ABSTRACT
Globally increased nitrogen (N) to phosphorus (P) ratios (N/P) affect the structure and functioning of terrestrial ecosystems, but few studies have addressed the variation of foliar N/P over time in subtropical forests. Foliar N/P indicates N versus P limitation in terrestrial ecosystems. Quantifying long-term dynamics of foliar N/P and their potential drivers is crucial for predicting nutrient status and functioning in forest ecosystems under global change. We detected temporal trends of foliar N/P, quantitatively estimated their potential drivers and their interaction between plant types (evergreen vs. deciduous and trees vs. shrubs), using 1811 herbarium specimens of 12 widely distributed species collected during 1920-2010 across China's subtropical forests. We found significant decreases in foliar P concentrations (23.1%) and increases in foliar N/P (21.2%). Foliar N/P increased more in evergreen species (22.9%) than in deciduous species (16.9%). Changes in atmospheric CO2 concentrations ( P CO 2 $$ {\mathrm{P}}_{{\mathrm{CO}}_2} $$ ), atmospheric N deposition and mean annual temperature (MAT) dominantly contributed to the increased foliar N/P of evergreen species, while P CO 2 $$ {\mathrm{P}}_{{\mathrm{CO}}_2} $$ , MAT, and vapor pressure deficit, to that of deciduous species. Under future Shared Socioeconomic Pathway (SSP) scenarios, increasing MAT and P CO 2 $$ {\mathrm{P}}_{{\mathrm{CO}}_2} $$ would continuously increase more foliar N/P in deciduous species than in evergreen species, with more 12.9%, 17.7%, and 19.4% versus 6.1%, 7.9%, and 8.9% of magnitudes under the scenarios of SSP1-2.6, SSP3-7.0, and SSP5-8.5, respectively. The results suggest that global change has intensified and will progressively aggravate N-P imbalance, further altering community composition and ecosystem functioning of subtropical forests.
Subject(s)
Ecosystem , Forests , Nitrogen , Phosphorus , ChinaABSTRACT
This article is a systematic review of reverse screening methods used to search for the protein targets of chemopreventive compounds or drugs. Typical chemopreventive compounds include components of traditional Chinese medicine, natural compounds and Food and Drug Administration (FDA)-approved drugs. Such compounds are somewhat selective but are predisposed to bind multiple protein targets distributed throughout diverse signaling pathways in human cells. In contrast to conventional virtual screening, which identifies the ligands of a targeted protein from a compound database, reverse screening is used to identify the potential targets or unintended targets of a given compound from a large number of receptors by examining their known ligands or crystal structures. This method, also known as in silico or computational target fishing, is highly valuable for discovering the target receptors of query molecules from terrestrial or marine natural products, exploring the molecular mechanisms of chemopreventive compounds, finding alternative indications of existing drugs by drug repositioning, and detecting adverse drug reactions and drug toxicity. Reverse screening can be divided into three major groups: shape screening, pharmacophore screening and reverse docking. Several large software packages, such as Schrödinger and Discovery Studio; typical software/network services such as ChemMapper, PharmMapper, idTarget, and INVDOCK; and practical databases of known target ligands and receptor crystal structures, such as ChEMBL, BindingDB, and the Protein Data Bank (PDB), are available for use in these computational methods. Different programs, online services and databases have different applications and constraints. Here, we conducted a systematic analysis and multilevel classification of the computational programs, online services and compound libraries available for shape screening, pharmacophore screening and reverse docking to enable non-specialist users to quickly learn and grasp the types of calculations used in protein target fishing. In addition, we review the main features of these methods, programs and databases and provide a variety of examples illustrating the application of one or a combination of reverse screening methods for accurate target prediction.