitian voodoo, Buddhism, Hinduism, Judaism, and Christianity [12]. There is a belief in some countries that people can be possessed by Satan and made to act in strange, immoral, and antisocial ways. In the United States, among European-American Catholics, there exists a belief that demons may possess a person. Possessing demons are presumed to cause experiences of proscribed feelings, thoughts, or behaviors in the person. Occasionally, solutions involve exorcism rituals [13].
It is generally being reported as single case studies in the literature. Although an uncommon psychiatric disorder, Capgras delusion has been central to the development of theories of delusions [6]. It is not dealt with particularly in the DSM-5 and may be classified as delusional disorder, suiting either the persecutory or the unspecified type [14]. With no consensual clinical criteria for this syndrome, it is usual to refer to their original description [7]. The basic manifestation was a false belief that real and familiar persons or oneself is replaced by strange, malicious imposters [15]. In fact, CS is a ‘hypoidentification’ of a person closely related to the patient [6]. CS is more frequent in women than men, with a sex ratio of approximately 2:1, but this result was not found across all studies [7]. Only a few reports have described this syndrome in patients during childhood [16].
The remarkable feature of Capgras delusion is that patients are able to recognize the close relation, the related person’s face, but deny his or her identity and often use subtle misperceived differences in behaviour, personality, or physical appearance to distinguish between him or her and the imagined impersonator [17, 18]. Patients with CS find ways to defend their irrational beliefs [4]. Generally, the patients support their conviction in revealing detail. This sign may be a habit or a personality trait; small misperceived differences, for instance, in physical appearance and behaviour, may vary over time [7]. And these are frequently used to distinguish the imposter from the loved one [19]. Surprisingly, patients may show implicit or explicit awareness of their true situation [6]. Some research suggests that a considerable number of patients with CS have some awareness of the bizarre nature of the misidentification delusions and therefore tend not to report them, especially during initial interviews when they are less likely to be confident with the clinician [20].
Common to all DMS is the delusional denial of identity of objects having affective significance for the patient, and it is exceptional for there to be only one imposter, but these objects are limited in number. CS may be associated with other DMSs, and these frequently evolve from one another because of this relation and similarity [7, 21].
It sometimes occurs isolated, hereby justifying its autonomy as a ‘delusion’ [7]. CS may be accompanied by other delusions and thus may rarely exemplify a ‘monothematic’ delusion [6]. Erotomanic delusions and delusional jealousy [i.e., Othello jealousy] were identified in 9.1% and 6.4% of patients with CS, respectively [22, 23]. However, delusional misidentification syndromes uncommonly appear independent of comorbid pathology [24].
The absence of consensual clinical criteria makes the epidemiological data uncertain [7]. Thus, the prevalence of CS may be underrated. More than half of the patients of the registered cases suffered from mental disorders without any organic association, among which schizophrenia spectrum disorders were diagnosed in 6 of 10 patients with CS [22, 23]. The Capgras delusion has been reported in association with other psychiatric disorders in 60–75% of cases and in organic illnesses in 25–40% of cases [24]. The Capgras delusion has usually been recognized in the contextual relationship of psychiatric disorders and often occurs in conjunction with paranoia, derealization, and depersonalization [6]. The Capgras syndrome may represent a delusional evolution of the phenomena of depersonalization and derealization [25]. Nonspecific, derealization-depersonalization experiences are frequent, especially in psychotic disorders, and are considered a significant core symptom of CS [7]. Studies on the prevalence of this disease or comorbid disease show differences. A study has found that the prevalence of DMS in psychiatric populations was less than 1% [15]. Another study has found that its prevalence in all psychiatric inpatients is 1.3–4.1% [26]. It is around 3% for hospitalized psychotic patients [18]. In a recent prospective study of patients hospitalized for a first psychotic episode, it was found that CS was diagnosed approximately 1 in 10 of patients. The prevalence was maximal among patients presenting schizophreniform psychosis 50%, brief psychosis 34.8%, and unspecified psychosis 23.9%, and the prevalence was moderate for a major depressive episode 15%, schizophrenia 11%, or delusional disorders 11% [15]. The most common psychiatric diagnoses in CS have been paranoid schizophrenia, schizoaffective disorder, and bipolar affective disorder [24]. CS has been linked with multiple pathologies. It has been described in psychiatric as well as organic disorders. In the last few decades, reports have increasingly stressed the aetiologic importance of heterogeneity of conditions that have been found in the patients with misidentification syndromes like the Capgras delusion, including cerebrovascular disease, post-traumatic encephalopathy, temporal lobe epilepsy, postencephalitic Parkinsonism, viral encephalitis, migraine, vitamin B12 deficiency, hepatic encephalopathy, chronic alcoholism, hypothyroidism, pseudohypoparathyroidism, and dementia [24]. Schizophrenia remains the most common co-occurring mental disorder associated with case reports of Capgras delusion [26, 27]. Also, family history of psychosis is reportedly present in half of CS patients [21]. Medications and drug toxicity have also been reported to cause CS [28].
