Landscape Patterns of Tropical Forest Recovery in the Republic of Palau1

A GIS (geographic information systems) database was constructed from aerial photographs, a vegetation map, and topographic map data of the Ngeremeduu Bay Drainage Area (NBDA), Palau, to examine relationships between upland land cover dynamics, environmental variables, and past land use. In 1992, 82.9 percent of the NBDA was forest, 16.6 percent was grassland, and 0.5 percent consisted of village areas. Between 1947 and 1992, there was a 11.2 percent reduction of grassland area primarily due to a 10.9 percent increase in forest cover. These land cover changes led to larger, more continuous stretches of forest and numerous, highly fragmented grassland patches. Significant relationships (P 0.001) were found between the spatial distribution of forest and grassland cover and slope, elevation, soil pH, and percent soil organic matter. These patterns, however, may have resulted from past farm site selection rather than from ecological relationships. Our results indicate that areas of forest expansion were significantly (P 0.001) associated with the location of abandoned agricultural communities. In addition, over 92 percent of areas of forest expansion occurred within 100 m of established forest. These results suggest that the proximity of established forest facilitate forest recovery following human disturbance.     

Land cover dynamics of different topographic conditions in Beijing, China

Topographic conditions play an important role in controlling land cover dynamic processes. In this study, remotely sensed data and the geographic information system were applied to analyze the changes in land cover along topographic gradients from 1978 to 2001 in Beijing, a rapidly urbanized mega city in China. The study was based on five periods of land cover maps derived from remotely sensed data: Landsat MSS for 1978, Landsat TM for 1984, 1992, 1996 and 2001, and the digital elevation model (DEM) derived from 1:250,000 topographic map. The whole area was divided into ten land cover types: conifer forest, broadleaf forest, mixed forest, shrub, brushwood, meadow, farmland, built-up, water body and bare land. The results are summarized as follows. (1) Shrub, forest, farmland and builtup consist of the main land cover types of the Beijing area. The most significant land cover change from 1978 to 2001 was the decrease of the farmland and expansion of the builtup area. Farmland decreased from 6354 to 3813 km2 in the 23 years, while the built-up area increased from 421 to 2642 km2. Meanwhile, the coverage of forest increased from 17.2% to 24.7% of the total area. The conversion matrix analysis indicated that the transformation of farmland to the built-up area was the most significant process and afforestation was the primary cause of the replacement of shrub to forest. (2) Topographic conditions are of great importance to the distribution of land cover types and the process of land cover changes. Elevation has an intensive impact on the distribution of land cover types. The area below 100 m mostly consists of farmland and built-up areas, while the area above 100 m is mainly covered by shrub and forest. Shrub has the maximum frequency in areas between 100 and 1000 m, while forest has dominance in areas above 800 m. According to the analysis of land cover changes in different ranges of elevation, the greatest change below 100 m was the process of urbanization. The process of the main land cover change occurred above 100 m was the transformation from shrub to forest. This result was consistent with the vertical change of natural vegetation distribution in Beijing. (3) Slope has a great influence on the distribution of land cover. Farmland and built-up areas are mostly distributed in flat areas, while shrub and forest occupy steeper areas compared with other land cover types. Forest frequency increased with the increasing slope. Land cover changes differed from the slope gradients. In the plain area, the land cover change occurred as the result of urbanization. With the increasing of the slope gradient, afforestation, which converts shrub to forest, was the process of the primary land cover change. __________ Translated from Journal of Plant Ecology, 2006, 30(2): 239–251 [译自: 植物生态学报]     

