Proportion Of Vegetation Cover Research Articles

Spatial Analysis of Changes in Normalization Differences Vegetation Index in Protected Forest Areas of South Lore District, Poso Regency

Detection of changes in vegetation density generally uses the vegetation index parameter. The value of the vegetation index can provide information on the proportion of vegetation cover, live plant index, plant biomass, cooling capacity, and estimation of carbon dioxide absorption. This study aims to analyze changes in the level of vegetation density using Sentinel 2-A imagery in the protected forest area of South Lore District. This study used the method of calculating the Normalized Difference Vegetation Index (NDVI) to identify changes in density over 5 years. The results of the NDVI analysis are the largest in the range of -0.92960 to 0.871725. The vegetation density class in the Protected Forest Area of South Lore District in 2017 is in the dense class with an area of 15,322.24 Ha or around 47.66%, while the smallest in the non-vegetation class, which is 103.11 Ha or 0.32%, while the largest vegetation density class is in the Protected Forest Area of South Lore District in 2022, namely in the medium/quite dense class with an area of 19,948.18 Ha or 62.01% while the smallest in the non-vegetation class of 219.17 Ha or 0.68%. The largest increase in area was in the moderate/quite dense class of 4,892.33 Ha or 15.20% while the largest decrease in area was in the dense class with an area of 6,651.16 Ha or 20.67% of the total area of the Protected Forest Area of South Lore District.

Dinâmica espacial da pesca comercial amazônica: uma análise da composição da paisagem e dos desembarques de pescado

Amazonian commercial fishing is artisanal, and landings can be influenced by the flood pulse, the consumer market, the level of exploitation of species, habitat quality and vegetation cover. In this study, landscape variables and the river level were evaluated as possible drivers in the composition of catches landed in three regions of the Solimões-Amazon River. Fish landing data were collected in the upper and lower Solimões River and lower Amazon River. Fishing locations were mapped with information from fishers, civil defense departments and from the literature. Information related to river level and landscape was acquired from databases available online. Maps with the the radius of action of the fishing fleet and the quantification of landscape variables were made for periods of high and low-water, and non-metric multidimensional scaling analysis (nMDS) with catches by species, by region and hydrological period were performed. The largest operating radius of the fishing fleet was of 1,028 km and was identified in the lower Amazon River, which is probably due to the larger size of the consumer market, vessel characteristics and level of exploitation of the species near the landing center. The proportion of vegetation cover was reduced from 87% in the upper stretches of the Solimões River to 46% in the lower stretches. The upper and lower Solimões River regions presented a greater variety of species in the composition of landings. It was identified that the composition of landings between the three analyzed regions possibly varied according to the availability of habitats, indicating the importance of landscape variables for fish landings.

American cutaneous leishmaniasis associated with degradation of native forest, regardless of economic, social and infrastructure vulnerability.

American cutaneous leishmaniasis (ACL) is a notifiable dermatozoonosis with relevant morbidity. The present study aimed to evaluate the epidemiological aspects of cases of ACL reported in Northern Paraná (2007-2016), as well as to georeference and analyse the influence of economic, social and environmental variables. Data from ACL notification forms were obtained and the patients' houses were georeferenced. Descriptive statistics, calculations of disease incidence and proportion of vegetation cover by municipality, spatial analysis, multiple linear regression and vulnerability analysis by census sector (CS) were performed. One thousand four hundred fifty-one cases of ACL were reported in the 89 municipalities of four regional health (RH). The average incidence of cases per 10,000 inhabitants was as follows: 11.58, 8.79, 4.92 and 4.03 in 18thRH, 15thRH, 16thRH and 17thRH. Peaks of incident cases were observed in 2008, 2012 and 2015. There was a statistically significant difference between the HR when comparing the proportions of the variables gender, age, education level, area of residence, clinical form, diagnostic criteria, response to treatment and drug used in case of failure. It was observed that the lower the proportion of remaining Atlantic Forest, the greater the incidence of ACL in the municipality. With regard to clusters analysis, treatment abandonment clusters were observed in the 15thRH and mucous form clusters were observed in the 15thRH, 16thRH and 17thRH. The vulnerability analysis by CS allowed us to observe a statistically significant difference in all vulnerability indicators: economic and social in 15thRH and 17thRH; home infrastructure in 15thRH and 18thRH, urban infrastructure in 15thRH and 18thRH and compound vulnerability index in 15thRH and 18thRH. However, the most vulnerable areas did not always have the highest number of cases. The data presented demonstrate that preventive and health education measures must be mainly directed to areas of greater degradation of native forest; regardless of the vulnerability situation.

