Priority services from nature and perceptions of national parks
When asked for choosing up to five most important benefits from nature, respondents tended to select mostly those of material character (52,8 % of all choices), i.e. provisioning services (Tab. 2). Drinking water, wood for heating purposes, harvesting plants and animals built up to nearly 40% of all choices. The rest was divided fairly equally between cultural (24,7%) and regulatory services (22,5%).
Table 2 The summary of chosen priority services from nature (all 5 choices summed up)
|
Count
|
% of total
|
% cumulated
|
Sourcing drinking water (P)
|
345
|
13,6
|
13,6
|
Sourcing wood for heating purposes (P)
|
252
|
9,9
|
23,5
|
Harvesting plants (P)
|
213
|
8,4
|
31,9
|
Animal farming (P)
|
195
|
7,7
|
39,5
|
Landscape values (C)
|
189
|
7,4
|
47,0
|
Picking up wild mushroom/sherbs/berries (P)
|
182
|
7,2
|
54,1
|
Puryfing water/air (R)
|
159
|
6,3
|
60,4
|
Flood and drought protection (R)
|
144
|
5,7
|
66,0
|
Practising sport/tourism/recreation (C)
|
124
|
4,9
|
70,9
|
Habitat of wild pollinators (R)
|
123
|
4,8
|
75,7
|
Spiritual or religous values (C)
|
91
|
3,6
|
79,3
|
Ecological education (C)
|
76
|
3,0
|
82,3
|
Mitigating climate extremes (R)
|
67
|
2,6
|
84,9
|
Noise protection (R)
|
64
|
2,5
|
87,5
|
Sourcing water for farming/industrial purposes (P)
|
61
|
2,4
|
89,9
|
Cultural heritage (C)
|
56
|
2,2
|
92,1
|
Sourcing wood for non-heating purposes (P)
|
53
|
2,1
|
94,1
|
Inherent value/value of being (C)
|
51
|
2,0
|
96,1
|
Scientific research (C)
|
40
|
1,6
|
97,7
|
Sourcing wild animals and derivatives (P)
|
27
|
1,1
|
98,8
|
Erosion control (R)
|
16
|
0,6
|
99,4
|
Extracting clay/gravel/minerals (P)
|
12
|
0,5
|
99,9
|
Other
|
3
|
0,1
|
100,0
|
Total
|
2543
|
100,0
|
|
Notes: P – provisioning, C – cultural, R – regulatory ecosystem services.
The priorities regarding benefits from nature significantly differed among respondents with different synthetic score representing the “approval of national parks” (Chi2 = 22.2879, p < .001). The respondents who were in general positive towards national parks valued mainly provisional ecosystem services (48% of all choices) while cultural (28%) and regulatory (24%) services played less important role for them (Fig. 2).
The respondents who had in general negative attitude towards national parks prioritized provisional services even more (57% of all choices), followed by regulatory (23%) and cultural (21%) services (Fig.3).
Priority services from nature and perceptions of Turnicki National Park (TuNP)
Share of prioritized provisional, cultural and regulatory services significantly varied (Chi2 = 24.9864, p < .001) between three groups of respondents with different attitudes (negative/neutral/positive) towards TuNP (Annex No 3). Nevertheless, the respondents seemed to value provisional ecosystem services most regardless of their attitude towards creation of the park (Annexes No 4-6).
We found significant differences (Kruskal Wallis test H = 92.521; p<0.001) in general approval of parks between respondents’ selection of key benefits. We revealed that respondents who scored relatively low in terms of approval of national parks were choosing sourcing wild living animals and sourcing wood for non-heating and heating purposes as priority compared to most of other benefits (Fig. 4). On the contrary, respondents scoring relatively highly in terms of approval of national parks were predominantly choosing scientific research, habitat of wild pollinators and landscape values as key benefits.
Significant differences (Kruskal Wallis test H = 43, 373; p=0,004) were found in approval of TuNP between respondents choosing particular key benefits. The respondents who chose sourcing wood for non-heating purposes as key benefit scored significantly lower in terms of approval of TuNP than respondents choosing habitat for wild pollinators and practicing sport/tourism/recreation (Fig. 5).