A new land-cover map of Africa for the year 2000

Aim In the framework of the Global Land Cover 2000 (GLC 2000), a land‐cover map of Africa has been produced at a spatial resolution of 1 km using data from four sensors on‐board four different Earth observing satellites. Location The map documents the location and distribution of major vegetation types and non‐vegetated land surface formations for the entire African continent plus Madagascar and the other surrounding islands. Methods The bulk of these data were acquired on a daily basis throughout the year 2000 by the VEGETATION sensor on‐board the SPOT‐4 satellite. The map of vegetation cover has been produced based upon the spectral response and the temporal profile of the vegetation cover. Digital image processing and geographical information systems techniques were employed, together with local knowledge, high resolution imagery and expert consultation, to compile a cartographic map product. Radar data and thermal sensors were also used for specific land‐cover classes. Results A total of 27 land cover categories are documented, which has more thematic classes than previously published land cover maps of Africa contain. Systematic comparison with existing land cover data and 30‐m resolution imagery from Landsat are presented, and the map is also compared with other pan‐continental land cover maps. The map and digital data base are freely available for non‐commercial uses from http://www.gvm.jrc.it/tem/africa/products.htm Main conclusions The map improves our state of knowledge of the land‐cover of Africa and presents the most spatially detailed view yet published at this scale. This first version of the map should provide an important input for regional stratification and planning purposes for natural resources, biodiversity and climate studies.     

Random Forest characterization of upland vegetation and management burning from aerial imagery

Aim The upland moorlands of Great Britain form distinctive landscapes of international conservation importance, comprising mosaics of heathland, acid grassland, blanket bog and bracken. Much of this landscape is managed by rotational burning to create gamebird habitat and there is concern over whether this is driving long‐term changes in upland vegetation communities. However, the inaccessibility and scale of uplands means that monitoring changes in vegetation and burning practices is difficult. We aim to overcome this problem by developing methods to classify aerial imagery into high‐resolution maps of dominant vegetation cover, including the distribution of burns on managed grouse moors. Location  Peak District National Park, England, UK. Methods Colour and infrared aerial photographs were classified into seven dominant land‐cover classes using the Random Forest ensemble machine learning algorithm. In addition, heather (Calluna vulgaris) was further differentiated into growth phases, including sites that were newly burnt. We then analysed the distributions of the vegetation classes and managed burning using detrended correspondence analysis. Results Classification accuracy was c. 95% and produced a 5‐m resolution map for 514 km² of moorland. Cover classes were highly aggregated and strong nonlinear effects of elevation and slope and weaker effects of aspect and bedrock type were evident in structuring moorland vegetation communities. The classification revealed the spatial distribution of managed burning and suggested that relatively steep areas may be disproportionately burnt. Main conclusions Random Forest classification of aerial imagery is an efficient method for producing high‐resolution maps of upland vegetation. These may be used to monitor long‐term changes in vegetation and management burning and infer species–environment relationships and can therefore provide an important tool for effective conservation at the landscape scale.     

Woody vegetation dynamics in the tropical and subtropical Andes from 2001 to 2014: Satellite image interpretation and expert validation

The interactions between climate and land‐use change are dictating the distribution of flora and fauna and reshuffling biotic community composition around the world. Tropical mountains are particularly sensitive because they often have a high human population density, a long history of agriculture, range‐restricted species, and high‐beta diversity due to a steep elevation gradient. Here we evaluated the change in distribution of woody vegetation in the tropical Andes of South America for the period 2001–2014. For the analyses we created annual land‐cover/land‐use maps using MODIS satellite data at 250 m pixel resolution, calculated the cover of woody vegetation (trees and shrubs) in 9,274 hexagons of 115.47 km², and then determined if there was a statistically significant (p < 0.05) 14 year linear trend (positive—forest gain, negative—forest loss) within each hexagon. Of the 1,308 hexagons with significant trends, 36.6% (n = 479) lost forests and 63.4% (n = 829) gained forests. We estimated an overall net gain of ~500,000 ha in woody vegetation. Forest loss dominated the 1,000–1,499 m elevation zone and forest gain dominated above 1,500 m. The most important transitions were forest loss at lower elevations for pastures and croplands, forest gain in abandoned pastures and cropland in mid‐elevation areas, and shrub encroachment into highland grasslands. Expert validation confirmed the observed trends, but some areas of apparent forest gain were associated with new shade coffee, pine, or eucalypt plantations. In addition, after controlling for elevation and country, forest gain was associated with a decline in the rural population. Although we document an overall gain in forest cover, the recent reversal of forest gains in Colombia demonstrates that these coupled natural‐human systems are highly dynamic and there is an urgent need of a regional real‐time land‐use, biodiversity, and ecosystem services monitoring network.     