Since initial reports of CS involved patients with psychiatric illness, their close relations, and how they interacted with each other, early explanations of the delusion were predominately psychodynamic interpretations. There are several psychodynamic approaches. Consequently, these explanations included suggestions that CS might develop out of Oedipal issues in women as a defence against hostility or incestuous, guilty desires, or out of hidden homosexuality in men. Later attempts to account for CS resulted in hypotheses of anxiety-induced regression of cognitive and emotional functioning, pathological splitting of internalized object representations, insufficiently repressed conflicting or ambivalent feelings toward the implicated person, and the projection of negative emotions that come to light from these conflicting feelings [18]. In the psychodynamic theory, it is supposed that the delusion is a way in which the patient copes with the ambivalent emotions that he feels toward the close family member who is duplicated [16]. There are several explanations brought about by psychodynamic approaches of misidentification syndromes. Premorbid psychopathology, motivation, and loss of ego functions may be important in determining which vulnerable patients develop CS [6].
Capgras delusion can occur due to ‘spatial disorientation, anatomic disconnection, memory and executive process impairment, and loss of ego’ [4]. While psychodynamic theories consist of ambivalence theory, depersonalization theory, and regression theory, neurocognitive hypotheses focus on right hemispheric dysfunction, face-recognition processing abnormalities, and focal structural cerebral abnormalities [29]. There are two components of the visual recognition of a familiar face, one of which is responsible for conscious recognition of the face and the remembrance of associated semantic information, while the other is responsible for the limbic-mediated emotional arousal including the feeling of familiarity that accompanies the conscious recognition of a known face [9].
Despite the sharp increase in the number of published cases accompanied by various suggestions regarding an organic etiology, to accurately explain the delusion, it is necessary to embrace the psychodynamic as well as the organic. Even if a specific neuropsychological lesion is found in the end, the psychodynamics of the individual will still be pertinent and remain substantial [10]. An association between CS and depersonalization has been thought to exist onward the time when the disorder was first described. Some authors put forward that depersonalization may be the basis of the disorder which may develop in some individuals. CS can be evaluated as a disorder of ego function which permeates the entire personality [10]. Some authors postulated that cerebral dysfunction leads to feelings of derealization and depersonalization which in turn may develop into Capgras’ syndrome in the presence of paranoid ideation [10].
The psychodynamic conception of the Capgras phenomenon is basically a love-hate conflict that is resolved by reflecting ambivalent feelings onto a fictitious double [10]. On the one hand, there are a long-standing love and on the other hand a visible hatred. In those cases when it occurs, it is very substantial that before the onset of the delusion of doubles, the patient shows an increased love and sexual desire toward the object. This overreaction results from a desire for reassurance regarding the love of the object and fear of losing it simultaneously. Theories suggested that CS could arise out of an Electra complex and incest desires, Oedipal problems, and latent homosexuality. Personality disintegration coupled with an evolutionary regression to more primitive modes of cognitive and emotional functioning; division of internalized object representations; ambivalent feelings toward a familiar other that are not sufficiently suppressed; and the feelings of anxiety, guilt, and anger resulting from this struggle are reflected onto imagined imposter [21]. Instead of approving these demands, the object becomes even more repulsed and is unable to cover up these feelings that clearly aggravate the situation, and a vicious circle is established [10].
