Ecosystem services impacted by agriculture are of fundamental importance for human life, but only some of them are valued by the market and affect the way natural resources are managed. Other services are currently being appreciated and rewarded by agricultural policy as an instrument for the management of natural resources in agriculture. Our research results indicate that the assessment of the impact of agricultural production on selected ecosystem services is a challenging task that requires access to many sources of information. The complexity of the problem is evidenced by the remarkably high variability of the level of agricultural production as well as the diversification and development of the natural landscape within the territory of Poland.
3.1. Variability of the Agricultural Productivity Factors and KPIs of ESs for Poland
The agricultural productivity factors indicate their large spatial diversity in particular territorial units of Poland, which is evident from the values of the coefficient of variation (CV). The greatest variability expressed by CV = 106.9% was observed for factor F.4—the share of ecological land in the area of agricultural land (
Table 3). This variability of agricultural production can be explained by the fact that Polish agriculture shows significant regional differences, resulting from natural, economic, organizational, infrastructural, and socio-cultural conditions, as well as historical conditions (partitions). The level of agricultural development is conditioned by the general level of economic development of the country and the region. On the other hand, the level and structure of production factor resources in the region define and determine the structure of agricultural production. The actual production volume in relation to potential possibilities is a measure of the use of agricultural production space [
31,
32]. On the other hand, the least spatial differentiation (CV = 7.3%) was obtained for the share of cereal crops in the sowing structure (F.5). It is worth emphasizing that the mean value of the factor was very high in all voivodships, with an average of 69.6%, and a maximum amounted to 76.7% in Śląskie voivodship (unit 13) (
Table S1, Supplementary Materials). Kapusta [
33] explains that cereals are an important component of Poland’s agriculture and economy since they play an important role in shaping food security in the country. They are cultivated by 89.5% of farms, and their share in the crop structure has always been high, oscillating on the level of almost ¾ of the crop area.
Similar to the agricultural productivity factors, all of the indicators we selected for the analysis show great diversification between individual territory units of the country, which confirm the range of the values presented in
Table 4. From the group of indicators evaluating the level of production ecosystem services, livestock density per 100 ha of agricultural land (P.2) shows the greatest differentiation within all the voivodeships. Changes in the concentration of animal production were analyzed by Rokicki et al. [
34]. The authors found out, that in Poland in the years 2005–2019, changes of this indicator were strongly associated to Poland’s entrance into the market of European Union. From that moment, milk, meat, and egg producers were subjected to many new regulations. The new regulations resulted in an increase in the specialization of farms, because of which the stock of animals increased significantly in certain voivodeships. These changes caused a strong diversification of the level of animal production between voivodeships. The most agriculturally developed Mazowieckie and Wielkopolskie voivodeships became the units with the highest concentration of animal production (units 7 and 5 in
Figure 1). On the other hand, the Podlaskie voivodship (unit 8) was strongly specialized in milk production. The concentration of other types of animal production such as live cattle and eggs was similar as for the population.
In the category of environmental services, the greatest variability was found in the gross nitrogen balance per 1 ha of agricultural land (indicator E.4) and in air quality assessment indicators (indicators E.6 and E.7). Research carried out in 2017 [
35] pointed out that the diversity of nitrogen management in Polish agriculture was so large that the level of nitrogen consumption in mineral fertilizers between voivodeships often differed by nearly three times. To a large extent, this is a consequence of the diversified area structure and the organizational and economic level of farms in Poland. The processes of polarization taking place in Polish agriculture, e.g., agrarian structures, the intensity of agricultural production, visible also in the height of regional balances of nitrogen balances, indicate the deepening of the existing diversification [
35]. Regarding air pollution, the main source of it is considered to be low emissions caused by combustion processes in households. This is due to the low quality of fuels, most often waste (brown coal, fine coal), and outdated heating systems used to heat buildings [
36]. Additionally, it is facilitated by the process of incineration of municipal waste. Research by Tomal [
37] showed that the type of area may affect the concentration of PM10 pollutants in the air. The greatest pollution occurs in cities, while it is much lower in the non-urban area. The suburbs were characterized by moderate levels of PM10 pollutants in the air.
When considering the group of cultural KPIs, the most diverse indicator was C.3, which concerned the area of nature reserves per 1000 inhabitants of the voivodship. In Poland, 60.1% of the country’s area is not covered by nature protection. The average distance in these areas to the nearest protected area is 3.3 km. These data indicate a high density of the network of protected areas, as well as their relatively large fragmentation. Previous research showed that the maximum distance from any type of protected area in Poland was less than 20.1 km [
38]. This value occurred in Lubelskie voivodeship (unit 4). The lowest maximum distance of 8.6 km was noted in the Warmińsko-mazurskie (unit 3), while at the same time, the average distance for this voivodship was only 1.6 km. The spatial differentiation of KPI indicators in individual territorial units in Poland is presented in
Table S2 in Supplementary Materials.