Global distribution and bioclimatic characterization of alpine biomes

Although there is a general consensus on the distribution and ecological features of terrestrial biomes, the allocation of alpine ecosystems in the global biogeographic system is still unclear. Here, we delineate a global map of alpine areas above the treeline by modelling regional treeline elevation at 30 m resolution, using global forest cover data and quantile regression. We then used global datasets to 1) assess the climatic characteristics of alpine ecosystems using principal component analysis, 2) define bioclimatic groups by an optimized cluster analysis and 3) evaluate patterns of primary productivity based on the normalized difference vegetation index. As defined here, alpine biomes cover 3.56 Mkm² or 2.64% of land outside Antarctica. Despite temperature differences across latitude, these ecosystems converge below a sharp threshold of 5.9°C and towards the colder end of the global climatic space. Below that temperature threshold, alpine ecosystems are influenced by a latitudinal gradient of mean annual temperature and they are climatically differentiated by seasonality and continentality. This gradient delineates a climatic envelope of global alpine biomes around temperate, boreal and tundra biomes as defined in Whittaker's scheme. Although alpine biomes are similarly dominated by poorly vegetated areas, world ecoregions show strong differences in the productivity of their alpine belt irrespectively of major climate zones. These results suggest that vegetation structure and function of alpine ecosystems are driven by regional and local contingencies in addition to macroclimatic factors.     

A new forest cover map of continental southeast Asia derived from SPOT‐VEGETATION satellite imagery

Question: Can recent satellite imagery of coarse spatial resolution support forest cover assessment and mapping at the regional level? Location: Continental southeast Asia. Methods: Forest cover mapping was based on digital classification of SPOT4‐VEGETATION satellite images of 1 km spatial resolution from the dry seasons 1998/1999 and 1999/2000. Following a geographical stratification, the spectral clusters were visually assigned to land cover classes. The forest classes were validated by an independent set of maps, derived from interpretation of satellite imagery of high spatial resolution (Landsat TM, 30 m). Forest area estimates from the regional forest cover map were compared to the forest figures of the FAO database. Results: The regional forest cover map displays 12 forest and land cover classes. The mapping of the region's deciduous and fragmented forest cover remained challenging. A high correlation was found between forest area estimates obtained from this map and from the Landsat TM derived maps. The regional and sub‐regional forest area estimates were close to those reported by FAO. Conclusion: SPOT4‐VEGETATION satellite imagery can be used for mapping consistently and uniformly the extent and distribution of the broad forest cover types at the regional scale. The new map can be considered as an update and improvement on existing regional forest cover maps.     

A new ecological-wind erosion model to simulate the impacts of aeolian transport on dryland vegetation patterns

Drylands cover more than 40% of the land surface of the Earth and are characterized by patchy vegetation and that permits erosion of the surface. Vegetation-aeolian transport is an important feedback in drylands, particularly those undergoing shrub encroachment. Although one side of the feedback, the influence of vegetation loss on aeolian transport, has been well studied, the other, the influence of aeolian transport on existing vegetation, has been never studied in detail. In this study, a new ecological-wind erosion model (ECO-WEMO) that contains an aeolian transport component was created to simulate how aeolian transport impacts vegetation pattern and causes the state change. Two modeling scenarios were investigated: 1) stable grass and shrub communities without/with aeolian transport and 2) unstable shrub and grass communities without/with aeolian transport disturbed by different drought conditions. The first scenario focuses on the simulation of the influence of aeolian transport on vegetation communities and the second scenario focuses on the simulation of the state change of vegetation communities. The results from the first scenario show that: First, the mean biomasses of grass and shrub become consistent in the case of no wind in both shrub-dominated and grass-dominated communities. Second, the mean biomass of shrub becomes higher than the grass in the case of wind in shrub-dominated communities and the mean biomass of grass becomes higher than the shrub in the case of wind in grass-dominated communities. Third, the dust flux of shrub-dominated communities is higher than the grass-dominated communities. Fourth, the net change in surface height in shrub-dominated communities has a considerably higher range than in grass-dominated communities. Fifth, the spatial pattern of shrub-dominated communities is sparser than the spatial pattern of grass in the vegetation communities in the case of wind. The results from the second scenario show that: First, the state change only took place from grass-dominated communities to shrub-dominated communities in the condition of drought. Second, the state change only took place in the case of wind. Third, the state change didn't take place after the slight and moderate droughts but only took place after the drought. Fourth, large vegetation biomass reduction only took place in the case of wind after the severe drought. Our results confirm, in a modeling context, the important role that aeolian transport can play in vegetation dynamics and state change in deserts.     

