Combined effect of fire and water scarcity on vegetation patterns in arid lands

In many arid zones around the word, the vegetation spontaneously forms regular patterns to optimize the use of the scarce water resources. The patterns act as early warning signal that fragile ecosystems may suddenly undergo irreversible shifts, thus, interpreting the structural shape of vegetation patterns is crucial to deciphering the ecosystem history and its expected further development. The sudden and irreversible shift of delicate ecosystems as a consequence of minor variation of the climatic forcing has been studied extensively in the past. The attitude of the ecosystem to recover after a catastrophic event, such as fire, did not receive as much attention so far. Here we modelled fire, as a sudden shift of the ecosystem state variables and functionality and evaluated post-fire scenarios under the hypothesis that two major feedbacks shaped the vegetation patterns: a positive feedback between preferential infiltration and plant growth, and a second feedback between infiltration and vegetation burning. A simple model solving a set of partial differential equations for soil moisture, plant biomass, surface water and dead biomass balance predicted significantly diverse post-fire vegetation patterns depending on the fire severity and on the degree of soil water repellency induced by the vegetation burning.     

Land-use changes and implications for management of a small protected island off the coast of Bretagne

Over the 20th century, reduced land cultivation has caused an extension of fallow land in several European countries, which has led to a decrease in biodiversity. Knowledge of dynamic vegetation processes and of the impact of human activities on biodiversity provides the basis for land management recommendations, as well as for wildlife management programs. We analysed land-use changes on a small protected island (Ushant, Bretagne, France) using historical documentation (1844) and aerial photographs taken in 1952 and 1992. Over this period, especially during the last 40 yr, Ushant underwent a complete transformation from rural landscape to extensive shrubland. No cultivated area remains, grazed areas were moved from the coastal fringe to the core of the island, while over 40% of the island is fallow land. The relationship between current sheep grazing and vegetation suggests that grazed meadows used to be close to inhabited areas, i.e. 150 m outside the villages. These results allowed us to analyse landcover potential related to changes in the intensity of sheep grazing. The scenarios highlighted by our method provide an objective framework for further assessment of fallow land management.     

A geostatistical approach for mapping thematic classification accuracy and evaluating the impact of inaccurate spatial data on ecological model predictions

Spatial information in the form of geographical information system coverages and remotely sensed imagery is increasingly used in ecological modeling. Examples include maps of land cover type from which ecologically relevant properties, such as biomass or leaf area index, are derived. Spatial information, however, is not error-free: acquisition and processing errors, as well as the complexity of the physical processes involved, make remotely sensed data imperfect measurements of ecological attributes. It is therefore important to first assess the accuracy of the spatial information being used and then evaluate the impact of such inaccurate information on ecological model predictions. In this paper, the role of geostatistics for mapping thematic classification accuracy through integration of abundant image-derived (soft) and sparse higher accuracy (hard) class labels is presented. Such assessment leads to local indices of map quality, which can be used for guiding additional ground surveys. Stochastic simulation is proposed for generating multiple alternative realizations (maps) of the spatial distribution of the higher accuracy class labels over the study area. All simulated realizations are consistent with the available pieces of information (hard and soft labels) up to their validated level of accuracy. The simulated alternative class label representations can be used for assessing joint spatial accuracy, i.e., classification accuracy regarding entire spatial features read from the thematic map. Such realizations can also serve as input parameters to spatially explicit ecological models; the resulting distribution of ecological responses provides a model of uncertainty regarding the ecological model prediction. A case study illustrates the generation of alternative land cover maps for a Landsat Thematic Mapper (TM) subscene, and the subsequent construction of local map quality indices. Simulated land cover maps are then input into a biogeochemical model for assessing uncertainty regarding net primary production (NPP).     

Quantifying sample biases of inland lake sampling programs in relation to lake surface area and land use/cover

We quantified potential biases associated with lakes monitored using non-probability based sampling by six state agencies in the USA (Michigan, Wisconsin, Iowa, Ohio, Maine, and New Hampshire). To identify biases, we compared state-monitored lakes to a census population of lakes derived from the National Hydrography Dataset. We then estimated the probability of lakes being sampled using generalized linear mixed models. Our two research questions were: (1) are there systematic differences in lake area and land use/land cover (LULC) surrounding lakes monitored by state agencies when compared to the entire population of lakes? and (2) after controlling for the effects of lake size, does the probability of sampling vary depending on the surrounding LULC features? We examined the biases associated with surrounding LULC because of the established links between LULC and lake water quality. For all states, we found that larger lakes had a higher probability of being sampled compared to smaller lakes. Significant interactions between lake size and LULC prohibit us from drawing conclusions about the main effects of LULC; however, in general lakes that are most likely to be sampled have either high urban use, high agricultural use, high forest cover, or low wetland cover. Our analyses support the assertion that data derived from non-probability-based surveys must be used with caution when attempting to make generalizations to the entire population of interest, and that probability-based surveys are needed to ensure unbiased, accurate estimates of lake status and trends at regional to national scales.     