General opinions on national parks (NPs)
The respondents presented a fairly balanced perspectives over various roles of NPs, with no extreme opinions over any statements (Fig. 6). Most of the respondents (65.6%) agreed that national parks prevent the excessive exploitation of the environment. At the same time, 65.8% of respondents indicated difficulties in using the forest caused by the presence of national parks. More than half of the respondents (61.2 %) agreed that national parks protect heritage of citizens while, 58,3% believed that they serve to interest of only a fraction of society. Quite on the contrary 51% did not agree that existence of national parks is no longer needed.
For nearly all the items (except the statement that national parks protect against excessive use of environment) we found statistically significant differences in responses between respondents from individual municipalities. In multiple pairwise comparisons, respondents from the Fredropol municipality showed greater support than respondents from the Bircza and Ustrzyki Dolne municipalities for statements that national parks: may stimulate local development (p = 0.003; 0.028), protect heritage of citizens (p = 0.007; 0.024) and that living within a NP may be a reason to be proud (p <0.001). On the other hand, respondents from the Fredropol municipality showed significantly lower support than respondents from other municipalities for statements that NPs serve to interests of only a fraction of society (p = 0.002; p <0.001) and that NPs may be replaced by other forms of nature protection (p = 0.003; p <0.001). Respondents from Bircza municipality showed greater support for the statement that NPs prevent local people from use of the forest (p <0.001) than the respondents from the Fredropol municipality, while the latter showed significantly greater support than respondents from both other municipalities for the statement that NPs hinder disposal of own property (p <0.001; p = 0.023).
Opinions on national parks (NPs) and planned Turnicki National Park (TuNP) across studied municipalities
There was a statistically significant (F = 14.912, p <0.001) differences between the three municipalities regarding the attitudes national parks. It should be noted though that the effect size of the examined factor was small (partial ŋ2 = 0.054). Post-hoc analysis (Tukey's test with correction for multiple comparisons) showed differences for the pair Fredropol-Bircza (p <0.001) and Fredropol-Ustrzyki Dolne (p <0.001), showing a more positive attitude of the inhabitants of the Fredropol municipality towards national parks (Fig.6).
From the total number (527) of respondents, 69,4% have heard of the planned TuNP and those were asked for expressing their attitude towards its creation. In general, respondents from all municipalities were rather skeptical towards the plans of establishing the park (Fig. 7): there were significant differences between municipalities (F = 5.881, p <0.003), while the effect size for the municipality variable turned out to be small (partial ŋ2 = 0.031). Respondents of Fredropol municipality showed more positive attitude towards this planned park then the other two municipalities (p <0.005 for Fredropol-Bircza and p <0.014 for Fredropol-Ustrzyki Dolne).
On average 28% of respondents had “neutral” opinion regarding the approval of the TuNP, with differences between particular municipalities, ranging from 25% (Bircza) to 32% (Ustrzyki Dolne) on average (Fig. 8).
The opinions on national parks and Turnicki National Park against socio-demographic and economic variables
The approval of NPs was weakly negatively correlated with the age of the respondents (Spearman's ρ = –0.155, p <0.001). With regard to the variable "number of years of living in the municipality", the strength of this negative correlation increased (ρ = –0.299, p <0.001). On the other hand, the higher level of education and the average monthly net income per person in a household had a slightly positive effect on support for NPs (ρ = 0.214 p <0.001, and ρ = 0.157 p = 0.002, respectively). However, no significant correlation was found between perceived role of parks and the number of people in a household, or respondents’ gender (t = 1.166; p = 0.244.) In relation to the occupational situation the results were inconclusive (Kruskall-Wallis test H = 9.506; p = 0.05; results of post hoc analysis in pairs - p> 0.05) (Tab.3).
Similarly to approvals of national parks in general, the positive attitude towards establishment of the TuNP was weakly negatively correlated with the age of the respondents (ρ = –0.104, p = 0.046) and the number of years of living in the municipality (ρ = –0, 244, p <0.001). The level of education was moderately positively correlated with the attitude towards TuNP (ρ = 0.296, p <0.001), as well as with the average monthly net income per person in a household (ρ = 0.176, p = 0.004). There was no correlation found between support for the establishment of TuPN and the number of people in the household, gender and the current professional situation. Additionally, there was a strong, positive correlation between the attitude towards the creation of the TuNP and the (positive) opinion on the current role of national parks (ρ = 0.705; p <0.001) (Tab. 3).
