Double sampling for stratification for the monitoring of sparse tree populations: the example of Populus euphratica Oliv. forests at the lower reaches of Tarim River, Southern Xinjiang, China

Abstract

Desertification is a pressing issue in the dry Tarim River basin, which is under anthropogenic stresses. In this study, double sampling for stratification (DSS) is employed to inventory Populus euphratica Oliv. forests in the lower reaches of the Tarim River Basin in Xinjiang, China. The two objectives were evaluating DSS as a sampling technique for monitoring desertification and generating baseline information for permanent observation. Here, DSS consists of two phases: in phase 1, crown cover is observed on a large sample of plots on a high resolution satellite image, and these photo-plots are stratified into five crown cover strata. Phase 2 is a stratified random sample from these photo-plots and the sampled plots are field observed. Approximately 32% of the study area is without P. euphratica trees. As expected, estimated mean poplar tree density and basal area increase with crown cover. DSS takes advantages of stratification (fieldwork efficiency and statistical precision) without the need for a priori strata delineation. It proves feasible for inventory the sparse poplar population and holds promise for the assessment of trees outside the forest, where density varies considerably and pre-stratification is intractable. It can be integrated into permanent observation systems for monitoring vegetation changes.

Trees outside forests in agricultural landscapes: spatial distribution and impact on habitat connectivity for forest organisms

“…Given this intrinsic limitation, simulations may provide usefuland cheap-information. TOF are generally assessed using stratified sampling and remote sensing-based approaches (Holmgren et al 1994;Corona and Fattorini 2006;Tokola 2006;Lam et al 2011;Baffetta et al 2011;Lister et al 2012;Meneguzzo et al 2013;Westinga et al 2013). A possible area of research would be to explore how point process models could be used to optimize field sampling and/or how point process simulation could be used to map TOF and complete the data available in forest inventories.…”

The benefit of synthetically generated RapidEye and Landsat 8 data fusion time series for riparian forest disturbance monitoring

“…Many areas in arid lands, including semi-arid and dry sub-humid lands, have sparse tree populations such as trees outside of forest, also defined as "other wooded land", where "tree canopy is between 5 and 10%". Trees outside forests play a major role in arid lands particularly where agroforestry systems are abundant (Lam et al, 2011). Arid land forests and wooded lands count for 6% of the world's forest area (Malagnoux, 2007).…”

“…For a consistent and comparable long time monitoring, twenty-five permanent sampling plots were established in 2005 (Lam et al, 2011) (Fig. 2.1).…”

“…Average monthly temperatures vary from just under −12 • C in January, to over 27 • C in July, while the annual average is at 11.7 • C. The area is dominated by open sandy areas with dense clusters of Populus euphratica along the riverbanks and to sparse isolated trees towards the desert. A forest inventory in 2004/2005 revealed that about 4500 P. euphratica trees exist within the study area (Lam et al, 2011).…”

Remote Sensing of Woodland Structure and Composition in the Sudano-Sahelian zone : Application of WorldView-2 and Landsat 8

“…A field campaign was performed during November and December 2012 in Saponé where data on tree attributes and land use were collected in strategically located field plots (Figure 4-5). A stratified random sampling procedure was applied in order to cover the range of tree densities and vegetation types present in the landscape (Lam, Kleinn, and Coenradie 2011). The stratification was achieved by partitioning the study areas into four classes based on normalized difference vegetation index (NDVI) thresholds using an October 2012 WorldView-2 image (Figure 4-5).…”