Spatial Relations Between Floodplain Environments and Land Use – Land Cover of a Large Lowland Tropical River Valley: Pánuco Basin, México

Large lowland river valleys include a variety of floodplain environments that represent opportunities and constraints for human activities. This study integrates extensive field observations and geomorphic data with analysis of satellite remote sensing data to examine spatial relations between land use/land cover (LULC) and floodplain environments in the lower Pánuco basin of eastern Mexico. The floodplain of the lower Pánuco basin was delineated by combining a digital elevation model with a satellite image of a large flood event. The LULC was classified by combining a hybrid classification strategy with image stratification, applied to 15-m-resolution ASTER data. A geomorphic classification of floodplain environments was performed using a dry-stage image (ASTER data) and a 1993 Landsat image acquired during a large flood event. Accuracy assessment was based on aerial photographs (1:38,000), global positioning satellite ground-truthing, and a Landsat 7ETM⁺ image from 2000, which resulted in an overall accuracy of 82.9% and a KHAT of 79.8% for the LULC classification. The geomorphic classification yielded 83.5% overall accuracy, whereas the KHAT was 81.5%. LULC analysis was performed for the entire floodplain and individually within four valley segments. The analysis indicates that the study area is primarily utilized for grazing and farming. Agriculture is primarily associated with coarse-grained (sandy/silty) natural levee and point bar units close to the river channel, whereas cattle grazing occurs in distal and lower-lying reaches dominated by cohesive fine-grained (clayey) deposits, such as backswamps. In the Pánuco valley, wetlands and lakes occur within backswamp environments, whereas in the Moctezuma segments, wetlands and lakes are associated with relict channels. This study reveals considerable variation in LULC related to spatial differences in floodplain environments and illustrates the importance of considering older anthropogenic influences on the landscape. The research design should be applicable for other large lowland coastal plain river valleys where agriculture is a major component of the floodplain landscape.     

Measuring Plant Cover in Sagebrush Steppe Rangelands: A Comparison of Methods

Methods that are more cost-effective and objective are needed to detect important vegetation change within acceptable error rates. The objective of this research was to compare visual estimation to three new methods for determining vegetation cover in the sagebrush steppe. Fourteen management units at the US Sheep Experiment Station were identified for study. In each unit, 20 data collection points were selected for measuring plant cover using visual estimation, laser-point frame (LPF), 2 m above-ground-level (AGL) digital imagery, and 100-m AGL digital imagery. In 11 of 14 management units, determinations of vegetation cover differed (P < 0.05). However, when combined, overall determinations of vegetation cover did not differ. Standard deviation, corrected sums of squares, coefficient of variation, and standard error for the 100 m AGL method were half as large as for the LPF and less than the 2-m AGL and visual estimate. For the purpose of measuring plant cover, all three new methods are as good as or better than visual estimation for speed, standard deviation, and cost. The acquisition of a permanent image of a location is an important advantage of the 2 and 100 m AGL methods because vegetation can be reanalyzed using improved software or to answer different questions, and changes in vegetation over time can be more accurately determined. The reduction in cost per sample, the increased speed of sampling, and the smaller standard deviation associated with the 100-m AGL digital imagery are compelling arguments for adopting this vegetation sampling method.     

Modelling the conversion of Colombian lowland ecosystems since 1940: drivers, patterns and rates

In biologically mega-diverse countries that are undergoing rapid human landscape transformation, it is important to understand and model the patterns of land cover change. This problem is particularly acute in Colombia, where lowland forests are being rapidly cleared for cropping and ranching. We apply a conceptual model with a nested set of a priori predictions to analyse the spatial and temporal patterns of land cover change for six 50-100 km(2) case study areas in lowland ecosystems of Colombia. Our analysis included soil fertility, a cost-distance function, and neighbourhood of forest and secondary vegetation cover as independent variables. Deforestation and forest regrowth are tested using logistic regression analysis and an information criterion approach to rank the models and predictor variables. The results show that: (a) overall the process of deforestation is better predicted by the full model containing all variables, while for regrowth the model containing only the auto-correlated neighbourhood terms is a better predictor; (b) overall consistent patterns emerge, although there are variations across regions and time; and (c) during the transformation process, both the order of importance and significance of the drivers change. Forest cover follows a consistent logistic decline pattern across regions, with introduced pastures being the major replacement land cover type. Forest stabilizes at 2-10% of the original cover, with an average patch size of 15.4 (+/-9.2)ha. We discuss the implications of the observed patterns and rates of land cover change for conservation planning in countries with high rates of deforestation.     

