**Investigating the Relative Roles of the Degradation of Land and Global Warming in Amazonia**

Sergio H. Franchito, J. P. R. Fernandez and David Pareja

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/58991

## **1. Introduction**

[52] Merritts, D., A. de Wet, and K. Menking, *Environmental Geology: an Earth System Sci‐ ence Approach*. New York, NY: W.H. Freeman and Company, 1998, chapter 1. ISBN:

[53] Thompson, G. R., and J. Turk. *Environmental Geoscience.* 3rd ed. Ft Worth, TX: Har‐

court Brace and Company, 1997. ISBN:<PHONE_NUMBER>660.

9780716728344.

72 Global Warming - Causes, Impacts and Remedies

Large-scale removal of the tropical rain forest will have significant negative effects on regional water and energy balance, climate and global bio-geochemical cycles. Numerical experiments using General Circulation Models (GCMs) [1, 2, 3 and many others], using statistical-dynam‐ ical simple climate models (SDMs) [4, 5, 6] and field observations) [7] have shown that the large-scale deforestation in Amazonia may indeed influence regional climate. Reduction in evapotranspiration and precipitation and an increase in the surface temperature in the tropical region occur when the forest is replaced by pasture.

Projections of future climate given in IPCC AR5 (2013) (to be published) indicated that climate change due to anthropogenic human activities is affecting adversely the ecosystems. Many model studies showed that the global warming may affect the biomes distribution over South America, where significant portions of rain forest may be replaced by nonforested areas [8, 9, 10, 11]. These studies suggest that due to increase of greenhouse gases concentration the process of savannization of the tropical forest can be accelerated. This indicates that the future distribution of biomes in the tropical region depends on the combination of the effects of the degradation of land surface and climate changes due to global warming. Some studies have been made to investigate the relative roles of future changes in greenhouse gases compared with future changes in land cover. [12] and [13] compared the climate change simulated under a 2050 SRES B2 greenhouse gases scenario to the one under a 2050 SRES B2 land cover change scenario. It was noted that the relative impact of vegetation change compared to greenhouse gas concentration increase was of the order of 10%, and could reach 30% over limited areas of tropical region. The same methodology was applied for the SRES A2 and B1 scenario over the 2000 to 2100 period [14]. It was also found that although there was no significant effect at the

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global scale, a large effect at the regional scale may occur, such as a warming of 2°C by 2100 over the Amazon for the A2 land cover change scenario. Recently, studies using SDMs showed that the percentage of the warming due to deforestation relative to the warming when greenhouse gas concentration increase was included together was around 60% in the tropical region [5, 6]. These results suggest that the climate change due to land cover changes may be important relative to the change due to greenhouse gases at the regional level, where intense land cover change occurs. Globally, however, the impact of greenhouse gas concentrations seems to dominate over the impact of land cover change.

Although GCMs and SDMs can provide useful information regarding the response of the global circulation to large-scale forcing, due to their coarse resolution the mesoscale forcing, such as complex topography, vegetation cover, lakes, etc, are not well represented. In this sense Regional Climate Models (RCMs) may be more adequate. RCMs have therefore been developed to downscale larger scale simulations and to provide predictions for specific regions [15, 16, 17, 18].

In this paper the relative roles of the land surface degradation in Amazonia and global warming are investigated using a RCM. The purpose is to inquire how is the effect on the regional climate and aridity due to deforestation and when the increase of concentration of greenhouse gases is also taken into account together. The model to be used is The Abdus Salam International Centre for Theoretical Physics Regional Climate Model v. 4 (ICTP/RegCM4) [19]. In order to take into account the effect of global warming the model will be run using a methodology for generating surrogate climate-change scenarios with a regional climate model [20]. The distribution of aridity is determined using the radiative dryness index of Budyko (AIB) [21] and the UNEP aridity index (AIU) [22]. A brief description of the RCM, the method‐ ology employed and the experiments design are given in section 2; the model simulations are presented in section 3 and section 4 contains the summary and conclusions.

## **2. Regional climate change model**

The model ICTP RegCM4 [19] is the version 4 of the regional climate model (RegCM) originally developed at the National Center for Atmospheric Research (NCAR) [15, 16]. The dynamic component of the model is based on the NCAR-Pennsylvania State University meso-escale model (MM5) [23]. For application in climate studies, a number of physical parameterizations were incorporated in the model. More details about the model and physical configurations for South America is given in [19]. In the present study modified parameters of BATS land-surface model for vegetation type 6 (tropical rain forest) are used to reduce the rainfall dry bias over tropical South America, as reported in earlier RegCM versions [24].

The model domain covers the entire South America (Fig. 1), following the CORDEX, an international effort to downscale climate projections over the world using RCMs [25]. The model domain is centered at 22S, 59W, and comprises 202EWx192NS grid points, with a horizontal grid spacing of 50 km over a rotated Mercator projection. Ten-yr simulations were performed (after discarding a 1 yr spin-up period), extending from 1 January of 1990 to 31 December of 1999.

**Figure 1.** Model domain. Also shown is the topography of South America. Units, m.

#### **2.1. Control experiment model**

global scale, a large effect at the regional scale may occur, such as a warming of 2°C by 2100 over the Amazon for the A2 land cover change scenario. Recently, studies using SDMs showed that the percentage of the warming due to deforestation relative to the warming when greenhouse gas concentration increase was included together was around 60% in the tropical region [5, 6]. These results suggest that the climate change due to land cover changes may be important relative to the change due to greenhouse gases at the regional level, where intense land cover change occurs. Globally, however, the impact of greenhouse gas concentrations

Although GCMs and SDMs can provide useful information regarding the response of the global circulation to large-scale forcing, due to their coarse resolution the mesoscale forcing, such as complex topography, vegetation cover, lakes, etc, are not well represented. In this sense Regional Climate Models (RCMs) may be more adequate. RCMs have therefore been developed to downscale larger scale simulations and to provide predictions for specific

In this paper the relative roles of the land surface degradation in Amazonia and global warming are investigated using a RCM. The purpose is to inquire how is the effect on the regional climate and aridity due to deforestation and when the increase of concentration of greenhouse gases is also taken into account together. The model to be used is The Abdus Salam International Centre for Theoretical Physics Regional Climate Model v. 4 (ICTP/RegCM4) [19]. In order to take into account the effect of global warming the model will be run using a methodology for generating surrogate climate-change scenarios with a regional climate model [20]. The distribution of aridity is determined using the radiative dryness index of Budyko (AIB) [21] and the UNEP aridity index (AIU) [22]. A brief description of the RCM, the method‐ ology employed and the experiments design are given in section 2; the model simulations are

The model ICTP RegCM4 [19] is the version 4 of the regional climate model (RegCM) originally developed at the National Center for Atmospheric Research (NCAR) [15, 16]. The dynamic component of the model is based on the NCAR-Pennsylvania State University meso-escale model (MM5) [23]. For application in climate studies, a number of physical parameterizations were incorporated in the model. More details about the model and physical configurations for South America is given in [19]. In the present study modified parameters of BATS land-surface model for vegetation type 6 (tropical rain forest) are used to reduce the rainfall dry bias over

The model domain covers the entire South America (Fig. 1), following the CORDEX, an international effort to downscale climate projections over the world using RCMs [25]. The model domain is centered at 22S, 59W, and comprises 202EWx192NS grid points, with a horizontal grid spacing of 50 km over a rotated Mercator projection. Ten-yr simulations were

presented in section 3 and section 4 contains the summary and conclusions.

tropical South America, as reported in earlier RegCM versions [24].

seems to dominate over the impact of land cover change.

regions [15, 16, 17, 18].

74 Global Warming - Causes, Impacts and Remedies

**2. Regional climate change model**

In the control experiment the model is forced using the ERA-Interim reanalysis data [26]. The greenhouse gas concentration corresponds to the present-day conditions. The distribution of aridity is obtained using the Budyko radiative dryness [21] and the UNEP aridity index [22]. The Budyko index has been used in many studies of land-surface effects, climate change and biogeography [27, 28, 29 and many others]. The UNEP index was adopted by UNEP to produce a dryness map [22].

The Budyko index, AIB, is defined as AIB=R/ (LP), where R is the mean annual net radiation; P, the mean annual precipitation and L is the latent heat of evaporation. Thresholds for different climate regimes are defined as:

0 < AIB ≤ 1=humid (surplus moisture regime; steppe to forest vegetation)

1 < AIB ≤ 2=semi-humid (moderately insufficient moisture; savanna)

2 < AIB ≤ 3=semi-arid (insufficient moisture; semi-desert)

AIB > 3=arid (very insufficient moisture; desert)

The UNEP index, AIU, is defined by AIU=P / PET, where P is the annual precipitation and PET is the annual potential evapotranspiration. P is provided by the model while PET is calculated using the formula of [30]. Thresholds for different climate regimes are:

AIU ≥ 1= humid regime 0.65 ≤ AIU < 1=dry land 0.50 ≤ AIU < 0.65=dry sub-humid regime 0.20 ≤ AIU < 0.50=semi-arid regime 0.05 ≤ AIU < 0.20=arid regime AIU < 0.05=hyper-arid regime

Results of [31] showed that in general the climate variables, such as temperature, precipitation and evaporation, and the distribution of aridity over South America using both the Budyko and UNEP indices, for the present-day climate are well simulated by the model.

## *2.1.1. Climate change experiment on deforestation*

The biomes distribution over South America according to the vegetation types given by BATS1e is given in Fig. 2a. In the deforestation experiment the entire tropical forest zone is converted into short grass (Fig. 2b). So, all the characteristic parameters of the tropical forest are replaced by those from short grass conditions according to BATS1e. Though extreme, it is important to evaluate a scenario of a hypothetical complete Amazon deforestation. The extreme scenario of total deforestation is useful to provide insight into underlying physical principles of the functioning of the climate system. Although it is unlikely that deforestation will affect the entire Amazonian forest, the extreme scenario of total deforestation is useful to identify the sensitivity of the climate system to changes in the land surface properties. In this experiment the effects of deforestation in Amazonia on the regional climate and aridity is studied.

#### *2.1.2. Surrogate climate change experiment including deforestation*

In this experiment the effects of global warming is taken into account together with the deforestation in Amazonia. For this purpose the methodology for generating a surrogate climate change scenario with a RCM proposed by [20] is used. It consists of a uniform 3 K temperature increase and an attendant increase of specific humidity. In this scenario, the ERA-Interim dataset of temperature is increased by 3K throughout the atmospheric column and the sea surface temperature OISST dataset [32] are warmed by 3 K. The atmospheric greenhouse gases concentration of the sensitivity experiment is set to two times its present-day values. A global mean equilibrium surface temperature increase of 3 K corresponds approximately to a CO2 equivalent concentration of 710 ppm [33].

The methodology for generating a surrogate climate change scenario is dynamically consistent and easy to incorporate in a RCM. The procedure can be applied to the study of the regional response to a pseudo-global warming with an accompanying increase of the Investigating the Relative Roles of the Degradation of Land and Global Warming in Amazonia http://dx.doi.org/10.5772/58991 77

The UNEP index, AIU, is defined by AIU=P / PET, where P is the annual precipitation and PET is the annual potential evapotranspiration. P is provided by the model while PET is calculated

Results of [31] showed that in general the climate variables, such as temperature, precipitation and evaporation, and the distribution of aridity over South America using both the Budyko

The biomes distribution over South America according to the vegetation types given by BATS1e is given in Fig. 2a. In the deforestation experiment the entire tropical forest zone is converted into short grass (Fig. 2b). So, all the characteristic parameters of the tropical forest are replaced by those from short grass conditions according to BATS1e. Though extreme, it is important to evaluate a scenario of a hypothetical complete Amazon deforestation. The extreme scenario of total deforestation is useful to provide insight into underlying physical principles of the functioning of the climate system. Although it is unlikely that deforestation will affect the entire Amazonian forest, the extreme scenario of total deforestation is useful to identify the sensitivity of the climate system to changes in the land surface properties. In this experiment the effects of deforestation in Amazonia on the regional climate and aridity is

In this experiment the effects of global warming is taken into account together with the deforestation in Amazonia. For this purpose the methodology for generating a surrogate climate change scenario with a RCM proposed by [20] is used. It consists of a uniform 3 K temperature increase and an attendant increase of specific humidity. In this scenario, the ERA-Interim dataset of temperature is increased by 3K throughout the atmospheric column and the sea surface temperature OISST dataset [32] are warmed by 3 K. The atmospheric greenhouse gases concentration of the sensitivity experiment is set to two times its present-day values. A global mean equilibrium surface temperature increase of 3 K corresponds approximately to a

The methodology for generating a surrogate climate change scenario is dynamically consistent and easy to incorporate in a RCM. The procedure can be applied to the study of the regional response to a pseudo-global warming with an accompanying increase of the

and UNEP indices, for the present-day climate are well simulated by the model.

using the formula of [30]. Thresholds for different climate regimes are:

AIU ≥ 1= humid regime 0.65 ≤ AIU < 1=dry land

0.50 ≤ AIU < 0.65=dry sub-humid regime

*2.1.1. Climate change experiment on deforestation*

*2.1.2. Surrogate climate change experiment including deforestation*

CO2 equivalent concentration of 710 ppm [33].

