**5. Cyst treatment options**

**Marsupialization** (Partsch I) procedure is a technique for making a surgical incision in the cyst capsule, minimizing intracystic pressure, and evacuating its contents, then suturing the edges of the cyst to the healthy surface of the oral mucosa to establish a large permanent opening (Figure 7).[17]

**Decompression** is a technique that relieves the pressure within the cyst by making a small opening in the cyst and keeping it open. This can be achieved with a drain or obturator. Each day the obturator should be removed and the cyst cavity should be irrigated. The cyst size will decrease and any damage to important structures upon enucleation will be diminished (Figures 8, 9). [18]

The decompression and marsupialization of cysts were first suggested by Partsch in the German literature in the late 19th century. [18] Indications for such marsupialization and decompression are large cysts with thin bony walls that may cause spontaneous fracture, cysts that are very close to structures such as the n. alveolaris inferior or nasal floor, and infected cysts. [17, 18, 19]

**Enucleation** (Partsch II procedure) is a procedure in which all pathological tissue is removed and wound edges are closed (Figure 10). [18]

**Figure 7.** Marsupialization (Partsch I) procedure of a ranula.

**4. Etiology of cysts localized in the maxillary sinus**

length 23 mm, 3.  Cysts are more commonly seen in the maxilla than the mandible. The most common causes of cysts localized in the maxillary sinus are chronic infection, allergic sinonasal disease, trauma, previous surgery, obstruction of the sinus ostium, accumulations of secretions, ectopic teeth, foreign bodies (e.g., dental implant, tooth roots, graft materials), dental infections, incomplete sealing of all communications between the root canal system and periradicular tissues during endodontic treatment, mechanical obstruction of mucociliary flow, defects in ciliary capabilities to propel the mucous blanket and genetic factors. Pathologically, a cyst can develop and grow in the sinus until it reaches a large size

**Figure 5.** The sinus maxillaries. Volume ~15 cc and pyramidal shape. 1. inferosuperior length 33 mm, 2. Mediolateral

with no serious complaint by the patient because of the anatomy of the sinus. [14-16]

**Figure 8.** Decompression technique for a dentigerous cyst.

**Figure 9.** Enucleation after 12 months of decompression.

**Figure 8.** Decompression technique for a dentigerous cyst.

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**Figure 10.** Enucleation (Partsch II procedure) of an odontogenic keratocyst.

## **6. Cases**

#### **6.1. Case 1**

A 19-year-old male was referred to our department of oral and maxillofacial surgery with a 3 week history of swelling on the right side of the face. There was no history of trauma, pain, paresis, paresthesia, or lymphadenopathy. There was slight but obvious facial asymmetry caused by the swelling over the right maxillary region. The mass was firm and non-tender on palpation and not adherent to the overlying skin. Intra-oral examination showed little expansion of the upper right third molar region.

A panoramic radiograph and CT showed a well-defined unilocular radiolucency involving the right maxillary sinus along with the impacted third molar in the top part of the maxillary sinus in conjunction with the orbital floor. A vitality test was performed; all the teeth were vital.

**Figure 11.** Panoramic radiograph and CT views.

**Figure 10.** Enucleation (Partsch II procedure) of an odontogenic keratocyst.

246 A Textbook of Advanced Oral and Maxillofacial Surgery Volume 2

expansion of the upper right third molar region.

A 19-year-old male was referred to our department of oral and maxillofacial surgery with a 3 week history of swelling on the right side of the face. There was no history of trauma, pain, paresis, paresthesia, or lymphadenopathy. There was slight but obvious facial asymmetry caused by the swelling over the right maxillary region. The mass was firm and non-tender on palpation and not adherent to the overlying skin. Intra-oral examination showed little

A panoramic radiograph and CT showed a well-defined unilocular radiolucency involving the right maxillary sinus along with the impacted third molar in the top part of the maxillary sinus in conjunction with the orbital floor. A vitality test was performed; all the teeth were

**6. Cases**

**6.1. Case 1**

vital.

In cases like this, careful examination is important. Points that should be checked include possible obstruction of the sinus ostium (Figures11, 12), the need for an antrostomy procedure, the route of the canalis nasolacrimalis, resorption of the posterior bony wall of the sinus, continuity of the orbital floor, and eye examinations before and after the operation. In such operations where visualization is a problem, an endoscopic-assisted approach is mandatory. [20] Endoscopic sinus surgery has been performed for various indications in maxillofacial surgical practice. It has been used for the assessment of antral pathologies, removal of foreign bodies, orthognathic procedures, and the treatment of facial fractures. [21, 22] Especially after finishing the removal of a cyst and tooth in operations like this using endoscopy, the surgeon should check any remaining pathology of the cyst, continuity of the orbital floor, to assess the possibility of a blow-out fracture [23], root tips of the teeth and any possible damage, check the aperture of sulcus nasolacrimalis, and perform an antrostomy using endoscopic assistance as needed. [24]

The operation was performed under general anesthesia, combined with local anesthesia. A mucoperiosteal flap was opened in two layers (Figure 13). Through a modified Caldwell-Luc approach, the cyst was exposed (Figure 14). At this stage in the operation, saving teeth vitality is the most important point, so it is important to work at least 5 mm away from the teeth apices. After the pus was removed from the cyst, the tooth was carefully extracted under endoscopic assistance and the remaining part of the cyst was then enucleated (Figure 15, 16). Using endoscopy, the cavity was checked (Figure 17) and packing of the sinus (Figure 18) was performed; this was removed 3 days later. Vitality of the teeth were checked for the last time at 3 months after the operation and all teeth were vital.

**Figure 12.** Panoramic radiograph, lateral cephalometric and CT views showing tooth in the right maxillary sinus.

**Figure 13.** Mucoperiosteal flap preparation.

**Figure 12.** Panoramic radiograph, lateral cephalometric and CT views showing tooth in the right maxillary sinus.

248 A Textbook of Advanced Oral and Maxillofacial Surgery Volume 2

**Figure 14.** Exposure of the cyst. Endoscopic view (right).

**Figure 15.** Enucleation of the cyst.

**Figure 16.** Extraction of the tooth.

**Figure 17.** Postoperative cavity checking.

**Figure 15.** Enucleation of the cyst.

250 A Textbook of Advanced Oral and Maxillofacial Surgery Volume 2

**Figure 16.** Extraction of the tooth.

**Figure 18.** Packing of the sinus after antrostomy.

#### *6.1.1. Intranasal inferior meatal antrostomy technique*

An intranasal inferior meatal antrostomy is a process of making an opening in the nasoantral wall of the inferior meatus by an intranasal route. The nasoantral wall of the inferior meatus is perforated with a curved hemostat and then this opening is enlarged. The opening should be 1.5-2 cm in diameter and as close to the floor of nose as possible (Figure 19). Intrasinus pus/ debris should be removed by suction. Packing into the sinus is achieved from the posterior, packing layer-by-layer upwards and forwards (to facilitate removal through the antrostomy) and nose packing may also be required if there is severe bleeding (Figure 20). [25]

**Figure 19.** Intranasal inferior meatal antrostomy technique.

**Figure 20.** Packing of the sinus maxillaris.

#### **6.2. Case 2**

During an incidental radiological exam (orthopantomograph, OPG, Figure 21 at our depart‐ ment of radiology, a 51-year-old male with no complaints and no history of any trauma, pain, paresis, paresthesia, or lymphadenopathy, was discovered to have an ectopic tooth in the right maxillary antrum. A CT scan (Figure 21) was performed and all important points were checked. An operation was performed under general anesthesia with combined local anes‐ thesia. Using a crestal incision, a trapezoid mucoperiosteal flap was designed and carefully elevated. The tooth was extracted under endoscopic assistance (Figures 22, 23) and a dentig‐ erous cyst was enucleated (Figure 24). Using endoscopy, all cavities were checked and packing of the sinus was performed; this was then removed 3 days later.

**Figure 21.** OPG and CT views.

is perforated with a curved hemostat and then this opening is enlarged. The opening should be 1.5-2 cm in diameter and as close to the floor of nose as possible (Figure 19). Intrasinus pus/ debris should be removed by suction. Packing into the sinus is achieved from the posterior, packing layer-by-layer upwards and forwards (to facilitate removal through the antrostomy)

During an incidental radiological exam (orthopantomograph, OPG, Figure 21 at our depart‐ ment of radiology, a 51-year-old male with no complaints and no history of any trauma, pain,

and nose packing may also be required if there is severe bleeding (Figure 20). [25]

**Figure 19.** Intranasal inferior meatal antrostomy technique.

252 A Textbook of Advanced Oral and Maxillofacial Surgery Volume 2

**Figure 20.** Packing of the sinus maxillaris.

**6.2. Case 2**

**Figure 22.** Extraction under endoscopic assistance.

**Figure 23.** Extraction under endoscopic assistance.

**Figure 24.** Enucleated dentigerous cyst.

#### **6.3. Case 3**

**Figure 22.** Extraction under endoscopic assistance.

254 A Textbook of Advanced Oral and Maxillofacial Surgery Volume 2

A 23-year-old female was referred to our department of oral and maxillofacial surgery with headache, fatigue, and difficulty in nasal breathing. After a radiological examination (figure 25), it was seen that there was an ectopic third molar in the left sinus and a wisdom lower left third molar in conjunction with a cyst. A CT scan (Figure 26) was performed and all important points were checked and it was seen that the third molar in the maxillary sinus was associated with a cyst that had occupied over two-thirds of the left maxillary sinus.

An operation was performed under general anesthesia with combined local anesthesia. A trapezoid mucoperiosteal flap was designed and carefully elevated (Figure 27). The tooth was extracted (Figure 28) and the cyst was enucleated (Figure 29). An intranasal inferior meatal antrostomy was performed with packing of the sinus (Figure 30); this was removed 3 days later. After the operation, all symptoms of headache, fatigue, and difficulty in nasal breathing resolved. Pathological specimens were sent for examination and the report showed that the cyst was an orthokeratotic odontogenic cyst.

