3. Results

#### 3.1. Climate change model selection

The results from the giss\_e2\_r model appeared on the Taylor diagram at the shortest distance from the observation point (Figure 1). On that basis, the giss\_e2\_r model was selected out of the 16 analyzed climate models for further analysis (Figure 2).

#### 3.2. Simulation of climate change on Colorado potato beetle development

Simulations performed on data registered at 16 localities showed that the best meteorological conditions for the earliest egg laying in 2005 occurred in the west and south-west, while the

the use of an equation describing the relationship between onset of the egg-laying period and

NumoGen 2 simulates the development of colorado Potato Beetle from the occurrence of egg clusters until meteorological conditions or photoperiods prevent further development of the pest. The model was developed from information presented in scientific reports. The development of the pest from egg to adult was based on information presented by Łarczenko [25]. The dates of egg laying by female beetles of succeeding generations were estimated according to data presented by Alyokhin and Ferro [26]. The beginning of the winter diapause was determined from data reported by Tauber et al. [27], who found that all females reared at a photoperiod between 10:14 and 14:10 (L:D) entered diapause. This information was used to determine the dates of diapause based on day length at the 16 localities analyzed in the study. Information about day length was found on the internet at: http://www.timebie.com/sun/.

For each locality, 20 simulations were performed. Each simulation generated information about CPB development based on meteorological data registered in the 20 years, 1986–2005, and data obtained after transformation of the recorded data to reflect temperature changes under four scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5) and four periods (2020–2039,

Additionally for each locality, a model was developed to estimate the minimum temperature increase, in relation to 1986–2005, that ensured the emergence of the second generation of CPB. The models were developed based on meteorological data (registered and obtained after transformation of the recorded data to reflect the temperature changes under four RCP scenarios) and simulation results describing the probability of the occurrence of CPB second genera-

where SGCPBP is the probability of the occurrence of CPB second generation; T the temperature increase for the temperature registered in 1986–2005; a, b and c are the equation coefficients.

The results from the giss\_e2\_r model appeared on the Taylor diagram at the shortest distance from the observation point (Figure 1). On that basis, the giss\_e2\_r model was selected out of

Simulations performed on data registered at 16 localities showed that the best meteorological conditions for the earliest egg laying in 2005 occurred in the west and south-west, while the

SGCPBP ¼ a þ exp bð Þ þ c � T (1)

2040–2059, 2060–2079 and 2080–2099) according to the giss\_e2\_r climate model.

tion. The models were developed with the use of the exponential function:

the 16 analyzed climate models for further analysis (Figure 2).

3.2. Simulation of climate change on Colorado potato beetle development

temperature increase [15].

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3. Results

3.1. Climate change model selection

Figure 1. Taylor diagram illustrating the statistics of the comparison between observed and 16 model estimates of air temperature at 16 localities in 1986–2005. Bcc\_csm1\_1, bcc\_csm1\_1\_m, ccsm4, cesm1\_cam5, csiro\_mk3\_6\_0, fio\_esm, gfdl\_cm3, gfdl\_esm2m, giss\_e2\_h, giss\_e2\_r, ipsl\_cm5a\_mr, miroc\_esm, miroc\_esm\_chem, miroc5, mri\_cgcm3, noresm1\_m: Model names used in the study.

worst conditions were noted in the northern and north-eastern parts of Poland (Table 3). Out of the four RCP scenarios, three (RCP4.5, RCP6.0 and RCP8.5) generated the greatest acceleration of egg laying in the period 2080–2099. But, according to the RCP2.6 scenario, the earliest egg laying is expected in the period 2020–2039 (Table 2). Comparison of meteorological data registered in 1986–2005 revealed that the differences between the earliest and the latest day of egg laying ranges from 12 at Białystok to 16 at Opole (Table 3).