A comparison of four land surface temperature retrieval method using TERRA-ASTER satellite images in the semi-arid region of Saudi Arabia

Land surface temperature is a significant source of energy budget and climate information, contributing to various environmental and biophysical processes. This research includes comparing the LSTs retrieved from the ASTER sensor using the Reference Channel method, the Emissivity Normalization method (NOR), TES method and Retrieving LSE by taking the proportion of vegetation cover coupled with NDVI and integrates it into the TES algorithm. The results of derived LST from the four algorithms compare with MODIS data of 7 control points having thermally homogenous sites. The analysis showed that the four algorithms are suitable for LST retrieval, whereby the proposed emissivity-derived NDVI algorithms exhibited the highest degree of accuracy (RMSE 0.145), and the NOR had the least accuracy (RMSE 0.403). The analysis shows that emissivity derived NDVI TES method more reliant on the upwelling, downwelling and transmittance and will achieve the best results compared to the other three algorithms.

Estimating Proportion of Vegetation Cover at the Vicinity of Archaeological Sites Using Sentinel-1 and -2 Data, Supplemented by Crowdsourced OpenStreetMap Geodata

Monitoring vegetation cover is an essential parameter for assessing various natural and anthropogenic hazards that occur at the vicinity of archaeological sites and landscapes. In this study, we used free and open access to Copernicus Earth Observation datasets. In particular, the proportion of vegetation cover is estimated from the analysis of Sentinel-1 radar and Sentinel-2 optical images, upon their radiometric and geometric corrections. Here, the proportion of vegetation based on the Radar Vegetation Index and the Normalized Difference Vegetation Index is estimated. Due to the medium resolution of these datasets (10 m resolution), the crowdsourced OpenStreetMap service was used to identify fully and non-vegetated pixels. The case study is focused on the western part of Cyprus, whereas various open-air archaeological sites exist, such as the archaeological site of “Nea Paphos” and the “Tombs of the Kings”. A cross-comparison of the results between the optical and the radar images is presented, as well as a comparison with ready products derived from the Sentinel Hub service such as the Sentinel-1 Synthetic Aperture Radar Urban and Sentinel-2 Scene classification data. Moreover, the proportion of vegetation cover was evaluated with Google Earth red-green-blue free high-resolution optical images, indicating that a good correlation between the RVI and NDVI can be generated only over vegetated areas. The overall findings indicate that Sentinel-1 and -2 indices can provide a similar pattern only over vegetated areas, which can be further elaborated to estimate temporal changes using integrated optical and radar Sentinel data. This study can support future investigations related to hazard analysis based on the combined use of optical and radar sensors, especially in areas with high cloud-coverage.

Spatial and temporal variation in prey color patterns for background matching across a continuous heterogeneous environment.

In heterogeneous habitats, camouflage via background matching can be challenging because visual characteristics can vary dramatically across small spatial scales. Additionally, temporal variation in signaling functions of coloration can affect crypsis, especially when animals use coloration seasonally for intraspecific signaling (e.g., mate selection). We currently have a poor understanding of how wild prey optimize background matching within continuously heterogeneous habitats, and whether this is affected by requirements of intraspecific signaling across biological seasons. Here, we quantified color patterns of a wild population of shore skink (Oligosoma smithi), a variably colored lizard endemic to New Zealand, to (a) investigate whether background matching varies across a vegetation gradient; (b) assess potential signaling functions of color; and (c) to determine whether there is a trade‐off between requirements for crypsis and intraspecific signaling in coloration across seasons. Although all pattern types occurred throughout the vegetation gradient, we found evidence for background matching in skinks across the vegetation gradient, where dorsal brightness and pattern complexity corresponded with the proportion of vegetation cover. There was also a significant disparity between ventral color (saturation) of juveniles and adults, and also between sexes, suggestive of sex recognition. However, there was little indication that color was condition‐dependent in adults. Despite some evidence for a potential role in signaling, crypsis did not greatly differ across seasons. Our study suggests that selection favors a mix of generalist and specialist background matching strategies across continuously heterogeneous habitats.

