a b s t r a c tForest fragmentation constitutes one of the main consequences of land cover change worldwide. Through this process gaps in habitat coverage are created and the ability of populations in the remaining fragments to maintain themselves is put in doubt. Hence, two options need to be considered: conserving the remaining forest fragments, and restoring habitat in some deforested patches with the aim of reestablishing the connections among the fragments. We established a mathematical index (SIR) that describes the suitability of individual habitat patches for restoration within a landscape. The index considers classes of distances among fragments and categories of habitat quality in the areas surrounding the fragments to assess habitat quality in terms of probability of dispersal and survival of propagules (especially seeds and cutting). In the present study, we created detailed maps depicting SIR values for two periods (1988 and 2011) for Sorocaba region (São Paulo State, Brazil). We derived land cover maps from satellite images for the two years of our study, and then surveyed the transition of land cover categories and landscape metrics between years. A model for the SIR was created using a map of distance classes among fragments and also a map of habitat quality established according to each land cover category. For both 1988 and 2011, pasture was the predominant land cover category. The main land cover transitions were from pasture to urban (10.6%) and from pasture to forest fragments (13.4%). Although the land cover class "wood sites" increased, the data of SIR revealed that the areas of habitat categorized as excellent and good both decreased, while habitat classes categorized as poor and very poor increased. Our model has the potential to be applied to other regions where the forest is fragmented. Hence, local policy makers will be able to use this model to determine local patches of high value for conservation and also the most ideal locations for restoration projects.
Projects focusing on the restoration of degraded ecosystems have to be financially appealing, spatially multiscaled, and ecologically efficient. Considering such premises, a model was elaborated to assess the locals in relation to the kind of management to be adopted (conservation or restoration) and, for locals indicated for restoration, the kind of restoration to be adopted (assisted or passive). Furthermore, we propose a set of ecologically-based alternatives at medium-and local-scale to assist the restoration of areas considered unsuitable for passive restoration. Such techniques are: install artificial connectors among forest fragments near each other, or, for areas where forest fragments are far each other, install nucleation techniques, revitalization of concrete-lined urban rivers, and the control of erosion and invasive plant species. We tested the potential of our model through a case study carried out in Sorocaba, Sao Paulo State, Brazil. The study area is predominantly occupied by pasture lands, but urbanization also is an important land cover category. There are 661 forest fragments, being 25 of them larger than 50 ha. From the area considered "non-habitat", i.e., modified due to human usage, 35.5% of the total study area and 45.5% of the study area classified as non-habitat is suitable for passive restoration, and the rest of the area needs is suitable only for assisted restoration techniques. We verified that the facility and low cost of installation are advantageous features of such techniques and the results obtained by mean of application of the assisted techniques indicate that the alternatives tend to accelerate the process of establishing connectivity of the landscape in locals devoid of connections.
The process of landscapes' fragmentation has led to having two realistic complementary options: (a) developing techniques and approaches for conserving the healthy remaining forest fragments and (b) restoring degraded places. The second option can be conducted by projects that focus on restoring or rehabilitating the degraded environment. In this research, a framework was tested through a set of pilot-scale projects in a highly urbanized Municipality of the southeastern Brazilian region (Sorocaba, São Paulo State). Four projects were carried out in order to test the efficacy of techniques devoted to solving different problems of environmental degradation (isolation of fragments, loss of biodiversity, soil erosion, and bioinvasion) in different environments (terrestrial [forested and nonforested] and aquatic [rivers]) through the acceleration and orientation of the process of restoration. Here, we show the main findings, discuss the potential and weaknesses found in each project, and offer some recommendations for future potential users. The projects are constituted of techniques and approaches that are all cheap, naturally based, and easy to be implemented and with a high probability of social comprehension and acceptance. In each project, we got interesting outcomes, considering all successes and limitations (for example, a high reappearance of vegetation in streams and strong control of soil erosion). This model embraces the main aspects of environmental recovering through a feasible, realistic, and socioecological approach, and it brings high potential to be used by other researchers and also for technicians and decision makers who search for feasible and realistic projects.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.