Nitrogen limitation and microbial diversity at the treeline

Tree growth limitation at treeline has mainly been studied in terms of carbon limitation while effects and mechanisms of potential nitrogen (N) limitation are barely known, especially in the southern hemisphere. We investigated how soil abiotic properties and microbial community structure and composition change from lower to upper sites within three vegetation belts (Nothofagus betuloides and N. pumilio forests, and alpine vegetation) across an elevation gradient (from 0 to 650 m a.s.l.) in Cordillera Darwin, southern Patagonia. Increasing elevation was associated with a decrease in soil N‐NH₄⁺ availability within the N. pumilio and the alpine vegetation belt. Within the alpine vegetation belt, a concurrent increase in the soil C:N ratio was associated with a shift from bacterial‐dominated in lower alpine sites to fungal‐dominated microbial communities in upper alpine sites. Lower forested belts (N. betuloides, N. pumilio) exhibited more complex patterns both in terms of soil properties and microbial communities. Overall, our results concur with recent findings from high‐latitude and altitude ecosystems showing decreased nutrient availability with elevation, leading to fungal‐dominated microbial communities. We suggest that growth limitation at treeline may result, in addition to proximal climatic parameters, from a competition between trees and soil microbial communities for limited soil inorganic N. At higher elevation, soil microbial communities could have comparably greater capacities to uptake soil N than trees, and the shift towards a fungal‐dominated community would favour N immobilization over N mineralization. Though evidences of altered nutrient dynamics in tree and alpine plant tissue with increasing altitude remain needed, we contend that the measured residual low amount of inorganic N available for trees in the soil could participate to the establishment limitation. Finally, our results suggest that responses of soil microbial communities to elevation could be influenced by functional properties of forest communities for instance through variations in litter quality.     

Spatial patterns of the Chaco vegetation of central Argentina: Integration of remote sensing and phytosociology

Abstract. In this study we report the first application of Landsat TM imagery to Chaco vegetation studies at a regional scale in Argentina. We produced a map showing 13 clearly differentiated land‐cover types, and described the composition and structure of the plant communities, in an area of almost 42002 km² in central Argentina. The land‐cover map obtained shows that the Chaco vegetation in central Argentina is highly disturbed. In the lowland part of the area the dominant land‐cover types are largely cultural landscapes and substitute shrublands, which have displaced the original Chaco forests, leaving only small isolated remnants generally confined to sites with some kind of constrain for agriculture. The use of TM images and the multivariate analysis of phytosociological data showed a qualified, high accuracy mapping capability for land‐cover types in the Chaco region (ca. 85% overall accuracy). Our results highlight the utility of TM and field data in a subtropical to warm‐temperate region, which is promising where other ancillary data are not available and a rapid acquisition of reliable vegetation data is required, so constituting a starting point for an imperative and more extensive classification and mapping of the endangered Chaco region.     

Influence of vegetation cover on evapotranspiration patterns in mountainous areas

The study presents results of calculation of potential evapotranspiration based on vegetation cover and actual solar energy income modeling obtained in the Jalovecky creek experimental hydrological basin in the Western Tatra mountains. Vegetation cover in the basin is represented by Bare rock, Grass, Natural grassland, Coniferous forest and Dwarf pine. Spatial evapotranspiration patterns for vegetation cover were calculated with three different methods build in the SOLEI model. They are Simple regression model, Radiation model by FAO and Penman-Monteith model. Vegetation cover is represented in all mentioned methods by albedo maps derived from the land use grid map. Together with Digital elevation model (DEM) it is the main input value to the SOLEI model. Albedo coefficients influence mainly solar energy income to the slopes. Because the Simple regression model and Radiation model by FAO are mainly based on solar energy income, the shapes of calculated spatial evapotranspiration patterns are similar to solar energy spatial maps. Results obtained from PenmanMonteith model are more closed to vegetation maps.     