0.20 ≤ AIU < 0.50=semi-arid regime

76 Global Warming - Causes, Impacts and Remedies

0.05 ≤ AIU < 0.20=arid regime AIU < 0.05=hyper-arid regime

studied.

**Figure 2.** a) Vegetation types over South America according BATS1e; b) Region of Amazonia where the evergreen broadleaf trees are replaced by short grass in the deforestation experiment. Also shown are the areas denoting: north Amazonia (NAM), central Amazonia (CAM) and south Amazonia (SAM).

atmospheric water vapor content. However, the surrogate climate change scenario is only a sensitivity experiment and not a real climate change experiment. In a surrogate climate change scenario the response to a combination of a horizontally uniform thermodynamic modification of the initial and external fields plus an unmodified external flow evolution is studied. Otherwise a real climate change would be accompanied by changes in the planetary and synoptic-scale circulation. In spite of this drawback, the methodology allows us to examine certain processes in isolation [20, 34, 35].

## **3. Results and discussion**

In order to discuss with more regional details the effects of deforestation and the pseudowarming on Amazonia, three regions are considered: north (0-5N, 70W-52W), central (8S-0, 74W-50W) and south (13S-8S, 70W-52W) Amazonia (Fig. 2b). This is because the changes are different in these regions, as will be seen in the next sections.

## **3.1. Effect of deforestation**

Figure 3 shows the distribution of aridity for the control and deforestation experiments and the change (deforestation minus control) using the Budyko and UNEP indices. As can be seen in Figs. 3a and 3b, areas of humid regime (forest) are replaced by sub-humid regime (savanna) in the part of central Amazonia southward from 5S and in the south Amazonia in the defor‐ estation experiment compared with the control. The Budyko index increases (increase of aridity) in these regions. In the north and most of the central Amazonia the aridity is decreased (Fig. 3c). As shown in Table 1, taking into account the values of AIB averaged over the entire three regions of Amazonia, the aridity increases 22% relative to the control in the south region. In the north and central areas there is a decrease of the aridity of 4% and 1.1%, respectively. For the case of the UNEP index, it can be noted from Figs. 3d and 3e that dry land substitutes regions of humid regime in Amazonia. The UNEP index decreases (the aridity increases) in the central and south Amazonia while in the north Amazonia it increases, as seen in Fig. 3f. These changes in the UNEP indicate an increase in the aridity of 22% and 4.8% relative to the control in the south and central Amazonia, respectively, while in the north Amazonia there is a decrease of 3% (Table 1).

Although the changes in the distribution of aridity due to deforestation using Budyko and UNEP indices show a very good agreement in the south and north Amazonia, the results diverge in the central region: the use of Budyko index indicates a decrease of aridity while the UNEP index suggests an increase.

Investigating the Relative Roles of the Degradation of Land and Global Warming in Amazonia http://dx.doi.org/10.5772/58991 79

**3. Results and discussion**

78 Global Warming - Causes, Impacts and Remedies

**3.1. Effect of deforestation**

a decrease of 3% (Table 1).

**Index Budyko**

UNEP index suggests an increase.

North Amazonia

Central Amazonia

South Amazonia

**Region IB**

**CTRL**

**IB defor**

In order to discuss with more regional details the effects of deforestation and the pseudowarming on Amazonia, three regions are considered: north (0-5N, 70W-52W), central (8S-0, 74W-50W) and south (13S-8S, 70W-52W) Amazonia (Fig. 2b). This is because the changes are

Figure 3 shows the distribution of aridity for the control and deforestation experiments and the change (deforestation minus control) using the Budyko and UNEP indices. As can be seen in Figs. 3a and 3b, areas of humid regime (forest) are replaced by sub-humid regime (savanna) in the part of central Amazonia southward from 5S and in the south Amazonia in the defor‐ estation experiment compared with the control. The Budyko index increases (increase of aridity) in these regions. In the north and most of the central Amazonia the aridity is decreased (Fig. 3c). As shown in Table 1, taking into account the values of AIB averaged over the entire three regions of Amazonia, the aridity increases 22% relative to the control in the south region. In the north and central areas there is a decrease of the aridity of 4% and 1.1%, respectively. For the case of the UNEP index, it can be noted from Figs. 3d and 3e that dry land substitutes regions of humid regime in Amazonia. The UNEP index decreases (the aridity increases) in the central and south Amazonia while in the north Amazonia it increases, as seen in Fig. 3f. These changes in the UNEP indicate an increase in the aridity of 22% and 4.8% relative to the control in the south and central Amazonia, respectively, while in the north Amazonia there is

Although the changes in the distribution of aridity due to deforestation using Budyko and UNEP indices show a very good agreement in the south and north Amazonia, the results diverge in the central region: the use of Budyko index indicates a decrease of aridity while the

> **AIB defor minus CTRL**

**Change in IB (defor relative to CTRL)**

0.74 0.71 -0.03 -4% 0.89 +0.15 +20%

0.92 0.93 -0.01 -1.1% 0.99 +0.07 +7.6%

1.00 1.22 +0.22 +22% 0.90 -0.10 -10%

**IB (defor plus pseudo)**

**IB (defor plus pseudo) minus CTRL**

**Change in IB (defor plus pseudo) relative to CTRL**

different in these regions, as will be seen in the next sections.

**Table 1.** Values of AIB and AIU and the relative changes in the experiments of deforestation and deforestation plus pseudo-warming.

**Figure 3.** Distribution of aridity using Budyko index: a) control experiment, b) deforestation experiment and c) changes (deforestation minus control); and using UNEP index: d) control experiment, e) deforestation experiment and f) changes (deforestation minus control).

The changes (perturbed minus control) in the net surface radiation, precipitation, evapotrans‐ piration and surface temperature due to deforestation are shown in Table 2. There is a decrease of the mean net surface radiation (-7.8 W m-2) due to the increase of the land surface albedo; the mean evapotranspiration and precipitation decrease (-0.25 mm day-1 and-0.54 mm day-1, respectively). The sign of the change in the surface temperature is different in the three regions of Amazonia. The mean surface temperature decreases in the north and central areas (-0.3C and-0.2C, respectively) and increases in the south region (+0.1C). As shown in Fig. 4a, the surface temperature increases by+0.6C in the south Amazonia and decreases by-0.9C in the north Amazonia. Since the higher decrease in evapotranspiration occurs in the south Amazo‐ nia it seems that the effect of the reduction in evapotranspiration in this region overcomes that of the increase of albedo while in the other two regions this does not occur. This leads to an increase of the temperature in the south Amazonia and a decrease in the north and central Amazonia. The changes in surface temperature in the three areas of Amazonia are in good agreement with the changes in the aridity given by Budyko index which indicates a high increase of the aridity in the south region (with a consequent increase in the surface tempera‐ ture) while in the other two areas a decrease of aridity (and a consequent decrease in the surface temperature) is noted (Fig. 3c). The UNEP index also indicates a high increase of aridity in the south Amazonia and a decrease in the north Amazonia. However, differently from the Budyko index an increase of the aridity in the central region is noted.

**Figure 4.** Changes in the surface temperature: a) deforestation minus control and b) deforestation plus pseudowarming minus control. Units, ºC.

Investigating the Relative Roles of the Degradation of Land and Global Warming in Amazonia http://dx.doi.org/10.5772/58991 81

**Table 2.** Changes (perturbed minus control) in the surface net radiation (W m−2), precipitation (mm day-1), evapotranspiration (mm day-1) and surface temperature (°C) for the experiment of deforestation and deforestation plus pseudo-warming.

#### **3.2. Effect of deforestation including pseudo-warming**

The changes (perturbed minus control) in the net surface radiation, precipitation, evapotrans‐ piration and surface temperature due to deforestation are shown in Table 2. There is a decrease of the mean net surface radiation (-7.8 W m-2) due to the increase of the land surface albedo; the mean evapotranspiration and precipitation decrease (-0.25 mm day-1 and-0.54 mm day-1, respectively). The sign of the change in the surface temperature is different in the three regions of Amazonia. The mean surface temperature decreases in the north and central areas (-0.3C and-0.2C, respectively) and increases in the south region (+0.1C). As shown in Fig. 4a, the surface temperature increases by+0.6C in the south Amazonia and decreases by-0.9C in the north Amazonia. Since the higher decrease in evapotranspiration occurs in the south Amazo‐ nia it seems that the effect of the reduction in evapotranspiration in this region overcomes that of the increase of albedo while in the other two regions this does not occur. This leads to an increase of the temperature in the south Amazonia and a decrease in the north and central Amazonia. The changes in surface temperature in the three areas of Amazonia are in good agreement with the changes in the aridity given by Budyko index which indicates a high increase of the aridity in the south region (with a consequent increase in the surface tempera‐ ture) while in the other two areas a decrease of aridity (and a consequent decrease in the surface temperature) is noted (Fig. 3c). The UNEP index also indicates a high increase of aridity in the south Amazonia and a decrease in the north Amazonia. However, differently from the Budyko

**Figure 4.** Changes in the surface temperature: a) deforestation minus control and b) deforestation plus pseudo-

index an increase of the aridity in the central region is noted.

80 Global Warming - Causes, Impacts and Remedies

warming minus control. Units, ºC.

Figure 5 shows the distribution of aridity for the experiment considering deforestation together with pseudo-warming and the change (deforestation plus pseudo-warming minus control) using the Budyko and UNEP indices. From Figs. 5a and 3b it can be seen that when the pseudowarming scenario is taken into account the areas humid regime (forest) are replaced by semihumid regime (savanna) northwards compared with the case of deforestation only. This leads to an increase of the aridity in this region. In the south Amazonia there is a decrease of the aridity, as shown in Fig. 5b. As can be seen in Table 1 the aridity increases 20% and 7.6% relative to the control in the north and central Amazonia, respectively, while in the case of only deforestation there is a decrease of aridity (4% and 1.1%, respectively). In the south Amazonia the aridity is decreased by 10% compared to the control while it increases in the case with only deforestation (22%).

Figures 5c and 5d show that in the case of the UNEP index there is a general increase of the aridity in the three regions in the deforestation plus pseudo-warming experiment compared with the control experiment. The increase of the aridity is higher in the north Amazonia (37.6%) followed by the central (28%) and south (10.3%) Amazonia. From Figs. 5d, 3f and Table 1 it can be seen that the aridity increases largely in the north Amazonia when the pseudo-warming is taken into account while it decreases in the case with only deforestation. Although in the two experiments there is an enhancement of the aridity in the central Amazonia the increase is much higher when the pseudo-warming is included. On the other hand the increase of the aridity in the south Amazonia is higher in the case of only deforestation.

It can be seen from above that the changes in the distribution of aridity due to deforestation together with pseudo-warming using Budyko and UNEP indices are in agreement. These

**Figure 5.** Distribution of aridity using Budyko index: a) deforestation plus pseudo-warming experiment and b) changes (deforestation plus pseudo-warming minus control); and using UNEP index: c) deforestation plus pseudowarming experiment and d) changes (deforestation plus pseudo-warming minus control).

changes are higher compared to the case with only deforestation. On the other hand, the results diverge in the south Amazonia: the use of Budyko index indicates a decrease of aridity while the UNEP index suggests an increase.

Table 2 shows that the main changes in the Amazonia (an average over the three regions) are a warming of 3.5C and decreases in evapotranspiration (0.37 mm day-1) and precipitation (0.44 mm day-1) relative to the control. It can be seen from Table 2 that the inclusion of the pseudowarming largely increases the changes in the surface temperature due to deforestation. However, deforestation may have a significant effect locally. As seen in Figs. 4a and 4b, the changes in the surface temperature due to deforestation may reach+0.6C in the south Amazo‐ nia, which correspond to 15% of the higher changes when the pseudo-warming is included (+4C). The increase in the surface temperature when the pseudo-warming is taken into account together is due mainly to the lower reduction in the net surface radiation in addition to the higher reduction in evapotranspiration. The changes in the surface temperature are large in the three regions of Amazonia. These changes are in good agreement with the changes in the aridity given by the UNEP index which indicate an increase of the aridity (and consequent increase of the surface temperature) in the three regions compared to the control (Table 1). The increase of the aridity is higher in the north Amazonia followed by the central and south Amazonia in agreement with the change in the surface temperature in these regions. The Budyko index also shows a higher increase of the aridity in the north Amazonia followed by the central Amazonia. However, in the south Amazonia an increase of the aridity is noted.