During the operation, using envelope incision, the lower-left-third molar was also extracted and its cyst was enucleated (Figure 31). The pathological report for the lower cyst showed it to be dentigerous. The patient remains under observation (Figure 32).

**Figure 25.** OPG view.

**Figure 26.** CT views.

**Figure 27.** Mucoperiosteal flap preparation.

**Figure 25.** OPG view.

256 A Textbook of Advanced Oral and Maxillofacial Surgery Volume 2

**Figure 26.** CT views.

**Figure 28.** Tooth extraction.

**Figure 29.** Enucleated cyst and extracted tooth.

**Figure 30.** Intranasal inferior meatal antrostomy and packing of the sinus maxillaris.

**Figure 31.** Extracted lower tooth.

**Figure 29.** Enucleated cyst and extracted tooth.

258 A Textbook of Advanced Oral and Maxillofacial Surgery Volume 2

**Figure 30.** Intranasal inferior meatal antrostomy and packing of the sinus maxillaris.

```
Figure 32. 5 year postoperative OPG.
```
#### **6.4. Case 4**

A 26-year-old female was referred to our department with severe headache, fatigue, difficulty in nasal breathing, halitosis, and a slowly growing facial deformity on the right site of the face. After radiological assessment (OPG and CT) and clinical examination (Figure 33), it was seen that there was a cyst that almost completely filled the right maxillary sinus and there was slight,

but obvious, facial asymmetry caused by the swelling over the right maxillary region. The mass

was firm and non-tender on palpation and not adherent to the overlying skin. Intra-oral

examination showed expansion of the upper right molar region.

Endodontic treatment was performed for the upper right first and second premolars and for the second molar tooth. It was decided that the first molar roots and third molars would be extracted. All important anatomical points were carefully checked on CT scans.

An operation was performed under general anesthesia, with combined local anesthesia. A trapezoid mucoperiosteal flap was designed and carefully elevated (Figure 34). The teeth were extracted and the cyst was enucleated (Figure 35); and apical resection was performed (Figure 36). An intranasal inferior meatal antrostomy was performed as was packing of the sinus (Figures 37, 38); this was removed 3 days later. Endoscopic assistance was not used because of good visualization. Pathological specimens were sent for examination and report confirmed a radicular cyst (Figure 39).

**Figure 33.** Radiological (OPG and CT) and intraoral clinical views.

that there was a cyst that almost completely filled the right maxillary sinus and there was slight,

but obvious, facial asymmetry caused by the swelling over the right maxillary region. The mass

was firm and non-tender on palpation and not adherent to the overlying skin. Intra-oral

Endodontic treatment was performed for the upper right first and second premolars and for

the second molar tooth. It was decided that the first molar roots and third molars would be

An operation was performed under general anesthesia, with combined local anesthesia. A

trapezoid mucoperiosteal flap was designed and carefully elevated (Figure 34). The teeth were

extracted and the cyst was enucleated (Figure 35); and apical resection was performed (Figure

36). An intranasal inferior meatal antrostomy was performed as was packing of the sinus

(Figures 37, 38); this was removed 3 days later. Endoscopic assistance was not used because

of good visualization. Pathological specimens were sent for examination and report confirmed

a radicular cyst (Figure 39).

extracted. All important anatomical points were carefully checked on CT scans.

examination showed expansion of the upper right molar region.

260 A Textbook of Advanced Oral and Maxillofacial Surgery Volume 2

**Figure 34.** Mucoperiosteal elevation and cyst exposure.

**Figure 35.** Cyst enucleation.

**Figure 34.** Mucoperiosteal elevation and cyst exposure.

262 A Textbook of Advanced Oral and Maxillofacial Surgery Volume 2

**Figure 36.** Apical resection.

**Figure 37.** Intranasal inferior meatal antrostomy and packing of the sinus maxillaris.

**Figure 38.** Closed mucoperiosteal flap and enucleated cyst.

**Figure 36.** Apical resection.

264 A Textbook of Advanced Oral and Maxillofacial Surgery Volume 2

**Figure 39.** 5 year postoperative OPG

#### **6.5. Case 5**

A 33-year-old male was referred to our department with difficulty in nasal breathing, halitosis, and a slowly growing facial deformity on the left side of the face. From radiological (OPG and CT) and clinical examinations (Figure 42), it was seen that there was a cyst, which was related to the left maxillary teeth and nasal floor, uplifting the sinus floor, although it did not obliterate the sinus ostium and the sinus mucosa was not infected. This information was important for the decision as to whether to perform an intranasal inferior meatal antrostomy or not. In this case, because the parameters for maxillary sinus ventilation were ideal, we did not perform an antrostomy. Before the operation all teeth on the left site underwent endodontic treatment (Figure 41).

An operation was performed under general anesthesia combined with local anesthesia. A trapezoid mucoperiosteal flap was designed and carefully elevated (Figure 42). The buccal cortex was decorticated using a round bur without damaging the cyst wall (Figure 43). Intracystic liquid was aspirated with a 20-cc syringe (Figure 44). During aspiration, cholesterol crystals were observed clearly in the cyst fluid. After enucleation of cyst (Figure 45), apical resection plus MTA retrograde filling was performed and the mucoperiosteal flap was sutured. Pathological specimens were sent for examination and the report was a radicular cyst.

Endodontic surgery involves a combination of curettage of infected tissue and removal of an infected or damaged root apex. Among the causes of failure in endodontic surgery, the most frequent is the incomplete sealing of all communications between the root canal system and periradicular tissues. Many studies have shown that bacteria that remain in the root canal system have access to the periradicular tissues after resection [26, 27] The main purpose of the root-end filling material is to provide an apical seal that prevents the movement of bacteria from the root canal system into the periapical tissues. Recently, an experimental substance, MTA, was suggested as a potential root-end filling material. In a series of *in vitro* studies, the sealing ability of MTA was evaluated, compared with commonly used root-end-filling materials. It was shown that MTA had significantly less dye and bacterial leakage. [26, 28, 29] Some studies have shown that when the root canal is confined hermetically and an adequate retrograde cavity depth is prepared, then variation in the root-end cutting angle does not necessarily cause any difference in microleakage. [26]

**Figure 40.** Radiological (OPG and CT) examination.

**6.5. Case 5**

266 A Textbook of Advanced Oral and Maxillofacial Surgery Volume 2

(Figure 41).

A 33-year-old male was referred to our department with difficulty in nasal breathing, halitosis, and a slowly growing facial deformity on the left side of the face. From radiological (OPG and CT) and clinical examinations (Figure 42), it was seen that there was a cyst, which was related to the left maxillary teeth and nasal floor, uplifting the sinus floor, although it did not obliterate the sinus ostium and the sinus mucosa was not infected. This information was important for the decision as to whether to perform an intranasal inferior meatal antrostomy or not. In this case, because the parameters for maxillary sinus ventilation were ideal, we did not perform an antrostomy. Before the operation all teeth on the left site underwent endodontic treatment

An operation was performed under general anesthesia combined with local anesthesia. A trapezoid mucoperiosteal flap was designed and carefully elevated (Figure 42). The buccal cortex was decorticated using a round bur without damaging the cyst wall (Figure 43). Intracystic liquid was aspirated with a 20-cc syringe (Figure 44). During aspiration, cholesterol crystals were observed clearly in the cyst fluid. After enucleation of cyst (Figure 45), apical resection plus MTA retrograde filling was performed and the mucoperiosteal flap was sutured.

Pathological specimens were sent for examination and the report was a radicular cyst.

necessarily cause any difference in microleakage. [26]

Endodontic surgery involves a combination of curettage of infected tissue and removal of an infected or damaged root apex. Among the causes of failure in endodontic surgery, the most frequent is the incomplete sealing of all communications between the root canal system and periradicular tissues. Many studies have shown that bacteria that remain in the root canal system have access to the periradicular tissues after resection [26, 27] The main purpose of the root-end filling material is to provide an apical seal that prevents the movement of bacteria from the root canal system into the periapical tissues. Recently, an experimental substance, MTA, was suggested as a potential root-end filling material. In a series of *in vitro* studies, the sealing ability of MTA was evaluated, compared with commonly used root-end-filling materials. It was shown that MTA had significantly less dye and bacterial leakage. [26, 28, 29] Some studies have shown that when the root canal is confined hermetically and an adequate retrograde cavity depth is prepared, then variation in the root-end cutting angle does not

**Figure 41.** Endodontic treatment of the teeth.

**Figure 42.** Preparation and elevation of the mucoperiosteal flap.

**Figure 43.** Buccal cortex decortication.

**Figure 41.** Endodontic treatment of the teeth.

268 A Textbook of Advanced Oral and Maxillofacial Surgery Volume 2

**Figure 42.** Preparation and elevation of the mucoperiosteal flap.

**Figure 44.** Intracystic liquid aspiration with a 20-cc syringe and view of cholesterol crystals.

**Figure 45.** Enucleation of the cyst.


4.3.1. High Geometric Accuracy

More specifically, the expressed need by government stakeholders for highly accurate spatial data can entirely be met by UAS imagery as shown by the low RMSE of checkpoint residuals in this study. Even though the national CORS in Rwanda cannot be considered as a source of GNSS corrections for PPK workflows, different means of georeferencing have proven to hit similar accuracies. This data characteristic facilitates the manual or digital delineation of parcel boundaries and support valuation and taxation processes–two needs which were prioritised by non-government stakeholders. The current cadastral map is based on the LTR programme which followed a general boundary approach which sometimes shows several meters offset to the correct location of the boundary. Most disputes arose during land transactions in densely populated areas, where plot sizes are small, and people depend on their land for subsistence farming. In those cases, UAS data ultimately facilitates a reliable and geometrically correct database to correct existing cadastral data.


