Predictability of Functional Diversity Depends on the Number of Traits

Analysis of functional diversity, based on plant traits and community structure, provides a promising approach for exploration of the adaptive strategies of plants and the relationship between plant traits and ecosystem functioning. However, it is unclear how the number of plant traits included influences functional diversity, and whether or not there are quantitatively dependent traits. This information is fundamental to the correct use of functional diversity metrics. Here, we measured 34 traits of 366 plant species in nine forests from the tropical to boreal zones in China. These traits were used to calculate seven functional diversity metrics: functional richness(functional attribute diversity(FAD), modified FAD(MFAD), convex hull hypervolume(FRic)), functional evenness(FEve), and functional divergence(functional divergence(FDiv), functional dispersion(FDis), quadratic entropy(Rao Q)). Functional richness metrics increased with an increase in trait number, whereas the relationships between the trait divergence indexes(FDiv and FDis) and trait number were inconsistent. Four of the seven functional diversity indexes(FAD, MFAD, FRic, and RaoQ) were comparable with those in previous studies, showing predictable trends with a change in trait number. We verified our hypothesis that the number of traits strongly influences functional diversity. The relationships between these predictable functional diversity metrics and the number of traits facilitated the development of a standard protocol to enhance comparability across different studies. These findings can support integration of functional diversity index data from different studies at the site to the regional scale, and they focus attention on the influence of quantitative selection of traits on functional diversity analysis.

Contrasting effects of N fertilization and mowing on ecosystem multifunctionality in a meadow steppe

There is little experimental field evidence on how multiple essential land use intensification drivers(LUIDs),such as nitrogen(N)fertilization and mowing,interact to control ecosystem multifunctionality.Here,we conducted a 4-year field experiment in a meadow steppe in northeast China and evaluated the direct and indirect effects of mowing and N fertilization on a range of ecosystemfunctions associated with nutrient cycle,carbon stocks,and organic matter decomposition during the past 2 years of the experiment(2017 and 2018).Mowing had negative effects on the ecosystem multifunctionality index(EMF),carbon(C)cycle multifunctionality index(CCMF),and N cycle multifunctionality index(NCMF)in 2 years of sampling.However,in general,the responses of multifunctionality to N fertilization were ratespecific and year-dependent.N fertilization had positive effects on EMF,CCMF,NCMF,and phosphorus(P)cycle multifunctionality index(PCMF)in 2017,with the higher precipitation rate during the growing season,which was likely associated with the strong monsoon season.However,in 2018,EMF,CCMF,and NCMF increased at the lower N fertilization levels(£10 g N m^(-2) yr^(-1)),but decreased at higher N rates.N fertilization had consistent positive effects on PCMF in the 2 years of sampling.The effects of land use drivers on multifunctionality were indirectly influenced by bacterial biomass,plant richness,and soil moisture changes.Our results also indicated that the impacts of land use drivers on multifunctionality played an important role in maintaining a range of functions at low levels of functioning(<50% functional threshold).Low N fertilization levels(£10 g N m^(-2) yr^(-1))were able to reduce the negative effects of mowing on ecosystem multifunctionality while promoting plant biomass(food for livestock)and C storage.These findings are useful for designing practical strategies toward promoting multifunctionality by managing multiple LUIDs in a meadow steppe.

New Framework for Evaluating Ecosystem Quality in Nature Reserves based on Ideal References and Key Indicators

With increasing numbers and types of nature reserves(NRs),objective evaluation and comparison of the effects of different nature NRs on conservation efforts are of great importance for protecting species diversity,ensuring reasonable national economic input,and adjusting government management schemes.Developing a method for the combined assessment of flagship or umbrella species and ecosystem quality will improve the evaluation of NRs.However,it is also important to establish a new framework for rapid evaluation of ecosystem quality,supported by the advantages of scientific,economic,and regular principles.Here,we proposed a new framework that incorporates the novel concept of ideal references into evaluation systems,which will facilitate the comparison of results from different periods and regions.Furthermore,from the perspective of making the framework as objective,rapid,and economical as possible,we recommended some key ecological indicators,such as net primary productivity,soil organic matter,plant diversity,for use in the new evaluation framework.The new framework,referred to as“ideal reference and key indicators”(IRKI),can sufficiently meet the requirements for the rapid evaluation of ecosystem quality both regionally and nationally.Furthermore,IRKI can identify the restoration potential and restoration periods of NRs,thus facilitating the rational distribution of resources and enhancing the protective effect.There are many types of NRs in China,and it is necessary to partially alter the assessment methods or parameters for different types of NRs.Overall,IRKI provides a simple,clear,and comparable framework that will strongly enhance the conservation of protected areas(PAs)and facilitate the standardization of management practices.