Usually, we do not strive for facial recognition. The ability to identify people who we met before is a headstone of our social interactions. Face recognition is a multistage process ending with the identification of a person. Prosopagnosia is defined as loss of familiarity to previously known faces and the inability to learn to recognize new faces. Although these patients fail to recognize faces, they are still able to show affective responses to these faces [30, 31]. Several studies have suggested that CS represents a ‘mirror image’ of prosopagnosia, thus suggesting different neural circuits for facial processing: a cognitive circuit (impaired in prosopagnosia) and an affective circuit (impaired in CS). In the affective circuit, the ventral route from the visual centers to the temporal lobes may be protected, also active in conscious face recognition; however, the dorsal visual track that gives the face its emotional significance is damaged. A brief disruption of the ventral visual pathway leads to prosopagnosia, whereas damage to the dorsal visual areas leads to an impaired sense of familiarity for known faces, as in CS [9, 18, 30, 32]. While the ability to identify that person is intact, patient with CS probably has a brain lesion that interferes with the patient’s ability to sense a familiarity toward the significant other [16]. It has been suggested that the impairment seen in the Capgras delusion was linked to a disruption of pathways connecting face-sensitive regions to limbic cortex, which is involved in the accompanying emotional response [30]. Perhaps arising from the conflicting experience of recognizing a known face without any accompanying affective reaction, the patient can understand that the absence of this emotional arousal is to establish the belief that the person he is looking at is an imposter [9, 33]. In another connectivity study, posterior coupled with anterior right hemisphere dysfunction may have involved in the emergence of Capgras delusion [34]. Also, it has been suggested that CS results from the disconnection of the face processing regions in the inferior temporal lobe from structures in the limbic system, especially the amygdala, which is very important in assigning emotional value to familiar faces [34]. Common to the CS is a fixed false belief but infrequently transient [35]. However, anatomical disconnection models fail to efficiently consider the transient nature of the misidentification episodes [34]. Therefore, it has been suggested that CS may be associated with the ‘kindling of subcortical structures’. Kindling refers to repeated subthreshold stimuli which may result in psychomotor outbursts or overt seizure activity [34]. Autonomic responses and eye movements are involved in face perception which may cause the patient believe that the person has been replaced by an imposter. Studies on patient with CS like other psychiatric disorders have shown abnormal scan paths to facial stimuli or abnormal skin conductance response (SCR) in face processing tasks [30, 33]. The absence of identity recognition, accompanied by a lack of SCR, stimulates the patient to explore unfamiliar faces, and identity recognition of familiar faces leads to a more detailed exploration in the eye region, and it results in gaze avoidance of the eye region [33]. Vision is important in accessing reserved knowledge in the etiology of CS. However, surprisingly CS has also been reported in a number of blind patients which suggests that it cannot have an exclusively visual basis [34]. Some theories assume that two deficits are necessary for delusions to occur in the case of Capgras delusion like other DMSs [32, 36]. This is also called ‘two-hit’ process [21]. The first one, the brain’s ability to attach emotional emphasis, may be the lack of autonomic arousal which leads to the abductive inference that the person is an imposter [30]. The other deficit is an impaired ability to reassess beliefs [the global consistency-checking mechanism] which prevents the rejection of the bizarre belief. The second deficit leads to the persistence of that abnormal perception as a delusion resistant to reasoning, also related to the right anterior cortex of the second deficit [9, 30, 32, 36].
Neuropsychological deficits in patient with CS were reported across multiple cognitive domains, including memory, executive functioning, and visuospatial processing. These studies suggest that memory was statistically more likely to be impaired than other cognitive domains. Therefore, the memory may be playing an important role in the development of these delusions [32]. The existence of confabulations may have a role in prognosis and predicted significantly longer delusion duration, once more supporting the importance of memory impairment in patients with CS [32]. To mention a little more about the confabulation, some authors are focusing on confabulation in these patients because they are thought to be confabulation and delusion are closely related. When asked how they can explain their beliefs, Capgras patients will often confabulate. Confabulation is a kind of false memory that occurs when patients produce stories that fill in gaps in their memories, whereas a delusion is a mental state, typically thought of as a belief. Confabulation and delusion cannot be completely the same [37, 38]. Some researchers suggested that CS comes out when right hemisphere dysfunction causes a memory disconnection that leads to a failure to put new information together with representations about a significant individual and to keep in reserved over time [18]. Against all of these, although many patients have subtle deficits in face recognition and memory for faces, they do not have difficulty in recognizing faces in everyday life [1, 2]. CS is distinguished by its delusional mechanism: it is neither a hallucination nor an illusion—the object is correctly recognized in its appearance. CS is not a memory disorder. The person is correctly recognized; people are memorized [7]. Language deficits may not be absent, because of the right hemispherical dominance of the lesions [32].
