Financial expenditure as a criterion for choosing the most appropriate method for ecological corridor implementationAbstract
To enhance landscape connectivity and mitigate the effects of forest fragmentation caused by urban expansion and human activities, ecological corridors (EC) have been proposed as a solution. This study evaluates the financial costs associated with land acquisition for the establishment of an EC between the Municipal Natural Park Biodiversity Corridors (PNMCBio) and the Ipanema National Forest (Flona Ipanema) using LSCorridors for EC modeling. Using land use and vegetation cover data as input, corridors were modeled based on four different resistance surfaces, which were generated in LSCorridors (pixel-based measure (PM), minimum (LMmin), average (LMavg), and maximum (LMmax) landscape measures. The models utilized a land use and vegetation cover resistance map from 2019. Additionally, an information plan was developed to assess the costs of land acquisition based on generic municipal maps. Among the LSCorridors methods, the PM approach resulted in 41.05% of the EC area being legally protected and yielded the lowest acquisition cost, totaling R$ (Brazilian real) 487,476.16. This proposed model can assist public managers in making informed decisions about EC proposals, thereby optimizing the allocation of public resources.
Key words
Connectivity; Financial cost; Expropriation; Multiple paths
INTRODUCTION
Intense land use driven by population growth has been leading to forest fragmentation and the destruction of habitats, especially in the state of São Paulo, which has the largest economy in Brazil and is home to approximately 45 million people (Pütz et al. 2011, SEADE 2021, Silva & Schwingel 2021).
Therefore, the establishment of protected areas (PA) is essential for preservation of natural resources, biodiversity and environmental services (Nery et al. 2024). According to the IUCN (International Union for Conservation of Nature), “A protected area is a clearly defined geographical space, recognized, dedicated and managed, through legal or other effective means, to achieve the long-term conservation of nature with associated ecosystem services and cultural values” (Dudley & Stolton 2008).
In this context, ecological corridors (EC) are important instruments for connecting the landscape and reversing the processes of forest fragmentation, especially in regions where there are PA, resulting from urban expansion and population growth, favoring the transition of fauna between forest fragments (Oliveira et al. 2024). So, it is crucial as they help mitigate the negative effects of forest fragmentation, facilitating gene flow between species and enhancing environmental resilience and balance (Saura & Torné 2009, Haddad et al. 2015, Santos et al. 2020).
Various methodologies, in conjunction with Geographic Information Systems (GIS), have been employed to propose corridors. While there is no consensus on the optimal algorithm to be used, the least-cost path (LCP) is widely adopted due to its ability to delineate an ideal path based on environmental factors that influence fauna movement (Guo & Liu 2017, Liang et al. 2018).
According to Almenar et al. (2019), who applied landscape ecology techniques to evaluate habitat loss, fragmentation, and ecological connectivity in Luxembourg, the LandScape Corridors software (LSCorridors) stands out by addressing certain limitations of other tools. LSCorridors can simulate multiple paths considering stochastic variations (such as edge effect, habitat quality, and species landscape perspective), ensuring that the simulations do not always rely on the same origin and destination points (Ribeiro et al. 2017).
According to Bhakti et al. (2021), who compared landscape permeability for birds in Ouro Preto (Minas Gerais, Brazil), LSCorridors, by modeling multiple ecological corridors, enable the identification of multiple paths that are more favorable for fauna passage, as studies demonstrate that the landscape is the most significant variable in species dispersion (Moraes et al. 2018, Diniz et al. 2020). In this regard, public planning and legislation for forest conservation and restoration are emphasized, especially in regions rich in biodiversity and heavily modified by human intervention, such as the Atlantic Forest biome.
Within this context, the Ipanema National Forest (Flona Ipanema in Portuguese) (Figure 1) was established on May 20, 1992, by Decree No. 530, to conserve one of the largest fragments of the Atlantic Forest in the interior of the State of São Paulo. The Federal Constitution recognizes the Atlantic Forest biome as a National Heritage (Brasil 1988, 1992, ICMBIO 2017).
The area of Flona Ipanema not only provides a refuge for biodiversity but also offers recreational opportunities for visitors through trails that allow them to observe the different ecosystems (Souza & Martos 2008, Toledo et al. 2024). As Souza (2014) states, it contributes to raising awareness in society about environmental issues.
