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

Improved exponential type ratio estimator in double sampling for stratification

The objective of this research is to create a chain-ratio-type exponential estimator in order to estimate the finite population mean in double sampling for stratification. An estimator for population mean has been constructed based on the concept of chain-ratio estimators. The constructed estimator is compared to the standard unbiased estimator, as well as the other relevant existing estimators and conditions are shown to yield better results in terms of efficiency. To support the theoretical results the study has been done on both natural as well as simulated populations.

The Euphrates Poplar Responses to Abiotic Stress and Its Unique Traits in Dry Regions of China (Xinjiang and Inner Mongolia): What Should We Know?

At the moment, drought, salinity, and low-temperature stress are ubiquitous environmental issues. In arid regions including Xinjiang and Inner Mongolia and other areas worldwide, the area of tree plantations appears to be rising, triggering tree growth. Water is a vital resource in the agricultural systems of countries impacted by aridity and salinity. Worldwide efforts to reduce quantitative yield losses on Populus euphratica by adapting tree plant production to unfavorable environmental conditions have been made in response to the responsiveness of the increasing control of water stress. Although there has been much advancement in identifying the genes that resist abiotic stresses, little is known about how plants such as P. euphratica deal with numerous abiotic stresses. P. euphratica is a varied riparian plant that can tolerate drought, salinity, low temperatures, and climate change, and has a variety of water stress adaptability abilities. To conduct this review, we gathered all available information throughout the Web of Science, the Chinese National Knowledge Infrastructure, and the National Center for Biotechnology Information on the impact of abiotic stress on the molecular mechanism and evolution of gene families at the transcription level. The data demonstrated that P. euphratica might gradually adapt its stomatal aperture, photosynthesis, antioxidant activities, xylem architecture, and hydraulic conductivity to endure extreme drought and salt stress. Our analyses will give readers an understanding of how to manage a gene family in desert trees and the influence of abiotic stresses on the productivity of tree plants. They will also give readers the knowledge necessary to improve biotechnology-based tree plant stress tolerance for sustaining yield and quality trees in China's arid regions.

Agricultural water allocation with climate change based on gray wolf optimization in a semi-arid region of China

Background

We quantified and evaluated the allocation of soil and water resources in the Aksu River Basin to measure the consequences of climate change on an agricultural irrigation system.

Methods

We first simulated future climate scenarios in the Aksu River Basin by using a statistical downscaling model (SDSM). We then formulated the optimal allocation scheme of agricultural water as a multiobjective optimization problem and obtained the Pareto optimal solution using the multi-objective grey wolf optimizer (MOGWO). Finally, optimal allocations of water and land resources in the basin at different times were obtained using an analytic hierarchy process (AHP).

Results

(1) The SDSM is able to simulate future climate change scenarios in the Aksu River Basin. Evapotranspiration (ET₀) will increase significantly with variation as will the amount of available water albeit slightly. (2) To alleviate water pressure, the area of cropland should be reduced by 127.5 km² under RCP4.5 and 377.2 km² under RCP8.5 scenarios. (3) To be sustainable, the allocation ratio of forest land and water body should increase to 39% of the total water resource in the Aksu River Basin by 2050.

Monitoring trees outside forests: a review

Trees outside forests (TOFs) are an important natural resource that contributes substantially to national biomass and carbon stocks and to the livelihood of people in many regions. Over the last decades, decision makers have become increasingly aware of the importance of TOF, and as a consequence, this tree resource is nowadays often considered in forest monitoring systems. Our review shows that in many cases, TOF are included in national forest inventories, applying traditional methodologies with relatively sparse networks of field sample plots. Only in some countries, such as India, the design of the inventories has considered the special features of how TOFs occur in the landscape. Several research studies utilising remote sensing for monitoring TOF have been conducted lately, but very few studies include comparative studies to optimise sampling strategies for TOF. Our review indicates that methods combining remote sensing and field surveys appear to be very promising, especially when remote sensing techniques that assess both the horizontal and vertical structures of tree resources are applied. For example, two-phase sampling strategies with laser scanning in the first phase and a field survey in the second phase appear to be effective for assessing TOF resources. However, TOFs often exhibit different characteristics than forest trees. Thus, to improve TOF monitoring, there is often a need to develop models, e.g. for biomass assessment, that are specifically adapted to this tree resource. Alternatively, field-based remote sensing methods that provide structural information about individual trees, notably terrestrial laser scanning, could be further developed for TOF monitoring applications. This also would have a potential to reduce the problem of accessing TOF during field surveys, which is a problem, for example, in countries where TOF are present on intensively utilised private grounds like gardens and agricultural fields.

Tree crown mapping in managed woodlands (parklands) of semi-arid West Africa using WorldView-2 imagery and geographic object based image analysis

Detailed information on tree cover structure is critical for research and monitoring programs targeting African woodlands, including agroforestry parklands. High spatial resolution satellite imagery represents a potentially effective alternative to field-based surveys, but requires the development of accurate methods to automate information extraction. This study presents a method for tree crown mapping based on Geographic Object Based Image Analysis (GEOBIA) that use spectral and geometric information to detect and delineate individual tree crowns and crown clusters. The method was implemented on a WorldView-2 image acquired over the parklands of Saponé, Burkina Faso, and rigorously evaluated against field reference data. The overall detection rate was 85.4% for individual tree crowns and crown clusters, with lower accuracies in areas with high tree density and dense understory vegetation. The overall delineation error (expressed as the difference between area of delineated object and crown area measured in the field) was 45.6% for individual tree crowns and 61.5% for crown clusters. Delineation accuracies were higher for medium (35-100 m(2)) and large (≥100 m(2)) trees compared to small (<35 m(2)) trees. The results indicate potential of GEOBIA and WorldView-2 imagery for tree crown mapping in parkland landscapes and similar woodland areas.