Integration of Landsat-8 Thermal and Visible-Short Wave Infrared Data for Improving Prediction Accuracy of Forest Leaf Area Index

Leaf area index (LAI) has been investigated in multiple studies, either by means of visible/near-infrared and shortwave-infrared or thermal infrared remotely sensed data, with various degrees of accuracy. However, it is not yet known how the integration of visible/near and shortwave-infrared and thermal infrared data affect estimates of LAI. In this study, we examined the utility of Landsat-8 thermal infrared data together with its spectral data from the visible/near and shortwave-infrared region to quantify the LAI of a mixed temperate forest in Germany. A field campaign was carried out in August 2015, in the Bavarian Forest National Park, concurrent with the time of the Landsat-8 overpass, and a number of forest structural parameters, including LAI and proportion of vegetation cover, were measured for 37 plots. A normalised difference vegetation index threshold method was applied to calculate land surface emissivity and land surface temperature and their relations to LAI were investigated. Next, the relation between LAI and eight commonly used vegetation indices were examined using the visible/near-infrared and shortwave-infrared remote sensing data. Finally, the artificial neural network was used to predict the LAI using: (i) reflectance data from the Landsat-8 operational land imager (OLI) sensor; (ii) reflectance data from the OLI sensor and the land surface emissivity; and (iii) reflectance data from the OLI sensor and land surface temperature. A stronger relationship was observed between LAI and land surface emissivity compared to that between LAI and land surface temperature. In general, LAI was predicted with relatively low accuracy by means of the vegetation indices. Among the studied vegetation indices, the modified vegetation index had the highest accuracy for LAI prediction (R2CV = 0.33, RMSECV = 1.21 m2m−2). Nevertheless, using the visible/near-infrared and shortwave-infrared spectral data in the artificial neural network, the prediction accuracy of LAI increased (R2CV = 0.58, RMSECV = 0.83 m2m−2). The integration of reflectance and land surface emissivity significantly improved the prediction accuracy of the LAI (R2CV = 0.81, RMSECV = 0.63 m2m−2). For the first time, our results demonstrate that the combination of Landsat-8 reflectance spectral data from the visible/near-infrared and shortwave-infrared domain and thermal infrared data can boost the estimation accuracy of the LAI in a forest ecosystem. This finding has implication for the prediction of other vegetation biophysical, or possibly biochemical variables using thermal infrared satellite remote sensing data, as well as regional mapping of LAI when coupled with a canopy radiative transfer model.

Organic farming favours bird communities and their resilience to climate change in Mediterranean vineyards

Farmland birds have suffered notable declines in Europe in recent decades, mainly due to agricultural intensification and climate change. Organic farming, which has been shown to enhance biodiversity, is increasingly being put into practice in European vineyards. Nevertheless, no previous studies have reported significant positive responses in avian communities to organic practices. On the other hand, cover cropping is a common practice in both organic and conventional vineyards and is thought to have positive effects on bird communities and, particularly, on insectivorous species that may help control pests in agroecosystems. In this work, we studied bird communities in Mediterranean vineyards in Catalonia (NE Iberian Peninsula) in both the breeding and wintering seasons, and tested the effects of two common management options – organic vs. conventional farming and herbaceous cover vs. bare soil – on bird communities. In particular, we focused on (a) insectivorous birds that may help control pests and (b) avian species negatively affected by climatic warming whose population fluctuations may reflect the resilience of these bird communities to future climate change. Organic farming had a positive effect on vineyard bird communities and, specifically, increased species richness and overall bird abundance. This farming technique also positively affected the abundance of both insectivorous species and species whose populations are declining due to climate change. The presence of inter-row herbaceous cover between vines also had positive effects on bird community parameters, specifically in spring and in organic vineyards, when herbaceous cover favours species richness and the abundance of insectivorous species. However, further investigations are still needed to better understand the effects of different types of vegetation cover - i.e. plant origin and composition (e.g. sown vs. spontaneous vegetation) and proportion of vegetation cover (full vs. partial vegetation cover) - when employed as tools in wildlife conservation. This work provides useful information regarding bird conservation, which will help mitigate the effects of climate change on bird populations.