3.2. Assessment of the Impact of the Agricultural Production Factors on Indicators of ESs
The linear regression analysis revealed that some of the agricultural productivity factors had a significant impact on shaping selected indicators assessing the level of ESs (
Table 5). Significant interdependences were found in 12 out of 32 analyzed production services, with 7 at the level of
p = 0.01. The strongest relationship (r = 0.81) occurred between the yield of cereal grains (P.1), which quantitatively expresses the potential of current crop production, and the agricultural production space suitability (F.1). The F.1 factor covers the quality of individual elements of the habitat, such as soil quality and suitability, soil water conditions, relief, and agro-climate. In addition, Harasim [
26] in his research confirmed a significant dependence (
p = 0.05) of the yield of cereal grains and the entire plant production on the index of agricultural production space suitability. Our outcomes are supported by several research results [
39,
40,
41], which proved that crop yields were the most reliable estimates for agricultural land evaluation and suitability for crop production. On the other hand, the results of studies conducted in Canada indicated that cereal crops, such as barley, oats, and mixed grains, were more tolerant to soil–climate–landscape variations and could be grown in many regions of the country, while non-grain crops were more sensitive to environmental factors [
42].
The increase in the yield of cereal grains is also significantly influenced by the rise of the level of nitrogen fertilization (r = 0.68) as well as the reduced share of permanent grassland in the agricultural area (r = −0.53). According to Podolska [
43], nitrogen fertilization was one of the most important factors affecting both the yield and the parameters of the technological value of winter wheat grain. Higher doses of nitrogen fertilization had a positive effect on all elements of the yield structure, increasing the number of ears, ear fertility, and grain abundance. It was also confirmed by the results of numerous studies, which indicate that long-term N fertilization can contribute to relieving the global food crisis by not only enhancing cereal yield, but also promoting its stability [
44,
45]. Mohammed et al. [
46] also observed the beneficial effect of an increase in fertilizer N rates in wheat grain yield and protein content. However, the authors noted that there were large differences in yields at different locations with the same N application rate. Similar observations were reported by Walsh et al. [
47]. When analyzing the impact of the agricultural productivity factors (F) on the production indicators (P), it was found that the investment subsidies under the Rural Development Program (F.7), as well as the percentage share of agricultural land in the total area (F.2), significantly influence the level of stocking density (P.2 r = 0.80 and r = 0.66, respectively), milk yield (P.3 r = 0.64 and r = 0.78, respectively), and the value of commodity production (P.4 r = 0.58 and r = 0.56, respectively). Couillard and Turkina [
48] examined the effects of Free Trade Agreements (FTAs) and subsidies under the Common Agricultural Policy of the European Union on dairy industry competitiveness. The authors found that the effects of FTAs on dairy industry competitiveness depended on the agreement type and that subsidies improved competitiveness. Zalewski et al. [
49] evaluated the efficiency of the use of public financial support investment activities in selected dairy farms in Poland. The authors surveyed over two-hundred milk production farms that were beneficent of European Union (EU) in the years 2011–2014. The results of the study showed that the external fundings enabled the farmers the investments, which improved their economic situation.
Kondratowicz-Pozorska [
50] obtained contrary results. It was indicated that there were difficulties in finding significant relationships between the number of subsidies for agriculture and rural development and the amount and value of production due to the multi-purpose nature of the aid provided to farmers. This aid is not mainly targeted to obtain high levels of production, but first and foremost it is aimed to maintain and protect the quality and benefits of rural areas. Selected dependences between agricultural productivity factors in Poland and KPIs of production/provisioning ecosystem services are presented in
Figure 2 along with linear regression equations.
Regarding indicators evaluating environmental ecosystem services, a significant interaction between some of them and agricultural production factors was found (
Table 6). Significant dependencies were found in 16 out of 56 analyzed combinations (with 12 at
p = 0.01). Soil quality (E.1), expressed as the share of soils with pH > 5.5, depended significantly on the index of agricultural production space suitability (F.1 r = 0.64) and the level of nitrogen fertilization (F.6 r = 0.72). It was proved that in territory units, where the level of nitrogen fertilization per 1 ha of agricultural land is greater, the share of soils with favorable pH > 5.5 is also greater (
Figure 3A). According to the study by Ochal et al. [
51], soil acidification remained a major barrier to plant production and posed a threat to the environment. Nitrogen fertilizers contributed to the increase in acidification, however, in the territory units where the level of nitrogen use is greater than in the others, more calcium fertilizers are also used [
52,
53,
54,
55,
56]. Dashuan Tian [
57] found that depending on ecosystem types, N fertilizer rate and form, and testing durations the soil pH varied. It decreased mostly in grassland. Higher risk of soil acidification was shown in the case of use of urea and NH
4NO
3 compared to the NH
4 form.