Land cover dynamics of different topographic conditions in Beijing,China

Topographic conditions play an important role in controlling land cover dynamic processes.In this study,remotely sensed data and the geographic information system were applied to analyze the changes in land cover along topographic gradients from 1978 to 2001 in Beijing,a rapidly urbanized mega city in China.The study was based on five periods of land cover maps derived from remotely sensed data:Landsat MSS for 1978,Landsat TM for 1984,"1992,1996 and 2001,and the digital elevation model (DEM) derived from 1:250,000 topographic map.The whole area was divided into ten land cover types:conifer forest,broadleaf forest,mixed forest,shrub,brushwood,meadow,farmland,built-up,water body and bare land.The results are summarized as follows.(1) Shrub,forest,farmland and builtup consist of the main land cover types of the Beijing area.The most significant land cover change from 1978 to 2001 was the decrease of the farmland and expansion of the builtup area.Farmland decreased from 6354 to 3813 km2 in the 23 years,while the built-up area increased from 421 to 2642 km2.Meanwhile,the coverage of forest increased from 17.2% to 24.7% of the total area.The conversion matrix analysis indicated that the transformation of farmland to the built-up area was the most significant process and afforestation was the primary cause of the replacement of shrub to forest.(2) Topographic conditions are of great importance to the distribution of land cover types and the process of land cover changes.Elevation has an intensive impact on the distribution of land cover types.The area below 100 m mostly consists of farmland and built-up areas,while the area above 100 m is mainly covered by shrub and forest.Shrub has the maximum frequency in areas between 100 and 1000 m,while forest has dominance in areas above 800 m.According to the analysis of land cover changes in different ranges of elevation,the greatest change below 100 m was the process of urbanization.The process of the main land cover change occurred above 100 m was the transformation from shrub to forest.This result was consistent with the vertical change of natural vegetation distribution in Beijing.(3) Slope has a great influence on the distribution of land cover.Farmland and built-up areas are mostly distributed in fiat areas,while shrub and forest occupy steeper areas compared with other land cover types.Forest frequency increased with the increasing slope.Land cover changes differed from the slope gradients.In the plain area,the land cover change occurred as the result of urbanization.With the increasing of the slope gradient,afforestation,which converts shrub to forest,was the process of the primary land cover change.     

Potential effects of warming and drying on peatland plant community composition

Boreal peatlands may be particularly vulnerable to climate change, because temperature regimes that currently constrain biological activity in these regions are predicted to increase substantially within the next century. Changes in peatland plant community composition in response to climate change may alter nutrient availability, energy budgets, trace gas fluxes, and carbon storage. We investigated plant community response to warming and drying in a field mesocosm experiment in northern Minnesota, USA. Large intact soil monoliths removed from a bog and a fen received three infrared warming treatments crossed with three water‐table treatments (n = 3) for five years. Foliar cover of each species was estimated annually. In the bog, increases in soil temperature and decreases in water‐table elevation increased cover of shrubs by 50% and decreased cover of graminoids by 50%. The response of shrubs to warming was distinctly species‐specific, and ranged from increases (for Andromeda glaucophylla) to decreases (for Kalmia polifolia). In the fens, changes in plant cover were driven primarily by changes in water‐table elevation, and responses were species‐ and lifeform‐specific: increases in water‐table elevation increased cover of graminoids – in particular Carex lasiocarpa and Carex livida– as well as mosses. In contrast, decreases in water‐table elevation increased cover of shrubs, in particular A. glaucophylla and Chamaedaphne calyculata. The differential and sometimes opposite response of species and lifeforms to the treatments suggest that the structure and function of both bog and fen plant communities will change – in different directions or at different magnitudes – in response to warming and/or changes in water‐table elevation that may accompany regional or global climate change.     

The spatial distribution of vegetation types in the Serengeti ecosystem: the influence of rainfall and topographic relief on vegetation patch characteristics