Spatial-temporal changes of vegetation cover in Guizhou Province, Southern China

Guizhou Province is an important karst area in the world and a fragile ecological area in China. Ecological risk assessment is very necessary to be conducted in this region. This study investigates different characteristics of the spatial-temporal changes of vegetation cover in Guizhou Province of Southern China using the data set of SPOT VEGETATION (1999–2015) at spatial resolution of 1-km and temporal resolution of 10-day. The coefficient of variation, the Theil-Sen median trend analysis, and the Mann-Kendall test are used to investigate the spatial-temporal change of vegetation cover and its future trend. Results show that: 1) the spatial distribution pattern of vegetation cover in Guizhou Plateau is high in the east whereas low in the west. The average annual normalized difference vegetation index (NDVI) from west to east is higher than that from south to north. 2) Average annual NDVI improved obviously in the past 17 years. The growth rate of average annual NDVI is 0.028/10 yr, which is slower than that of vegetation in the country (0.048/10 yr) from 1998 to 2007. Average annual NDVI in karst area is lower than that in non-karst area. However, the growing rate of average annual NDVI in karst area (0.030/10 yr) is faster than that in non-karst area (0.023/10 yr), indicating that vegetation coverage increases more rapidly in karst area. 3) Vegetation coverage in the study area is stable overall, but fluctuates in the local scales. 4) Vegetation coverage presents a continuous increasing trend. The Hurst exponent of NDVI in different vegetation types has an obvious threshold in various elevations. 5) The proportion of vegetation cover with sustainable increase is higher than that of vegetation cover with sustainable decrease. The improvement in vegetation cover may expand to most parts of the study area.

The Role of Vegetation in Mitigating Urban Land Surface Temperatures: A Case Study of Munich, Germany during the Warm Season

The Urban Heat Island (UHI) is the phenomenon of altered increased temperatures in urban areas compared to their rural surroundings. UHIs grow and intensify under extreme hot periods, such as during heat waves, which can affect human health and also increase the demand for energy for cooling. This study applies remote sensing and land use/land cover (LULC) data to assess the cooling effect of varying urban vegetation cover, especially during extreme warm periods, in the city of Munich, Germany. To compute the relationship between Land Surface Temperature (LST) and Land Use Land Cover (LULC), MODIS eight-day interval LST data for the months of June, July and August from 2002 to 2012 and the Corine Land Cover (CLC) database were used. Due to similarities in the behavior of surface temperature of different CLCs, some classes were reclassified and combined to form two major, rather simplified, homogenized classes: one of built-up area and one of urban vegetation. The homogenized map was merged with the MODIS eight-day interval LST data to compute the relationship between them. The results revealed that (i) the cooling effect accrued from urban vegetation tended to be non-linear; and (ii) a remarkable and stronger cooling effect in terms of LST was identified in regions where the proportion of vegetation cover was between seventy and almost eighty percent per square kilometer. The results also demonstrated that LST within urban vegetation was affected by the temperature of the surrounding built-up and that during the well-known European 2003 heat wave, suburb areas were cooler from the core of the urbanized region. This study concluded that the optimum green space for obtaining the lowest temperature is a non-linear trend. This could support urban planning strategies to facilitate appropriate applications to mitigate heat-stress in urban area.

An approach of surface coal fire detection from ASTER and Landsat-8 thermal data: Jharia coal field, India

Radiant temperature images from thermal remote sensing sensors are used to delineate surface coal fires, by deriving a cut-off temperature to separate coal-fire from non-fire pixels. Temperature contrast of coal fire and background elements (rocks and vegetation etc.) controls this cut-off temperature. This contrast varies across the coal field, as it is influenced by variability of associated rock types, proportion of vegetation cover and intensity of coal fires etc. We have delineated coal fires from background, based on separation in data clusters in maximum v/s mean radiant temperature (13th band of ASTER and 10th band of Landsat-8) scatter-plot, derived using randomly distributed homogeneous pixel-blocks (9×9 pixels for ASTER and 27×27 pixels for Landsat-8), covering the entire coal bearing geological formation. It is seen that, for both the datasets, overall temperature variability of background and fires can be addressed using this regional cut-off. However, the summer time ASTER data could not delineate fire pixels for one specific mine (Bhulanbararee) as opposed to the winter time Landsat-8 data. The contrast of radiant temperature of fire and background terrain elements, specific to this mine, is different from the regional contrast of fire and background, during summer. This is due to the higher solar heating of background rocky outcrops, thus, reducing their temperature contrast with fire. The specific cut-off temperature determined for this mine, to extract this fire, differs from the regional cut-off. This is derived by reducing the pixel-block size of the temperature data. It is seen that, summer-time ASTER image is useful for fire detection but required additional processing to determine a local threshold, along with the regional threshold to capture all the fires. However, the winter Landsat-8 data was better for fire detection with a regional threshold.

