Biodiversity conservation, traditional agriculture and ecotourism: Land cover/land use change projections for a natural protected area in the northeastern Yucatan Peninsula, Mexico

Garcı́a-Frapolli, Eduardo; Ayala-Orozco, Bárbara; Bonilla‐Moheno, Martha; Espadas-Manrique, Celene; Ramos‐Fernández, Gabriel

doi:10.1016/j.landurbplan.2007.03.007

Cited by 101 publications

(86 citation statements)

References 31 publications

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“…Even though CA models face challenges to incorporate human decision making, they have been nevertheless found them useful for modeling ecological aspects of LULC [13][14][15]68]. While CA Markov models have been more commonly used to evaluate the impact of protection on a forested landscape by projecting forest cover changes in the future [109,110], we used this model to generate a hypothetical scenario of our present observable landscape without the effect of a policy intervention. We found this modeling approach useful and transferable to other areas where policy evaluation using traditional methods are not possible.…”

Section: Discussionmentioning

confidence: 99%

Simulating Forest Cover Changes of Bannerghatta National Park Based on a CA-Markov Model: A Remote Sensing Approach

2012

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Establishment of protected areas (PA) has been one of the leading tools in biodiversity conservation. Globally, these kinds of conservation interventions have given rise to an increase in PAs as well as the need to empirically evaluate the impact of these PAs on forest cover. Few of these empirical evaluations have been geared towards comparison of pre and post policy intervention landscapes. This paper provides a method to empirically evaluate such pre and post policy interventions by using a cellular automata-Markov model. This method is tested using remotely sensed data of Bannerghatta National park (BNP) and its surrounding, which have experienced various national level policy interventions (Indian National Forest Policy of 1988) and rapid land cover change between 1973 and 2007. The model constructs a hypothetical land cover scenario of BNP and its surroundings (1999 and 2007) in the absence of any policy intervention, when in reality there has been a significant potential policy intervention effect. The models predicted a decline in native forest cover and an increase in non forest cover post 1992 whereas the actual observed landscape experienced the reverse trend where after an initial decline from 1973 to 1992, the forest cover in BNP is towards recovery post 1992. Furthermore, the models show a higher deforestation and lower reforestation than the observed deforestation and reforestation patterns for BNP post 1992. Our results not only show the implication of national level policy changes on forest cover but also show the usefulness of our method in evaluating such conservation efforts.

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Section: Discussionmentioning

confidence: 99%

Simulating Forest Cover Changes of Bannerghatta National Park Based on a CA-Markov Model: A Remote Sensing Approach

2012

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“…This reduction in native vegetal cover is not exclusive from our study region; it is rather a worldwide pattern [6] that has increased in recent years in NPAs and different areas from other countries [8, 9,62,63]. Although the causes of these changes were not assessed in this work, recent studies on LULCC [12,25,26] that include the evaluation of NPAs [27,28] and their surrounding areas [31] have shown that deforestation due to overexploitation, uncontrolled logging, agricultural activities, consumer demand, fires, pests, and urban growth, as well as natural phenomena arising from climate change, are some of the main factors that influence the loss of vegetation in Mexico [2]. In other areas, the increase in land cover changes has been caused by the rapid population growth, the multiplication of human settlements, and regional economic development [8- 10,64].…”

Section: Land Use-cover Changes Within the Natural Protected Area Altmentioning

confidence: 93%

Assessment of Land Use-Cover Changes and Successional Stages of Vegetation in the Natural Protected Area Altas Cumbres, Northeastern Mexico, Using Landsat Satellite Imagery

et al. 2017

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Loss of vegetation cover is a major factor that endangers biodiversity. Therefore, the use of geographic information systems and the analysis of satellite images are important for monitoring these changes in Natural Protected Areas (NPAs). In northeastern Mexico, the Natural Protected Area Altas Cumbres (NPAAC) represents a relevant floristic and faunistic patch on which the impact of loss of vegetation cover has not been assessed. This work aimed to analyze changes of land use and coverage (LULCC) over the last 42 years on the interior and around the exterior of the area, and also to propose the time of succession for the most important types of vegetation. For the analysis, LANDSAT satellite images from 1973, 1986, 2000, 2005 and 2015 were used, they were classified in seven categories through a segmentation and maximum likelihood analysis. A cross-tabulation analysis was performed to determine the succession gradient. Towards the interior of the area, a significant reduction of tropical vegetation and, to a lesser extent, temperate forests was found, as well as an increase in scrub cover from 1973 to 2015. In addition, urban and vegetation-free areas, as well as modified vegetation, increased to the exterior. Towards the interior of the NPA, the processes of perturbation and recovery were mostly not linear, while in the exterior adjacent area, the presence of secondary vegetation with distinct definite time of succession was evident. The analysis carried out is the first contribution that evaluates LULCC in this important NPA of northeastern Mexico. Results suggest the need to evaluate the effects of these modifications on species.

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“…This study selected temperature, precipitation, elevation and slope [28] to represent natural factors, the distance to rivers and roads [29] to represent the effect of location and population density and gross domestic production [32] to show the human activities. Among them, the source and processing of temperature, precipitation, elevation and slope has been introduced in Section 3.1.…”

Section: Driving Forces Selectionmentioning

confidence: 99%

Spatiotemporal Dynamics and Drivers of Farmland Changes in Panxi Mountainous Region, China

Chen

2016

Sustainability

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Due to the multiple impacts of landform effects, spatial heterogeneity and land use policies, farmland dynamics in mountainous areas are complicated. This study investigated farmland dynamics based on land use data from a typical mountainous area, Panxi, in China for 1990, 2000 and 2010, discussed the relationship between altitude, slope and farmland changes and presented an analysis of the driving forces of farmland change. Our findings are as follows: (1) from 1990 to 2010, the area of converted farmland was relatively small (313 km 2 ), accounting for only 2.6% of the region's farmland. Farmland was mainly converted to forest and grassland as a result of the Returning Farmland to Forest Program; (2) The spatial distribution of land use types differed significantly. The presence of water bodies influenced farmland and built-up land, while forest and grassland showed "landform-oriented" characteristics. Built-up land was especially variable in distribution, indicating that it was more vulnerable to human activities; (3) The vertical differentiation of farmland changes was obvious. At altitudes <2500 m, the data displayed a trend of conversion from forest to farmland, while at >2500 m, this trend reversed. Thus, 2500 m serves as an altitudinal boundary between farmland and forest in Panxi. The largest area of forest-farmland transfer occurred on slopes steeper than 15 • , not 25 • , as defined by China's policy of Returning Farmland to Forest; (4) The driving forces of farmland changes varied. Decreases in farmland were negatively correlated with proximity to rivers and roads. Increases in farmland were positively related to temperature and negatively related to both population density and altitude.

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Biodiversity conservation, traditional agriculture and ecotourism: Land cover/land use change projections for a natural protected area in the northeastern Yucatan Peninsula, Mexico

Cited by 101 publications

References 31 publications

Simulating Forest Cover Changes of Bannerghatta National Park Based on a CA-Markov Model: A Remote Sensing Approach

Simulating Forest Cover Changes of Bannerghatta National Park Based on a CA-Markov Model: A Remote Sensing Approach

Assessment of Land Use-Cover Changes and Successional Stages of Vegetation in the Natural Protected Area Altas Cumbres, Northeastern Mexico, Using Landsat Satellite Imagery

Spatiotemporal Dynamics and Drivers of Farmland Changes in Panxi Mountainous Region, China

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