The present results agree with some studies with GCMs [8, 9, 10, 11, 36, 37] and with simple mechanistic models [5, 6, 38] which suggest that tropical South America is a region where significant portions of rainforest may be replaced by savanna (grassland) in future due to the global warming. The results also showed that the warming due to deforestation may have important effect locally; on the other hand when the effect of the global warming is included, the change of tropical forest areas of Amazonia by savanna may be enhanced compared with the present climate. This reinforces the hypothesis that due to global warming the process of savannization of tropical forest of Amazonia can be accelerated.

## **4. Conclusions**

changes are higher compared to the case with only deforestation. On the other hand, the results diverge in the south Amazonia: the use of Budyko index indicates a decrease of aridity while

**Figure 5.** Distribution of aridity using Budyko index: a) deforestation plus pseudo-warming experiment and b) changes (deforestation plus pseudo-warming minus control); and using UNEP index: c) deforestation plus pseudo-

warming experiment and d) changes (deforestation plus pseudo-warming minus control).

Table 2 shows that the main changes in the Amazonia (an average over the three regions) are a warming of 3.5C and decreases in evapotranspiration (0.37 mm day-1) and precipitation (0.44 mm day-1) relative to the control. It can be seen from Table 2 that the inclusion of the pseudowarming largely increases the changes in the surface temperature due to deforestation. However, deforestation may have a significant effect locally. As seen in Figs. 4a and 4b, the changes in the surface temperature due to deforestation may reach+0.6C in the south Amazo‐ nia, which correspond to 15% of the higher changes when the pseudo-warming is included (+4C). The increase in the surface temperature when the pseudo-warming is taken into account together is due mainly to the lower reduction in the net surface radiation in addition to the higher reduction in evapotranspiration. The changes in the surface temperature are large in the three regions of Amazonia. These changes are in good agreement with the changes in the

the UNEP index suggests an increase.

82 Global Warming - Causes, Impacts and Remedies

In this paper the relative roles of the land surface degradation in Amazonia and global warming on the regional climate and aridity were investigated using the RegCM4 model. Two experiments were performed: 1) deforestation and 2) deforestation together with global warming. The distribution of the aridity over South America, particularly over the tropical region, was obtained using the dryness index of Budyko and the UNEP aridity index. The results showed that the deforestation may have large influence locally (15% of the warming when the pseudo-warming was included together). The higher increase of the surface tem‐ perature occurred in the south Amazonia (+0.6C) whereas in the north and central Amazonia a decrease of temperature was noted (higher decrease of-0.9C). The changes in the distribution of aridity due to deforestation using Budyko and UNEP indices showed a very good agree‐ ment. It was suggested that there was an increase of 22% in the drying in the south Amazonia and a decrease of 3%-4% in the north Amazonia.

When the pseudo-warming was taken into account the changes in surface temperature were largely enhanced in relation to the deforestation case and the warming occurred in the entire Amazonia (higher increase of+4C). The changes in the distribution of aridity using Budyko and UNEP indices were similar. The aridity increased in most of Amazonia compared to the deforestation case. The higher increase occurred in the north Amazonia (20% for the Budyko index and 37.6% for the UNEP index).

Thus, the present study indicated that the global warming may affect the distribution of aridity over the tropical region of Amazonia, where significant portions of rain forest may be replaced by nonforested areas and this corroborates the hypothesis that the process of savannization of the tropical forest of Amazonia can be accelerated in future.

## **Acknowledgements**

Thanks are due to Dr. Erika Coppola and the ICTP group for providing the RegCM4 code. Thanks are also due to Dr. V. Brahmananda Rao for going through the manuscript.

## **Author details**

Sergio H. Franchito\* , J. P. R. Fernandez and David Pareja

\*Address all correspondence to<EMAIL_ADDRESS>
Centro de Previsão de Tempo e Estudos Climáticos, CPTEC, Instituto Nacional de Pesquisas Espaciais, INPE, SP, Brazil

## **References**

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**Acknowledgements**

84 Global Warming - Causes, Impacts and Remedies

**Author details**

Sergio H. Franchito\*

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Espaciais, INPE, SP, Brazil

Thanks are due to Dr. Erika Coppola and the ICTP group for providing the RegCM4 code.

Centro de Previsão de Tempo e Estudos Climáticos, CPTEC, Instituto Nacional de Pesquisas

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## **Influence of Climate Change on Weed Vegetation**

## Vytautas Pilipavičius

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/58782

## **1. Introduction**

Climate is the biggest abiotical factor influencing the whole vegetation. At climate changing conditions adaptation ability of vegetation changes to grow in certain territory. Competitive abilities of plants are changing showing through new plant and weed biological qualities.

Global warming and climate change refer to an increase in average global temperatures. Global warming is primarily caused by increases in "greenhouse" gases (GHG). A warming planet thus leads to climate changes which can adversely affect weather in different ways. Some of the prominent indicators for a global warming are: temperature over land, snow cover and glaciers on hills, ocean heat content, sea ice, sea level, sea surface temperature, temperature over ocean, humidity, tropospheric temperature. Global warming in today's scenario is threat to the survival of mankind [55]. Climate change inspired by global warming could lead to change of natural climatic zones, i.e. Tundra would disappear, Taiga would decrease essen‐ tially, Mediterranean climate zone would decrease and move to north, deserts and Arid world zones would move 400-800 km north to populous subtropical areas, main agricultural zones would move to north areas with low-fertile and worse soils [56, 57]. Global warming is closely associated as well with a broad spectrum of other climate changes, such as increases in the frequency of intense rainfall, decreases in snow cover and sea ice, more frequent and intense heat waves, rising sea levels, and widespread ocean acidification [55].

"*The damage that climate change is causing and that will get worse if we fail to act goes beyond the hundreds of thousands of lives, homes and businesses lost, ecosystems destroyed, species driven to extinction, infrastructure smashed and people inconvenienced.*" – David Suzuki1

<sup>1</sup> Suzuki D. BrainyQuote.com, XploreInc, 2014. Available from http://www.brainyquote.com/quotes/quotes/d/ davidsuzuk471841.html

© 2015 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Seasons of the years are constantly attended by the increase of marginal air conditions. Many researchers agree that anthropogenic activity is reason for climate change and it induced changes of the nature [1]. Agriculture and forestry take important place in Lithuanian national economy, therefore it is actual to adjust those sectors to climate change for mitigating conse‐ quences [2]. The constant competition between agricultural plants and weeds is seen in agroecosystems when the yields minimize. Alongside with other factors its progress can be explained by the plant resistance to abiotical factors. Different sensitivity of various varieties and their adaptability to the human activity may govern their relationship in agro-ecosystems. Thus, the adaptability of different abiotical factors for both agricultural plants and weeds should be estimated [3]. Weed spreading regularities are significantly dependent on weed ability to adapt, that is to adapt to changeable factors of environment.

Analogous weed chemical composition to agricultural plants induces competition in agro‐ phytocenoses for growth factors. Weeds occupied place where agricultural plants could grow [4]. Adaptation possibility of separate plant species is different and can vary their competition as environment conditions change. It can cause serious agricultural problems. Undesirable change of plant species follows when environment conditions vary in ecosystems. Usually weeds signify by higher plasticity [5].

Biological invasions and climate warming are two major threats to the world's biodiversity. To date, their impacts have largely been considered independently, despite indications that climate warming may increase the success of many invasive alien species [50].

The climate system is a complex, interactive system consisting of the atmosphere, land surface, snow and ice, oceans and other bodies of water, and living things. Climate is usually described in terms of the mean and variability of temperature, precipitation and wind over a period of time, ranging from months to millions of years (the classical period is 30 years) [6]. Observa‐ tions of the climate system are based on direct measurements and remote sensing from satellites and other platforms. Global-scale observations from the instrumental era began in the mid-19th century for temperature and other variables. Paleoclimate reconstructions extended some records back hundreds to millions of years [7].

Changes in the atmospheric abundance of greenhouse gases and aerosols, in solar radia‐ tion and in land surface properties alter the energy balance of the climate system [8]. Global GHG emissions due to human activities have grown since pre-industrial times, with an increase of 70% between 1970 and 2004 (Figure 1). Annual CO2 emissions from fossil fuel combustion and cement production were 8.3 GtC12 yr-1 averaged over 2002-2011 and were 9.5 GtC yr-1 in 2011, 54% more than the level in 1990. Annual net CO2 emissions from anthropogenic land use change were 0.9 GtC yr-1 on average during 2002 to 2011 [7]. The global atmospheric concentration of carbon dioxide has increased from a pre-industrial value of about 280 ppm to 379 ppm in 2005 (Figure 2). The annual carbon dioxide concentration growth rate was larger during the last 10 years (1995-2005 average: 1.9 ppm per year), than it has been during 1960-2005 (average: 1.4 ppm per year) although there is year-to-year variability in growth rates [8]. In 2011 the concentrations of CO2 were 391 ppm, and exceeded the pre-industrial levels by about 40% [7].

Seasons of the years are constantly attended by the increase of marginal air conditions. Many researchers agree that anthropogenic activity is reason for climate change and it induced changes of the nature [1]. Agriculture and forestry take important place in Lithuanian national economy, therefore it is actual to adjust those sectors to climate change for mitigating conse‐ quences [2]. The constant competition between agricultural plants and weeds is seen in agroecosystems when the yields minimize. Alongside with other factors its progress can be explained by the plant resistance to abiotical factors. Different sensitivity of various varieties and their adaptability to the human activity may govern their relationship in agro-ecosystems. Thus, the adaptability of different abiotical factors for both agricultural plants and weeds should be estimated [3]. Weed spreading regularities are significantly dependent on weed

Analogous weed chemical composition to agricultural plants induces competition in agro‐ phytocenoses for growth factors. Weeds occupied place where agricultural plants could grow [4]. Adaptation possibility of separate plant species is different and can vary their competition as environment conditions change. It can cause serious agricultural problems. Undesirable change of plant species follows when environment conditions vary in ecosystems. Usually

Biological invasions and climate warming are two major threats to the world's biodiversity. To date, their impacts have largely been considered independently, despite indications that

The climate system is a complex, interactive system consisting of the atmosphere, land surface, snow and ice, oceans and other bodies of water, and living things. Climate is usually described in terms of the mean and variability of temperature, precipitation and wind over a period of time, ranging from months to millions of years (the classical period is 30 years) [6]. Observa‐ tions of the climate system are based on direct measurements and remote sensing from satellites and other platforms. Global-scale observations from the instrumental era began in the mid-19th century for temperature and other variables. Paleoclimate reconstructions

Changes in the atmospheric abundance of greenhouse gases and aerosols, in solar radia‐ tion and in land surface properties alter the energy balance of the climate system [8]. Global GHG emissions due to human activities have grown since pre-industrial times, with an increase of 70% between 1970 and 2004 (Figure 1). Annual CO2 emissions from fossil fuel combustion and cement production were 8.3 GtC12 yr-1 averaged over 2002-2011 and were 9.5 GtC yr-1 in 2011, 54% more than the level in 1990. Annual net CO2 emissions from anthropogenic land use change were 0.9 GtC yr-1 on average during 2002 to 2011 [7]. The global atmospheric concentration of carbon dioxide has increased from a pre-industrial value of about 280 ppm to 379 ppm in 2005 (Figure 2). The annual carbon dioxide concentration growth rate was larger during the last 10 years (1995-2005 average: 1.9 ppm per year), than it has been during 1960-2005 (average: 1.4 ppm per year) although there is year-to-year variability in growth rates [8]. In 2011 the concentrations of CO2 were 391 ppm,

climate warming may increase the success of many invasive alien species [50].

extended some records back hundreds to millions of years [7].

and exceeded the pre-industrial levels by about 40% [7].

ability to adapt, that is to adapt to changeable factors of environment.

weeds signify by higher plasticity [5].

