J.P.M. Witte

Cover‐weighted averaging of indicator values in vegetation analyses

Abstract Question: How should species cover be weighted when calculating average indicator values of vegetation relevés? Location: The Netherlands. Method: Various weighting methods were statistically investigated with 188 relevés from The Netherlands for which accurate groundwater levels were available. For each method the correlation between average Ellenberg indicator value for moisture and mean spring groundwater level was calculated. A permutation test on correlation coefficients revealed whether differences between methods were significant or not. Results: Optimization of a general weighting function did not produce a significantly higher correlation than disregarding cover and calculating the average as the arithmetical mean of indicator values. Giving a higher weight to species at both ends of the indicator scale and using indifferent species as indicators of mediocre conditions did improve the correlation significantly. Weighting species proportionate to their cover yielded a significantly lower correlation than the correlation obtained with the method that disregards cover. A significantly lower correlation was also established when taking into account the fact that cover is related to the growth strategy of species. Abbreviations: Fm = Site mean Ellenberg indicator value for moisture; MSL = Mean spring groundwater level.

Plant strategies in relation to resource supply in mesic to wet environments: does theory mirror nature?

In ecology, strategy schemes based on propositions about the selection of plant attributes are common, but quantification of such schemes in relation to nutrient and water supply is lacking. Through structural equation modeling, we tested whether plant strategies related to nutrient and water/oxygen supply are reflected in a coordination of traits in natural communities. Structural equation models, based on accepted ecological concepts, were tested with measured plant traits of 105 different species across 50 sites in mesic to wet plant communities in the Netherlands. For each site, nutrient and water supply were measured and modeled. Hypothesized multivariate strategy models only partly reflected current theoretical schemes. Alternative models were consistent, showing that lack of consistency of the original models was because of (i) strong correlations among traits that supposedly belong to different strategy components; (ii) poor understanding of mechanisms determining the covariation of plant maximum height, leaf size, and stem density; and (iii) lack of integrative and long‐term measures of nutrient supply needed to predict coordinated plant trait responses. Our main conclusion is that a combination of trade‐offs (partly) across different plant organs and diverging effects of resource supply ultimately determines the coordination of plant traits needed to “make a living.”

Ecological effects of water management in the Netherlands : the model DEMNAT

Abstract In the Netherlands extensive drainage of agricultural land and extraction of groundwater has caused a structural lowering of the phreatic groundwater level as well as a decreasing influence of upward seepage in the root zone of the soil with negative consequences for most groundwater-dependent ecosystems. In Dutch, this environmental stress is known as ‘verdroging’. The English term most frequently used is desiccation, but here the term is used with a broader interpretation, to include changes in (soil)water quality due to groundwater depletion. Since the late 1980s desiccation has been recognised by the Dutch government as a major environmental problem. As part of the development of abatement strategies various models have been built. These models are used to analyse the consequences of different water management scenarios for separate landuse functions, such as agriculture, shipping and public water supply. In order to account for the natural environment in these analyses the national ecohydrological model DEMNAT (Dose Effect Model NAture Terrestrial) was developed. A brief description is given of the latest model version. Moreover, results are discussed based on recent applications at national, regional, as well as local scales. Some perspectives for future model developments are discussed.

Leaf habit and woodiness regulate different leaf economy traits at a given nutrient supply