Estimating Vertical Distribution of Vegetation Cover in Temperate Heterogeneous Forests Using Airborne Laser Scanning Data

Vertical structure is important for understanding forest environment, yet difficult to characterize, especially in temperate heterogeneous forests where the structure is complex. This study used data from a small-footprint airborne laser scanning (ALS) to estimate vegetation coverage in four stratum ranges in a warm temperate forest in Japan: >12 m, 8 - 12 m, 4 - 8 m, and 0 - 4 m in height. Field data were collected in 17 broad-leaved and 12 coniferous sample plots, consisting of the proportion of vegetation cover in each stratum range. The field and ALS measurements were conducted in summer, during leaf-on conditions. Using echo attributes (first, last, intermediate, and only), we calculated the vegetation coverage index (VCI) at 1-m height intervals. The cumulative sum of the VCI (CUMVCI) was then computed and compared with field observations. Linear regression analysis showed that the ALS data gave reasonable estimates of vegetation coverage in the upper two or three stratum ranges in broad-leaved stands, and in the upper two stratum ranges in coniferous stands. The model gave reproducible estimates until approximately 95% of the total returns had been applied. We conclude that ALS data can provide useful information on natural habitats in the management of warm temperate forest.

Comparative habitat use by syntopic Kelp Gulls (Larus dominicanus) and Olrog's Gulls (L. atlanticus) in coastal Patagonia

We studied comparative microhabitat use by breeding Kelp Gull (Larus dominicanus) and the threatened Olrog's Gull (Larus atlanticus) at six colonies through the distributional range of Olrog's Gull in coastal Patagonia, Argentina. The ranges of values for most of the 13 microhabitat variables measured (related to vegetation, soil and topography) were broader for the Kelp Gull than Olrog's Gull, with those of that latter within the range of Kelp Gull, indicating potential spatial conflict between the two species. There was particular overlap in nest-site characteristics, but differences were observed between the two species. Multivariate analyses showed that the most important differences in habitat between the two species related to vegetation cover and distance to the high-tide line. Compared with Kelp Gulls, Olrog's Gulls placed their nests in sites with lower proportion of vegetation cover, lower percentages of silt-clay in the substrate, and closer to the high-tide line. For both species the patterns of nest-site selection did not vary among colonies, although the extent of differences between the two species varied with availability of habitat at each colony. Although Olrog's Gulls started laying 12–14 days earlier than the larger Kelp Gulls, the latter occupied breeding colonies earlier and may, therefore, interfere with settlement of Olrog's Gulls. Considering the increase in the numbers, colony area and nesting density of Kelp Gulls currently observed in coastal Patagonia, there is an urgent need to implement monitoring programs for both species and conduct studies to better predict the results of their interactions.

大阪市中心部の街路樹と越冬期の鳥類の出現状況の関係

I investigated birds from 15 January to 24 February 2004 along 8 wooded streets in central area of Osaka, Japan, in order to determine which environmental factors of wooded street are important as habitat of birds in winter. Eight species of 218 individuals were recorded at 2 times observation of the streets. I used a satellite image to identify the distribution of vegetation in my study area. The normalized difference vegetation index (NDVI) of each grid cell was calculated. The value of NDVI that indicated the threshold value for vegetation cover were 0.3 and more, based on the ground-truthing from December 2003 to February 2004. The proportion of vegetation cover within 50 m from a recording point was calculated in each bird species. The average vegetation cover proportion of Hypsipetes amaurotis and Sturnus cineraceus was more than 25 %, while that of Passer montanus was around 5 %. Almost all individuals of species except Passer montanus were significantly recorded in buffer areas within 100 m, 200 m, 300 m and 400 m from the edge of 2 ha and more woodlot.

Surface Temperature Variation with Vegetation Phenology over Deciduous Forests – A Study over Nagarjunasagar Srisailam Tiger Reserve (NSTR) Using ENVISAT ‐ AATSR Data

Combined analysis of reflective and thermal data recorded by coarse resolution and high repetitive satellites provide a useful means to study seasonal vegetation characteristics and other related phenological parameters. ENVISAT Advanced Along Track Scanning Radiometer (AATSR) data for different seasons from January 04 to April 04 has been analyzed to derive the Normalized Difference Vegetation Index (NDVI) and Surface Temperature (ST) images for the forest regions of Nagarjunasagar Srisailam Tiger Reserve (NSTR), India. Temporal variation of NDVI and ST reflected the phenology of the forest area. A negative relationship was observed between the NDVI and ST over all the vegetation types and the proportion of vegetation cover seemed to has bearing on the ST. Scatter plots for NDVI and ST drawn for winter season showed a good separability of land use/land cover types of the study area.