In 1971 a case of Capgras was described in a young man following a head injury, with no previous history of psychiatric disorder. Since then, many patients with CS have undergone more thorough neurological investigations [10]. Identification disorders like CS are very frequent in neurodegenerative diseases [7]. Regarding the organic conditions that occur in Capgras delusion, this appears mainly in various types of dementia like Alzheimer, Lewy bodies, and Parkinson [39]. The prevalence of CS in Lewy body dementia may be as high as 25% and 10% in Alzheimer-type dementia. Identification disorders are much rarer in other types of dementia, especially those associated with Parkinson’s disease [7]. Nearly half of the cases in CS were associated with neurocognitive disorders, such as delirium, traumatic brain encephalopathy, cerebrovascular disease, dementia, meningioma, encephalitis, and multiple sclerosis [22, 23]. Although there is usually a delay in the presentation of Capgras delusion after cerebral events, there are also such cases of immediate presentation [31]. Psychotic disorders with CS tend to present in the late teens and early twenties. It reflects the long mean duration of the delusion in the functional group [27]. Those with neurological disorder associated with the onset of the delusion had a mean age of 60, in keeping with their presentation in middle to late adulthood, especially as Capgras delusion in dementia tends to occur in the later stages [27]. Therefore all individuals with Capgras should be examined for organic pathology [9]. In a literature review of patients with CS who had associated organic factors, there are several single case reports in patients with Capgras delusion which suggest structural and metabolic anomalies in mostly right-sided frontal, temporal, or parietal brain regions. But most of CS patients had bilateral lesions although, for those with unilateral lesions, right hemisphere lesions were much more likely [30]. Some studies give emphasis to the presence of two lesion sites, one in right frontal and the other in right temporal cortex [30]. The identity of the imposter is significantly associated with the reported underlying etiology. Capgras’ delusion is reportedly due to functional psychiatric disorder, which is more likely to view their parent as an imposter, whereas the spouse is involved in those with suspected neurological etiology. There may be mentioned two reasons. The first one is may be because of the different mean age for the groups. The age of onset of Capgras delusion is different between those with organic disorders and those with neurological disorders [27]. The other reason is about Capgras delusion’s feature. Capgras delusion is the phenomenon mostly specific to close relatives. This supports the role of intimacy [9, 27]. Selectivity for familiar persons is essential, though sometimes relative, and the syndrome can extend to persons who are simply known or famous [7]. Against this, the frequency with which strangers and multiple imposters are implicated in all cases of Capgras delusion can be up to 39% [27]. Multiple imposters are significantly more likely to occur in functional cases, while the involvement of inanimate objects would seem to suggest organic etiology [27]. The neuropsychological findings discussed may lead to some account of the possible mechanisms by which an abnormal experience may be generated in a subset of Capgras patients, but some researchers do not think in itself account for the formation of delusional belief [40]. Consequently, the explanation may offer a useful, helpful analysis of a certain step in the pathology of the CS in a subgroup of more neurological patients but could be unlikely to enlighten about delusions more generally or those with Capgras in the context of a functional psychosis such as schizophrenia or bipolar disorder [40].
The term CS does not demonstrate a well-defined mental disorder. Over the years various studies have suggested psychodynamic and neurophysiological interpretations for CS, and various aetiologies have been recommended for the condition’s development [16, 18, 29].