90 Global Warming - Causes, Impacts and Remedies

**Figure 1.** a) Global annual emissions of anthropogenic GHGs from 1970 to 2004. (b) Share of different anthropogenic GHGs in total emissions in 2004 in terms of carbon dioxide equivalents (CO2-eq). (c) Share of different sectors in total anthropogenic GHG emissions in 2004 in terms of CO2-eq (Forestry includes deforestation). Source: Climate Change 2007: Synthesis Report [9]

**Figure 2.** Atmospheric concentrations of carbon dioxide over the last 10,000 years (large panels) and since 1750 (inset panels). Measurements are shown from ice cores (symbols with different colours for different studies) and atmospher‐ ic samples (red lines). The corresponding radiative forcings are shown on the right hand axes of the large panels. Source: IPCC, 2007: Summary for Policymakers [8]

The great part of GHG emissions locally, i.e. in Lithuania evaluating separate sectors of economy, is generated from energy supply objects and transport (Figure 3). It is in accordance with other developed industrial countries. As well it is forecasted increase of CO2 emissions till 2030 in all sectors of economy in Lithuania (Figure 3). Lithuania together with other modern world countries work solving global climate change problems. In Lithuania annual GHG emission terms of carbon dioxide equivalents (CO2-eq) covered about 4-5 tons per inhabitant and is one of the lowest in European countries where annual GHG of CO2-eq is about 3-15 tons per inhabitant [10]. shown on the right hand axes of the large panels. Source: IPCC, 2007: Summary for Policymakers [8] The great part of GHG emissions locally, i.e. in Lithuania evaluating separate sectors of economy, is generated from energy supply objects and transport (Figure 3). It is in accordance with other developed industrial countries. As well it is forecasted increase in CO2 emissions till 2030 in all sectors of economy in Lithuania (Figure 3). Lithuania together with other modern world countries work solving global climate change problems. In Lithuania annual GHG emission terms of carbon dioxide equivalents (CO2-eq) covered about 4-5 tons per inhabitant and is one of the lowest in

European countries where annual GHG of CO2-eq is about 3-15 tons per inhabitant [10].

since 1750 (inset panels). Measurements are shown from ice cores (symbols with different colours for different studies) and atmospheric samples (red lines). The corresponding radiative forcings are

Figure 3. Present and forecasted share of anthropogenic GHGs in total emission in terms of carbon dioxide equivalent (CO2-eq) in Lithuania. Source: Ministry of Environment of the Republic of **Figure 3.** Present and forecasted share of anthropogenic GHGs in total emission in terms of carbon dioxide equivalent (CO2-eq) in Lithuania. Source: Ministry of Environment of the Republic of Lithuania [10]

Lithuania [10] Global warming is the increase in the average temperature of the Earth's near-surface air and the oceans since the mid-twentieth century and its projected continuation. Global mean surface Global warming is the increase of the average temperature of the Earth's near-surface air and the oceans since the mid-twentieth century and its projected continuation. Global mean surface temperature anomaly relative to 1961–1990 is presented in figure 4. Each of the last three decades has been successively warmer at the Earth's surface than any preceding decade since 1850 [7]. The warmest eleven years from twelve records in the world since 1850 were stated in the period of 1995-2006 [8].

In Lithuania there was registered unique climate expression – even seven warm winters successively in the period of 1988/1989 – 1994/1995. Such long period of anomalously warm winters in the Baltic region were not registered during last 200 years [13]. Climate changes in Lithuania manifest through increasing air temperatures and precipitation during winter and slightly increase of air temperatures and decrease of precipitation during summer time [14].

Dynamics of average air temperature in Lithuania during 1961–2006 is presented in figure 5. The results from three locations, i.e. Klaipėda, Kaunas and Vilnius, showed increasing calculated trend-lines (dotted lines) and actual air temperature variation (solid lines).

Lithuanian average year air temperature in 1991–2006 increased by 0.7-1.0 °C relatively to 1961-1990 (Figure 6). That shows fast local climate warming in Lithuania. Climate warming

The great part of GHG emissions locally, i.e. in Lithuania evaluating separate sectors of economy, is generated from energy supply objects and transport (Figure 3). It is in accordance with other developed industrial countries. As well it is forecasted increase of CO2 emissions till 2030 in all sectors of economy in Lithuania (Figure 3). Lithuania together with other modern world countries work solving global climate change problems. In Lithuania annual GHG emission terms of carbon dioxide equivalents (CO2-eq) covered about 4-5 tons per inhabitant and is one of the lowest in European countries where annual GHG of CO2-eq is about 3-15 tons

European countries where annual GHG of CO2-eq is about 3-15 tons per inhabitant [10].

Energy supply Industry Transport Other sectors

(CO2-eq) in Lithuania. Source: Ministry of Environment of the Republic of Lithuania [10]

Figure 2. Atmospheric concentrations of carbon dioxide over the last 10,000 years (large panels) and since 1750 (inset panels). Measurements are shown from ice cores (symbols with different colours for different studies) and atmospheric samples (red lines). The corresponding radiative forcings are shown on the right hand axes of the large panels. Source: IPCC, 2007: Summary for Policymakers [8]

The great part of GHG emissions locally, i.e. in Lithuania evaluating separate sectors of economy, is generated from energy supply objects and transport (Figure 3). It is in accordance with other developed industrial countries. As well it is forecasted increase in CO2 emissions till 2030 in all sectors of economy in Lithuania (Figure 3). Lithuania together with other modern world countries work solving global climate change problems. In Lithuania annual GHG emission terms of carbon dioxide equivalents (CO2-eq) covered about 4-5 tons per inhabitant and is one of the lowest in

Figure 3. Present and forecasted share of anthropogenic GHGs in total emission in terms of carbon dioxide equivalent (CO2-eq) in Lithuania. Source: Ministry of Environment of the Republic of

**Figure 3.** Present and forecasted share of anthropogenic GHGs in total emission in terms of carbon dioxide equivalent

Global warming is the increase of the average temperature of the Earth's near-surface air and the oceans since the mid-twentieth century and its projected continuation. Global mean surface temperature anomaly relative to 1961–1990 is presented in figure 4. Each of the last three decades has been successively warmer at the Earth's surface than any preceding decade since 1850 [7]. The warmest eleven years from twelve records in the world since 1850 were stated in

In Lithuania there was registered unique climate expression – even seven warm winters successively in the period of 1988/1989 – 1994/1995. Such long period of anomalously warm winters in the Baltic region were not registered during last 200 years [13]. Climate changes in Lithuania manifest through increasing air temperatures and precipitation during winter and slightly increase of air temperatures and decrease of precipitation during summer time [14].

Dynamics of average air temperature in Lithuania during 1961–2006 is presented in figure 5. The results from three locations, i.e. Klaipėda, Kaunas and Vilnius, showed increasing

Lithuanian average year air temperature in 1991–2006 increased by 0.7-1.0 °C relatively to 1961-1990 (Figure 6). That shows fast local climate warming in Lithuania. Climate warming

calculated trend-lines (dotted lines) and actual air temperature variation (solid lines).

Global warming is the increase in the average temperature of the Earth's near-surface air and the oceans since the mid-twentieth century and its projected continuation. Global mean surface

per inhabitant [10].

92 Global Warming - Causes, Impacts and Remedies

Lithuania [10]

the period of 1995-2006 [8].

Million tons of CO2equivalent

**Figure 4.** Global mean surface temperature anomaly relative to 1961–1990. Source: Climate Change 2007: The Physi‐ cal Science Basis [8, 11, 12]

tendencies are the most expressed in North and West Lithuania. Therefore, the last 16 year (1991-2006) average air temperature in Lithuania overcame the limit of 6°C.

**Figure 5.** Average year air temperature (°C) change dynamics linear trends (dotted lines) in Lithuania during 1961– 2006. Source: Lithuanian Hydrometeorological Service under the Ministry of Environment [10]

**Figure 6.** Lithuanian average year air temperature (°C) in 1961–1990. The air temperature differences between 1961-1990 and 1991-2006 are shown by isolines. Source: Lithuanian Hydrometeorological Service under the Ministry of Environment [10]

During the second half of the 20th century and early part of the 21st century, global average surface temperature increased and sea level rose. Over the same period, the amount of snow cover in the Northern Hemisphere decreased (Figure 7). If radiative forcing was to be stabilised in 2100 at A1B levels, thermal expansion alone would lead to 0.3 to 0.8 m of sea level rise by 2300 (relatively to 1980–1999) [8].

The best estimates and likely ranges for global average surface air warming for six SRES emissions marker scenarios are shown in figure 8. Including uncertainties in the future greenhouse gas concentrations and climate sensitivity, the IPCC, scientific intergovernmental body set up by the World Meteorological Organization (WMO) and by the United Nations Environment Programme (UNEP), anticipates a warming of 1.1°C to 6.4°C by the end of the 21st century, relatively to 1980–1999 [8].

The globally averaged combined land and ocean surface temperature data show a warming of 0.85°C, over the period of 1880 to 2012. The total increase between the average of the 1850– 1900 and the 2003–2012 periods is 0.78°C. For the longest period when calculation of regional trends is sufficiently complete (1901 to 2012), almost the entire globe has experienced surface warming [7]. If radiative forcing was to be stabilised in 2100 at B1or A1B levels (Figure 8), a further increase in global average temperature of about 0.5°C would be still expected, mostly by 2200. Thermal expansion would continue for many centuries, due to the time required to transport heat into the deep ocean [8].

**Figure 6.** Lithuanian average year air temperature (°C) in 1961–1990. The air temperature differences between 1961-1990 and 1991-2006 are shown by isolines. Source: Lithuanian Hydrometeorological Service under the Ministry

During the second half of the 20th century and early part of the 21st century, global average surface temperature increased and sea level rose. Over the same period, the amount of snow cover in the Northern Hemisphere decreased (Figure 7). If radiative forcing was to be stabilised in 2100 at A1B levels, thermal expansion alone would lead to 0.3 to 0.8 m of sea level rise by

The best estimates and likely ranges for global average surface air warming for six SRES emissions marker scenarios are shown in figure 8. Including uncertainties in the future greenhouse gas concentrations and climate sensitivity, the IPCC, scientific intergovernmental body set up by the World Meteorological Organization (WMO) and by the United Nations Environment Programme (UNEP), anticipates a warming of 1.1°C to 6.4°C by the end of the

The globally averaged combined land and ocean surface temperature data show a warming of 0.85°C, over the period of 1880 to 2012. The total increase between the average of the 1850– 1900 and the 2003–2012 periods is 0.78°C. For the longest period when calculation of regional trends is sufficiently complete (1901 to 2012), almost the entire globe has experienced surface warming [7]. If radiative forcing was to be stabilised in 2100 at B1or A1B levels (Figure 8), a further increase in global average temperature of about 0.5°C would be still expected, mostly by 2200. Thermal expansion would continue for many centuries, due to the time required to

of Environment [10]

2300 (relatively to 1980–1999) [8].

94 Global Warming - Causes, Impacts and Remedies

21st century, relatively to 1980–1999 [8].

transport heat into the deep ocean [8].

**Figure 7.** Changes in global average temperature, global average sea level and Northern Hemisphere snow cover. Source: Climate Change 2007: The Physical Science Basis, Summary for Policymakers, IPCC [8]

Over the last two decades, the Greenland and Antarctic ice sheets have been losing mass, glaciers have continued to shrink almost worldwide, and Arctic sea ice and Northern Hemi‐ sphere spring snow cover have continued to decrease in extent [7]. Analogous to global tendencies, due to warming climate, day number with snow cover became more unstable and is being decreasing in Lithuania. Day number with snow cover during 1991-2006 relatively to 1961-1990 averagely decreased by 4-10 days (Figure 9). However, during winter emerging maximal snow cover thick increased by 0.8-2.0 cm. It is connected with last year's increase of cold season precipitation amount and more often heavy snowing [10].

connected with last year's increase of cold season precipitation amount and more often heavy snowing [10]. **Figure 8.** Global warming: estimations of past and future global warming. Source: Climate Change 2007: The Physical Science Basis, Summary for Policymakers, IPCC [8]

Figure 9. Average number of days with snow cover in Klaipėda, Kaunas and Vilnius, Lithuania during 1961-1990 and 1991-2006. Source: Lithuanian Hydrometeorological Service under the **Figure 9.** Average number of days with snow cover in Klaipėda, Kaunas and Vilnius, Lithuania during 1961-1990 and 1991-2006. Source: Lithuanian Hydrometeorological Service under the Ministry of Environment [10]

Projected global average surface warming for the 2020-2029 and the end of the 21st century (2090–2099) relatively to 1980–1999 are shown in figure 10. Projected warming in the 21st century shows scenario independent geographical patterns similar to those observed over the past several decades. Warming is expected to be the greatest over land and at the highest northern latitudes, and

the least over the Southern Ocean and parts of the North Atlantic Ocean (Figure 10) [8].