Ground-based method for measuring thermal infrared effective emissivities: Implications and perspectives on the measurement of land surface temperature from satellite data

Thermal infrared emissivity is an important parameter for surface characterization and for determining surface temperature. The field-based measurements for ground and vegetation emissivities in 8-14 w m waveband were performed with an emissivity box. A theoretical analysis was carried out using the box and a correcting factor has been determined. The average value for thermal band emissivity of the exposed bare soil was found to be around 0.909; the average value measured for most of the varieties of vegetation present were in the range of 0.980-0.985. A theoretical model is used for obtaining effective emissivity in the 8-14 w m region from Advanced Very High Resolution Radiometer (AVHRR) data considering the proportion of vegetation cover in a pixel and the field-measured emissivity values. The error of the methodology is found to be within 1.5%. Narrow band emissivities for AVHRR channels 4 and 5 have been derived from the emissivity values in the 8-14 w m waveband. The surface temperature has been derived from AVHRR data using a split-window algorithm as a function of emissivities derived in narrow bands. The split-window algorithm accounted for absorption effects of the atmosphere by incorporating the water vapour concentration measured in the campaign. A good agreement was obtained between the satellite-derived surface temperature and the in situ observations. The result suggest that the methodology allows us to derive land surface temperature with an accuracy better than 1.5° C provided the surface emissivity is known. The paper describes the field-based emissivity measurement and approach for deriving surface temperature over land surface.

ENVIRONMENTAL DETERIORATION IN RURAL MEXICO: AN EXAMINATION OF THE CONCEPT

Mexico, like many other countries worldwide, faces an environmental crisis of enormous proportions. While in its urban dimension environmental problems are more similar to those of developed countries, in rural areas they are analogous to those prevailing in developing countries. In rural areas, which are largely devoted to food production based on traditional methods, environmental concerns are mainly related to phenomena such as deforestation and soil erosion, and not to chemical pollution or ozone-layer depletion, which are the primary concerns of the broad public. The future food production in these regions and the possibility of improving the life quality of their inhabitants depend on our understanding of these kinds of problems, and our capacity to confront them. An overview of the theoretical framework on environmental deterioration reveals a lack of definition of the concepts and terms related to this issue. Several terms, such as “desertification” and “fragmentation,” among others, are widely used by ecologists but are clearly not synonymous with environmental deterioration. A consequence of this vagueness is the lack of clear criteria to differentiate areas that are only moderately modified from those in which true deterioration has occurred. Also, unified methods to efficiently evaluate environmental deterioration in rural areas are lacking. We briefly present a case study in which environmental deterioration was evaluated in La Montana, an extremely poor and climatically and topographically heterogeneous rural region inhabited by indigenous people in southern Mexico. Three deterioration categories are recognized based on degree of human influence, proportion of vegetation cover, and soil erosion severity. Use of air photogrammetry supplemented with field surveys revealed that 13% of La Montana is already damaged (i.e., lacking native vegetation and affected, perhaps irreversibly, by severe erosion), while 36% is altered (i.e., where native vegetation is substantially modified, but productive activities are still possible). In turn, almost three quarters of the land in the latter category is at high risk of becoming damaged. An analysis of the patterns of land-use changes around selected villages for the period 1979–1992 showed local annual deforestation rates ranging between 1 and 17%, depending upon climatic conditions. Based on the conceptual review and the analysis of the case study, we suggest that environmental deterioration comprises at least three clearly distinct dimensions: the abiotic setting, the biological attributes, and the social characteristics of the process. Finally, we define environmental deterioration as any modification of the environment that implies a reduction or loss of its physical and biological qualities, caused by natural phenomena or human activities, ultimately representing a decrease in the availability of ecosystem goods and services to human populations. The methods used to evaluate environmental deterioration at La Montana allowed us to separate modifications that cause deterioration from those that do not. This investigation, carried out in a relatively short time and with a minimum financial investment, yielded a satisfactory assessment of the state of the environment at the regional and community scales, recognizing early indicators of deterioration. This approach may be particularly useful in rural regions that share many characteristics with La Montana, such as critical environmental problems, extreme poverty, and insufficient background information about these issues.