**1. Introduction**

64 Sleep Disorders

Yamada, H., Yatsushiro, S., Ishio, S., Hayashi, M., Nishi, T., Yamamoto, A., et al. (1998).

pinealocytes. *The Journal of Neuroscience*, Vol. 18, No. 6, pp. 2056-2062.

Metabotropic glutamate receptors negatively regulate melatonin sintesis in rat

Snoring and obstructive sleep apnoea (OSA) both exhibit multilevel upper airway obstruction. The Importance of evaluating the dynamics of the obstructing upper airway cannot be emphasised enough. Accurate assessment and evaluation of the upper airway could potentially lead to improved surgical and non-surgical treatment outcomes. Most of these patients would have undergone an ambulatory sleep study or a polysomnography prior to deciding what treatment modality is going to be offered to them. Treatment options available include nasal continuous positive airway pressure (nCPAP), mandibular advancement splints (MAS) or surgery. In terms of selecting a treatment option, in cases where the sleep study has confirmed moderate or severe OSA, nCPAP would be favoured. In the remainder and the nCPAP failed patients, further evaluation of the upper airway is useful and necessary. This chapter will not address sleep studies but will discuss various methods of assessing the upper airway and will include clinical evaluation of the upper airway during wakefulness and sleep.


**5. Compartmental mathematical models**

These models can be either Susceptible-Infectious-Recovered (SIR), Susceptible-Infectious-Recovered-Susceptible (SIRS), Susceptible-Exposed-Infectious-Recovered (SEIR), Susceptible-Infected (SI) or Susceptible-Infectious-Susceptible (SIS). Number of compartments in the model depend on the disease being studied and the objective of the study. In this approach, the progress of the disease is defined in terms of level of pathogen within the host.

#### **5.1. SIR model**

output. A model is usually expressed in terms of variables which are related to experimentally

A mathematical model helps in establishment of links between sets of epidemiological data through well-understood mathematical relationships. This is facilitated only through a thorough understanding of various factors associated with the disease like, incubation, transmission and mortality and also factors associated with the vector. Models may also help to characterize and integrate the cellular network and molecular data operating within the different compartments of the host immunity system for disease progression. At a mechanistic level, they help in finding answers to several biological questions which cannot be addressed experimentally. Different conceptual qualitative results and threshold values of paramount importance like basic reproduction ratio, contact numbers, replacement numbers and herd immunity, are derived from mathematical models, since the quantity and diversity of available data is limited. Conditions for local and global stability of various equilibria, relationships among these stability conditions and endemicity are also derived from the epidemiological models. Prediction and recommendations for control of an epidemic outbreak are therefore, the most important outcomes of mathematical modeling of a communicable disease and then they are known as decision models. These models facilitate economic evaluation of different courses of action for mitigation of a particular infection and finally help in selection of optimal

Spatio-temporal progression and temporal development of communicable diseases can be explained by compartmental, agent-based or contact network-based model. In the compart‐ mental model, the host population is divided into different states or compartments, depending on the level of infection in them. Rates of transfer e.g. transmission rate, removal rate between compartments are expressed as derivatives of the sizes of the compartments with respect to time and are assumed to be constant. Ordinary differential equations form the basic framework of compartmental models. In agent-based model, the region of interaction of people in a population is considered as a system of software agents interacting in time and space. It is a high fidelity model and involves complex parameterization and extensive computation. Modern concepts of network theory are employed in dissecting the transmission dynamics within heterogeneous population in a contact network model. Social networking among the individuals influence the possibility, extent and speed of epidemic spreading. This model is intermediate between compartmental model and agent-based model. In this model, the pathogen and the social network within the population are closely intertwined and represent‐ ed by a node for each individual. The framework of contact network highly depends on the

Accuracy, transparency and flexibility are the key elements which should be balanced to develop a mathematical model of high quality. For development of any type of mathematical model, mathematical modelers formulate a set of equations by feeding into them various type of factors like the length of time one is ill, the length of time one can infect others, the level of contagiousness of the disease, the number of uninfected individuals who can contract the disease, human behavior and any such known component of disease dynamics. Once a model with biological significance and relevance has been formulated, the model can be fitted to the

measurable quantities.

186 Trends in Infectious Diseases

control measure [8].

mode of transmission of the disease [2], [9].

Number or density of individuals in each stage of infection is more important than the load of the pathogen per person in modeling of microparasitic infections. In the SIR model in order to emulate epidemics, population is classified as Susceptible, currently Infectious and Recovered. The total size of the host population is the summation of the three classes. When an individual is concerned, he is assumed to exist in either of the three states. Susceptible means that the individual has never had the disease and is susceptible to contraction of the disease by an infected individual, at random from the population. The mode of transmission of infection depends on the type of the pathogen. Depending on the relative magnitude of the latent period of the infection, the infected host can infect others and then it becomes Infectious. The total time spent in the infected state by an individual is a geometric random variable. When the infectious agent is removed from the system of the infected class or death occurs, they become Recovered with immunity and will never be infected again. In case of a dead individual, he cannot get infected or cannot infect anybody and thus is equivalent to a recovered individual with acquired immunity. Then, it can be assumed that the number of infected individuals tends to decrease towards zero and finally disappears from the network permanently. In the study of disease dynamics, six distinct and well-defined events can be assumed to occur : birth, death of a susceptible individual, death of an infected individual, death of a recovered individual, infection and recovery. Epidemic data supports the assumption that the per capita rate at which a given susceptible individual becomes infected is proportional to the prevalence of infection in the population. Therefore, according to SIR model, number of cases increases exponentially initially till there has been a sufficient decrease in the proportion of susceptible when the growth rate slows; this process goes on until the epidemic can no longer be maintained and the number of cases goes below a threshold level resulting in disease eradication. Human behavior can affect the disease dynamics in an individual as also in the whole population because it may influence the disease state of an individual, rate of infection or recovery rate and the contact network structure. Therefore, behavioral responses should be considered as an integral part of the study of dynamics of infectious diseases. An intriguing feature of childhood microparasitic infections is that the children are born in the susceptible category as there is no vertical transmission. Birth rate and vaccination affect the recruitment to the susceptible compartment. Moreover, in case of common cold, there is no permanent removal state because the individual enters the susceptible class soon after recovery. This widely used model is applicable for diseases which are contracted by an individual only once in its lifetime and either acquired lifelong immunity develops or death occurs as in case of measles, mumps, SARS, influenza. An important drawback of the model is that it ignores the random effects, specially at early stages of infection, when the number of both susceptible and infected classes is low. This model is unable to describe the spatial aspects of the spread of the disease. Moreover, in this modeling approach it is assumed that each individual has the same amount of contacts as every other individual. Therefore, if the rate of contact varies during course of infection, it cannot be appropriately included in the simple SIR model. Precision in prediction can be improved by incorporating realistic contact patterns or by using modeling approaches possessing higher fidelity.

Infectious and Infectious-Recovered is not very distinct because of variability in responses between different individuals and variability in pathogen levels over the infectious period [7].

Unearthing the Complexities of Mathematical Modeling of Infectious Disease Transmission Dynamics

http://dx.doi.org/10.5772/57387

189

This modeling approach is unrealistic in case of animal or human infections because here it is assumed that an infected individual remains in this state forever. Hence, the ultimate conse‐ quence of the presence of one infected individual in the population is the infection of the entire population. In the early stages of an infection, when the count of infected cases is low, the SI and SIR models behave in a similar fashion as there is limited number of recovered individuals.

In this model, individuals run stochastically through the cycle of Susceptible-Infected – Susceptible. Thus, here exist only two states because the infected individual, after recovery, again becomes susceptible to infection. Removal due to death or acquired immunization is not considered. Therefore, the number of infected individuals increases up to a stationary nonzero constant value as observed in case of sexually transmitted diseases [10]. The renewed susceptibility of an individual is due to vast antigenic variation associated with gonorrhea and other similar sexually transmitted diseases [7]. This model is based on assumptions like, different contagion probabilities between different pairs of people, probabilistic recovery from

the disease and multiple stages of infection, with varying disease properties [9].

**6. Deterministic and Stochastic approach to mathematical modeling**

If the objective of the study is to model disease propagation in a large population, with continuous variations of population sizes, deterministic model is the most appropriate one. Such model indicates same output or same fate of individuals subjected to same possible events with identical probabilities [6]. For a given set of parameter values, the deterministic model has one solution which can be fitted to data using various methods. The most common method minimizes the sum of squares of differences between observed data and model prediction.

Natural and biological discrete events of random occurrence in a small population cannot be explained by deterministic and continuous modeling and here comes the utility of stochastic modeling. Stochastic models capture the randomness of birth and death rates associated with disease dynamics and also the variability among disease strains. The earliest stages of an infection are stochastic. This occurs because encounter with a pathogen may either lead to an infection or elimination from the system. Stochasticity decreases as the number of cases increases. Emergent behaviors that have neither been defined nor expected are simulated in this modeling approach. Probability distributions associated with such systems are typically memory-less. If the objective of modeling of disease dynamics is to establish the conditions for disease eradication, or if irregular epidemics are to be modeled, stochastic model is the choice. Stochasticity can induce chance extinctions of the disease and it introduces variances and co-

**5.4. SI model**

**5.5. SIS model**

The SIR model can also be expressed by a stochastic version where the future course of the infection is independent of the past, if present is known completely [2], [6], [9-10].

#### **5.2. SIRS**

This model assumes that after recovery, the person becomes susceptible again as immunity wanes, i.e. recovered individuals possess short-term immunity [4], [14].