Ministry of Environment [10]

Projected global average surface warming for 2020-2029 and the end of the 21st century (2090– 2099) relatively to 1980–1999 are shown in figure 10. Projected warming in the 21st century shows scenario independent geographical patterns similar to those observed over the past several decades. Warming is expected to be the greatest over land and at the highest northern latitudes, and the least over the Southern Ocean and parts of the North Atlantic Ocean (Figure 10) [8].

**Figure 10.** Projected changes in mean surface temperature by the late 21st century according to the A1B climate change scenario. All values for the period 2020-2029 and 2090–2099 are shown relatively to the mean temperature values for the period of 1980–1999. Source: Climate Change 2007: The Physical Science Basis, Summary for Policymak‐ ers, IPCC [8]

## **2. Material and methods**

snowing [10].

Science Basis, Summary for Policymakers, IPCC [8]

96 Global Warming - Causes, Impacts and Remedies

Day number

Ministry of Environment [10]

1991-2006. Source: Lithuanian Hydrometeorological Service under the Ministry of Environment [10]

**Figure 9.** Average number of days with snow cover in Klaipėda, Kaunas and Vilnius, Lithuania during 1961-1990 and

**Figure 8.** Global warming: estimations of past and future global warming. Source: Climate Change 2007: The Physical

Projected global average surface warming for the 2020-2029 and the end of the 21st century (2090–2099) relatively to 1980–1999 are shown in figure 10. Projected warming in the 21st century shows scenario independent geographical patterns similar to those observed over the past several decades. Warming is expected to be the greatest over land and at the highest northern latitudes, and

the least over the Southern Ocean and parts of the North Atlantic Ocean (Figure 10) [8].

Figure 9. Average number of days with snow cover in Klaipėda, Kaunas and Vilnius, Lithuania during 1961-1990 and 1991-2006. Source: Lithuanian Hydrometeorological Service under the Lithuanian territory situated between 53o 54'N and 56o 27'N latitude, 20o 56'E and 26o 51'E longitude [53] occupies intermediate geographical position between west European oceanic climate and Eurasian continental climate. Cold air masses transfered from Arctic induce decrease of air temperatures which is reason of spring and early autumn frosts and of hard frost in winter time. Warm air masses from tropics are seldom which form thaws during winter and clear hot days during summer. Climate of the Lithuanian territory forms in different radiation and circulation conditions. Differences in these conditions hardly cross the bounda‐ ries of microclimatic differences; therefore, Lithuania belongs to western region of the Atlantic Ocean continental climatic area [45, 52] with average annual precipitation of 675 mm (572-907 mm) and temperature of 6-7o C [53, 54].

*Phytotron vegetative pot experiments*. The plastic pots (capacity of 5 L) substrata of turf (pH 6.0-6.5) were used. Till the emergence of white goosefoot *Chenopodium album* L. and one week after, pots were kept in a greenhouse, and then moved to the phytotron for 2 weeks. The emerged weeds were thinned out to 25 seedlings per pot. Results were evaluated after 21 days from weed emergence. Length of sprouts was measured (mm) and weed biomass (g per pot) was established oven-dried at 65o C.

Investigated weed genus white goosefoot *Chenopodium album* L. is widely spread in Europe, Asia and belongs to cosmopolitan group of plants. *C. album* is spread in agricultural lands and set–aside all over the world [15, 16]. White goosefoot *C. album* is annual hardly exterminated weed because one plant can give about 100,000 or till 200,000 seeds that germinate not all at once [15, 17].

## **2.1. Complex effect of CO2 and temperature**

The experimental factor was the environment of contrasting carbon dioxide (CO2) concentra‐ tions and temperature level combinations.

Four levels of CO2 concentration:

Two levels of temperature regimes:

CO2 concentration, temperature regimes and their combinations were tested in the Phytotron vegetative pot experiments.

Concentration of CO2 was regulated using CO2 cylinder-reservoir controlled by CO2 measurer "CO2RT-5" (produced by Regin, Sweden). Photoperiod 16/8 h was achieved using highpressure sodium (HPS) lamps SON-T Agro (Philips). The level of background radiation (PAR) made 170 micro-mol m-2 s-1. PAR was measured with RF-100 Radiometer-Photometer with G.PAR-100 detector cell (produced by Sonopan, Poland).

## **2.2. Effect of UV-B radiation**

Six levels of UV–B radiation (wavelength 290-320 nm) were tested:

climate and Eurasian continental climate. Cold air masses transfered from Arctic induce decrease of air temperatures which is reason of spring and early autumn frosts and of hard frost in winter time. Warm air masses from tropics are seldom which form thaws during winter and clear hot days during summer. Climate of the Lithuanian territory forms in different radiation and circulation conditions. Differences in these conditions hardly cross the bounda‐ ries of microclimatic differences; therefore, Lithuania belongs to western region of the Atlantic Ocean continental climatic area [45, 52] with average annual precipitation of 675 mm (572-907

*Phytotron vegetative pot experiments*. The plastic pots (capacity of 5 L) substrata of turf (pH 6.0-6.5) were used. Till the emergence of white goosefoot *Chenopodium album* L. and one week after, pots were kept in a greenhouse, and then moved to the phytotron for 2 weeks. The emerged weeds were thinned out to 25 seedlings per pot. Results were evaluated after 21 days from weed emergence. Length of sprouts was measured (mm) and weed biomass (g per pot)

Investigated weed genus white goosefoot *Chenopodium album* L. is widely spread in Europe, Asia and belongs to cosmopolitan group of plants. *C. album* is spread in agricultural lands and set–aside all over the world [15, 16]. White goosefoot *C. album* is annual hardly exterminated weed because one plant can give about 100,000 or till 200,000 seeds that germinate not all at

The experimental factor was the environment of contrasting carbon dioxide (CO2) concentra‐

CO2 concentration, temperature regimes and their combinations were tested in the Phytotron

Concentration of CO2 was regulated using CO2 cylinder-reservoir controlled by CO2 measurer "CO2RT-5" (produced by Regin, Sweden). Photoperiod 16/8 h was achieved using highpressure sodium (HPS) lamps SON-T Agro (Philips). The level of background radiation (PAR) made 170 micro-mol m-2 s-1. PAR was measured with RF-100 Radiometer-Photometer with

C [53, 54].

C.

mm) and temperature of 6-7o

98 Global Warming - Causes, Impacts and Remedies

was established oven-dried at 65o

**2.1. Complex effect of CO2 and temperature**

tions and temperature level combinations.

Four levels of CO2 concentration: **•** 350 ppm (control treatment)

Two levels of temperature regimes:

vegetative pot experiments.

C (control treatment)

G.PAR-100 detector cell (produced by Sonopan, Poland).

once [15, 17].

**•** 700 ppm **•** 1500 ppm **•** 3000 ppm

**•** 21o

**•** 25o

C/17o

C/21o C

To generate the chosen UV–B radiation Medical lamps "Philips TL 40W/12 RS" UV–B were used.

## **2.3. Effect of ozone**

Four levels of ozone concentrations were tested:

The selected ozone concentration was reached using the ozone generator OSR-8 (Ozone Solutions, Inc.) 5 days per week, 7 hours per day. Ozone concentration was measured by the mobile ozone measuring equipment OMC-1108 (Ozone Solutions, Inc.).

#### **2.4. Complex effect of UV-B radiation and ozone**

Combination influence of two levels of ozone concentrations 120 μg m-3 and 360 μg m-3 with two levels of UV–B radiation: 3 kJ m-2d-1and 9 kJ m-2 d-1was tested.

Experimental schema of UV–B radiation and ozone combinations is as follows:

### **2.5. Complex effect of ozone and temperature**

Experimental photoperiod is 14/10 h. Ozone impact duration is 12 days.

Three levels of ozone concentrations:

Two levels of temperature regimes:

#### **2.6. Complex effect of UV-B radiation and temperature**

Experimental photoperiod is 14/10 h. Impact duration is 8 days.

Three levels of UV–B radiation:

Two levels of temperature regimes:

The experiments were conducted in three replications [18].

*Data analysis*. The collected data of the experiments were analysed by means of ANOVA. The treatment effects were tested for significance using the *Sigma Stat* software package [19] and the *Selekcija* software package [20].

## **3. Auto-ecological adaptability of weeds**

*Weeds* are plants growing in undesirable places (i.e. crops and etc.) by human and competing with cultural plants for the growth factors and elements. Cultural plants can be counted as weeds if they are growing in crops of other cultural plants, for example, rye in wheat and etc. *Autoecology* is the branch of ecology which deals with individual species and their reactions to environmental factors. *Adaptivity* is the ability to react to change; adaptability allows the plant (weed) to function despite changes in the environment.

## **3.1. Complex effect of CO2 and temperature**

**•** CT+O3 – plants exposed to 360 μg m-3 ozone concentration.

Experimental photoperiod is 14/10 h. Ozone impact duration is 12 days.

**•** CT+UVB-plants exposed to 9 kJ m-2 d-1 UV-B radiation.

**2.5. Complex effect of ozone and temperature**

Three levels of ozone concentrations:

Two levels of temperature regimes:

Three levels of UV–B radiation: **•** 0 kJ m-2 d-1 (control treatment)

Two levels of temperature regimes:

the *Selekcija* software package [20].

C (control treatment)

C (control treatment)

**2.6. Complex effect of UV-B radiation and temperature**

The experiments were conducted in three replications [18].

**3. Auto-ecological adaptability of weeds**

*Data analysis*. The collected data of the experiments were analysed by means of ANOVA. The treatment effects were tested for significance using the *Sigma Stat* software package [19] and

*Weeds* are plants growing in undesirable places (i.e. crops and etc.) by human and competing with cultural plants for the growth factors and elements. Cultural plants can be counted as weeds if they are growing in crops of other cultural plants, for example, rye in wheat and etc. *Autoecology* is the branch of ecology which deals with individual species and their reactions to

Experimental photoperiod is 14/10 h. Impact duration is 8 days.

**•** 20 μg m-3 (control treatment)

100 Global Warming - Causes, Impacts and Remedies

**•** 40 μg m-3 **•** 80 μg m-3

C/14o

C/16o C

**•** 2 kJ m-2 d-1 **•** 4 kJ m-2 d-1

C/14o

C/16o C

**•** 21o

**•** 25o

**•** 21o

**•** 25o

During the past decades the climate change and environment pollution became the important factors influencing the plant growth, development and productivity. The anthropogenic activity constantly changes the abiotical factors that surround us. The increasing air temper‐ ature, carbon dioxide, ozone, UV-B radiation and etc. are the factors constantly felt by the plants and their ability to adapt to the changing situation secures their productivity and agroecosystem stability [3].

Continued emissions of greenhouse gases will cause further warming and changes in all components of the climate system [7]. Limiting climate change will require substantial and sustained reductions of greenhouse gas emissions. Climate-carbon cycle coupling is expected to add carbon dioxide to the atmosphere as the climate system warms, but the magnitude of this feedback is uncertain. Based on current understanding of climatecarbon cycle feedback, model studies suggest that to stabilise at 450 ppm carbon dioxide could require that cumulative emissions over the 21st century would be reduced from the average of approximately 670 GtC (2460 GtCO2) to approximately 490 GtC (1800 GtCO2). Similarly, to stabilise at 1000 ppm, this feedback could require that cumulative emissions would be reduced from the model average of approximately 1415 GtC (5190 GtCO2) to approximately 1100 GtC (4030 GtCO2) [6, 8]. Depending on the scenario, about 15 to 40% of emitted CO2 will remain in the atmosphere longer than 1,000 years [7]. This could result in the global climate change. Plants react to the increased concentration of CO2, therefore this can trigger the processes of plant biomass accumulation [21].

Carbon dioxide as the carbon source used to synthesize the plant biomass is a very important abiotical factor in agriculture. Estimating the influence of CO2 concentration for the growth of white goosefoot *Chenopodium album* L., the control treatment was compared with 350 ppm CO2. Gradually CO2 concentration was increased up to 700 ppm and 1500 ppm and it maxi‐ mized the growth of white goosefoot and its biomass accumulation on the regular basis. When CO2 concentration was increased up to 3000 ppm, the growth of *C. album* was reduced but still remained greater than CO2 concentration in the control treatment (Figure 11). This means, that *C. album* can successfully adapt to the twice as great CO2 concentrations, but it reaches the limit of the maximum growth. Other researchers [51] estimated also more intensive growth of other crop weed – *Parthenium hysterophorus* L. (whitetop weed) under a climate change scenario involving an elevated atmospheric CO2 (550 *μ*mol mol-1) concentration. *P. hysterophorus* plants grew significantly taller (52%) and produced more biomass (55%) than under the ambient atmospheric CO2 concentration (380 *μ*mol mol-1) [51].