Municipal conservation units (MCU), PA created through the municipal government, also play a significant role in the conservation of the Atlantic Forest (Grelle et al. 2021), as exemplified by the creation of the Municipal Biodiversity Corridors National Park (PNMCBio in Portuguese), which even received this name due to its objective of establishing corridors between PA, through Municipal Decree No. 19,424 on August 17, 2011. The PNMCBio is of fundamental importance for protecting the region’s typical fauna and flora (Mota Júnior et al. 2015).
Furthermore, the PNMCBio was strategically established to expand the permanent preservation areas (PPA) of the tributaries of the Sorocaba River, aiming to establish ecological corridors through the existing riparian forests (Sorocaba 2011, Mota Júnior et al. 2015). Measures such as the establishment of ecological corridors, the creation of conservation units, and the strengthening of territorial management are essential for biodiversity conservation (Grelle et al. 2021).
Therefore, to assist in public planning, the present study evaluated the cost of expropriation of private areas for the implementation of an ecological corridor between PNMCBio and Flona Ipanema. We applied four approaches using the LSCorridors software and the development of a cost information plan for expropriating the areas. This plan was used as one of the criteria for choosing the most appropriate method for the area.
MATERIALS AND METHODS
Study Area
The study area (Figure 1) is located in the municipalities of Araçoiaba da Serra, Boituva, Capela do Alto, Iperó, Porto Feliz, and Sorocaba in the interior of the State of São Paulo, covering an area of 406 km2. It encompasses the following conservation units: PNMCBio and Flona Ipanema. According to the Sistema Nacional de Unidades de Conservação (SNUC), Flona Ipanema is a sustainable use conservation unit, while PNMCBio is a full protection conservation unit (Brasil 2000).
The municipalities in the study area have a population of approximately 870,000 inhabitants, with 687,000 residing in the city of Sorocaba, which is considered the 32nd most populous city in Brazil and the 9th in the State of São Paulo (IBGE 2021).
The area is also part of the Sorocaba Metropolitan Region, established on May 8, 2014, by State Complementary Law No. 1,241. It comprises 27 municipalities with over 2.1 million inhabitants. The city of Sorocaba, the headquarters of the metropolitan region, stands out with a per capita GDP of R$ 52,169.13 for the year 2018 and a population density of 1,304.18 inhabitants/km2 (São Paulo 2014, IBGE 2021). Therefore, there are numerous challenges to sustainable development in the region, as the growth of Sorocaba is characterized by urban expansion and forest fragmentation.
Furthermore, according to SNUC, buffer zones with specific restrictions are planned for both conservation units to minimize negative impacts on protected areas, facilitate EC, and ensure the quality of water resources (Brasil 2000). However, the buffer zone of Flona Ipanema, with a radius of 10 km and covering a total area of 73,851 ha encompassing 11 municipalities, has a radius of fewer than 10 km near the municipality of Sorocaba due to the presence of urban areas (ICMBIO 2017).
Therefore, to guarantee environmental preservation and the population’s right to an ecologically balanced environment, as provided for in article 225 of the Federal Constitution of 1988, government strategies to support conservation units are necessary (Brasil 1988). Therefore, considering that the consolidation of the implementation of ecological corridors is the objective of the PNMCBio (Mota Júnior et al. 2015, Graciano-Silva et al. 2020), the creation of this park can be seen as a strategy of the municipal government to expand the conservation of biodiversity and natural resources.
Methodological procedure: development of thematic maps
To determine the optimal route for establishing an EC between PNMCBio and Flona Ipanema, the LSCorridors software was employed. LSCorridors is a freely available software that enables the simulation of ecological corridors for various species based on biodiversity response to landscape characteristics, utilizing the LCP approach and an algorithm that generates multiple paths in each run (Ribeiro et al. 2017).
The LCP method calculates the minimal cumulative cost at each point based on Euclidean distance, which, as noted by Teng et al. (2011), is considered the most effective model for proposing ecological corridors. Developed in Python, LSCorridors operates through a user-friendly Graphical User Interface (GUI) and relies on the Geographic Resources Analysis Support System (GRASS GIS) for data analysis and support.