Simulations performed on real data, except for Białystok (95.8%), Gdańsk (85%) and Olsztyn (99.3%), as well as on transformed data showed a 100% probability of the appearance of the first generation of CPB (Figure 3). Simulations performed on real data revealed that the average number of days needed for the development of the first generation of CPB was 56. Use of transformed data resulted in a shortening of the first generation development of the

pest to 46–51 days for RCP2.6, 44 days for RCP4.5, 41–48 days for RCP4.5 and 39–46 days for RCP8.5. The greatest decreases were obtained for Gdańsk (9–14 days for RCP2.6, 15–16 days for RCP4.5, 11–19 days for RCP6.0 and 14–21 days for RCP8.5), Białystok (10–14 days for RCP2.6, 14–17 days for RCP4.5, 13–19 days for RCP6.0 and 16–22 days for RCP8.5), Kielce (9–15 days for RCP2.6, 16–17 days for RCP4.5, 13–19 days for RCP6.0 and 14–21 days for RCP8.5), Lublin (9–14 days for RCP2.6, 15–16 days for RCP4.5, 12–18 days for RCP6.0 and 14–20 days for RCP8.5) and Olsztyn (8–12 days for RCP2.6, 13–14 days for RCP4.5, 10–17 days for RCP6.0 and 14–20 days for RCP8.5). The smallest decreases were noted in simulations performed for Opole (1–6 days for RCP2.6, 7–8 days for RCP4.5, 4–11 days for RCP6.0 and 5–12 days for RCP8.5), Wrocław (0–6 days for RCP2.6, 8–9 days for RCP4.5, 4–11 days for RCP6.0 and 6–13 days for RCP8.5) and ZielonaGóra (1–6 days for RCP2.6, 8–9 days for

Table 2. Effects of RCP scenario on the offset of the egg-laying period in relation to temperature registered in 1986–2005.

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Simulations performed on meteorological data registered in the period 1986–2005 showed that the average probability of the appearance of the Colorado potato beetle second generation was 26% (Figure 4). The highest probabilities were obtained for Opole 62%, Wrocław 46% and ZielonaGóra 45%, whereas the smallest probabilities were achieved for Gdańsk 0%, Olsztyn

The use of data obtained after transformation of the recorded data to reflect temperature changes under four scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5) and four periods (2020– 2039, 2040–2059, 2060–2079 and 2080–2099), according to the giss\_e2\_r climate model, did not lead to much alteration in the list of the localities least threatened by the occurrence of CPB second generation. Out of 16 combinations of scenarios and periods, only four resulted in the replacement of Białystak by another locality in third position on the list. But, changes in the list

RCP4.5, 4–12 days for RCP6.0 and 6–14 days for RCP8.5).

3.2% and Białystok 6%.

Figure 2. Effects of climate change on number of days needed to complete the first generation of CPB at 16 localities in Poland.



Table 2. Effects of RCP scenario on the offset of the egg-laying period in relation to temperature registered in 1986–2005.

pest to 46–51 days for RCP2.6, 44 days for RCP4.5, 41–48 days for RCP4.5 and 39–46 days for RCP8.5. The greatest decreases were obtained for Gdańsk (9–14 days for RCP2.6, 15–16 days for RCP4.5, 11–19 days for RCP6.0 and 14–21 days for RCP8.5), Białystok (10–14 days for RCP2.6, 14–17 days for RCP4.5, 13–19 days for RCP6.0 and 16–22 days for RCP8.5), Kielce (9–15 days for RCP2.6, 16–17 days for RCP4.5, 13–19 days for RCP6.0 and 14–21 days for RCP8.5), Lublin (9–14 days for RCP2.6, 15–16 days for RCP4.5, 12–18 days for RCP6.0 and 14–20 days for RCP8.5) and Olsztyn (8–12 days for RCP2.6, 13–14 days for RCP4.5, 10–17 days for RCP6.0 and 14–20 days for RCP8.5). The smallest decreases were noted in simulations performed for Opole (1–6 days for RCP2.6, 7–8 days for RCP4.5, 4–11 days for RCP6.0 and 5–12 days for RCP8.5), Wrocław (0–6 days for RCP2.6, 8–9 days for RCP4.5, 4–11 days for RCP6.0 and 6–13 days for RCP8.5) and ZielonaGóra (1–6 days for RCP2.6, 8–9 days for RCP4.5, 4–12 days for RCP6.0 and 6–14 days for RCP8.5).