The gross nitrogen balance (E.4), which is an important agri-environmental indicator, correlated positively and at a significant level with three agricultural productivity factors: mainly with the level of investment subsidies (F.7 r = 0.86), the share of agricultural land in the total area (F.2 r = 0.67), and the level of nitrogen fertilization (F.6 r = 0.66) (
Figure 3B). According to Kopiński [
58], the greatest balances of nitrogen are found in countries, or in Polish regions, in which the agricultural production is very intensive. Research on the effect of agri-environment schemes (2007–2014) on groundwater quality in Bavaria, Germany [
59], showed that agri-environment schemes (AESs), as a part of the CAP, can be effective in reducing nitrate levels in grassland. However, organic farming and the cultural landscape showed no significant effect on groundwater quality. It is noteworthy that cereal crops and forage showed a positive effect on groundwater quality. High levels of nitrates in the groundwater were concentrated in cropland areas rather than grasslands.
Another significant positive correlation was found between the level of environmental subsidies (F.8) and the increase in forestation (E.5 r = 0.68) (
Figure 3C). The results of research carried out in five countries of the European Union showed that thanks to the flexibility that the CAP gives countries to adapt their subsidy programs to specific national needs, the European Agricultural Fund for Rural Development and equivalent national subsidies have indeed been used in a wide range of activities [
60]. Due to the diverse needs of forestry and the functions performed by forest areas, subsidized investments were also varied. Their goals were oriented, e.g., on improving machinery resources, but also on increasing the ecological value of forests. As the authors pointed out, the countries’ current subsidy systems focused on different forest policy goals. Comparison of results from the countries surveyed was hampered by inconsistencies and many inaccuracies in the documentation of the distribution of funds. This shows that to increase the effectiveness of subsidy schemes and achieve the objectives of European forest area policy, it is crucial to understand and unify the current distribution of subsidies.
Air quality expressed by two indicators (E.6 and E.7) depended on two agricultural productivity factors: the share of cereals in the sowing structure (F.5 r = 0.86 and r = 0.81, respectively) and the share of ecological land in the area of agricultural land (F.4 r = −0.60 and r = −0.66, respectively). Inferior air quality concerned territory units characterized by an increased share of cereals in the sowing structure (F.5) (
Figure 3D) and a smaller share of ecological lands (F.4). These are probably indirect relationships since, according to the analysis of Parlińska and Pomiechowski [
61], the main source of air pollution with the PM10 dust is considered to be low emissions, which are caused by combustion processes in households. The population density in rural areas, and thus also the number of small farms, is the highest in the southern part of Poland in the territory units 13, 15, and 16 (Śląskie, Małopolskie, and Podkarpackie voivodeships), where the share of cereals in the sowing structure is the largest. On the other hand, in voivodships where the population density in rural areas is the lowest, such as in voivodeships 1, 3, and 8 (West Pomeranian, Warmińsko-mazurskie, and Podlaskie), the share of cereals in the sowing structure is also the lowest. Łowicki [
62] stated that landscape indicators can be useful for generating new sources of information to explain the presence of PM in the atmospheric air. The author emphasized that any changes in the landscape should consider green areas that function as a pollution filter. Planning of all investments should be closely related to the design of such areas. As a result, by providing an entire range of ecosystem services (regulatory and cultural), it is possible to ensure better air quality and increase the quality of life of the inhabitants. Lin and Chen [
63] analyzed the effect of landscape patterns on the concentration of particulate matter in the atmosphere in Fujian Province, China. The authors confirmed that forest areas had a substantial impact on PM10 concentrations in spring and summer. However, in the autumn–winter period, air quality depended significantly on built-up areas. Huang [
64] proved that the presence of pollutants in the atmospheric air, e.g., PM2.5 and PM10, significantly depends on the share of impermeable surfaces and arable land and this relationship is positive. However, in the case of the share of wetland, water reservoirs, and forests, this correlation is negative. The author stated that these relations do not depend on the seasons. The strength of the correlation between the forms of land cover and the state of the air may vary slightly during the entire year.