LSCorridors allows simulating EC for different species considering the responses of biodiversity to landscape attributes, which according to Almenar et al. (2019) stands out for mitigating some limitations of other tools for EC model and is based on the lowest cost path and the multipath algorithm, which allows multiple ecological corridors to be generated in each simulation.
The LCP method calculates the minimal cumulative cost at each point based on Euclidean distance, which, as noted by Teng et al. (2011), is considered the most effective model for proposing ecological corridors. Developed in Python, LSCorridors operates through a user-friendly Graphical User Interface (GUI) and relies on the Geographic Resources Analysis Support System (GRASS GIS) for data analysis and support.
To perform the analysis, two input base maps are necessary: a resistance map representing land use and land cover (LULC), with assigned weights to different land use and vegetation classes. Lower values are assigned to classes conducive to wildlife movement, while higher values are assigned to unfavorable areas recognized as barriers to wildlife movement. Additionally, another map is employed to indicate the origin and destination of the EC, identifying the areas to be connected by the corridor and assigning them a unique identifier (Ribeiro et al. 2017, Almenar et al. 2019).
Of 100 total combinations, conducted using the four methods: PM, LMmin, LMmax, and LMavg, in each run the algorithm selects different origin and destination points to be connected, resulting in different starting and ending points, referred to as Source Target (ST) (Ribeiro et al. 2017, Diniz et al. 2021). For this study, the two conservation units were designated as the origin and destination points to be connected.
The LULC data used to develop the surface resistance map were extracted from the MapBiomas database for the year 2019. This dataset was derived from a representative mosaic of Landsat 8 satellite images with a spatial resolution of 30 m (MapBiomas 2021). Mapping land use is crucial for identifying areas that may impede or facilitate the presence and dispersal of fauna (Loro et al. 2016, Hong et al. 2017).
Using ArcGIS 10.6 software, the LULC classes were classified into the following categories based on MapBiomas (2021): agriculture, forest plantations, natural forest, urban infrastructure, pasture, and rivers and lakes. These classes were then rescaled, assigning a weight of 1 to natural forest areas, which are favorable for wildlife movement, and a weight of 100 to areas that are unfavorable for wildlife movements, such as agriculture, urban infrastructure, rivers, and lakes. Areas with intermediate favorability, such as forest plantations and pasture, were assigned a weight of 50, following the weights proposed by Louzada et al. (2012) and Oliveira et al. (2016). Furthermore, it was possible to observe that the method presents great sensitivity in the EC propositions, as presented by the authors.
LSCorridors can generate three additional resistance maps beyond the pixel measure (PM) approach, which assigns resistance values based on land cover types. These include the minimum landscape measure (LMmin), average landscape measure (LMavg), and maximum landscape measure (LMmax), which adjust the resistance of each pixel by considering the influence of surrounding pixels on species movement (Ribeiro et al. 2017). In this study, we adopted a generalist modeling approach to represent the movement of large mammals, avoiding excessive specificity and potential biases associated with species-specific habitat preferences.
Furthermore, according to Ribeiro et al. (2017), it is recommended to use PM, LMmin, and LMavg for modeling the movement of generalist species, while LMmax is suggested for specialist species as it generates more restricted routes based on a greater restriction of the raster image. Therefore, for this study, to consider potential routes for different species, all simulation methods were employed, similar to Almenar et al. (2019) who selected different species for their case study.
The software requires a variability parameter, which represents spatial stochasticity in the modeled corridors and the degree of noise added to the resistance map. Furthermore, according to Ribeiro et al. (2017), a higher variability parameter value results in higher values in the resistance surface pixels, generating a greater number of modeled ecological corridors, becoming less consistent presenting a greater number of routes. This can be used to assess alternative routes for species. For this study, a variability value of 2, the default value provided by the software, was chosen.
The scale data, representing the species’ perception of the landscape, was set to the default value of 100 m. This corresponds to a perception matrix of 3 x 3 pixels on the resistance surface. LSCorridors generates a raster file as output, which identifies the least-cost paths for each ST pair.
The frequency with which each pixel is selected in multiple runs is expressed in the Route Selection Frequency Index (RSFI). Pixels with high RSFI values indicate better potential routes for connecting each ST. After generating multiple EC between the conservation units using LSCorridors, the data were exported to ArcGIS 10.6 to select the path with the highest RSFI. The width of the EC was determined through buffer analysis, following the guidelines of Resolution No. 9 of the Conselho Nacional do Meio Ambiente (CONAMA), dated October 24, 1996, which sets a minimum width of 100 m.