Simulations performed on meteorological data registered in the period 1986–2005 showed that the average probability of the appearance of the Colorado potato beetle second generation was 26% (Figure 4). The highest probabilities were obtained for Opole 62%, Wrocław 46% and ZielonaGóra 45%, whereas the smallest probabilities were achieved for Gdańsk 0%, Olsztyn 3.2% and Białystok 6%.

The use of data obtained after transformation of the recorded data to reflect temperature changes under four scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5) and four periods (2020– 2039, 2040–2059, 2060–2079 and 2080–2099), according to the giss\_e2\_r climate model, did not lead to much alteration in the list of the localities least threatened by the occurrence of CPB second generation. Out of 16 combinations of scenarios and periods, only four resulted in the replacement of Białystak by another locality in third position on the list. But, changes in the list

Figure 2. Effects of climate change on number of days needed to complete the first generation of CPB at 16 localities in

Poland.

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Figure 3. Effects of climate change on probability of the appearance of CPB first generation.

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Table 3. Effects of locality and year on the offset of the egg-laying period.

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Figure 3. Effects of climate change on probability of the appearance of CPB first generation.

Table 3. Effects of locality and year on the offset of the egg-laying period.

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of the highest threatened localities were noticed. ZielonaGóra and Wrocław were replaced

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Of the four scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5), three (RCP4.5, RCP6.0 and RCP8.5) generated a significant increase in the probability of CPB second generation appearance at the end of the century. But, in the periods 2020–2039, 2040–2059 and 2060–2079, increases in the probability of the second generation pest occurrence were generated under all

For the end of the century, the highest probability of the appearance of the second generation of CPB (99.5–100%) was obtained under scenario RCP8.5, whereas the smallest (5.5–50.3) was under RCP2.6. Scenarios RCP4.5 and RCP6.0 generated the following results, respectively:

Simulation under scenarios RCP2.6, RCP4.5 and RCP6.0 revealed that for the end of the century, the highest increase in probability (SGCPBP) were generated respectively for Kielce (42.3, 88.5, 92), Lublin (34, 84.8, 92) and Białystok (12.5, 70.3, 86.3), whereas under scenario RCP8.5, these were for Gdańsk (99.5) Olsztyn (96.8) and Białystok (94). The smallest increase in SGCPBP obtained in simulations under scenarios RCP4.5, RCP6.0 and RCP8.5 were, respectively, revealed for Opole (35.3, 37.3, 38), Wrocław (41.5, 52, 53.8) and ZielonaGóra (34.3, 52, 55.3). In simulations under scenario RCP2.6, besides an increase in SGCPBP, a decrease was also achieved. The highest decrease was generated for Opole (27.5), Wrocław (17.8) and

Simulations under scenario RCP2.6 produced 29 results with SGCPBP lower than 50%, 34 with SGCPBP ranging from 50 to 75% and one higher than 75%. The use of scenarios RCP4.5 and RCP6.0 resulted, respectively, in two and three results with SGCPBP lower than 50%, 18 and 17 results with SGCPBP ranged from 50 to 75% and 43 results higher than 75%. Simulations under RCP8.5 produced 10 results with SGCPBP ranging from 50 to 75% and 54 results higher than 75%. Simulations also showed that the average number of days needed for completion of the second generation was 51–54 for RCP2.6, 47–52 for RCP4.5, 44–51 for RCP6.0 and 39–51 for RCP8.5.

Simulations on real data sets revealed no possibility of the third generation of CPB appearance at all analyzed localities, except for Opole (Figure 5). Introduction of transformed data did not change the results very much, except for scenarios RCP6.0 (period 2080–2099) and RCP8.5

The results of the simulations were also used to estimate the minimum temperature increase for 1986–2005 that ensure the emergence of the second generation of CPB. To achieve that aim,

With a 95% probability, 1C temperature rise at Opole guaranteed the appearance of CPB second generation (Figure 6). At Katowice, Rzeszów, Szczecin and Wrocław, temperatures ought to increase by 1.6C. At Kraków and Toruń, 1.7 and 1.8C temperature rises, respectively, led to the appearance of the pest second generation. At Łódź, Poznan, Warszawa and ZielonaGóra, temperatures ought to rise by 1.9C. A temperature increase of 2.1 and 2.3C

mostly by Lublin and Kielce.