#### **5.3. SEIR**

It is an extended SIR model where a new compartment or state is added. It is known as Exposed or E which is positioned between the susceptible and infectious compartments. The Exposed individual is infected but not infectious, i.e. the disease remains in latent state [15].This concept can also be explained on the basis of the level of pathogen within the host and immunological status of the host. When the host is susceptible, it indicates that no pathogen is present and only a low level of non-specific immunity exists within the host. As soon as the susceptible encounters an infectious individual, he becomes infected. The pathogen increases in number and the infected host may not show any signs of infection and thus he enters the Exposed compartment. As soon as the pathogen burden is sufficiently high, the Exposed host becomes Infectious and disease is transmitted to another susceptible individual. When the Infectious individual can no longer transmit infection as the pathogen is cleared from his immunity system, he belongs to the Recovered category. The class distinction between ExposedInfectious and Infectious-Recovered is not very distinct because of variability in responses between different individuals and variability in pathogen levels over the infectious period [7].

### **5.4. SI model**

in the population. Therefore, according to SIR model, number of cases increases exponentially initially till there has been a sufficient decrease in the proportion of susceptible when the growth rate slows; this process goes on until the epidemic can no longer be maintained and the number of cases goes below a threshold level resulting in disease eradication. Human behavior can affect the disease dynamics in an individual as also in the whole population because it may influence the disease state of an individual, rate of infection or recovery rate and the contact network structure. Therefore, behavioral responses should be considered as an integral part of the study of dynamics of infectious diseases. An intriguing feature of childhood microparasitic infections is that the children are born in the susceptible category as there is no vertical transmission. Birth rate and vaccination affect the recruitment to the susceptible compartment. Moreover, in case of common cold, there is no permanent removal state because the individual enters the susceptible class soon after recovery. This widely used model is applicable for diseases which are contracted by an individual only once in its lifetime and either acquired lifelong immunity develops or death occurs as in case of measles, mumps, SARS, influenza. An important drawback of the model is that it ignores the random effects, specially at early stages of infection, when the number of both susceptible and infected classes is low. This model is unable to describe the spatial aspects of the spread of the disease. Moreover, in this modeling approach it is assumed that each individual has the same amount of contacts as every other individual. Therefore, if the rate of contact varies during course of infection, it cannot be appropriately included in the simple SIR model. Precision in prediction can be improved by incorporating realistic contact patterns or by using modeling approaches

The SIR model can also be expressed by a stochastic version where the future course of the

This model assumes that after recovery, the person becomes susceptible again as immunity

It is an extended SIR model where a new compartment or state is added. It is known as Exposed or E which is positioned between the susceptible and infectious compartments. The Exposed individual is infected but not infectious, i.e. the disease remains in latent state [15].This concept can also be explained on the basis of the level of pathogen within the host and immunological status of the host. When the host is susceptible, it indicates that no pathogen is present and only a low level of non-specific immunity exists within the host. As soon as the susceptible encounters an infectious individual, he becomes infected. The pathogen increases in number and the infected host may not show any signs of infection and thus he enters the Exposed compartment. As soon as the pathogen burden is sufficiently high, the Exposed host becomes Infectious and disease is transmitted to another susceptible individual. When the Infectious individual can no longer transmit infection as the pathogen is cleared from his immunity system, he belongs to the Recovered category. The class distinction between Exposed-

infection is independent of the past, if present is known completely [2], [6], [9-10].

wanes, i.e. recovered individuals possess short-term immunity [4], [14].

possessing higher fidelity.

188 Trends in Infectious Diseases

**5.2. SIRS**

**5.3. SEIR**

This modeling approach is unrealistic in case of animal or human infections because here it is assumed that an infected individual remains in this state forever. Hence, the ultimate conse‐ quence of the presence of one infected individual in the population is the infection of the entire population. In the early stages of an infection, when the count of infected cases is low, the SI and SIR models behave in a similar fashion as there is limited number of recovered individuals.

### **5.5. SIS model**

In this model, individuals run stochastically through the cycle of Susceptible-Infected – Susceptible. Thus, here exist only two states because the infected individual, after recovery, again becomes susceptible to infection. Removal due to death or acquired immunization is not considered. Therefore, the number of infected individuals increases up to a stationary nonzero constant value as observed in case of sexually transmitted diseases [10]. The renewed susceptibility of an individual is due to vast antigenic variation associated with gonorrhea and other similar sexually transmitted diseases [7]. This model is based on assumptions like, different contagion probabilities between different pairs of people, probabilistic recovery from the disease and multiple stages of infection, with varying disease properties [9].


**3. Neuroplasticity and music: macrostructural and microstructural adaptations**

**2. Phylogenetic and ontogenetic claims: the role of adaptation**

making and immersion in a culture [41, 42].

88 Neuroplasticity - Insights of Neural Reorganization

taking the concept of adaptation as a working hypothesis.

Brain plasticity is an adaptation to the environment with an evolutionary advantage. It allows an organism to be changed in order to survive in its environment by providing better tools for coping with the world [40]. This biological concept of adaptation can be approached from two different scales of description: the larger evolutionary scale of the human as a species (phylogeny) and the more limited scale of the human from newborn to old age (ontogeny). This phylogenetic/ontogenetic distinction is related to the "nature/nurture" and "culture/biology" dichotomy, which refers to the neurobiological claims of wired-in circuitry for perceptual information pickup as against the learned mechanisms for information processing and sense-

These approaches may seem to be diverging at first glance, but they are complementary to some extent. This holds, in particular, for the here-hypothesised music-induced plasticity, which espouses a biocultural view that aims at a balance between genetic or biological constraints and historical/cultural contingencies. This places all human beings on equal ground (unity) by stating that diversity in culture is only an epiphenomenon of an underlying biological disposition that is shared by people all over the world [43]. The assumed unity is attributed to the neural constraints that underlie musical processing in general, but these constraints should not be considered as a static dispositional machinery. The picture that emerges from recent research is arguing, on the contrary, for a definition of the neural machinery as a dynamic system that is able to adapt in answer to the solicitations of a challenging environment [6]. The neurobiological approach to music, therefore, deals not only with the nature and evolution of the innate and wired-in neural mechanisms that are the hallmark of the hominid phylogenetic evolution but also with the ontogenetic development of these mechanisms [43]. As such, it makes sense to conflate neurobiological and developmental claims by

The relation between adaptation and development, however, is asymmetrical in the sense that it is possible to conceive of development without adaptation, but no adaptation is conceivable without development. This development, further, can be natural, when it is the outcome of maturation, but it is possible also to intervene in its trajectory by combining development and learning. This is the case when an organism faces continued and long-term exposure to challenging environments, which triggers plastic changes in the structure and the functions of the brain. This brings us to the concept of brain plasticity, which refers to the fact that neuronal circuits are tuned in close interaction with the environment. It was introduced by William James, who defined plasticity as "the possession of a structure weak enough to yield to an influence, but strong enough not to yield all at once" [44] (p. 106). The idea was further developed by Ramón y Cajal, who claimed that to fully understand the phenomenon it is necessary to admit the formation of new pathways in the brain through ramification and progressive growth of the dendritic arborisation and the nervous terminals in addition to the reinforcement of pre-established organic pathways. The same idea was elaborated further by Donald Hebb, who proposed that neuronal cortical connections are strengthened and remodelled by experience. There is, however, another aspect of plasticity that goes beyond the level of The evolutionary claims of adaptation—both at the phylogenetic and ontogenetic level—have received empirical evidence from neuroimaging and morphometric studies. In order to elucidate its underlying mechanisms, there is currently a whole body of research related to the psychobiological approach to the study of action, cognition and perception. A major claim in this research field is that the nervous system provides the immediate, necessary and sufficient mechanisms that underlie all mental processes, and that mental processes are reducible to the function, arrangement and interaction of neurons as the constituent building blocks of the nervous system [46]. This is the axiom of psychobiological equivalence, which claims an equivalence of maintained information from the neural to the psychological state [47]. The related research revolves around three major themes: (i) the localisation of functions in the brain, (ii) the representation or coding and (iii) the dynamic change or learning [46]. The first investigates which brain structures are responsive for particular processes. The second investigates how neural networks represent, encode or instantiate cognitive processes, both at macrostructural and microstructural level of description (see [48]). The third, finally, investigates how our brain adapts to experience and learning, what changes occur in its neural networks and how these changes correspond to externally observed behaviour.

The third theme—dynamic change or learning—concerns the neural correlates of skill acquisition and has been studied mainly at the level of perceptual processing and motor output. Yet, there is also the whole domain of creativity [49], musical aesthetics [6, 50–53] and human interaction [54, 55], which have been poorly investigated in relation to long-term music training. However, the topic is exemplary of a paradigm shift in current neuromusicological research, with a transition from a static conception of brain modules to a conception of reorganisational plasticity of the developing and adult brain [6]. Plasticity, in fact, is a fundamental organisational feature of the human brain, which can be modified throughout the life span in response to changes in environmental stimulation. This has been observed not only during a critical period in the developing brain but also even throughout the whole life span.