Although frequently seen in psychotic cases, Capgras has also been associated with neurological disorders suggesting that the syndrome has an organic basis [15]. According to a study, CS patients were classified into groups according to whether or not they had evidence of neurological disorder. Some of the patients identified as having no neurological lesion might be found to have organic brain disease with more sophisticated imaging techniques or at post-mortem evaluation [41]. In another study, approximately one in five of patients with CS presented with organic mental disorders [1, 2]. Multiple hypotheses have been put forth regarding the underlying pathophysiology of CS. Some areas of the brain are responsible for the etiology of this disease. Results of structural and neuroimaging studies of CS provide support for an organic etiology [18]. Multiple studies and reports have remarked on CS in the setting of various neurological and neurodegenerative diseases [42]. There is a study that found more widespread bilateral frontal and temporal cortex atrophy in schizophrenia patients with CS than schizophrenia patients without the syndrome by using computerized tomography (CT) [18]. Likewise other studies using CT found global brain atrophy in combination with right hemisphere lesions in patients with dementia. There is also reported that positron emission tomography [PET] demonstrated abnormal brain glucose metabolism in paralimbic structures and temporal lobes of patients with Alzheimer’s dementia comorbid with CS and other subcategories of delusional misidentification syndromes [18]. Numerous neuropsychological researches support an association between CS and right frontal and temporal lobe abnormalities, and also many study reports indicate that patients with CS tend to have inferior scores on neuropsychological tests of frontal lobe function [18]. Even though less well documented, regions of the prefrontal cortex are also associated within facial processing: projections from the face processing areas in the right ventromedial occipitotemporal regions to the ventromedial prefrontal cortex via the uncinate fasciculus as well as limbic-thalamic pathways are well established [34].
Some people with schizophrenia exhibit this syndrome, but it is not related directly to schizophrenia itself; there are people with schizophrenia who do not exhibit CS, as well as people with CS who do not exhibit schizophrenia. The mean age of schizophrenic patients with Capgras syndrome is older than the age at which schizophrenia alone is usually expected to occur. When brain abnormalities of people with schizophrenia affect certain areas, CS and schizophrenia will occur concurrently. Capgras delusion and schizophrenia seem to be statistically related, at least in the case of the paranoid subtype of schizophrenia. It has been claimed that right hemisphere damage is a characteristic of schizophrenia; perhaps the imperfect evaluation of beliefs, which we have suggested, occurs as an outcome of damage to a particular area of the right frontal lobe, which is necessary for the occurrence even of the persecutory and grandiose delusions that are common in paranoid schizophrenia. Accounting the association of Capgras delusion with paranoid schizophrenia, the same neuropsychological deterioration of belief assessment is required for both, and in cases of patients with persecutory or grandiose delusions where the neuropathology also has affected the track from face recognition to the autonomic nervous system, Capgras delusion will also be existing [43, 44]. CS in paranoid schizophrenia may improve with successful treatment. But recurrence of illness may be accompanied by a return of delusional material [44].
It is important to note that the Capgras delusion can be either a primary condition that is part of a ‘mental illness’ or a secondary condition that is the direct result of an organic disease of the brain. Also, the primary and secondary versions differ significantly in their presentation. In primary Capgras syndrome, the patient is more likely to be furious or violent toward the imposter. In secondary CS, the imposters do not change over time. This is different from the situation in schizophrenia where the delusions can vary [45]. The mean age of onset of the delusion was earlier in primary Capgras (mean age 32 years) than in secondary Capgras (mean age 48.5 years). Primary cases are more likely to have a subtle onset which evolved gradually, whereas secondary cases are more likely to have sudden-onset delusions. Primary cases show associated psychotic symptoms, particularly paranoid thought, whereas psychotic symptoms are not very often of the secondary cases. The patients with CS without apparent organic cerebral dysfunction were more likely to have experienced other psychiatric symptoms prior to the onset of the Capgras delusion than those with organic cerebral dysfunction [41]. Patients with neurological impairments were more likely to regard the misidentification as benign or as due to illusory, whereas patients without evidence of neurological basis were more likely to appraise the delusions as being threatening [41]. Thus, hostility and violence are seen much more frequently in those patients diagnosed as schizophrenic than in other patients [46].