60.3–97–3% and 79–100%.

ZielonaGóra (12).

(periods 2060–2079, 2080–2099).

exponential models for 16 localities were developed (Table 4).

four scenarios.

Figure 4. Effects of climate change on probability of the appearance of CPB second generation.

of the highest threatened localities were noticed. ZielonaGóra and Wrocław were replaced mostly by Lublin and Kielce.

Of the four scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5), three (RCP4.5, RCP6.0 and RCP8.5) generated a significant increase in the probability of CPB second generation appearance at the end of the century. But, in the periods 2020–2039, 2040–2059 and 2060–2079, increases in the probability of the second generation pest occurrence were generated under all four scenarios.

For the end of the century, the highest probability of the appearance of the second generation of CPB (99.5–100%) was obtained under scenario RCP8.5, whereas the smallest (5.5–50.3) was under RCP2.6. Scenarios RCP4.5 and RCP6.0 generated the following results, respectively: 60.3–97–3% and 79–100%.

Simulation under scenarios RCP2.6, RCP4.5 and RCP6.0 revealed that for the end of the century, the highest increase in probability (SGCPBP) were generated respectively for Kielce (42.3, 88.5, 92), Lublin (34, 84.8, 92) and Białystok (12.5, 70.3, 86.3), whereas under scenario RCP8.5, these were for Gdańsk (99.5) Olsztyn (96.8) and Białystok (94). The smallest increase in SGCPBP obtained in simulations under scenarios RCP4.5, RCP6.0 and RCP8.5 were, respectively, revealed for Opole (35.3, 37.3, 38), Wrocław (41.5, 52, 53.8) and ZielonaGóra (34.3, 52, 55.3). In simulations under scenario RCP2.6, besides an increase in SGCPBP, a decrease was also achieved. The highest decrease was generated for Opole (27.5), Wrocław (17.8) and ZielonaGóra (12).

Simulations under scenario RCP2.6 produced 29 results with SGCPBP lower than 50%, 34 with SGCPBP ranging from 50 to 75% and one higher than 75%. The use of scenarios RCP4.5 and RCP6.0 resulted, respectively, in two and three results with SGCPBP lower than 50%, 18 and 17 results with SGCPBP ranged from 50 to 75% and 43 results higher than 75%. Simulations under RCP8.5 produced 10 results with SGCPBP ranging from 50 to 75% and 54 results higher than 75%.

Simulations also showed that the average number of days needed for completion of the second generation was 51–54 for RCP2.6, 47–52 for RCP4.5, 44–51 for RCP6.0 and 39–51 for RCP8.5.

Simulations on real data sets revealed no possibility of the third generation of CPB appearance at all analyzed localities, except for Opole (Figure 5). Introduction of transformed data did not change the results very much, except for scenarios RCP6.0 (period 2080–2099) and RCP8.5 (periods 2060–2079, 2080–2099).

The results of the simulations were also used to estimate the minimum temperature increase for 1986–2005 that ensure the emergence of the second generation of CPB. To achieve that aim, exponential models for 16 localities were developed (Table 4).

With a 95% probability, 1C temperature rise at Opole guaranteed the appearance of CPB second generation (Figure 6). At Katowice, Rzeszów, Szczecin and Wrocław, temperatures ought to increase by 1.6C. At Kraków and Toruń, 1.7 and 1.8C temperature rises, respectively, led to the appearance of the pest second generation. At Łódź, Poznan, Warszawa and ZielonaGóra, temperatures ought to rise by 1.9C. A temperature increase of 2.1 and 2.3C

Figure 4. Effects of climate change on probability of the appearance of CPB second generation.

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Table 4. Parameters of the exponential models [SGCPBP = a + exp.(b + c � T)] expressing the influence of temperature

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Figure 6. Effects of temperature increase on probability of the appearance of the second generation of CPB.

increase (Ti) on probability of the appearance of the second generation of CPB (SGCPBP).

Figure 5. Effects of climate change on probability of the appearance of CPB third generation.

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Table 4. Parameters of the exponential models [SGCPBP = a + exp.(b + c � T)] expressing the influence of temperature increase (Ti) on probability of the appearance of the second generation of CPB (SGCPBP).