Skill learning, such as learning to play a musical instrument, can thus be used for the study of neuroplasticity.  It involves multiple sensory modalities and motor planning, preparation and execution systems [27, 56]. The role of environmental enrichment—being defined as a combination of complex inanimate and social stimulation [57]—on the other hand, should be stressed also as an emerging area of research. Music, in this view, can be considered as "sounding environment" [42], which is likely to drive brain plasticity. Even in the foetal phase of development, sounds can trigger ways of implicit learning [58]. Neonates and infants also learn to talk and sing quasi-effortless as the result of mere exposure, thus demonstrating implicit learning and developmental plasticity, which is even cross-modal to a large extent, in the sense that loss of one sensory modality may lead to neural organisation of the remaining modalities [2].

been studied in the context of deafferentation studies—in the case of brain lesion—and in the case of motor skill learning [62]. In the former, some cortical remodelling has been found, including microstructural changes, such as the strengthening of existing synapses, the formation of new synapses (synaptogenesis), axonal sprouting and dendrite growth. In the latter, similar changes have been found, including an increased number of synapses per neuron and changes in the number of microglia and capillaries [63], which all lead to volumetric changes

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The bulk of studies on neuroplasticity has been performed in the context of within-modality plasticity, particularly in the domain of sensory and motor modalities. They aim at demonstrating the adaptive capabilities of the human brain to shape the processing of sensory stimuli or to perform motor acts after repeated sensory exposure or action [9]. With regard to the sensory modality, animal studies have shown that environmental change critically affects brain development. Experience-driven neural activity, in fact, regulates the refinement of the neural circuitry by influencing various neural processes, such as synapse formation, pruning and synaptic plasticity (see **Box 1**) with modifications in synaptic connectivity as a result [65]. This enhanced connectivity, further, acts as a basis for learning and memory through alterations at the level of neural circuits [66], such as strengthening or weakening of the synaptic links or altering their number, changes in the number or properties of postsynaptic receptors in transmitter release and the formation of new synapses. The result is an increase in synaptic strength, which may be persistent and facilitate learning and memory so that experiencedependent plasticity could involve selective changes in pre-existing brain circuits [65].

As to the enhanced auditory skills, it has been argued that they may prime the brain for the processing of musical sounds and that these skills may percolate to other domains, such as speech, emotion and auditory processing in general [67, 68]. This has been observed already in the early stages of the auditory pathway, which are located mainly in the brainstem. Musicians have enhanced temporal and frequency coding in the auditory brainstem with

**Myelinisation**: the acquisition, development or formation of a myelin sheath around a nerve fibre. This fatty coating serves as insulation of individual fibres to enhance specificity of connections and increases markedly the quick and

**Pruning**: a process that helps sculpt the adult brain and by which neurons and synaptic connections that are no

**Sprouting**: a process by which a neuron generates additional branches or outgrowths to establish new links between existing neurons, as seen frequently in the case of growth of axons or dendrites from a damaged or intact neuron that

**Synaptic plasticity**: strengthening or weakening of the synaptic links either by modulating the strength of synapses

**Synaptic efficacy**: changes in the number or properties of postsynaptic receptors in transmitter release and the for-

**Adult neurogenesis**: birth of neurons from neural stem cells in the adult brain. In humans, adult neurogenesis has been shown to occur only in the hippocampus (particularly in the sub-granular zone of the dentate gyrus) and in the

longer used or useful are eliminated in order to increase the efficiency of neuronal transmissions.

that are detectable also at the macrostructural level [27, 64].

accurate transmission of electrical current from one nerve cell to another.

**Box 1.** Overview of some basic mechanisms for refinement of the neural circuitry

projects to an area that is denervated.

mation of new synapses (synaptogenesis).

striatum. It differs from developmental neurogenesis.

or by altering their numbers.

Neuroplasticity is also related to the field of sensory-motor learning, with a major role attributed to the challenges of a rich environment. It favours multiple interactions with the world both at the sensory and at the motor level—stressing the interdependency of an organism and its environment through which it "enriches its repertory of genetic adaptations with acquired dispositions that are immediately at hand and mobilizable when confronted with a situation that can be foreseen or recognized as a familiar one" [59] (p. 925).

Musical training, accordingly, may be related to sensory and motor changes in the human brain of professional musicians. As a rule, music training involves years of sensory-motor training, often beginning in early childhood, with the aim to develop an expertise in a chosen instrument or mastery over the own voice, together with an improvement of the ability to attend to the fine-grained acoustics of musical sounds, including pitch, timing and timbre [3]. The brains of musicians might adapt to the demands of their instrumental practice at two levels: the gross anatomical differences between professional musicians and amateurs or laymen, and the subtle functional differences after enhanced musical practice and/or experience, which have to be sought in ever finer modifications of synaptic strength in distributed cortical networks. As such, it is possible to distinguish between macrostructural and microstructural adaptations. The macrostructural differences related to volume, morphology, density and connectivity of brain structures are measured with magnetic resonance imaging (MRI), whereas the microstructural differences in the functional activity of brain regions are measured with functional magnetic resonance imaging (fMRI), positron emission tomography (PET) and neurophysiology (electroencephalography, EEG and magnetoencephalography [MEG]) (see [5] for an overview). It is further hypothesised that functional reorganisation may cause structural adaptation. For instance, bimanual instrument training, such as for the piano, may cause an increase in cortical functionality for symmetric areas involved in motor, auditory and visuospatial processing, as well as in the white matter tracts of the corpus callosum [20] as compared with less bimanual training (such that for the violin) and especially as opposed to laypersons.

At the macrostructural level, studies show differences in the size of the primary motor cortex size, the cerebellum, the planum temporale, the corpus callosum, Heschl's gyrus and the arcuate fasciculus, all of which seem to correlate with the ability of musicians to identify and process acoustic variations [60]. The microstructural adaptations, on the other hand, happen at the level of individual neurons and synapses, with the aim to change the efficacy of neural connectivity. In general, the brain shows adaptation to extraordinary challenges by giving birth to new neurons (neurogenesis) and glial cells and by the formation and remodelling of new connections by the outgrowth of dendrites, axonal sprouting and increasing or strengthening of synaptic connections [61] (see **Box 1** for an overview). Such adaptations have been studied in the context of deafferentation studies—in the case of brain lesion—and in the case of motor skill learning [62]. In the former, some cortical remodelling has been found, including microstructural changes, such as the strengthening of existing synapses, the formation of new synapses (synaptogenesis), axonal sprouting and dendrite growth. In the latter, similar changes have been found, including an increased number of synapses per neuron and changes in the number of microglia and capillaries [63], which all lead to volumetric changes that are detectable also at the macrostructural level [27, 64].

the other hand, should be stressed also as an emerging area of research. Music, in this view, can be considered as "sounding environment" [42], which is likely to drive brain plasticity. Even in the foetal phase of development, sounds can trigger ways of implicit learning [58]. Neonates and infants also learn to talk and sing quasi-effortless as the result of mere exposure, thus demonstrating implicit learning and developmental plasticity, which is even cross-modal to a large extent, in the sense that loss of one sensory modality may lead to neural

Neuroplasticity is also related to the field of sensory-motor learning, with a major role attributed to the challenges of a rich environment. It favours multiple interactions with the world both at the sensory and at the motor level—stressing the interdependency of an organism and its environment through which it "enriches its repertory of genetic adaptations with acquired dispositions that are immediately at hand and mobilizable when confronted with a situation

Musical training, accordingly, may be related to sensory and motor changes in the human brain of professional musicians. As a rule, music training involves years of sensory-motor training, often beginning in early childhood, with the aim to develop an expertise in a chosen instrument or mastery over the own voice, together with an improvement of the ability to attend to the fine-grained acoustics of musical sounds, including pitch, timing and timbre [3]. The brains of musicians might adapt to the demands of their instrumental practice at two levels: the gross anatomical differences between professional musicians and amateurs or laymen, and the subtle functional differences after enhanced musical practice and/or experience, which have to be sought in ever finer modifications of synaptic strength in distributed cortical networks. As such, it is possible to distinguish between macrostructural and microstructural adaptations. The macrostructural differences related to volume, morphology, density and connectivity of brain structures are measured with magnetic resonance imaging (MRI), whereas the microstructural differences in the functional activity of brain regions are measured with functional magnetic resonance imaging (fMRI), positron emission tomography (PET) and neurophysiology (electroencephalography, EEG and magnetoencephalography [MEG]) (see [5] for an overview). It is further hypothesised that functional reorganisation may cause structural adaptation. For instance, bimanual instrument training, such as for the piano, may cause an increase in cortical functionality for symmetric areas involved in motor, auditory and visuospatial processing, as well as in the white matter tracts of the corpus callosum [20] as compared with less bimanual training (such that for the violin) and especially as opposed to laypersons. At the macrostructural level, studies show differences in the size of the primary motor cortex size, the cerebellum, the planum temporale, the corpus callosum, Heschl's gyrus and the arcuate fasciculus, all of which seem to correlate with the ability of musicians to identify and process acoustic variations [60]. The microstructural adaptations, on the other hand, happen at the level of individual neurons and synapses, with the aim to change the efficacy of neural connectivity. In general, the brain shows adaptation to extraordinary challenges by giving birth to new neurons (neurogenesis) and glial cells and by the formation and remodelling of new connections by the outgrowth of dendrites, axonal sprouting and increasing or strengthening of synaptic connections [61] (see **Box 1** for an overview). Such adaptations have

organisation of the remaining modalities [2].

90 Neuroplasticity - Insights of Neural Reorganization

that can be foreseen or recognized as a familiar one" [59] (p. 925).

The bulk of studies on neuroplasticity has been performed in the context of within-modality plasticity, particularly in the domain of sensory and motor modalities. They aim at demonstrating the adaptive capabilities of the human brain to shape the processing of sensory stimuli or to perform motor acts after repeated sensory exposure or action [9]. With regard to the sensory modality, animal studies have shown that environmental change critically affects brain development. Experience-driven neural activity, in fact, regulates the refinement of the neural circuitry by influencing various neural processes, such as synapse formation, pruning and synaptic plasticity (see **Box 1**) with modifications in synaptic connectivity as a result [65]. This enhanced connectivity, further, acts as a basis for learning and memory through alterations at the level of neural circuits [66], such as strengthening or weakening of the synaptic links or altering their number, changes in the number or properties of postsynaptic receptors in transmitter release and the formation of new synapses. The result is an increase in synaptic strength, which may be persistent and facilitate learning and memory so that experiencedependent plasticity could involve selective changes in pre-existing brain circuits [65].