In riparian areas, the resolution stipulates that the minimum width should be established on both sides of the water resource, resulting in a total width of 200 m. Therefore, considering that the proposed ecological corridors may pass through riparian zones, a width of 200 m was adopted.
Next, information regarding PPA and Legal Reserve (LR) in rural properties registered in the Rural Environmental Registry (RER) was obtained from Oliveira et al. (2022). The areas defined as PPA according to the Law on Protection of Native Vegetation (LPNV), commonly known as the “New Forest Code” (Brasil 2012), were obtained using the methodology proposed by Oliveira et al. (2022). The information layers, riparian zones and legal reserve in rural properties, were resampled to 30 m and combined with layers representing PPA and LR using map algebra tools.
To estimate the acquisition values of the areas for protection and implementation of the EC, which would assist public managers in decision-making and feasibility assessments, generic value charts, monetary values per square meter of land and construction of the municipality, for the municipalities of Araçoiaba da Serra, Boituva, Capela do Alto, Iperó, Porto Feliz, and Sorocaba were used as a base. A layer was created with the costs for acquiring the areas in Brazilian real per square meter (R$/m2), obtained through supervised analysis using Google Earth Pro. The values per square meter in each location of the municipality were considered (generic value charts).
The typology and category (commercial, rural, industrial or residential) of buildings were estimated using the Street View tool. When multiple typologies and categories were identified, the predominant or most expensive scenarios for acquisition were considered. For locations where identification was not possible using the generic value chart, the values of neighboring or adjacent properties were adopted, considering any typological differences.
Sampling points were demarcated with the expropriation values of the areas based on the property’s typology and land value. The Inverse Distance Squared (IDS) interpolation method, a deterministic method that considers the proximity of the sampling points, was then used. Each point has reduced local influence with increasing distance, as shown in Equation 1 (Silva et al. 2021).
Where: IQD is the interpolated variable; Xi represents the value of the variable at the ith neighboring location; di refers to the Euclidean distance between the ith neighboring point and the sampled point.
Later, the PPA and LR were subtracted from the obtained EC for the four methods of LSCorridors since these areas are already protected by law and do not need to be acquired by the government. In this way, it was determined which EC had the lowest expropriation cost. Then, a verification of the points with the highest conflict of use and/or barriers to implementation was carried out, such as urban infrastructure areas, to assess the agreement between the classifications performed in the GIS and the reference information observed in the field.
RESULTS
The modeled corridors obtained can be observed in Figure 2 and Table I. As depicted in Figure 2, LSCorridors enable the modeling of multiple EC utilizing the minimum cumulative cost (MCC) approaches by establishing various starting points within each ST.
Lengths of the proposed ecological corridors through the four available methods in LSCorridors.
Hence, the paths with the highest occurrence frequency in the simulations, corresponding to the paths with the highest RSFI values (shown as red paths), were selected. Subsequently, using the buffer tool in ArcGIS 10.6, the width of the obtained EC was delineated for each of the employed methods (Figure 3).
Regarding the LMmin and LMavg methods, which consider the influence of the landscape on generalist species that tend to move more easily across the landscape in search of resources (Ye et al. 2014), LMavg exhibited the highest coverage of existing natural forest in the modeled (41.37%). In contrast, the EC created by the LMmin method, like the one delineated by LMmax, is predominantly located in pastureland areas (50.11%).
The PM method displayed the longest distance for connecting the CU and a predominance in natural forest areas (49.68%), followed by pastureland (38.19%). The proposed EC is further away from the urban area of Sorocaba municipality and less susceptible to the effects of real estate speculation, anthropogenic pressure, and other impacts resulting from the presence of urban infrastructure, as shown in Table II.
Land use and vegetation cover classes of the proposed ecological corridors through LSCorridors.
Subsequently, after excluding the legally protected areas (PPA and LR), which should be conserved and do not require government expropriation for the implementation of EC, the cost of acquiring the proposed corridor was determined. The maps of PPA and LR used in this study are available in Oliveira et al. (2024). This was achieved by interpolating from 2200 points using the deterministic IDS method (Inverse Distance Squared – Equation 1) (Supplementary Documentation) with the expropriation values obtained through the generic value maps of the municipalities of Araçoiaba da Serra, Boituva, Capela do Alto, Iperó, Porto Feliz, and Sorocaba, as shown in Figure 4.