Cultural ecoservices CESs enable direct, intellectual, and identity interactions with an animate nature, including nature constituting an element of natural heritage. An even more utilitarian type of cultural ecosystem service is the opportunity for recreation, including tourism, aesthetics, and providing inspirational, educational, spiritual, and religious provisions. Specific benefits include the chance of taking landscape trips, visiting places of worship, etc.
The impact of agricultural productivity factors on the level of these services was limited. Only 11 out of 40 analyzed correlations were found to be significant (with 5 of them at
p = 0.01) (
Table 7). A positive association was found between the share of ecological land (F.4) and all CESs except C2 (the correlation coefficients for C.1, C.3, C.4, and C.5 surpassed r = 0.57), as well as for permanent grassland in the area of agricultural land (F.3) and C.2 and C.3 services (r = 0.54 and 0.51, respectively). The share of cereals in the sowing structure (F.5.) had a negative impact on the analyzed indicators C.1, C.2, C.3, and C.5, except C4 (the correlation coefficients surpassed r = −0.57). Moreover, a positive correlation between the level of environmental subsidies (F.8) and the number of nature monuments (C.1 r = 0.53) was found. Selected relationships between agricultural productivity factors in Poland and indicators of cultural ecosystem services, along with linear regression equations, are shown in
Figure 4. The lack of a larger number of unambiguous correlations is primarily explained by the difficult valuation of the potential of ecosystems to provide cultural services. Direct indicators, which are sometimes difficult to calculate, or assess subjectively by an expert, are most often used for this purpose.
Rasmusen et al. [
65] found that intensive agricultural production is rarely compatible with the production of positive cultural ecosystem services and well-being. Auer et al. [
66] confirmed that agriculture in Balcarce County has significantly modified the rural landscape over the past two decades. As a result of those changes, the supply of cultural ecosystem services was limited, and this affected intangible assets and social activities, causing the risk of their discontinuity in the future. The negative impact of agricultural activity on cultural ecosystem services is manifested, among others, by the risk of losing the cultural identity characteristic for certain habitats (such as cultural and spiritual practices, as well as recreational, tourist, educational, ecological, and technological potential [
67]). Wang et al. [
68] argued that human controlled rewilding can be an important alternative to afforestation of degraded agricultural land. The main beneficiaries of cultural ecosystems are residents and the tourism industry, although landscape managers can indirectly benefit from the interaction between cultural and other activities. An example of such cooperation is Tuscany, where tourism has significantly increased the demand for regional agricultural products [
69]. Moreover, an increase in agri-tourism forces the improvement of infrastructure, which is beneficial for the local community. The development of suburban areas is a good example of positive changes in agricultural landscapes and benefits for the economy of the entire region. Additionally, Flood et al. [
70] showed that areas such as peatlands are important for building social bonds. The authors emphasized historical, educational, and health aspects of such areas, which is crucial for creating social and ecological potential.
From the point of view of decision-makers, the evaluation of the impact of the Rural Development Policy (RDP) tools on the development of ecosystems is an important instrument for planning diverse activities related to agriculture and environmental protection. It can help to identify the most satisfactory agricultural practices, as well as select synergistic actions that will help achieve an effective and sustainable response to climate change. Successful management of the multifunctionality of agriculture is also key to protecting biodiversity and ensuring access to various ecosystem services. Evaluating the impact of RDP tools can help determine what farming practices are most beneficial for distinct types of ecosystems and what actions can help protect the environment and deliver ecosystem services, which has been already confirmed in other studies [
71,
72,
73,
74,
75].
The future perspective of our research is the development of a module within the AGRICORE tool for modeling agricultural structures surrounding farmers (markets and land) and their context (environmental and climate impacts, socio-economic impacts (rural integration), ecosystem services delivery, and political environment) in Poland. The module of ES elaborated based on the available data will allow for the development of a module for the ABM model that employs the desired environmental parameters to provide different assessments of the impact of selected agricultural productivity factors and ecosystem services on the economic farm status. Data from ABM on agricultural production in a given area will allow for the modeling of predicted changes in the state of the environment. One of the goals for the future is to find ES assessment methods that would integrate economic and social goals with environmental goals. On the other hand, finding the most satisfactory solutions for individual stakeholders and their different interests in the development of ES can be a challenge both in the spatial context and in terms of environmental conditions and economic interests, because they can often conflict with various stakeholders due to their different needs and preferences. Consequently, the future goals are not only to expand the research by taking into account the scale and complexity of the studies, but also to engage economists and sociologists to find the answer how certain ES preferences influence the processes of making decisions at different levels, the individual and the public, and how to translate the knowledge of ESs on market economy to indicate the current versus future costs and benefits of ESs in unified units.