Andrew V. Bradley

Scale dependence in multitemporal mapping of forest fragmentation in Bolivia: implications for explaining temporal trends in landscape ecology and applications to biodiversity conservation☆

Landsat TM and ETM data were used to create forest/non-forest maps with which spatial patterns of forest fragmentation created by road building, agricultural colonisation and hydrocarbon exploration in Chapare (Bolivia) since the 1980s were analysed. Different spatial patterns of forest fragmentation were identified and analysed using landscape ecology metrics. These patterns are a function of their deforestation histories which, in turn, can be explained by a variety of Bolivian government policies. The relationships between landscape metrics and different simulated spatial resolutions of image data (from 30 to 1100 m) were also examined and most metrics were found to be highly dependent on pixel size. The implications of these findings for biodiversity conservation in humid tropical lowlands are considered.

Coca and Colonists: Quantifying and Explaining Forest Clearance under Coca and Anti-Narcotics Policy Regimes

The impacts of coca cultivation and coca eradication on rates of humid tropical forest clearance were examined in the agricultural colonization zone of Chapare, Bolivia. Using satellite image- derived land-use maps, interviews with farmers, and analyses of economic data and policy documents, forest clearance rates were analyzed in three contrasting communities from 1963 to 2003. Deforestation rates were very low from the late 1970s to the early 1990s when coca cultivation was widespread and anti- coca policies were weakly enforced. Before and after this period, deforestation rates were significantly higher. This study provides the first detailed quantitative analysis of deforestation rates under different policy regimes in a coca source region. It provides weak support for the argument that labor constraints lead to a reduction in forest clearance rates during periods of coca cultivation advanced by Kaimowitz (1997); but stronger support for Henkels (1995) hypothesis that farmers would clear large areas of forest after abandoning coca to maintain household incomes. However, economic arguments based on household data alone are inadequate in explaining forest clearance in this region, and a political ecological approach that analyses economic drivers in a policy framework provides better explains deforestation dynamics.

Spatial and temporal scale issues in determining biomass burning regimes in Bolivia and Peru

ATSR‐2 active fire data from 1996 to 2000, TRMM VIRS fire counts from 1998 to 2000 and burn scars derived from SPOT VEGETATION (the Global Burnt Area 2000 product) were mapped for Peru and Bolivia to analyse the spatial distribution of burning and its intra‐ and inter‐annual variability. The fire season in the region mainly occurs between May and October; though some variation was found between the six broad habitat types analysed: desert, grassland, savanna, dry forest, moist forest and yungas (the forested valleys on the eastern slope of the Andes). Increased levels of burning were generally recorded in ATSR‐2 and TRMM VIRS fire data in response to the 1997/1998 El Niño, but in some areas the El Niño effect was masked by the more marked influences of socio‐economic change on land use and land cover. There were differences between the three global datasets: ATSR‐2 under‐recorded fires in ecosystems with low net primary productivities. This was because fires are set during the day in this region and, when fuel loads are low, burn out before the ATSR‐2 overpass in the region which is between 02.45 h and 03.30 h. TRMM VIRS was able to detect these fires because its overpasses cover the entire diurnal range on a monthly basis. The GBA2000 product has significant errors of commission (particularly areas of shadow in the well‐dissected eastern Andes) and omission (in the agricultural zone around Santa Cruz, Bolivia and in north‐west Peru). Particular attention was paid to biomass burning in high‐altitude grasslands, where fire is an important pastoral management technique. Fires and burn scars from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) data for a range of years between 1987 and 2000 were mapped for areas around Parque Nacional Río Abiseo (Peru) and Parque Nacional Carrasco (Bolivia). Burn scars mapped in the grasslands of these two areas indicate far more burning had taken place than either the fires or the burn scars derived from global datasets. Mean scar sizes are smaller and have a smaller range in size between years the in the study area in Peru (6.6–7.1 ha) than Bolivia (16.9–162.5 ha). Trends in biomass burning in the two highland areas can be explained in terms of the changing socio‐economic environments and impacts of conservation. The mismatch between the spatial scale of biomass burning in the high‐altitude grasslands and the sensors used to derive global fire products means that an entire component of the fire regime in the region studied is omitted, despite its importance in the farming systems on the Andes.