The increasing concentration of atmospheric CO2 is observed to increase plant photosynthesis and plant growth, which drives an increase of carbon storage in terrestrial ecosystems. However, plant growth is constrained by the availability of anthropogenic reactive nitrogen (Nr) in soils. This means that in some nitrogen-poor ecosystems, insufficient Nr availability 6 7 24.91

influence on early growth of *C. album*.

**14** 3

**15** 23

(Figu re 11)

**14** 10 Note. – significant differences in comparison with

C/17o

**<sup>15</sup>**20 decreases by decreased by

**15** 12 has a tendency have a tendency

**18** 9 growth were 3.5-5.8 growth was 3.5-5.8

**20** 3 climate-temperature climate temperature

**20** 7 times accordingly. times, accordingly.

**20** 6 ) while ), while

**19** 3 Increase weed ability Increase of weed ability

C+350 ppm) at *P* 0.05

**16** 22 white goosefoot biomass and length of the above-ground white goosefoot air-dry biomass and length of the over-ground

control treatment (21<sup>o</sup>

and \*\*-at *P* 0.01.

decreases till

will limit carbon sinks, while the deposition of Nr may instead alleviate this limitation and enable larger carbon sinks [22]. **26** 16 [55] Singh B.R. Singh O. [55] Singh B.R., Singh O. 28.61 28.64 26.96 30 35 8 9 mm Sprout air-dry biomass Root air-dry biomass Sprout length

**Figure 11.** *Chenopodium album* L. white goosefoot accumulated biomass from a pot (g) and seedlings length (mm) under different CO2 concentrations [23] Continuing experiment under controlled phytotron conditions, complex impact of actual and forecasted CO2 and temperature to the growth of white goosefoot *C. album* were tested (Figure 12). Increase of temperature to forecasted 25<sup>o</sup> C/21<sup>o</sup> C initiates growth of white goosefoot more quickly and accumulates its biomass more intensively. But the increase of CO2 concentration up to 700 ppm at

In addition to land use and climate-induced vegetation changes, CO2 affects vegetation forcing indirectly, reducing transpiration from plants as stomata open less with increasing CO2, resulting in localized atmospheric drying and warming [22, 24]. this forecasted temperature starts to inhibit the growth of white goosefoot and its roots (Figure 12). It was established that the most favourable conditions for *C. album* early growth were at higher temperature regime 25o C/21<sup>o</sup> C with both CO2 concentrations. However, for the root growth initiation, especially, optimal conditions were with lower – 350 ppm – CO2 concentration (Figure 12). Higher CO2 concentration 700 ppm with actual lower temperature regime 21o C/17<sup>o</sup> C showed the negative

2

6.49 5.51

Note. \* – significant differences in comparison with

C/17<sup>o</sup>

24.91

control treatment (21<sup>o</sup>

20 25 and \*\*-at *P* < 0.01.

decreased till

Biomass, g per pot

0.73 0.59

C+350 ppm) at *P* < 0.05

350 700

28.61

Sprout air-dry biomass Roo

CO2 concentr

 Note. – significant differences in comparison with control treatment (21<sup>o</sup> C/17<sup>o</sup> C + 350 ppm) at *P* 0.05 and \*\* - at *P* 0.01. Note. \* – significant differences in comparison with control treatment (21oC/17oC+350 ppm) at *P* < 0.05 and \*\*-at *P* < 0.01.

**Figure 12.** *Chenopodium album* L. white goosefoot accumulated biomass from a pot (g) and seedlings length (mm) under different combinations of temperature regimes and CO2 concentrations [23]

Continuing experiment under controlled phytotron conditions, complex impact of actual and forecasted CO2 and temperature to the growth of white goosefoot *C. album* were tested (Figure 12). Increase of temperature to forecasted 25o C/21o C initiates growth of white goosefoot more quickly and accumulates its biomass more intensively. But the increase of CO2 concentration up to 700 ppm at this forecasted temperature starts to inhibit the growth of white goosefoot and its roots (Figure 12). It was established that the most favourable conditions for *C. album* early growth were at higher temperature regime 25o C/21o C with both CO2 concentrations. However, for the root growth initiation, especially, optimal conditions were with lower – 350 ppm – CO2 concentration (Figure 12). Higher CO2 concentration 700 ppm with actual lower temperature regime 21o C/17o C showed the negative influence on early growth of *C. album*.

#### **3.2. Effect of UV-B radiation**

(Figure 13).

**3.3. Effect of ozone**

2

6.49 5.51

Note. \* – significant differences in comparison with

C/17<sup>o</sup>

C showed the negative

36.18\*\*

C + 350 ppm) at *P*

C initiates growth of white goosefoot more

Sprout lenght cm

Sprout lenght,

 mm

Sprout lenght,mm

24.91

control treatment (21<sup>o</sup>

and \*\*-at *P* < 0.01.

decreased till

Biomass, g per pot

0.73 0.59

C+350 ppm) at *P* < 0.05

350 700

28.61

Sprout air-dry biomass Roo

CO2 concentr

will limit carbon sinks, while the deposition of Nr may instead alleviate this limitation and

Sprout air-dry biomass Root air-dry biomass Sprout length

0.73 0.59 1.0 0.69

CO2 concentration ppm

**26** 16 [55] Singh B.R. Singh O. [55] Singh B.R., Singh O.

6.49 5.51 8.33 8.21

350 700 1500 3000

Figure 11. *Chenopodium album* L. white goosefoot accumulated biomass from a pot (g) and seedlings

6.49 5.51 8.33 8.21

0.73 0.59 1.0 0.69

Sprout air-dry biomass Root air-dry biomass Sprout length

CO2 concentration ppm

350 700 1500 3000

In addition to land use and climate-induced vegetation changes, CO2 affects vegetation forcing indirectly, reducing transpiration from plants as stomata open less with increasing CO2, resulting in

 Continuing experiment under controlled phytotron conditions, complex impact of actual and forecasted CO2 and temperature to the growth of white goosefoot *C. album* were tested (Figure 12).

**Figure 11.** *Chenopodium album* L. white goosefoot accumulated biomass from a pot (g) and seedlings length (mm)

C/21<sup>o</sup>

In addition to land use and climate-induced vegetation changes, CO2 affects vegetation forcing indirectly, reducing transpiration from plants as stomata open less with increasing CO2,

accumulates its biomass more intensively. But the increase of CO2 concentration up to 700 ppm at this forecasted temperature starts to inhibit the growth of white goosefoot and its roots (Figure 12). It was established that the most favourable conditions for *C. album* early growth were at higher

especially, optimal conditions were with lower – 350 ppm – CO2 concentration (Figure 12). Higher

Sprout air-dry biomass Root air-dry biomass Sprout length

6.51 7.28 5.72 6.70

21oC/17oC + 350 ppm 25oC/21oC + 350 ppm 21oC/17oC + 700 ppm 25oC/21oC + 700 ppm

Note. \* – significant differences in comparison with control treatment (21oC/17oC+350 ppm) at *P* < 0.05 and \*\*-at *P* <

**Figure 12.** *Chenopodium album* L. white goosefoot accumulated biomass from a pot (g) and seedlings length (mm)

Continuing experiment under controlled phytotron conditions, complex impact of actual and forecasted CO2 and temperature to the growth of white goosefoot *C. album* were tested (Figure

C/21o

quickly and accumulates its biomass more intensively. But the increase of CO2 concentration up to 700 ppm at this forecasted temperature starts to inhibit the growth of white goosefoot

Temperature (oC) and CO2 concentration (ppm)

41.04\*\*

1.53\*

resulting in localized atmospheric drying and warming [22, 24].

CO2 concentration 700 ppm with actual lower temperature regime 21o

Note. – significant differences in comparison with control treatment (21<sup>o</sup>

under different combinations of temperature regimes and CO2 concentrations [23]

28.61 28.64 26.96

C with both CO2 concentrations. However, for the root growth initiation,

34.44\*

C initiates growth of white goosefoot more quickly and

C/17<sup>o</sup>

C/17<sup>o</sup>

0.82 0.87

28.61 28.64 26.96

enable larger carbon sinks [22].

102 Global Warming - Causes, Impacts and Remedies

24.91

length (mm) under different CO2 concentrations [23]

localized atmospheric drying and warming [22, 24].

C/21<sup>o</sup>

1.10

12). Increase of temperature to forecasted 25o

30.40

Increase of temperature to forecasted 25<sup>o</sup>

influence on early growth of *C. album*.

24.91

Biomass, g per pot

under different CO2 concentrations [23]

temperature regime 25o

0.05 and \*\* - at *P* 0.01.

Air-dry biomass g per pot

0.01.

Biomass, g per pot

**14** 3

**15** 23

(Figu re 11)

**14** 10 Note. – significant differences in comparison with

C/17o

**<sup>15</sup>**20 decreases by decreased by

**15** 12 has a tendency have a tendency

**18** 9 growth were 3.5-5.8 growth was 3.5-5.8

**20** 3 climate-temperature climate temperature

**20** 7 times accordingly. times, accordingly.

**21** 9 it to threats them to threats

**20** 6 ) while ), while

**19** 3 Increase weed ability Increase of weed ability

C+350 ppm) at *P* 0.05

**16** 22 white goosefoot biomass and length of the above-ground white goosefoot air-dry biomass and length of the over-ground

control treatment (21<sup>o</sup>

and \*\*-at *P* 0.01.

decreases till

The shorter are waves of the radiation, the greater is the effect of the ultraviolet radiation on living organisms [25, 26]. Molecule alternations and damages inevitably alter other processes: activity of genes, metabolism, intensity of photosynthesis which, consequently, influence the growth of the plant [27]. The reduction of the photosynthesis intensity due to the impact of UV-B radiation is related to slight conductance of stomata and the quantity of photosynthetic pigments [28]. Height and biomass of the majority of plant species have a tendency to reduce due to the UV-B radiation [28-30]. Figure 12. *Chenopodium album* L. white goosefoot accumulated biomass from a pot (g) and seedlings length (mm) under different combinations of temperature regimes and CO2 concentrations [23] **3.2. Effect of UV-B radiation**

Experimental data showed that low UV-B radiation of 0, 1 and 3 kJ m-2 d-1 had a positive effect on early growth of *Chenopodium album* white goosefoot (Figure 13). *C. album* can accumulate up to 30% of biomass in excess in the background of 1 kJ m-2 d-1 UV-B radiation with reference to the control treatment. Increasing the intensity of UV-B radiation, the length of the *Chenopo‐ dium album* L. over-ground part was systemically decreasing. Consequently, as UV-B radiation constantly increased up to 9 kJ m-2 d-1, the length of *C. album* over-ground part starting from 3 kJ m-2 d-1 gradually decreased by 28%. The over-ground part biomass of the *C. album* was decreasing respectively when increasing the UV-B radiation. The least over-ground part and root biomass of *C. album* were accumulated at the 9 kJ m-2d-1 UV-B radiation. Gradually increasing UV-B radiation till 9 kJ m-2d-1 *C. album* biomass decreased till 2 times compared it to the control treatment 0 kJ m-2 d-1 (Figure 13). The shorter are waves of the radiation, the greater is the effect of the ultraviolet radiation on living organisms [25, 26]. Molecule alternations and damages inevitably alter other processes: activity of genes, metabolism, intensity of photosynthesis which, consequently, influence the growth of the plant [27]. The reduction of the photosynthesis intensity due to the impact of UV-B radiation is related to slight conductance of stomata and the quantity of photosynthetic pigments [28]. Height and biomass of the majority of plant species has a tendency to reduce due to the UV-B radiation [28-30]. Experimental data showed that low UV-B radiation of 0, 1 and 3 kJ m-2 d-1 had a positive effect on early growth of *Chenopodium album* white goosefoot (Figure 13). *C. album* can accumulate up to 30% of biomass in excess in the background of 1 kJ m-2 d-1 UV-B radiation with reference to the control treatment. Increasing the intensity of UV-B radiation, the length of the *Chenopodium album* L. over-ground part was systemically decreasing. Consequently, as UV-B radiation constantly increased up to 9 kJ m-2 d-1, the length of *C. album* over-ground part starting from 3 kJ m-2 d-1 gradually decreases by 28%. The over-ground part biomass of the *C. album* was decreasing respectively when increasing the UV-B radiation. The least over-ground part and root biomass of *C. album* were accumulated at the 9 kJ m-2d-1 UV-B radiation. Gradually increasing UV-B radiation till 9 kJ m-2d-1 *C. album* biomass decreases till 2 times compared it to the control treatment 0 kJ m-2 d-1