Acting on delusions is a crucial clinical issue. There is a positive relationship between delusions and serious violent acts. Although the pathway from delusions to violent outcomes is not direct, the risk is greatly increased when symptoms are acute, especially at the time of initial presentation and if not treated [20]. And the risk also can be changed according to the etiology of delusions. There is a requirement to be concerned about the patient’s tendency for violence and to evaluate for it thoroughly in Capgras delusion [45]. In patients with CS of an organic nature, violence may be associated with few or no affective manifestations (e.g., hostility, aggression, and auditory hallucinations), and may not be associated with paranoid elements [7]. Delusional symptoms in CS such as persecutory thoughts, threat-control symptoms, command auditory and/or visual hallucinations, and hallucinations of threatening content have all demonstrated to be significant predictors of violence act and aggressive behaviour [29]. If the patients are married, divorced, or separated, the most frequent doubles are the spouse. If the patients are single, the most frequent doubles are the siblings [20]. It should be noted that healthcare professionals may become the objects of delusional misidentification [42]. Because the double is usually assumed to have malicious, the CS could be characterized by hostility toward misidentified objects, and, later, it can lead to physical harm to others [20]. The assault associated with CS, the tendency to violence, cannot be attributed purely to the delusion’s existence. Other factors are presumably to affect the possibility of violent act. A significantly higher tendency for interpersonal violence are men disclosed among male subjects, average age at 40 years old, with a history of aggressive behaviour and substance abuse; social withdrawal prior to the violent act is common, and the violence is usually well planned [20, 22, 23]. Persecutory paranoid motivations have been implicated as a key factor in acts of violence toward family members who constitute the majority of victims in CS [29]. Physical violence was expressed by 58.2% of patients with CS and 62.5% of patients with CS engaged in acts of interpersonal violence toward their close family members and caregivers [22, 23]. Mothers and spouses were the most frequently attacked group of relatives, respectively. Also, it was found that 1 of 10 Capgras patients attempted homicide [22, 23]. Most of the perpetrators were males suffering from mental disorders without organic association. A higher incidence of self-harm and suicide attempts, which is about 1 in 10 of patients with CS, was detected among females even in patients with psychiatric disorders and in patients with neurodegenerative disorders [22, 23]. Although in the usual cases, the misidentified object is a person, hence justifying the title of delusional identification of people, the CS is not restricted to person misidentification but can also involve other living or lifeless objects [7, 20]. Physical violence against objects was also common, such as setting fire to one else’s estate [22, 23].
The differential diagnosis of patients who suffered CS is crucial. It is substantial to rule out the presence of brain disease in every patient with Capgras delusion [45]. Many patients with CS also present with medical illnesses of organic etiologies, associated with delusional misidentification; these patients may respond well to treatment of the medical condition underlying the onset of CS [47]. The syndrome should be differentiated from the quite common false recognitions which occur in confusional states and the transient misidentifications encountered in mania [8]. For this purpose, ending with a complete mental status examination, as well as thorough testing of cognition, is important. Neuropsychological testing and neuroimaging are often indicated. Clinicians should clarify the nature of the underlying psychiatric illness [45].
Low platelet monoamine oxidase (MAO) activity is a biochemical abnormality which is present in some psychiatric disease. Some authors suggested that the low platelet MAO activity might be proposed as a potential biochemical marker of CS. It is also thought that reduced monoamine oxidase activity in primary psychiatric patients with CS may give a piece of information to the pathogenetic mechanism underlying the reported cases of CS in organic patients without a primary behavioral disorder. However, study results show that platelet monoamine oxidase activity in patients with delusional misidentifications did not differ notably from that of schizophrenia and nonpsychiatric controls [41, 48].
The key features currently considered to be critical to the development of the Capgras delusion are as follows:
There is an abnormal perceptual experience that is a prerequisite for the delusion.
This perceptual experience is accompanied by a paranoid which leads to misattribution of the abnormal perceptual experience.
The loss of normal response to known faces occurs in the context of more generalized derealization-depersonalization [41].