BIOFRAG - a new database for analyzing BIOdiversity responses to forest FRAGmentation

Habitat fragmentation studies have produced complex results that are challenging to synthesize. Inconsistencies among studies may result from variation in the choice of landscape metrics and response variables, which is often compounded by a lack of key statistical or methodological information. Collating primary datasets on biodiversity responses to fragmentation in a consistent and flexible database permits simple data retrieval for subsequent analyses. We present a relational database that links such field data to taxonomic nomenclature, spatial and temporal plot attributes, and environmental characteristics. Field assessments include measurements of the response(s) (e.g., presence, abundance, ground cover) of one or more species linked to plots in fragments within a partially forested landscape. The database currently holds 9830 unique species recorded in plots of 58 unique landscapes in six of eight realms: mammals 315, birds 1286, herptiles 460, insects 4521, spiders 204, other arthropods 85, gastropods 70, annelids 8, platyhelminthes 4, Onychophora 2, vascular plants 2112, nonvascular plants and lichens 320, and fungi 449. Three landscapes were sampled as long-term time series (>10 years). Seven hundred and eleven species are found in two or more landscapes. Consolidating the substantial amount of primary data available on biodiversity responses to fragmentation in the context of land-use change and natural disturbances is an essential part of understanding the effects of increasing anthropogenic pressures on land. The consistent format of this database facilitates testing of generalizations concerning biologic responses to fragmentation across diverse systems and taxa. It also allows the re-examination of existing datasets with alternative landscape metrics and robust statistical methods, for example, helping to address pseudo-replication problems. The database can thus help researchers in producing broad syntheses of the effects of land use. The database is dynamic and inclusive, and contributions from individual and large-scale data-collection efforts are welcome.

Template phenology for vegetation models

To assist the representation of phenology in vegetation models we created several templates of phenology-driver relations by characterizing the annual phase differences between phenology and two phenology drivers. We did this using the results of a cross spectral analysis of MODIS EVI with radiation (CPTEC) and with precipitation (TRMM). Four phase ranges were identified for phenology-radiation and three phase ranges for phenology-precipitation. These ranges were classified and mapped together into 12 zones of our study area where particular phase relationships coincided. Around ~25% area was in phase with radiation, with varying phase ranges of precipitation, and ~16 % was in phase with precipitation with varying phase ranges of radiation. For each zone we conceptualized the phenology-driver relationships with phase lagged curves. The phase timing of these plots matched well with average time series plots from the same zones, but more work is needed on the representation of amplitude.

Exploring the Biophysical Drivers of Amazon Phenology: Preparing Data Sets to Improve Dynamic Global Vegetation Models

We explore the relative influence of biophysical drivers on phenology to assist validation and parameterization of Dynamic Global Vegetation Models. Using 6.8 years of MODIS data we created a vegetation index time series to map the spatial variability of vegetation phenology in the Amazon. TRMM and CERES data were used as a measure of two biophysical variables, precipitation and net radiation respectively. Using a Fourier transform and cross spectral analysis two aspects were considered from these data, the coincidence of: (A) spatial patterns, presence and strength in the annual cycle, and (B) the coherency and phase differences between the phenology and the biophysical variables. Using the Amazon as a study area we find that the coincidence between phenology and the drivers in annual power strength was not linear and in an area of high coherency we found radiation and phenology was almost in phase, whilst precipitation was not. The correspondence of slightly subdued annual phenology with strong annual radiation indicated that other drivers also influence the strength of the phenology.

The ESA climate change initiative: Merging burned area estimates for the Fire Essential Climate Variable

The ESA Fire Essential Climate Variable provides a 1km pixel and 0.5 degree grid burned area product by merging several burned area data sets to a set of user requirements for the climate, atmospheric and ecological modeling communities. A description of the merging is given from preliminary results during the first phase of the project. Allowing for errors, some contributed to by ongoing algorithm development, results are reported for a test site in northern Australia. In the pixel product 50-60% of the burned areas corresponded in at least two data sets allowing for an improvement on the earliest detection date and the confidence level of a burn. The grid product shows good spatial and temporal consistency in burned area whilst providing further information on measures of confidence, cloudiness, burned area patchiness and dominant vegetation burned, useful information for modeling burning dynamics.