Aim The aim of this study is to introduce a structural vegetation map of the Serengeti ecosystem and, based on the map, to test the relative influences of landscape factors on the spatial heterogeneity of vegetation in the ecosystem. Location This study was conducted in the Serengeti–Maasai Mara ecosystem in northern Tanzania and southern Kenya, between 34° and 36° E longitude, and 1° and 2° S latitude. Methods The vegetation map was produced from satellite imagery using data from over 800 ground‐truthing points. Spatial characteristics of the vegetation were analysed in the resulting map using the fragstats software package. Average patch area and nearest neighbour distance (NND) were determined for grassland, shrubland and woodland vegetation types. The heterogeneity of vegetation types was estimated with Simpson’s diversity index (D). Structural equation modelling (SEM) was used to explore the relationships between the spatial characteristics of vegetation and three predictor variables: annual rainfall, coefficient of variation (CV) in annual rainfall, and topographic moisture index (TMI). Results A vegetation map is presented along with a detailed summary of the distribution of land‐cover classes and spatial heterogeneity in the ecosystem. Significant relationships were found between vegetation diversity (D) and TMI, and also between D and average rainfall. The average area of grassland patches showed significant relationships with average rainfall, with rainfall CV and with TMI. Grassland NND was positively associated with average rainfall. Woodland patch area showed a unimodal response to average rainfall and a negative linear association with TMI. Woodland NND showed a U‐shaped association with annual rainfall and a weaker positive linear association with TMI. An acceptable model that explained variation in shrubland patch characteristics could not be identified. Main conclusions The vegetation map and analysis thereof resulted in three significant causal explanatory models that demonstrate that both rainfall and topography are important contributors to the distribution of woodlands and grasslands in the Serengeti. These findings further indicate that changes in patch characteristics have a complex interaction with rainfall and with topography. Our results are concordant with recent studies suggesting that percent woody cover in African savannas receiving less than c. 650 mm year^?1 is bounded by average annual rainfall.     

Estimating soil carbon fluxes following land-cover change: a test of some critical assumptions for a region in Costa Rica

Changes in soil carbon storage that accompany land‐cover change may have significant effects on the global carbon cycle. The objective of this work was to examine how assumptions about preconversion soil C storage and the effects of land‐cover change influence estimates of regional soil C storage. We applied three models of land‐cover change effects to two maps of preconversion soil C in a 140 000 ha area of northeastern Costa Rica. One preconversion soil C map was generated using values assigned to tropical wet forest from the literature, the second used values obtained from extensive field sampling. The first model of land‐cover change effects used values that are typically applied in global assessments, the second and third models used field data but differed in how the data were aggregated (one was based on land‐cover transitions and one was based on terrain attributes). Changes in regional soil C storage were estimated for each combination of model and preconversion soil C for three time periods defined by geo‐referenced land‐cover maps. The estimated regional soil C under forest vegetation (to 0.3 m) was higher in the map based on field data (10.03 Tg C) than in the map based on literature data (8.90 Tg C), although the range of values derived from propagating estimation errors was large (7.67–12.40 Tg C). Regional soil C storage declined through time due to forest clearing for pasture and crops. Estimated CO₂ fluxes depended more on the model of land‐cover change effects than on preconversion soil C. Cumulative soil C losses (1950–1996) under the literature model of land‐cover effects exceeded estimates based on field data by factors of 3.8–8.0. In order to better constrain regional and global‐scale assessments of carbon fluxes from soils in the tropics, future research should focus on methods for extrapolating regional‐scale constraints on soil C dynamics to larger spatial and temporal scales.     

Fine‐scale determinants of butterfly species richness and composition in a mountain region

Aim Global patterns of species richness are often considered to depend primarily on climate. We aimed to determine how topography and land cover affect species richness and composition at finer scales. Location Sierra de Guadarrama (central Iberian Peninsula). Methods We sampled the butterfly fauna of 180 locations (89 in 2004, 91 in 2005) at 600–2300 m elevation in a region of 10800 km². We recorded environmental variables at 100‐m resolution using GIS, and derived generalized linear models for species density (number of species per unit area) and expected richness (number of species standardized to number of individuals) based on variables of topoclimate (elevation and insolation) or land cover (vegetation type, geology and hydrology), or both (combined). We evaluated the models against independent data from the alternative study year. We also tested for differences in species composition among sites and years using constrained ordination (canonical correspondence analysis), and used variation partitioning analyses to quantify the independent and combined roles of topoclimate and land cover. Results Topoclimatic, land cover and combined models were significantly related to observed species density and expected richness. Topoclimatic and combined models outperformed models based on land cover variables, showing a humped elevational diversity gradient. Both topoclimate and land cover made significant contributions to models of species composition. Main conclusions Topoclimatic factors may dominate species richness patterns in regions with pronounced elevational gradients, as long as large areas of natural habitat remain. In contrast, both topoclimate and land cover may have important effects on species composition. Biodiversity conservation in mountainous regions therefore requires protection and management of natural habitats over a wide range of topoclimatic conditions, which may assist in facilitating range shifts and alleviating declines in species richness related to climate change.     