 Note. Significant differences from control treatment (0 kJ m-2 d-1) at \* *P* < 0.05 and \*\* - at *P* < 0.01 Note. Significant differences from control treatment (0 kJ m-2 d-1) at \* *P* < 0.05 and \*\*-at *P* < 0.01

Figure 13. The above-ground and root biomass from a pot (g) and seedling length (mm) of *Chenopodium album* L. white goosefoot under different UV–B radiation (kJ m-2 d-1) levels [31] **Figure 13.** The above-ground and root biomass from a pot (g) and seedling length (mm) of *Chenopodium album* L. white goosefoot under different UV–B radiation (kJ m-2 d-1) levels [31]

 When the ozone layer in the stratosphere becomes thinner, the ozone concentration at the soil surface increases. Ozone concentration at the soil surface is also insecure to the plant development

#### **3.3. Effect of ozone**

When the ozone layer in the stratosphere becomes thinner, the ozone concentration at the soil surface increases. Ozone concentration at the soil surface is also insecure to the plant devel‐ opment [3]. The ozone gas acts as strong oxidator in the plant cells and destabilizes the vital functions [32]. Short impact of ozone may cause various injuries to leaves, moreover, under the long-term continuous influence plants become less, the crop decreases, leaves are injured [33, 34]. Ozone adds to quicker senescence of plant leaves and their early fall. These processes are determined by the increase of free radicals in the plant cells [35, 36].

Evaluating the effect of ozone concentration on *C. album* white goosefoot growth, it has been established that the increasing ozone concentration had no statistically reliable impact on *C. album* growth, however, the tendency of over-ground part length (p=0.074) and air-dry biomass (p=0.958) decreasing was observed (Figure 14). The sprout height decreased by 15.4%, 16.8% and 2.0% in ozone concentration of 120 μg m-3, 240 μg m-3 and 360 μg m-3 accordingly, compared it with the control treatment. *C. album* white goosefoot have lost 20.3%, 5.2% and 21.1% their sprout air-dry biomass at ozone concentration of 120 μg m-3, 240 μg m-3 and 360 μg m-3 in respond to control treatment of 0 μg m-3 of ozone, respectively. [3]. The ozone gas acts as strong oxidator in the plant cells and destabilizes the vital functions [32]. Short impact of ozone may cause various injuries to leaves, moreover, under the long-term continuous influence plants become less, the crop decreases, leaves are injured [33, 34]. Ozone adds to quicker senescence of plant leaves and their early fall. These processes are determined by the increase of free radicals in the plant cells [35, 36]. Evaluating the effect of ozone concentration on *C. album* white goosefoot growth, it has been established that the increasing ozone concentration had no statistically reliable impact on *C. album* growth, however, the tendency of over-ground part length (p=0.074) and air-dry biomass (p=0.958) decreasing was observed (Figure 14). The sprout height decreased by 15.4%, 16.8% and 2.0% in ozone concentration of 120 µg m-3, 240 µg m-3 and 360 µg m-3 accordingly, compared it with the

Plants are known to suffer damage due to exposure to levels of ozone (O3) above about 40 ppb [22, 37]. It is established that surface ozone detrimentally affects plant productivity [38]. Tropospheric ozone can also affect the natural uptake of CO2 by decreasing plant productivity [22]. control treatment. *C. album* white goosefoot have lost 20.3%, 5.2% and 21.1% their sprout air-dry biomass at ozone concentration of 120 µg m-3, 240 µg m-3 and 360 µg m-3 in respond to control treatment of 0 µg m-3 of ozone, respectively. Plants are known to suffer damage due to exposure to levels of ozone (O3) above about 40 ppb [22, 37]. It is established that surface ozone detrimentally affects plant productivity [38].

Tropospheric ozone can also affect the natural uptake of CO2 by decreasing plant productivity [22].

 Figure 14. The *Chenopodium album* L. white goosefoot biomass and length of the above-ground part under the influence of ozone [31] **Figure 14.** The *Chenopodium album* L. white goosefoot air-dry biomass and length of the over-ground part under the influence of ozone [31]

#### **3.4. Complex effect of UV-B radiation and ozone 3.4. Complex effect of UV-B radiation and ozone**

radiation [25, 26].

protects plants and live organisms from their negative impact. Ozone depletion would increase the amount of ultraviolet light reaching the surface damaging terrestrial and marine ecosystems [22]. Since the beginning of the eight decade of the XX century the rapid breaking of the ozone layer in the stratosphere has been noticed as well as the increase of the intensity of UV radiation. Ozone O3 formed in the troposphere as a result of NOx and volatile organic compound emissions Ozone layer absorbs the greatest part of UV rays radiated by the Sun and other space bodies and protects plants and live organisms from their negative impact. Ozone depletion would increase the amount of ultraviolet light reaching the surface damaging terrestrial and marine ecosystems [22]. Since the beginning of the eight decade of the XX century the rapid breaking

reduces plant productivity, and therefore reduces CO2 uptake from the atmosphere [22]. The depletion of the ozone layer is induced by the pollutants containing chlorine and bromine ions released into the environment [39]. The thickness of the ozone layer has the greatest impact on the flow of the UV-B

During the complex research (Table 1) the negative impact of ozone and UV-B radiation on white goosefoot *C. album* growth increased in comparison to the impact of ozone (Figure 14) and

Ozone layer absorbs the greatest part of UV rays radiated by the Sun and other space bodies and

of the ozone layer in the stratosphere has been noticed as well as the increase of the intensity of UV radiation.

Ozone O3 formed in the troposphere as a result of NOx and volatile organic compound emissions reduces plant productivity, and therefore reduces CO2 uptake from the atmosphere [22]. The depletion of the ozone layer is induced by the pollutants containing chlorine and bromine ions released into the environment [39]. The thickness of the ozone layer has the greatest impact on the flow of the UV-B radiation [25, 26].

During the complex research (Table 1) the negative impact of ozone and UV-B radiation on white goosefoot *C. album* growth increased in comparison to the impact of ozone (Figure 14) and UV-B (Figure 13) when effecting separately. *C. album* is unable to adapt to the increasing UV-B radiation and the intensifying complex impact of ozone and UV-B.

Note. #CT – control treatment; significant differences from control treatment (#CT) at \* *P* < 0.05 and \*\*-at *P* < 0.01

**Table 1.** *Chenopodium album* L. white goosefoot biomass and length of the over-ground part after the exposure to both ozone and UV-B radiation [31]

#### **3.5. Complex effect of ozone and temperature**

**3.3. Effect of ozone**

104 Global Warming - Causes, Impacts and Remedies

productivity [22].

When the ozone layer in the stratosphere becomes thinner, the ozone concentration at the soil surface increases. Ozone concentration at the soil surface is also insecure to the plant devel‐ opment [3]. The ozone gas acts as strong oxidator in the plant cells and destabilizes the vital functions [32]. Short impact of ozone may cause various injuries to leaves, moreover, under the long-term continuous influence plants become less, the crop decreases, leaves are injured [33, 34]. Ozone adds to quicker senescence of plant leaves and their early fall. These processes

Evaluating the effect of ozone concentration on *C. album* white goosefoot growth, it has been established that the increasing ozone concentration had no statistically reliable impact on *C. album* growth, however, the tendency of over-ground part length (p=0.074) and air-dry biomass (p=0.958) decreasing was observed (Figure 14). The sprout height decreased by 15.4%, 16.8% and 2.0% in ozone concentration of 120 μg m-3, 240 μg m-3 and 360 μg m-3 accordingly, compared it with the control treatment. *C. album* white goosefoot have lost 20.3%, 5.2% and 21.1% their sprout air-dry biomass at ozone concentration of 120 μg m-3, 240 μg m-3 and 360 μg m-3 in

[3]. The ozone gas acts as strong oxidator in the plant cells and destabilizes the vital functions [32]. Short impact of ozone may cause various injuries to leaves, moreover, under the long-term continuous influence plants become less, the crop decreases, leaves are injured [33, 34]. Ozone adds to quicker senescence of plant leaves and their early fall. These processes are determined by the increase of free

Evaluating the effect of ozone concentration on *C. album* white goosefoot growth, it has been established that the increasing ozone concentration had no statistically reliable impact on *C. album* growth, however, the tendency of over-ground part length (p=0.074) and air-dry biomass (p=0.958) decreasing was observed (Figure 14). The sprout height decreased by 15.4%, 16.8% and 2.0% in ozone concentration of 120 µg m-3, 240 µg m-3 and 360 µg m-3 accordingly, compared it with the control treatment. *C. album* white goosefoot have lost 20.3%, 5.2% and 21.1% their sprout air-dry biomass at ozone concentration of 120 µg m-3, 240 µg m-3 and 360 µg m-3 in respond to control

Plants are known to suffer damage due to exposure to levels of ozone (O3) above about 40 ppb [22, 37]. It is established that surface ozone detrimentally affects plant productivity [38]. Tropospheric ozone can also affect the natural uptake of CO2 by decreasing plant productivity [22].

20.85 18.07 17.85 20.44

Sprout air-dry biomass Sprout length

Sprout lenght,

 cm

Figure 14. The *Chenopodium album* L. white goosefoot biomass and length of the above-ground part

3.62 3.01 3.44 2.99

0 120 240 360

Ozone concentration µg m-3

**Figure 14.** The *Chenopodium album* L. white goosefoot air-dry biomass and length of the over-ground part under the

Ozone layer absorbs the greatest part of UV rays radiated by the Sun and other space bodies and protects plants and live organisms from their negative impact. Ozone depletion would increase the amount of ultraviolet light reaching the surface damaging terrestrial and marine ecosystems [22]. Since the beginning of the eight decade of the XX century the rapid breaking

Ozone layer absorbs the greatest part of UV rays radiated by the Sun and other space bodies and protects plants and live organisms from their negative impact. Ozone depletion would increase the amount of ultraviolet light reaching the surface damaging terrestrial and marine ecosystems [22]. Since the beginning of the eight decade of the XX century the rapid breaking of the ozone layer in the

 Ozone O3 formed in the troposphere as a result of NOx and volatile organic compound emissions reduces plant productivity, and therefore reduces CO2 uptake from the atmosphere [22]. The depletion of the ozone layer is induced by the pollutants containing chlorine and bromine ions released into the environment [39]. The thickness of the ozone layer has the greatest impact on the flow of the UV-B

During the complex research (Table 1) the negative impact of ozone and UV-B radiation on white goosefoot *C. album* growth increased in comparison to the impact of ozone (Figure 14) and

stratosphere has been noticed as well as the increase of the intensity of UV radiation.

Plants are known to suffer damage due to exposure to levels of ozone (O3) above about 40 ppb [22, 37]. It is established that surface ozone detrimentally affects plant productivity [38]. Tropospheric ozone can also affect the natural uptake of CO2 by decreasing plant

are determined by the increase of free radicals in the plant cells [35, 36].

respond to control treatment of 0 μg m-3 of ozone, respectively.

radicals in the plant cells [35, 36].

under the influence of ozone [31]

radiation [25, 26].

0

1

2

Air-dry biomass g per pot

influence of ozone [31]

3

4

**3.4. Complex effect of UV-B radiation and ozone**

**3.4. Complex effect of UV-B radiation and ozone**

treatment of 0 µg m-3 of ozone, respectively.

Continuing research of ozone concentration, impact on white goosefoot *Chenopodium album* growth, complex effect of ozone concentration 20, 40 and 80μg m-3 and of actual and forecasted climate temperature regimes were evaluated (Figure 15). Increase of the ozone concentration from 20 μg m-3, increased accumulation of *C. album* sprout air-dry biomass by 74% at 40 μg m-3 and by 68% at 80 μg m-3 and root air-dry biomass by 280% at 40 μg m-3 and by 200% at 80 μg m-3 in the actual climate temperature conditions 21°C/14°C. At forecasted climate higher temperature (25°C/16°C), the rising ozone concentration from 20 to 40 and 80μg m-3 increased the accumulation of *C. album* sprout air-dry biomass by 27-33% and root air-dry biomass by 23-50%, accordingly. Investigated ozone concentration and temperature regimes complex had no significant effect on *C. album* plant height (Figure 15). It was established that *C. album* is adapted to the actual and forecasted climate temperature and ozone concentration variations till 80 μg m-3 of ozone in the environment. Increasing ozone concentration further till 120, 240 and 360 μg m-3, there was observed negative effect on *C. album* growth and abilities to adapt to higher ozone concentration were not determined (Figure 14).