Table 3 Influence of socio-demographic and economic factors on support for national parks and planned Turnicki National Park
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)
Notes: Icons mark negative (red) and positive (green) correlations between the variables. Darker color marks strong correlation. A cross means there was no demonstrated statistically significant relationship between the variables. A question mark means an ambiguous result.
Type of activity versus general opinions on national parks and Turnicki National Park
Ownership of a farm was a significant factor which stayed in negative relationship with positive attitudes towards national parks, i.e. farm owners tended to be more skeptical about national parks in general. At the same time there was no relationship between farm ownership and attitude towards planned TuNP (Tab. 4). On the contrary, respondents related professionally to tourist sector had more positive attitude both to TuNP and parks in general. At the same time, respondents belonging to broadly perceived logging industry had negative attitude towards parks in general. Belonging to such industry was not, however, related to particular attitudes towards TuNP.
Table 4 Effect of type of activity on opinions about national parks
|
Do you have farm?
|
N
|
Mean
|
SD
|
Std. Error
|
t
|
df
|
Sig. (two tailed)
|
Approval of national parks
|
No
|
246
|
3,29
|
.92211
|
.05879
|
3.911
|
522.981
|
.000*
|
|
Yes
|
279
|
2,95
|
1.05240
|
.06301
|
|
|
|
Attitude towards Turnicki NP.
|
No
|
158
|
2,61
|
1.382
|
.110
|
1.958
|
364
|
.051
|
|
Yes
|
208
|
2,32
|
1.423
|
.099
|
|
|
|
|
Are your incomes related to tourism?
|
N
|
|
|
|
|
|
|
Approval of national parks
|
No
|
482
|
3,08
|
.99126
|
.04515
|
-2.059
|
523
|
.040*
|
|
Yes
|
43
|
3,41
|
1.13571
|
.17319
|
|
|
|
Attitude towards Turnicki NP.
|
No
|
332
|
2,39
|
1.390
|
.076
|
-2.175
|
364
|
.030*
|
|
Yes
|
34
|
2,94
|
1.536
|
.263
|
|
|
|
|
Are your incomes related to logging industry?
|
N
|
|
|
|
|
|
|
Approval of national parks
|
No
|
414
|
3,19
|
.99996
|
.04915
|
3.370
|
523
|
.001*
|
|
Yes
|
111
|
2,83
|
.98541
|
.09353
|
|
|
|
Attitude towards Turnicki NP.
|
No
|
277
|
2,52
|
1.418
|
.085
|
1.767
|
364
|
.078
|
|
Yes
|
89
|
2,21
|
1.369
|
.145
|
|
|
|
|
Perception of limitations and threats to benefits from nature, benefits and losses from creation of TuNP versus opinion on national parks and TuNP
Perceived current limitations to benefits drawn from nature showed no effect on opinions towards national parks and planned TuNP (Annex No 7). In turn the respondents who saw future threats to benefits from nature were more likely to approve the role of national parks (mean score of approval: 3.19 to 2.97). However, no such relation was found with regard to the attitude towards planned TuNP (Annex 5).
Majority of respondents perceived losses rather than benefits from the potential establishment of the park (Tab. 5). Those who saw benefits were prone to perceive national parks, including TuNP, in more accepting manner. In similar way perception of losses was correlated with more negative opinions on both the planned TuNP and national parks in general.
Table 5 Effect of perceived benefits and losses from the creation of Turnicki National Park on opinions of national parks
|
Can you see potential benefits from creation of TuNP?
|
N
|
Mean
|
SD
|
t
|
Sig. (two tailed)
|
Approval of national parks
|
No
|
264
|
2,65
|
0,89827
|
-11.230
|
0,000*
|
|
Yes
|
102
|
3,78
|
0,77474
|
|
|
Attitude towards TuNP
|
No
|
264
|
1,94
|
1,129
|
-13,399
|
0,000*
|
|
Yes
|
102
|
3,75
|
1,224
|
|
|
|
Can you see potential losses from creation of TuNP?
|
N
|
Mean
|
SD
|
t
|
Sig. (two tailed)
|
Approval of national parks
|
No
|
70
|
3,79
|
0,90778
|
8.324
|
0,000*
|
|
Yes
|
296
|
2,77
|
0,92382
|
|
|
Attitude towards TuNP
|
No
|
70
|
3,79
|
1,215
|
9,984
|
0,000*
|
|
Yes
|
296
|
2,13
|
1,260
|
|
|