Characterizing land-use diversity in village landscapes for sustainable mountain development: a case study from Indian Himalaya

This study aimed to analyze the ecological, socio-economic and policy implications of land-use diversity in a traditional village landscape (900–1,000 m amsl.) in the Garhwal region of Indian Himalaya. The village landscape was differentiated into three major land-use types viz., forests, settled agriculture and shifting agriculture. Settled agriculture was further differentiated into four agroecosystem types viz., homegarden system (HGS), rainfed agroforestry system (RAS), rainfed crop system (RCS) and irrigated crop system (ICS), and shifting agriculture system (SAS) was differentiated into different stages of a 4-year long cropping phase and a 7-year long fallow phase, and forests into Community Forests (CF) and Reserve Forests (RF). HGS is the most productive agroecosystem, with soil organic carbon and nutrient concentrations significantly higher than all other forest/agricultural land-uses. Farmers capitalize upon crop diversity to cope with the risks and uncertainties of a monsoon climate and spatial variability in ecological factors influencing productivity. The SAS, a land-use adopted as a means of acquiring inheritable rights over larger land holdings provided in the policies during the 1890s, is less efficient in terms of land productivity than the traditional RAS and HGS but is maintained for its high labour productivity coupled with availability of high-quality fuelwood from fallow vegetation. Dominance of fodder trees in the RAS seems to derive from policies causing shortage of fodder available from forests. Cultural norms have favoured equity by allowing hiring of labour only from within the village community and income from non-timber forest products only to the weaker section of the society. Conversion of rainfed to irrigated cropping, a change facilitated by the government, improves agricultural productivity but also increases pressure on forests due to higher rates of farmyard manure input to the irrigated crops. Existing forest management systems are not effective in maintenance of a large basal area in forests together with high levels of species richness, soil fertility and resistance to invasive alien species Lantana camara. Farmers have to spend huge amount of labour and time in producing manure, managing livestock and other subsidiary farm activities. Interlinkages among agriculture, forests and rural economy suggest a need of replacing the present policies of treating agricultural development, forest conservation and economic development as independent sectors by an integrated sustainable development policy. The policy should promote technological and institutional innovations enabling parallel improvements in agricultural productivity and functions of forest ecosystems.     

Ground-Cover Measurements: Assessing Correlation Among Aerial and Ground-Based Methods

Wyoming’s Green Mountain Common Allotment is public land providing livestock forage, wildlife habitat, and unfenced solitude, amid other ecological services. It is also the center of ongoing debate over USDI Bureau of Land Management’s (BLM) adjudication of land uses. Monitoring resource use is a BLM responsibility, but conventional monitoring is inadequate for the vast areas encompassed in this and other public-land units. New monitoring methods are needed that will reduce monitoring costs. An understanding of data-set relationships among old and new methods is also needed. This study compared two conventional methods with two remote sensing methods using images captured from two meters and 100 meters above ground level from a camera stand (a ground, image-based method) and a light airplane (an aerial, image-based method). Image analysis used SamplePoint or VegMeasure software. Aerial methods allowed for increased sampling intensity at low cost relative to the time and travel required by ground methods. Costs to acquire the aerial imagery and measure ground cover on 162 aerial samples representing 9000 ha were less than $3000. The four highest correlations among data sets for bare ground—the ground-cover characteristic yielding the highest correlations (r)—ranged from 0.76 to 0.85 and included ground with ground, ground with aerial, and aerial with aerial data-set associations. We conclude that our aerial surveys are a cost-effective monitoring method, that ground with aerial data-set correlations can be equal to, or greater than those among ground-based data sets, and that bare ground should continue to be investigated and tested for use as a key indicator of rangeland health.     

Satellite-based indices in the analysis of land cover for municipalities in the province of Siena, Italy

Territorial indicators based on the satellite measured reflected or emitted energy can provide valuable information on the spatial evolution of a territory. Information regarding land use, biomass coverage and radiant temperature were obtained from remotely obtained measurements for each municipality in the Province of Siena. Remotely sensed data were combined into different indices to compare characteristics of land cover between territories and create an information base for continued study. A classification was performed on a municipal level and land use classes were grouped together and a general index of use pressure was created. A vegetation index was used to compare biomass densities. A radiant temperature index was calculated using measure thermal infrared emissions. The results of these analyses allowed researchers to examine the intra and inter-municipal spatial heterogeneity within the Province. A comparison between the results of each index was made and the problems related to the use of such indices were examined.