Figure 6. Effects of temperature increase on probability of the appearance of the second generation of CPB.

Figure 5. Effects of climate change on probability of the appearance of CPB third generation.

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generated the appearance of the second pest generation at Lublin and Białystok, respectively. At Kielce and Olsztyn, temperature rises of 2.5 and 3C were needed to trigger the appearance of the second generation, whereas at Gdańsk, the probability of the appearance of the second generation did not exceed 93%.

of the pest development under scenarios RCP4.5, RCP6 and RCP8.5 showed that the second generation usually developed faster than the first generation. We decided not to compare the development time of the generations obtained in simulations on real data and under scenario

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As expected, the lowest values for SGCPBP were generated under scenario RCP2.6, whereas the highest were noted under RCP8.5. The SGCPBP values produced by the former are usually lower than 75%. That is why we did not use it to specify the regions to be threatened by CPB in the future. The values for SGCPBP produced by RCP8.5 are usually higher than 75%, but there are almost no differences in this analyzed parameter between localities, so this scenario was also not used for specification of the regions at most risk from CPB in the future. On the other hand, scenarios RCP4.5 and RCP6 can be helpful in identifying regions at risk from CPB in the future. Both produced quite differential results, usually higher than 75%. Comparison of simulation results obtained under scenario RCP4.5 enables identification of the south-western region (Opole, Wrocław), the south-eastern (Rzeszów), eastern (Lublin) and southern parts of central Poland (Kielce), as being the most threatened by CPB in the future. Simulations under scenario RCP6.0 additionally included the south of Poland (Katowice) as one of the region most at risk of CPB.

Comparison of SGCPBP obtained in simulations on real and transformed data also enables identification of the regions vulnerable to higher changes in SGCPBP. Based on scenarios RCP2.6, RCP4.5 and RCP6.0, the south of central Poland (Kielce) and the eastern part of Poland (Lublin) should be included into that category. The predicted increase in SGCPBP obtained in simulations under these scenarios for these two localities distinctly differs from the rest. According to simulation results from scenario RCP8.5, it appears that besides these two localities, another three (Białystok, Gdańsk and Olsztyn) are more vulnerable to increase

Considering the results of the study dealing with the risk of CPB third generation appearance, it seems that the south-western region (Opole), eastern region (Lublin) and southern part of central Poland (Kielce) may face the most problems caused by increased numbers of CPB generations. Results obtained in the present study are also in line with predictions of CPB development under expected climate change in the Czech Republic presented by Kocmankowa et al. [28], who used a simulation performed with the use of the CLIMEX model to show a growing danger of an increase in the number of CPB generations. This is in line with the predictions by Menéndez [29], Das et al. [30] and Sangle et al. [31], who expected greater numbers of generation of so-called "stop and go" insects following climate change. Kocmankowa et al. [28] also predicted a widening of the area of CPB occurrence and a shifting of the pest to higher altitudes. The significant increase in SGCPBP in the Małopolska upland located in the southern part of central Poland (Kielce) showed in our study confirms the findings of Kocmankowa et al. [28]. Similar results were also presented by Pulatov et al. [32], who analyzed the effect of climate change on the potential spread of the Colorado potato beetle in Scandinavia. They showed a substantial increase in the frequency of years in which the temperature requirement for development of one generation was fulfilled. Additionally, they indicated regions where

RCP2.6 because of the excessive number of SGCPBP results lower than 50%.

in SGCPBP than other localities.

two generations per year may occur more often.

With a probability of 99%, a temperature rise of 1.4C generated the second generation of CPB at Opole. At Katowice and Rzeszów, temperature had to increase by 1.9C. At Kraków, Szczecin and Wrocław, a 2C temperature rise triggered the appearance of the pest second generation. At ZielonaGóra and Łódź temperature had to rise by 2.2C. A temperature increase of 2.3, 2.4 and 2.5C generated the appearance of the second pest generation at Poznań, Toruń and Lublin. At Kielce and Białystok, temperature rises of 2.9 and 3.2C were needed to trigger the appearance of the second generation, whereas for Gdańsk and Olsztyn, the models did not generate the appearance of the second generation with a probability of 99%.