As to the enhanced auditory skills, it has been argued that they may prime the brain for the processing of musical sounds and that these skills may percolate to other domains, such as speech, emotion and auditory processing in general [67, 68]. This has been observed already in the early stages of the auditory pathway, which are located mainly in the brainstem. Musicians have enhanced temporal and frequency coding in the auditory brainstem with

**Myelinisation**: the acquisition, development or formation of a myelin sheath around a nerve fibre. This fatty coating serves as insulation of individual fibres to enhance specificity of connections and increases markedly the quick and accurate transmission of electrical current from one nerve cell to another.

**Pruning**: a process that helps sculpt the adult brain and by which neurons and synaptic connections that are no longer used or useful are eliminated in order to increase the efficiency of neuronal transmissions.

**Sprouting**: a process by which a neuron generates additional branches or outgrowths to establish new links between existing neurons, as seen frequently in the case of growth of axons or dendrites from a damaged or intact neuron that projects to an area that is denervated.

**Synaptic plasticity**: strengthening or weakening of the synaptic links either by modulating the strength of synapses or by altering their numbers.

**Synaptic efficacy**: changes in the number or properties of postsynaptic receptors in transmitter release and the formation of new synapses (synaptogenesis).

**Adult neurogenesis**: birth of neurons from neural stem cells in the adult brain. In humans, adult neurogenesis has been shown to occur only in the hippocampus (particularly in the sub-granular zone of the dentate gyrus) and in the striatum. It differs from developmental neurogenesis.

**Box 1.** Overview of some basic mechanisms for refinement of the neural circuitry

earlier (as early as 10 ms after acoustic onset) and larger responses than non-musicians to both speech and music stimuli. This has been shown for the onset response and the frequencyfollowing response (FFR), i.e., a neuronal ensemble response that phase-locks to the incoming stimulus and that underlies perception of pitch as it relates to the sustained portion of a periodic sound with less or more stable frequencies [68, 69].

Functional connectivity can be defined as the temporal dependence of neuronal activity patterns of anatomically separated and removed regions in the brain, reflecting the level of communication between them [80]. It makes it possible to examine the brain as an integrative network of functionally interacting regions and to gain new insights into large-scale neuronal communication in the human brain. Such whole-brain connectivity patterns can be studied by measuring the synchronisation of spontaneous fMRI or MEEG time-series reflecting neural activity of anatomically separated brain regions, which are recorded during rest. These resting–state networks are believed to reflect the functional communication between brain regions [78, 81] and suggest an ongoing information processing and functional connectivity between them even at rest, which is related to neuronal firing. The pattern of correlations between distinct brain areas, moreover, points at the existence of organisational networks in the brain [81], which seems to be analogous to the networks that are engaged during the performance of sensory-motor and cognitive tasks, and which are dependent upon the brain's anatomical connectivity [10]. Such spontaneous neuronal interaction has been first investigated in motor cortices but were later extended to other cortical systems, such as the visual and auditory networks, the default mode network (DMN) and attention and memory related regions. It has been suggested that at least 10–12 resting-state networks (RSNs) can be detected in the cerebral cortex in resting state, which implicates that they represent some intrinsic form of brain connectivity with temporal correlations

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DMN has been related to specific brain functions, such as self-referential thoughts, emotional perspectives and levels of self-awareness. DMN is believed to be a neural circuit that constantly monitors the sensory environment and displays high activity during lack of focused attention on external events [83]. It seems to function as a toggle switch between outwardly focused mind states and the internal or subjective sense of self [84] and can be used to explore the functional connections of the complex integrative network of functionally linked brain regions, which continuously share information with each other. As such, there are interconnected resting-state neuronal communities or functional brain networks with functional communication between them. Being organised according to an efficient topology, they combine efficient local information processing with efficient global information integration with the most pronounced functional connections found between those regions

Overall, resting-state fMRI oscillations reflect ongoing functional communication between distinct brain regions [78], which makes them indicative of the level of cognitive functioning in general. There seems to be, in fact, a link between an efficient organisation of the brain network and intellectual performance—this is the neural efficiency hypothesis—so that functional connectivity patterns may be used as a powerful predictor for cognitive performance [85]. This resting-state connectivity, further, is not to be considered as an established and fixed property, but as a state that can be modulated by recent experiences and learning episodes, both within and between the networks they recruit. Such modulation points in the direction of a learning consolidation function of resting-state brain activity, as evidenced by the findings that high learners manifest stronger pre-task resting-state functional connectivity between the involved regions than low learners [10]. It thus seems that, even in the absence of

between spatially discrete regions [82].

that share common functions.

The role of auditory brainstem processing of behaviourally relevant sounds such as speech and music is important here. It can be measured by using the onset response and the FFR to see how the brainstem represents pitch, timing and timbre [68]. It has been shown that both temporal and spectral characteristics of sounds are preserved in this subcortical response (see [70] for an overview), reflecting the physical properties of sound with an unrivalled fidelity. As a rule, it occurs automatically at pre-attentive levels of auditory processing but is shaped by both long-term and short-term experience [71–73]. Subcortical function, moreover, is neither passive nor hardwired but interacts dynamically with higher-level cognitive processes refining the transcription of sounds into neural code. Hence, the responses do not originate merely in the brainstem but receive feedback from top-down cortical influences even at the earliest stages of auditory processing [3] via corticofugal feedback pathways [74, 75]. As such, it can be demonstrated that musical practice changes the early sensory encoding of auditory stimuli [68] relying on a top-down feedback system—consisting of efferent effects on cochlear biomechanics—that is continuously and automatically engaged to extract and represent regularities in the auditory system [3]. Musical training is thus not limited to the modification of cortical organisation but the modifications extend to subcortical sensory structures and generalise to early processing of speech and sounds in general.

Moreover, early auditory evoked responses and particularly the negative–positive complex (N19-P30) in the auditory evoked potential [76] localised in the primary auditory cortex (the anteromedial portion of Heschl's gyrus) have been found to be larger in musicians compared to amateurs and non-musicians. Moreover, it has been found that the generating neural tissue, namely the grey matter volume of the primary auditory cortex, was broader in volume for professional musicians [77] as compared to laypersons. It thus seems that music can trigger both macrostructural and microstructural or functional changes, not as separate and distinct levels of adaptations, but as phenomena that are dynamically and tightly interconnected.


The biomass of individual tree was significantly different with different tree species (**Table 2**). The order of biomass per plant of eight tree species was as follows: *Cupressus lusitanica* (382.483 kg/plant) > *Taiwania cryptomenoides* (239.907 kg/plant) > *Corylus chinensis* (205.245 kg /plant) > *Toona sinensis* (167.054 kg/ plant) > *Quercus acutissima* (149.734 kg/ plant) > *Choerospondias axillaris* (126.345 kg/ plant) > *Nyssa sinensis* (124.824 kg/ plant) > *Liriodendron chinensis* (117.456 kg/ plant). The results showed that the biomass of each component of tree species was as follows: stem > branches> roots of *Cupressus lusitanica* and *Taiwania cryptomenoides*; the biomass of *Corylus chinensis*, *Toona sinensis*, *Quercus acutissima*, *Choerospondias axillaris*, *Nyssa sinensis* and *Liriodendron chinensis* shows:Stem > roots> branches.

**111**

**Table 3.**

*Afforestation in Karst Area*

*DOI: http://dx.doi.org/10.5772/intechopen.95294*

**4.3 Stand biomass and its distribution pattern**

analyzed under the condition of similar forest age.

*sinensis* > *Quercus acutissima* > *Nyssa sinensis.*

*sis > Choerospondias axillaris.*

*sima* > *Choerospondias axillaris*.

*chinensis* > *Choerospondias axillaris.*

**forest /a**

**Tree species Age of**

*Taiwania cryptomenoides*

*Liriodendron chinensis*

*Choerospondias axillaris*

*Stand biomass of different tree species.*

5.Tree layer > litter layer > understory vegetation layer

The biomass of individual tree is converted into stand biomass as shown

(210.264 t·ha−1) > *Taiwania cryptomenoides* (186.601 t·ha−1) > *Toona sinensis* (18 5.386 t·ha−1) > *Choerospondias axillaris* (181.875 t·ha−1) > *Liriodendron chinensis* (161.548 t·ha−1) > Nyssa sinensis (158.32 t·ha−1).The biomass of tree layer, understory vegetation layer and litter layer of different stands were compared and

1.Tree layer: *Cupressus lusitanica > Quercus acutissima > Corylus chinensis > Toona sinensis > Taiwania cryptomenoides > Nyssa sinensis > Liriodendron chinen-*

2.Undergrowth vegetation layer: *Taiwania cryptomenoides* > Choerospondias axillaris > *Cupressus lusitanica* > *Corylus chinensis* > *Liriodendron chinensis* > *Toona*

3.Litter layer: *Corylus chinensis* > Nyssa sinensis > *Cupressus lusitanica* > *Taiwania cryptomenoides* > *Liriodendron chinensis* > *Toona sinensis* > *Quercus acutis-*

4.Total biomass:*Cupressus lusitanica* > *Quercus acutissima* > *Coryl*us chinensis > *Taiwania cryptomenoides* > *Toona sinensis* > *Nyssa sinensis* > *Liriodendron*

The results showed that: the total biomass of *Cupressus lusitanica* forest was the largest, the biomass of understory vegetation layer and litter layer was also higher than that of other forests, and the growth trend was better than that of other tree species. It can be seen that there are some problems in the regeneration of evergreen

**Stem Branch Tree**

*Cupressus lusitanica* 25 201.79 62.34 48.23 2.65 4.16 319.17

*Quercus acutissima* 20 207.02 31.72 38.27 1.71 2.48 281.20 *Corylus chinensis* 42 162.01 4.60 33.51 2.06 8.09 210.26 *Toona sinensis* 40 152.70 6.20 22.08 1.81 2.60 185.39 *Nyssa sinensis* 40 138.43 13.24 25.16 0.76 4.28 181.88

**Stand biomass /t·ha−1**

**Undergrowth vegetation**

**Litter Total**

**root**

40 116.01 37.10 26.82 2.98 3.69 186.60

37 124.02 5.84 26.75 1.94 3.00 161.55

35 119.09 8.20 26.43 2.79 1.81 158.32

in **Table 3**. The biomass of each stand is as follows: *Cupressus lusitanica* (319.171 t·ha−1) > *Quercus acutissima* (281.197 t·ha−1) > *Corylus chinensis*

#### **Table 2.**

*Biomass comparison of different tree species.*

*Silviculture*

value of 0.0097 m3

value of 0.0057 m3

maximum value of 0.0194 m3

of 0.0112 m3

roots> branches.