Cost of acquiring the areas to compose the proposed ecological corridors in each available method in LSCorridors.
The EC created using the PM method necessitated an expropriation area of 2.30 km² (59% of the EC), while the LMmin, LMmax. and LMavg methods required successive expropriation areas of 2.71 km² (77%), 2.08 km² (89%), and 1.93 km² (79%), respectively.
Therefore, for the four methods illustrated in Figure 4, the cost of acquiring each EC generated by LSCorridors was R$ 487,476.16 for MP, R$ 496,948.83 for LMmin, R$ 593,431.00 for LMavg, and R$ 692,299.48 for LMmax.
The PM method had 41% of the EC already legally protected, yielding the best result among the four methods and consequently incurring the lowest cost for its development. It mainly consisted of natural forest areas (49.68%) and pastureland (38.19%). Furthermore, urban infrastructure areas, which have higher acquisition values and pose greater complexities for expropriation, constituted only 0.27% of the total EC area.
To evaluate the agreement between the classifications performed by LSCorridors and the reference information, areas with the highest and lowest expropriation costs were selected for on-site verification, as displayed in Figure 5a, Figure 5b, and Figure 5c.
Selection of areas for verifying the agreement between the classifications performed by LSCorridors.
Upon conducting on-site evaluations, as illustrated in Figure 6, a concordance was observed between the classifications performed in the GIS and the reference information. In the trajectory situated in Iperó (Figure 6a), the area is characterized by orchards and low population density in its vicinity.
On-site observations to verify the agreement between the classifications performed in the GIS and the reference information.
In the trajectories located in Sorocaba, it was observed that the region is mainly comprised of small farms (Figure 6b) and residential condominiums on the outskirts of the urban area. Additionally, due to the proximity to highways, there are obstacles to fauna movement and an increased risk of accidents (Figure 6c).
DISCUSSION
The RSFI indicates the frequency at which each pixel was considered in the simulations. EC with lower RSFI values (depicted as yellow paths) represent areas less favorable for species movement, primarily due to their vicinity to urban areas (Ribeiro et al. 2017).
Unlike Linkage Mapper, which expands the least-cost paths to lower-cost corridors based on the values of adjacent pixels (Gallo et al. 2019), in this study we used a uniform-width buffer for the delimitation of ecological corridors. This approach was adopted based on CONAMA Resolution No. 9 of 1996, which defines the width of the EC at 10% of its total length, with a minimum limit of 100 meters. The standardization of the width of the corridors aims to ensure the functional connectivity of the landscape and facilitate the application of normative guidelines for its implementation.
Diniz et al. (2021) also found a prevalence of pastureland surrounding forest fragments in another region of the Atlantic Forest, highlighting that more sensitive species may face dispersal hindrances. In such cases, the authors emphasize the importance of restoration initiatives to ensure their movement.
As depicted in Table II, the percentage of agricultural and urban areas was low in the ECs, regardless of which method was employed. This is due to the higher weight assigned to these land cover and land use classes, as they are recognized as barriers to fauna movement and less favorable for inclusion in EC (Louzada et al. 2012, Oliveira et al. 2016). It can be inferred that analysis methods have a significant impact on the trajectory of the EC (Bhakti et al. 2021), as the landscape plays a crucial role in species dispersal (Moraes et al. 2018).
Figure 5a reveals that the areas with the lowest acquisition cost are situated near the boundaries of the Ipanema National Forest (Flona), in the municipality of Iperó, which exhibits lower urban density. According to the estimate by the Instituto Brasileiro de Geografia e Estatística (IBGE), the municipality has a population of 38,771 (IBGE 2021).
Conversely, the trajectory of the EC located in the municipality of Sorocaba, as observed in Figures 5b and 5c, incurs the highest expropriation cost, reflecting the population density of the municipality, as Sorocaba is home to approximately 695,328 inhabitants (IBGE 2021).
The classification performed demonstrated consistency with the on-site reality. LSCorridors proved to be efficient in identifying areas within the landscape that offer greater permeability to wildlife. These areas can serve as a criterion for establishing conservation areas to form the ecological corridor (Ribeiro et al. 2017).