The sprout root ratio of air-dry biomass changing concentration of ozone at different levels of temperatures showed, that *C. album* root growth was 3.5-5.8 times more intensive at forecasted than at actual climate temperature regimes (Lithuanian conditions). At actual climate temper‐ ature under ozone concentration of 20, 40 and 80 μg m-3 white goosefoot *C. album* sprout root ratio of air-dry biomass covered 39.8, 24.8 and 33.5 and at forecasted climate temperature covered 6.9, 7.1 and 6.1, accordingly.

 Note. \* – significant differences from the control treatment (20 µg m-3) at *P* < 0.05. Note. \* – significant differences from the control treatment (20 µg m-3) at *P* < 0.05.

**3.6.** *Complex effect of UV-B radiation and temperature*

 Figure 15.The influence of ozone on *Chenopodium album* L. white goosefoot growth at actual and forecasted climate temperature [40] **Figure 15.** The influence of ozone on *Chenopodium album* L. white goosefoot growth at actual and forecasted cli‐ mate temperature [40]

At changing climate conditions competitive abilities of plants are changing showing through new weed biological qualities. Increase weed ability of over-wintering for weed species that during winter time traditionally were frosting at conventionally colder climate conditions [41, 42]. It was established that during winter time in winter wheat crop annual weeds, even some summer annual ones, had increased adaptivity of successful surviving winter frosts and accumulated higher one plant average mass by 5-6% during winter time; especially when the weather is favourable for prolonged development of weeds even at low density of perennial weeds in the crop [42-44]. Even short-time brief changes of meteorological conditions in crop during vegetation are inducing mechanism of plant/weed adaptivity. Namely, weed seed rain in the crop regularly intensified with increase of temperature and sunlight duration and vice versa [45, 46]. Under heavily polluted or dark cloudy skies, plant productivity may decline as the diffuse effect is insufficient to offset decreased surface irradiance [47]. Plants need a certain amount of UV-B radiation. They stimulate biochemical processes and inhibit to fast plant growing and slow accumulation of air-dry biomass [48]. Due to UV-B radiation height and air-dry biomass of many plant genus decrease [28, 29]. The intensity of UV-B radiation is determined by the seasson, day and night period and meteorological conditions.

#### **3.6. Complex effect of UV-B radiation and temperature**

the accumulation of *C. album* sprout air-dry biomass by 27-33% and root air-dry biomass by 23-50%, accordingly. Investigated ozone concentration and temperature regimes complex had no significant effect on *C. album* plant height (Figure 15). It was established that *C. album* is adapted to the actual and forecasted climate temperature and ozone concentration variations till 80 μg m-3 of ozone in the environment. Increasing ozone concentration further till 120, 240 and 360 μg m-3, there was observed negative effect on *C. album* growth and abilities to adapt

The sprout root ratio of air-dry biomass changing concentration of ozone at different levels of temperatures showed, that *C. album* root growth was 3.5-5.8 times more intensive at forecasted than at actual climate temperature regimes (Lithuanian conditions). At actual climate temper‐ ature under ozone concentration of 20, 40 and 80 μg m-3 white goosefoot *C. album* sprout root ratio of air-dry biomass covered 39.8, 24.8 and 33.5 and at forecasted climate temperature

12.82 12.6 12.97

Sprout air-dry biomass Root air-dry biomass Sprout length

At actual climate temperature 210C/140C

3.47 3.35

Sprout lenght cm

Sprout lenght cm

0.05 0.14 0.1

20 40 80

9.4 11.97\* 12.51\*

At forecasted climate temperature 250C/160C

Ozone concentration µg m-3

Note. \* – significant differences from the control treatment (20 µg m-3) at *P* < 0.05.

Figure 15.The influence of ozone on *Chenopodium album* L. white goosefoot growth at actual and

**Figure 15.** The influence of ozone on *Chenopodium album* L. white goosefoot growth at actual and forecasted cli‐

1.37 1.69 2.06

20 40 80

Ozone concentration µg m-3

31.67 33.14 31.07

Sprout air-dry biomass Root air-dry biomass Sprout length

At changing climate conditions competitive abilities of plants are changing showing through new weed biological qualities. Increase weed ability of over-wintering for weed species that during winter time traditionally were frosting at conventionally colder climate conditions [41, 42]. It was established that during winter time in winter wheat crop annual weeds, even some summer annual ones, had increased adaptivity of successful surviving winter frosts and accumulated higher one plant average mass by 5-6% during winter time; especially when the weather is favourable for prolonged development of weeds even at low density of perennial weeds in the crop [42-44]. Even short-time brief changes of meteorological conditions in crop during vegetation are inducing mechanism of plant/weed adaptivity. Namely, weed seed rain in the crop regularly intensified with increase of temperature and sunlight duration and vice versa [45, 46]. Under heavily polluted or dark cloudy skies, plant productivity may decline as the diffuse effect is insufficient to offset decreased surface irradiance [47]. Plants need a certain amount of UV-B radiation. They stimulate biochemical processes and inhibit to fast plant growing and slow accumulation of air-dry biomass [48]. Due to UV-B radiation height and air-dry biomass of many plant genus decrease [28, 29]. The intensity of UV-B radiation is determined by the seasson, day and night period and meteorological conditions.

to higher ozone concentration were not determined (Figure 14).

covered 6.9, 7.1 and 6.1, accordingly.

106 Global Warming - Causes, Impacts and Remedies

1.99

0

mate temperature [40]

Air-dry biomass g per pot

1

2

Air-dry biomass g per pot

3

4

forecasted climate temperature [40]

**3.6.** *Complex effect of UV-B radiation and temperature*

Note. \* – significant differences from the control treatment (20 µg m-3) at *P* < 0.05.

At changing climate conditions competitive abilities of plants are changing showing through new weed biological qualities. Increase of weed ability of over-wintering for weed species that during winter time traditionally were frosting at conventionally colder climate conditions [41, 42]. It was established that during winter time in winter wheat crop annual weeds, even some summer annual ones, had increased adaptivity of successful surviving winter frosts and accumulated higher one plant average mass by 5-6% during winter time; especially when the weather is favourable for prolonged development of weeds even at low density of perennial weeds in the crop [42-44]. Even short-time brief changes of meteorological conditions in crop during vegetation are inducing mechanism of plant/weed adaptivity. Namely, weed seed rain in the crop regularly intensified with increase of temperature and sunlight duration and vice versa [45, 46]. Under heavily polluted or dark cloudy skies, plant productivity may decline as the diffuse effect is insufficient to offset decreased surface irradiance [47]. Plants need a certain amount of UV-B radiation. They stimulate biochemical processes and inhibit to fast plant growing and slow accumulation of air-dry biomass [48]. Due to UV-B radiation height and airdry biomass of many plant genus decrease [28, 29]. The intensity of UV-B radiation is deter‐ mined by the seasson, day and night period and meteorological conditions. According to the data of Kaunas meteorological station and Palanga avia-meteorological station, the average UV-B radiation doses during clear summer days reach 2.1–2.5 kJ m-2 d-1 [49].

**Table 2.** The influence of UV-B radiation on white goosefoot *C. album* growth at actual and forecasted climate temperature [40]

The next experiment increasing UV-B radiation intensity till 4 kJ m-2 d-1 showed significant negative influence on white goosefoot *C. album* development already at UV-B radiation 2 kJ m-2 d-1 at both-actual 21°C/14°C and forecasting 25°C/16°C climate temperature regimes (Table 2).The over-ground green biomass of *C. album* effected by UV-B radiation of 4 kJ m-2 d-1decreased 5.6 and 4.5 times at actual and forecasted climate temperature respectively compared it with the control treatment (UV-B radiation 0 kJ m-2 d-1), while root green biomass decreased 2.7 and 3.1 times, accordingly. *C. album* over-ground part and root air-dry biomass accumulation decreased nearly twice (1.9 times) already at UV-B radiation 2 kJ m-2 d-1 at both temperature regimes and declined till 3.6-3.7 and 2.8-3.4 times at UV-B radiation 4 kJ m-2 d-1, accordingly. Increasing intensity of UV-B radiation, *C. album* height growth inhibited signifi‐ cantly as well. The highest evaluated UV-B radiation in the experiment decreased plant height by 11% at actual climate temperature and by 43% at forecasted warmer climate temperature. Received data of experiment confirmed that *C. album* is sensitive to UV-B radiation in actual colder and forecasted warmer temperature regimes. *C. album* plant over-ground part and root green and air-dry biomass ratio with increase of UV-B radiation regularly decreased. It could be result of plant protection mechanism activation intensifying transpiration process.

## **4. Conclusions**

## **Acknowledgements**

The next experiment increasing UV-B radiation intensity till 4 kJ m-2 d-1 showed significant negative influence on white goosefoot *C. album* development already at UV-B radiation 2 kJ m-2 d-1 at both-actual 21°C/14°C and forecasting 25°C/16°C climate temperature regimes (Table 2).The over-ground green biomass of *C. album* effected by UV-B radiation of 4 kJ m-2 d-1decreased 5.6 and 4.5 times at actual and forecasted climate temperature respectively compared it with the control treatment (UV-B radiation 0 kJ m-2 d-1), while root green biomass decreased 2.7 and 3.1 times, accordingly. *C. album* over-ground part and root air-dry biomass accumulation decreased nearly twice (1.9 times) already at UV-B radiation 2 kJ m-2 d-1 at both temperature regimes and declined till 3.6-3.7 and 2.8-3.4 times at UV-B radiation 4 kJ m-2 d-1, accordingly. Increasing intensity of UV-B radiation, *C. album* height growth inhibited signifi‐ cantly as well. The highest evaluated UV-B radiation in the experiment decreased plant height by 11% at actual climate temperature and by 43% at forecasted warmer climate temperature. Received data of experiment confirmed that *C. album* is sensitive to UV-B radiation in actual colder and forecasted warmer temperature regimes. *C. album* plant over-ground part and root green and air-dry biomass ratio with increase of UV-B radiation regularly decreased. It could

be result of plant protection mechanism activation intensifying transpiration process.

**1.** Plant ability to survive under unfavourable conditions depends upon the intensity and character of the unfavourable factors. Abiotical factors of low intensity influencing plants induce weed growth, however, weed growth is regularly smothered as their intensity

**2.** Increase of CO2 concentration positively affected the early growth of white goosefoot *Chenopodium album* L. and reached the optimum at 1500 ppm. Higher temperature regime

**3.** Minor UV-B radiation concentrations 1-3 kJ m-2 d-1 induced *C. album* growth; however, the increasing UV-B radiation (5-9 kJ m-2 d-1) reliably decreased both the length of the over-

**4.** Increasing ozone concentration to 120, 240 and 360 μg m-3 had a tendency to suppress *C. album* growth by 2-14% of its sprout length and by 5-17% of its accumulated air-dry biomass. However, complex investigation of ozone and temperature showed that *C. album* is adapted to actual and forecasted climate temperature and ozone concentration

**5.** Complex investigation of UV-B radiation and temperature showed significantly negative influence on *C. album* growth and biomass accumulation already at UV-B radiation 2 kJ m-2 d-1 of both actual 21°C/14°C and forecast 25°C/16°C climate temperature regimes.

*album* early growth at both – 350 ppm and 700 ppm – CO2 concentrations. White goosefoot

C compounded more favourable conditions for *C.*

C/17o

successfully adapts even to several times increased concentration of CO2.

**4. Conclusions**

108 Global Warming - Causes, Impacts and Remedies

increases.

C compared with 21o

ground part and the biomass of white goosefoot.

variations till 80 μg m-3 of the environment.

25o C/21o The Lithuanian State Science and Studies Foundation as a part of the research project "Complex effect of anthropogenic climate and environment changes on the forest and agro ecosystem flora" supported this research.

We would like to thank Vilma Pilipavičienė for the manuscript English reviewing linguistically.

## **Author details**

Vytautas Pilipavičius\*

Address all correspondence to<EMAIL_ADDRESS>
Aleksandras Stulginskis University, Faculty of Agronomy, Institute of Agroecosystems and Soil Sciences, Akademija, Lithuania

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