0.0068 m3

at 20 years, and the average growth reached the maximum

when VQ(t) was 25 years. VZ(t) and VQ(t) intersect at 27th

at 37 years, and the average growth reached the maximum value of

when VQ(t) was 42 years. VZ(t) and VQ(t) intersect, and the best cut-

at 25th year and 0.0099m3

at 42th

at 40 years. VZ (t) reaches the

**Stem Branches Tree root Total**

at VQ(t) 40th year. VZ(t)

year, which is the best cutting age of *Choerospondias axillaris*. After afforestation, the growth of *Corylus chinensis* was slow in the first seven years, and entered the fast-growing stage after seven years. The volume growth reached 0.2783m3

year. The annual volume growth of *Corylus chinensis* reached the maximum value

ting age at 42th year. After afforestation, *Taiwania cryptomenoides* experienced slow growth period in the first 10 years, and entered the fast-growing stage after

and VQ(t) do not intersect before 40th year. Therefore, the best cutting age of

The biomass of individual tree was significantly different with different tree species (**Table 2**). The order of biomass per plant of eight tree species was as follows: *Cupressus lusitanica* (382.483 kg/plant) > *Taiwania cryptomenoides* (239.907 kg/plant) > *Corylus chinensis* (205.245 kg /plant) > *Toona sinensis*

(167.054 kg/ plant) > *Quercus acutissima* (149.734 kg/ plant) > *Choerospondias axillaris* (126.345 kg/ plant) > *Nyssa sinensis* (124.824 kg/ plant) > *Liriodendron chinensis* (117.456 kg/ plant). The results showed that the biomass of each component of tree species was as follows: stem > branches> roots of *Cupressus lusitanica* and *Taiwania cryptomenoides*; the biomass of *Corylus chinensis*, *Toona sinensis*, *Quercus acutissima*, *Choerospondias axillaris*, *Nyssa sinensis* and *Liriodendron chinensis* shows:Stem >

*Cupressus lusitanica* 247.09 76.34 59.06 382.48 *%* 64.60 20.00 15.40 100.00 *Taiwania cryptomenoides* 154.68 49.47 35.75 239.91 *%* 64.50 20.60 14.90 100.00 *Corylus chinensis* 166.16 4.72 34.37 205.25 *%* 81.00 2.30 16.70 100.00 *Toona sinensis* 140.95 5.73 20.38 167.05 *%* 84.40 3.40 12.20 100.00 *Quercus acutissima* 111.9 17.15 20.69 149.73 *%* 74.70 11.50 13.80 100.00 *Choerospondias axillaris* 97.88 6.74 21.72 126.35 *%* 77.50 5.30 17.20 100.00 *Nyssa sinensis* 97.72 9.35 17.76 124.82 *%* 78.30 7.50 14.20 100.00 *Liriodendron chinensis* 93.02 4.38 20.06 117.46 *%* 79.20 3.70 17.10 100.00

**Tree species Biomass per plant /(kg/plant)**

10 years, and the volume growth reached 0.3959 m3

*Taiwania cryptomenoides* is at least 40th year.

**4.2 Biomass per tree and its distribution**

**110**

**Table 2.**

*Biomass comparison of different tree species.*

#### **4.3 Stand biomass and its distribution pattern**

The biomass of individual tree is converted into stand biomass as shown in **Table 3**. The biomass of each stand is as follows: *Cupressus lusitanica* (319.171 t·ha−1) > *Quercus acutissima* (281.197 t·ha−1) > *Corylus chinensis* (210.264 t·ha−1) > *Taiwania cryptomenoides* (186.601 t·ha−1) > *Toona sinensis* (18 5.386 t·ha−1) > *Choerospondias axillaris* (181.875 t·ha−1) > *Liriodendron chinensis* (161.548 t·ha−1) > Nyssa sinensis (158.32 t·ha−1).The biomass of tree layer, understory vegetation layer and litter layer of different stands were compared and analyzed under the condition of similar forest age.

The results showed that: the total biomass of *Cupressus lusitanica* forest was the largest, the biomass of understory vegetation layer and litter layer was also higher than that of other forests, and the growth trend was better than that of other tree species. It can be seen that there are some problems in the regeneration of evergreen

#### **Table 3.**

*Stand biomass of different tree species.*

broad-leaved trees, which need to be paid attention to. It is not our ultimate goal to build artificial pure forest. We need to use artificial afforestation technology to restore its ecological function, carry out natural regeneration, and finally form a complex and stable ecological community structure.

#### **4.4 Differences of undergrowth plant diversity in different stands**

Habitat heterogeneity and plant biological characteristics are the main factors affecting the diversity of understory plants (see [8]). The diversity index and evenness index of different plantations were significantly different (**Figure 6**), indicating that there were differences in the diversity level of understory plants in different plantations. The Berger Parker index of shrub layer in different stands was the largest in *Liriodendron chinensis*. The Simpson index of is the largest of *Corylus chinensis* forest, and that of *Cupressus lusitanica* is the smallest among 8 stands. For Shannon Wiener index, *Cupressus lusitanica* is the largest, *Liriodendron chinensis* is the smallest. The Berger Parker index of herbaceous layer in different stands was the largest in *Toona sinensis* forest and the smallest in *Taiwania cryptomenoides* forest; Simpson index of eight stands was the largest in *Taiwania cryptomenoides* forest and the smallest in *Quercus acutissima* forest. For Shannon Wiener index*, Nyssa sinensis* forest is the largest, *Taiwania cryptomenoides* forest is the smallest. The analysis of variance of undergrowth shrub and herb diversity in each stand shows that the diversity of undergrowth plants is significant, but there is no significant difference in Pielou index among the eight stands, indicating that the evenness of plants in the eight stands is basically similar. Secondly, the Shannon Wiener index of undergrowth shrub in *Cupressus lusitanica* was higher than that in other forest stands, indicating that the plant diversity under *Cupressus lusitanica* was richer than that in other stands, but the diversity index of shrub grassland without afforestation was higher than that of other stands (P < 0.05).

#### **4.5 The regeneration difference of young trees in different stands**

The horizontal spatial distribution of seedlings and young trees is often reflected by the spatial distribution pattern, which will change with the biological characteristics of plants and the comprehensive influence of environmental conditions (see [9]). There are many factors that affect the spatial distribution of seedlings and saplings, and the main factors are seed dispersal and different habitats (see [10]). It can be seen from **Table 4** that saplings of dominant species dominate the undergrowth vegetation of different stands. The regeneration of saplings under *Taiwania cryptomenoides* and *Toona sinensis* stands has gradually appeared other tree

**113**

species, and the natural regeneration of each stand has become stable. The growth of undergrowth plants is closely related to the growth of trees. The composition and structural characteristics of understory plants are closely related to the internal environmental conditions of plantations. On the one hand, because the growth and management of plantation affect the soil, water, light intensity, temperature and humidity and other micro environmental conditions, the growth and development of understory plants is limited, which directly affects the species, coverage,

*Relationship between tree growth and natural regeneration of young forest under the forest.*

*Nyssa sinensis Nyssa sinensis* 1.95 ± 0.82 2.07 ± 1.11 0.46 ± 0.28

*Toona sinensis Acer davidii* 4.25 ± 1.07 2.82 ± 0.52 2.88 ± 1.02

*Afforestation in Karst Area*

*Choerospondias axillaris*

*Cupressus lusitanica*

*Liriodendron chinensis*

*Taiwania cryptomenoides*

*Quercus acutissima*

**Table 4.**

*Note: Mean ± standard error.*

*DOI: http://dx.doi.org/10.5772/intechopen.95294*

*Choerospondias axillaris*

*Cinnamomum camphora*

*Cinnamomum camphora*

*Zanthoxylum bungeanum*

*Cinnamomum camphora*

*Liriodendron chinensis*

*Liriodendron chinensis*

*Cinnamomum camphora*

*Taiwania cryptomenoides*

*Taiwania cryptomenoides*

*Cinnamomum camphora*

**Sample plot Seedling species Tree height /m DBH/cm Average crown**

*Corylus chinensis Corylus chinensis* 1.73 ± 0.11 2.90 ± 0.28 36.5 ± 2.12

*Lindera communis* 2.87 ± 0.06 1.93 ± 0.55 2.74 ± 0.61

*Camellia japonica* 1.10 ± 0.83 18.22 ± 52.38 0.41 ± 0.65 *Cupressus lusitanica* 2.40 ± 0.28 3.65 ± 0.21 0.09 ± 0.11 *Eriobotrya japonica* 1.25 ± 0.35 0.65 ± 0.21 0.04 ± 0.00 *Rhus chinensis* 1.55 ± 0.66 2.18 ± 2.07 0.09 ± 0.08

*Vernicia fordii* 3.25 ± 0.21 9.95 ± 7.14 0.16 ± 0.00

*Acer davidii* 6.68 ± 1.72 3.05 ± 0.56 2.77 ± 2.67

*Vernicia fordii* 4.81 ± 0.57 3.15 ± 0.49 3.24 ± 1.19

*Phoebe bournei* 1.48 ± 0.82 1.61 ± 0.82 0.37 ± 0.27 *Camellia japonica* 1.15 ± 0.48 1.71 ± 0.66 0.56 ± 0.25