Evaluating strategies for facilitating native plant establishment in northern Nevada crested wheatgrass seedings

Non‐native crested wheatgrasses (Agropyron cristatum and A. desertorum) were used historically within the Great Basin for the purpose of competing with weed species and increasing livestock forage. These species continue to be used in some areas, especially after wildfires occurring in low elevation/precipitation, formerly Wyoming big sagebrush (Artemisia tridentata ssp. wyomingensis)/herbaceous communities. Seeding native species in these sites is often unsuccessful, and lack of establishment results in invasion and site dominance by exotic annuals. However, crested wheatgrass often forms dense monocultures that interfere competitively with the establishment of desirable native vegetation and do not provide the plant structure and habitat diversity for wildlife species equivalent to native‐dominated sagebrush plant communities. During a 5‐year study, we conducted trials to evaluate chemical and mechanical methods for reducing crested wheatgrass and the effectiveness of seeding native species into these sites after crested wheatgrass suppression. We determined that discing treatments were ineffective in reducing crested wheatgrass cover and even increased crested wheatgrass density in some cases. Glyphosate treatments initially reduced crested wheatgrass cover, but weeds increased in many treated plots and seeded species diminished over time as crested wheatgrass recovered. We concluded that, although increases in native species could possibly be obtained by repeating crested wheatgrass control treatments, reducing crested wheatgrass opens a window for invasion by exotic weed species.     

Terrestrial ecosystems from space: a review of earth observation products for macroecology applications

Aim Earth observation (EO) products are a valuable alternative to spectral vegetation indices. We discuss the availability of EO products for analysing patterns in macroecology, particularly related to vegetation, on a range of spatial and temporal scales. Location Global. Methods We discuss four groups of EO products: land cover/cover change, vegetation structure and ecosystem productivity, fire detection, and digital elevation models. We address important practical issues arising from their use, such as assumptions underlying product generation, product accuracy and product transferability between spatial scales. We investigate the potential of EO products for analysing terrestrial ecosystems. Results Land cover, productivity and fire products are generated from long‐term data using standardized algorithms to improve reliability in detecting change of land surfaces. Their global coverage renders them useful for macroecology. Their spatial resolution (e.g. GLOBCOVER vegetation, 300 m; MODIS vegetation and fire, ≥ 500 m; ASTER digital elevation, 30 m) can be a limiting factor. Canopy structure and productivity products are based on physical approaches and thus are independent of biome‐specific calibrations. Active fire locations are provided in near‐real time, while burnt area products show actual area burnt by fire. EO products can be assimilated into ecosystem models, and their validation information can be employed to calculate uncertainties during subsequent modelling. Main conclusions Owing to their global coverage and long‐term continuity, EO end products can significantly advance the field of macroecology. EO products allow analyses of spatial biodiversity, seasonal dynamics of biomass and productivity, and consequences of disturbances on regional to global scales. Remaining drawbacks include inter‐operability between products from different sensors and accuracy issues due to differences between assumptions and models underlying the generation of different EO products. Our review explains the nature of EO products and how they relate to particular ecological variables across scales to encourage their wider use in ecological applications.     

A land cover map of South America

A digital land cover map of South America has been produced using remotely sensed satellite data acquired between 1995 and the year 2000. The mapping scale is defined by the 1 km spatial resolution of the map grid‐cell. In order to realize the product, different sources of satellite data were used, each source providing either a particular parameter of land cover characteristic required by the legend, or mapping a particular land cover class. The map legend is designed both to fit requirements for regional climate modelling and for studies on land cover change. The legend is also compatible with a wider, global, land cover mapping exercise, which seeks to characterize the world's land surface for the year 2000. As a first step, the humid forest domain has been validated using a sample of high‐resolution satellite images. The map demonstrates both the major incursions of agriculture into the remaining forest domains and the extensive areas of agriculture, which now dominate South America's grasslands.