Delusion in CS should be treated timely because it can cause a dangerous condition [42]. However, there are no guidelines to assist clinicians to care for patients presenting with CS in selecting complementary examinations to be performed or in selecting treatment [7]. Likewise, the symptoms of DMS are very refractory to treatment despite various interventions including psychotherapy and pharmacotherapy approaches [20]. The CS like other DMSs is known to develop similar to the comorbid disorder that they accompany, disappearing after remission even though it is not unusual for them to continue after the disappearance of the comorbid disorder [7]. Thus, treatment of the underlying neurological or psychiatric conditions may not lead to remission of CS [28]. The presence of depersonalization, derealization or visual-perceptual disturbances, and other comorbidities may influence the treatment of CS [47]. The syndrome has been linked to dopaminergic overactivity, and serotonin abnormality has been implicated in some but not all studies. Similarly, reduced platelet monoamine oxidase activity has been noted by some but not by others [18]. According to the results of the case studies in the literature, CS patients are sometimes responsive to typical and atypical antipsychotics such as olanzapine, risperidone, quetiapine, sulpiride, trifluoperazine, and pimozide [20]. Pharmacological treatment of CS is based on antipsychotics, antidepressants, anticonvulsant, and benzodiazepines considering patient needs and characteristics, but no control trials are available [49]. In the literature, there have been reported cases with a diagnosis of organic or functional delusional disorder associated with CS whose DMS responded well to pimozide that is well known for the treatment of monosymptomatic delusional disorders [49]. Experience with the new generation of atypical antipsychotics for the treatment of CS is quite limited. Although for patients manifesting any psychotic disorder, atypical antipsychotics are usually recommended because of the reduced risk of adverse effects [6, 47]. A crucial point of a case report is the positive outcome in response to antipsychotic medication [olanzapine] [49]. The combination of antipsychotic drug therapy and selective serotonin reuptake inhibitor (SSRI) may produce a positive outcome in patients with CS [16].
A case report also suggested the use of clorazepate which is benzodiazepine. In this case report, in addition to the antipsychotic properties of clorazepate, its anticonvulsant properties were also utilized in CS patient with the suggestion of some researches that found an over 90% incidence of electroencephalographic abnormalities in CS patients [27]. According to the results of the case studies, it showed a positive outcome in a patient with CS after treatment with mirtazapine that is also a serotonin 2A receptor antagonist, which could potentially afford its antipsychotic effects resulting in significantly decreasing the symptoms of CS [20, 28].
With patients who have progressive dementia, such as dementia with Lewy bodies, in which misidentification syndromes are common occurred, cholinesterase inhibitors have demonstrated benefit to reduce psychiatric symptoms [6].
Electroconvulsive therapy (ECT) has been reported to benefit either alone or in conjunction with antipsychotics, mood stabilizer, or antidepressant medication in patients with CS. It has been suggested that ECT provides permanent effective control of CS [42, 47, 49].
Psychotherapy may be beneficial in the treatment of selected patients with CS in order to reform the patient’s relationship with his family. The psychoanalytic theories show that the emotions which the patient experiences in regard to the people with whom he is confronted are transferred to the imposters, and therefore, in this way from a safe delusional distance, the patient gives himself to refuse them without guilt, sometimes manifesting an aggressive behaviour toward them [22, 23]. It has been shown that group psychotherapy may also be beneficial by becoming less prone to feel hostile toward others, thereby weakening the delusional misidentification process for psychotic patients with DMS [40]. Cognitive behavioural therapy (CBT) may be a utilized form of psychotherapy intervention in some cases by assisting the patient to overcome the delusional beliefs [22, 23].
It is quite common in cases of delusion for his/her family members of the deluded person to be concerned about the delusion and to try to get rid of it by constantly challenging it [43]. It may be beneficial to know that just as an impairment in the interpersonal relationship between the patient and the object may occur before the onset of the delusion, an amelioration in this relationship is an essential factor in the amelioration of symptoms. Therefore treatment must include helping the partner or person implicated to gain insight and perhaps change their attitude toward the patient [10].
CS is a different neuropsychiatric symptom of interest to researchers over the past century. No approved questionnaires focus on CS. While noting that the Capgras syndrome has no formal place in recognized diagnostic systems, it should be emphasized that this is of significance. It is crucial to keep them in mind as a possibility and to pursue any possible clues. Capgras delusion is a complex psychopathological phenomenon that presents in a wide range of psychiatric and neurological disorders with differing patterns dependent on the main etiology. Misidentifications in CS are fixed false beliefs and, therefore, represent true delusions. Even if when patients are confronted over and over with the illogical nature of the delusion, they keep their beliefs. Specific questions and interventions may assist to clinicians in successfully identifying patients with CS. In a series of interviews with these patients, some focus on identifying CS, rather than a single interview which is likely to increase the detection of the delusional misidentification. The clinician should always be mindful of the risk of aggression and homicide in CS.
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