*Quercus acutissima* 7.37 ± 3.32 3.63 ± 1.12 3.41 ± 1.84

**diameter /m**

3.47 ± 1.21 3.15 ± 0.88 3.47 ± 2.81

4.32 ± 1.17 3.32 ± 0.75 4.35 ± 2.02

1.40 ± 0.14 2.11 ± 0.43 28.6 ± 20.67

1.17 ± 0.32 33.2 ± 55.95 0.14 ± 0.19

1.02 ± 0.6 1.43 ± 0.15 0.11 ± 0.08

1.27 ± 0.43 3.16 ± 1.81 0.03 ± 0.01

6.21 ± 2.82 3.22 ± 1.10 0.97 ± 0.36

5.22 ± 2.36 3.02 ± 0.90 0.92 ± 0.32

3.77 ± 1.10 3.19 ± 0.75 2.51 ± 0.89

2.51 ± 1.13 2.41 ± 1.43 0.75 ± 0.74

4.33 ± 1.73 3.35 ± 1.17 3.65 ± 3.61

**Figure 6.** *Diversity index of understory plants; a. The shrub diversity index; b. The herb diversity index.*

#### *Afforestation in Karst Area DOI: http://dx.doi.org/10.5772/intechopen.95294*

*Silviculture*

broad-leaved trees, which need to be paid attention to. It is not our ultimate goal to build artificial pure forest. We need to use artificial afforestation technology to restore its ecological function, carry out natural regeneration, and finally form a

Habitat heterogeneity and plant biological characteristics are the main factors affecting the diversity of understory plants (see [8]). The diversity index and evenness index of different plantations were significantly different (**Figure 6**), indicating that there were differences in the diversity level of understory plants in different plantations. The Berger Parker index of shrub layer in different stands was the largest in *Liriodendron chinensis*. The Simpson index of is the largest of *Corylus chinensis* forest, and that of *Cupressus lusitanica* is the smallest among 8 stands. For Shannon Wiener index, *Cupressus lusitanica* is the largest, *Liriodendron chinensis* is the smallest. The Berger Parker index of herbaceous layer in different stands was the largest in *Toona sinensis* forest and the smallest in *Taiwania cryptomenoides* forest; Simpson index of eight stands was the largest in *Taiwania cryptomenoides* forest and the smallest in *Quercus acutissima* forest. For Shannon Wiener index*, Nyssa sinensis* forest is the largest, *Taiwania cryptomenoides* forest is the smallest. The analysis of variance of undergrowth shrub and herb diversity in each stand shows that the diversity of undergrowth plants is significant, but there is no significant difference in Pielou index among the eight stands, indicating that the evenness of plants in the eight stands is basically similar. Secondly, the Shannon Wiener index of undergrowth shrub in *Cupressus lusitanica* was higher than that in other forest stands, indicating that the plant diversity under *Cupressus lusitanica* was richer than that in other stands, but the diversity index of shrub grassland without afforestation was

**4.4 Differences of undergrowth plant diversity in different stands**

complex and stable ecological community structure.

higher than that of other stands (P < 0.05).

**4.5 The regeneration difference of young trees in different stands**

*Diversity index of understory plants; a. The shrub diversity index; b. The herb diversity index.*

The horizontal spatial distribution of seedlings and young trees is often reflected

by the spatial distribution pattern, which will change with the biological characteristics of plants and the comprehensive influence of environmental conditions (see [9]). There are many factors that affect the spatial distribution of seedlings and saplings, and the main factors are seed dispersal and different habitats (see [10]). It can be seen from **Table 4** that saplings of dominant species dominate the undergrowth vegetation of different stands. The regeneration of saplings under *Taiwania cryptomenoides* and *Toona sinensis* stands has gradually appeared other tree

**112**

**Figure 6.**

#### **Table 4.**

*Relationship between tree growth and natural regeneration of young forest under the forest.*

species, and the natural regeneration of each stand has become stable. The growth of undergrowth plants is closely related to the growth of trees. The composition and structural characteristics of understory plants are closely related to the internal environmental conditions of plantations. On the one hand, because the growth and management of plantation affect the soil, water, light intensity, temperature and humidity and other micro environmental conditions, the growth and development of understory plants is limited, which directly affects the species, coverage,

biomass and diversity of understory plants. On the other hand, after nearly 40 years of development, the plantations in the study area have formed a relatively stable understory environment. The pattern of understory plants is mainly formed by natural competition, which fully reflects the advantages and disadvantages of internal environmental conditions of different artificial forests and the intermediate relationship of understory niche. Therefore, most of the plantations are shade tolerant plants with strong adaptability.

#### **4.6 The difference of soil physical and chemical properties among different stands**

Soil density and total porosity are not only the basic physical characteristics of forest soil, but also important indicators of soil and water conservation, which affect the growth and development of understory plants (see [11]). The soil physical properties of typical *Taiwania cryptomenoides* (coniferous forest), *Liriodendron chinensis* (broad-leaved forest) and *Taiwania cryptomenoides*-*Liriodendron chinensis* mixed forest (coniferous and broad-leaved forest) were determined (**Table 5**). The average soil density in 0 ~ 30 cm depth soil layer was as follows: *Taiwania cryptomenoides* > *Liriodendron chinensis* > mixed forest > shrub grassland (CK)Plot.

In the depth of 0 ~ 30 cm, the average soil porosity was mixed forest (*Taiwania cryptomenoides- Liriodendron chinensis*) > shrub grassland > *Taiwania cryptomenoides* pure forest >*Liriodendron chinensis* pure forest. The soil density in 0–15 cm and 15–30 cm soil layers of the shrub grassland was significantly lower than that of the pure *Taiwania cryptomenoides* forest (P ≤ 0.05), but there was no significant difference in soil density between the mixed forest of *Taiwania cryptomenoides* and pure forest. The soil density of each stand decreased with the increase of soil depth. The soil total porosity of different stands increased with the increase of soil depth, and with the increase of soil layer, the soil porosity of different stands showed significant difference. On the whole, the soil water holding capacity of the mixed forest of *Taiwania cryptomenoides* and *Liriodendron chinensis* was higher than that of pure *Taiwania cryptomenoides* and pure *Liriodendron chinensis*. Compared with pure forest, the maximum water holding capacity of *Taiwania cryptomenoides- Liriodendron chinensis* mixed forest was significantly increased, and the field water holding capacity of 0 ~ 15 cm soil layer in different stands did not reach significant difference. Except for *Taiwania cryptomenoides*, the maximum water holding capacity and field water holding capacity of other stands increased with the increase of soil depth. Among them, the maximum water holding capacity and field water holding capacity of 15 ~ 30 cm soil layer of *Taiwania cryptomenoides* -*Liriodendron chinensis* mixed forest and *Liriodendron chinensis* mixed forest were significantly higher than those of *Taiwania cryptomenoides* pure forest and Liriodendron chinensis pure forest (P ≤ 0.05), but there was no significant difference between 0 ~ 15 cm soil layer.

Soil is the matrix of plant growth, and its physical and chemical characteristics determine the distribution of plant community types. At the same time, the plant community reacts on the soil to improve its habitat conditions and make the community develop. Through the analysis of soil chemical properties under different stands, the results show that there are some differences in soil properties under different stands (**Table 6**). Among the eight stands, the contents of TP, SOM and TN in the soil of *Choerospondias axillaris* forest were the highest, the contents of NH4-N and NO3-N in *Quercus acutissima* forest were higher than those in other stands, the AP content of *Taiwania cryptomenoides* was the highest, and the SOM content of shrub grassland was significantly lower than that of plantation. There were significant differences in SOM, TN, NO3-N, NH4-N and AP contents in the soil of the eight stands.

**115**

**Thickness of soil layer (cm)**

0-15 cm

*Liriodendron chinensis*

*Taiwania cryptomenoides- Liriodendron*

*chinensis*

*Taiwania cryptomenoides*

shrub grassland

*Liriodendron chinensis*

*Taiwania cryptomenoides- Liriodendron*

*chinensis*

*Taiwania cryptomenoides*

shrub grassland

*Note: Mean ± standard error; the same letter means no significant difference; no same letter means significant difference.*

**Table 5.**

*Soil physical properties of different stands.*

0.17 ± 0.01b 0.29 ± 0.05a

1.13 ± 0.11b

1.39 ± 0.06a

0.24 ± 0.02b 0.40 ± 0.06a

0.20 ± 0.01b 0.33 ± 0.05a

0.38 ± 0.01c

0.43 ± 0.02b

15-30 cm

0.18 ± 0.01b 0.23 ± 0.03ab

0.16 ± 0.01b 0.33 ± 0.01a

1.22 ± 0.02ab

1.38 ± 0.04a

1.21 ± 0.13b

1.47 ± 0.01a

0.24 ± 0.01a 0.35 ± 0.07a 0.28 ± 0.01b 0.40 ± 0.02a

0.22 ± 0.01a 0.28 ± 0.04a 0.23 ± 0.01b 0.34 ± 0.02a

0.36 ± 0.01b

0.41 ± 0.04a

0.34 ± 0.01d

0.49 ± 0.01a

0.15 ± 0.05b 0.32 ± 0.03a

1.29 ± 0.03ab

1.39 ± 0.02ab

**Stand type**

**Moisture content (100%)**

**Bulk density (g/cm3**

**Maximum water holding**

**Minimum water holding**

**capacity**

**(100%)**

0.22 ± 0.03a 0.33 ± 0.03a

**capacity**

**(100%)**

0.24 ± 0.02a 0.36 ± 0.02a

**)**

*Afforestation in Karst Area*

*DOI: http://dx.doi.org/10.5772/intechopen.95294*

**porosity**

**(100%)**

0.33 ± 0.03b

0.46 ± 0.02a

**Total**