It is important to note that the prevalence of pastureland and highways should be taken into account when developing action plans for landscape conservation. This consideration is crucial to ensure functional connectivity between forest fragments, thereby promoting wildlife dispersal and preservation (Moraes et al. 2018). Given that anthropogenic land use is the main cause of fragmentation, habitat loss, and biodiversity decline, it is essential to establish well-founded conservation and restoration plans to avoid ineffectiveness (Baz et al. 2009, González-Varo et al. 2013, Haddad et al. 2015, Tapia-Armijos et al. 2015, Arantes et al. 2024).
Promoting actions for forest conservation and restoration requires financial resources that contribute to the management of the Atlantic Forest, thus preventing species extinction (Young & Castro 2021). By estimating the costs of expropriation and implementation of the EC, a strategy for resource mobilization is promoted. Financial incentives can be obtained through the Atlantic Forest Law, Green Funds, Environmental Recovery Commitment Agreements, and Conduct Adjustment Terms signed with environmental agencies or the Public Prosecutor’s Office, as provided in the LPNV (Brasil 2006, 2012).
Environmental compensation, an instrument under the SNUC, can also be utilized to obtain resources. It stipulates that projects with significant environmental impact are responsible for compensating through the implementation or maintenance of CU (Brasil 2000). Similarly, compensation through LR allows landowners with surpluses forest areas to negotiate with those who have liabilities (Young & Castro 2021).
This study provides valuable guidance for strategic planning and resource mobilization related to environmental compensation measures. For example, the implementation of PNMCBio was partially funded through environmental compensation resulting from the establishment of a Toyota factory in Sorocaba municipality (Smith & Ribeiro 2015).
However, it is important to consider the caution raised by Cuperus et al. (2002) regarding green funds and their potential impact on land values in the Netherlands. In Brazil, expropriation values are determined by the generic value plan, which makes them less susceptible to biased actions aimed at increasing financial gains. Furthermore, according to Decree-Law No. 3,365 of 1941, which provides for expropriations for public utility, the State may remove property from a private individual for purposes of public interest (Brasil 1941), which also provides for fair and prior compensation.
Furthermore, the implementation of an EC can generate carbon credits following Article 6 of the Paris Agreement, adopted at COP 21 in 2015, and the rules and procedures discussed at COP 26 in 2021. This enables companies and countries to purchase carbon credits to offset their emissions (UNFCCC 2021a, b).
However, landscape management and land use planning involve multiple factors, including stakeholders, legal frameworks, conflicts of interest, and socioeconomic considerations. Therefore, recognizing barriers to promoting biodiversity conservation improves decision-making in action planning.
We recommend that managers and government agencies carefully consider the presented results as an opportunity to design an ecological corridor that connects the studied CU in alignment with the Sustainable Development Goals (SDG).
CONCLUSIONS
In conclusion, this study contributes to determining the most effective approach for implementing an ecological corridor, thereby supporting the achievement of the SDG. Particularly, it aligns with SDG 11, which aims to create inclusive, safe, resilient, and sustainable cities; SDG 13, which addresses measures to combat climate change; and SDG 15, which focuses on protecting, restoring, and sustainably using terrestrial ecosystems to reduce biodiversity loss (UN 2021).
LSCorridors proved effective in identifying areas with higher potential for wildlife movement, facilitating the proposal of ecological corridors between the Municipal Park Corridors of Biodiversity and the National Forest of Ipanema, ensuring the sustainability of these valuable conservation units. So, it would be important to monitor if different species are using the corridors to ensure conservation objectives are met in future studies.
Among the methods employed in LSCorridors, LMmax resulted in the shortest distance (11.66 km) and area (2.33 km²). However, it only accounted for 10.60% of the already legally protected area. On the other hand, the PM method had the longest distance (19.56 km) and area (3.90 km²), with 41.05% of the area already protected. Consequently, it presented the lowest acquisition cost, totaling R$ 487,476.16.
The evaluation model for expropriation costs, based on generic plans, was found to be a valuable tool for decision-making in ecological corridor implementation. It offers flexibility by allowing different proposal models to be considered, taking into account the budget feasibility of public management. Additionally, it serves as an important reference for the private sector interested in engaging in environmental compensation initiatives with the government.
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