The large variation in the relationships between environmental factors and plant traits observed in natural communities exemplifies the alternative solutions that plants have developed in response to the same environmental limitations. Qualitative attributes, such as growth form, woodiness, and leaf habit can be used to approximate these alternative solutions. Here, we quantified the extent to which these attributes affect leaf trait values at a given resource supply level, using measured plant traits from 105 different species (254 observations) distributed across 50 sites in mesic to wet plant communities in The Netherlands. For each site, soil total N, soil total P, and water supply estimates were obtained by field measurements and modeling. Effects of growth forms, woodiness, and leaf habit on relations between leaf traits (SLA, specific leaf area; LNC, leaf nitrogen concentration; and LPC, leaf phosphorus concentration) vs. nutrient and water supply were quantified using maximum-likelihood methods and Bonferroni post hoc tests. The qualitative attributes explained 8-23% of the variance within sites in leaf traits vs. soil fertility relationships, and therefore they can potentially be used to make better predictions of global patterns of leaf traits in relation to nutrient supply. However, at a given soil fertility, the strength of the effect of each qualitative attribute was not the same for all leaf traits. These differences may imply a differential regulation of the leaf economy traits at a given nutrient supply, in which SLA and LPC seem to be regulated in accordance to changes in plant size and architecture while LNC seems to be primarily regulated at the leaf level by factors related to leaf longevity.

The need of data harmonization to derive robust empirical relationships between soil conditions and vegetation

Abstract Question: Is it possible to improve the general applicability and significance of empirical relationships between abiotic conditions and vegetation by harmonization of temporal data? Location: The Netherlands. Methods: Three datasets of vegetation, recorded after periods with different meteorological conditions, were used to analyze relationships between soil moisture regime (expressed by the mean spring groundwater level – MSLt calculated for different periods) and vegetation (expressed by the mean indicator value for moisture regime Fm). For each relevé, measured groundwater levels were interpolated and extrapolated to daily values for the period 1970–2000 by means of an impulse-response model. Sigmoid regression lines between MSLt and Fm were determined for each of the three datasets and for the combined dataset. Results: A measurement period of three years resulted in significantly different relationships between Fm and MSLt for the three datasets (F-test, p < 0.05). The three regression lines only coincided for the mean spring groundwater level computed over the period 1970–2000 (MSLclimate) and thus provided a general applicable relationship. Precipitation surplus prior to vegetation recordings strongly affected the relationships. Conclusions: Harmonization of time series data (1) eliminates biased measurements, (2) results in generally applicable relationships between abiotic and vegetation characteristics and (3) increases the goodness of fit of these relationships. The presented harmonization procedure can be used to optimize many relationships between soil and vegetation characteristics.

A model to predict and assess the impacts of hydrologic changes on terrestrial ecosystems in The Netherlands, and its use in a climate scenario

Current water management policy in The Netherlands aims to serve a multitude of land use functions, such as agriculture, industry, shipping, and drinking water supply. To attune this policy to the diversity of functions, computer models are used to predict the consequences of various policy options as a part of PAWN: the governments Policy Analysis of Water management for The Netherlands.Nature conservation and development is a relatively new aspect of water management policy. This article describes the PAWN model DEMNAT, which is designed to predict the impact of hydrologic changes on terrestrial ecosystems in The Netherlands. The main components of the model are explained and the predicted effects of an assumed climatic change are discussed.

Relationships between Nutrient-Related Plant Traits and Combinations of Soil N and P Fertility Measures

Soil fertility and nutrient-related plant functional traits are in general only moderately related, hindering the progress in trait-based prediction models of vegetation patterns. Although the relationships may have been obscured by suboptimal choices in how soil fertility is expressed, there has never been a systematic investigation into the suitability of fertility measures. This study, therefore, examined the effect of different soil fertility measures on the strength of fertility–trait relationships in 134 natural plant communities. In particular, for eight plot-mean traits we examined (1) whether different elements (N or P) have contrasting or shared influences, (2) which timescale of fertility measures (e.g. mineralization rates for one or five years) has better predictive power, and (3) if integrated fertility measures explain trait variation better than individual fertility measures. Soil N and P had large mutual effects on leaf nutrient concentrations, whereas they had element-specific effects on traits related to species composition (e.g. Grimes CSR strategy). The timescale of fertility measures only had a minor impact on fertility–trait relationships. Two integrated fertility measures (one reflecting overall fertility, another relative availability of soil N and P) were related significantly to most plant traits, but were not better in explaining trait variation than individual fertility measures. Using all fertility measures together, between-site variations of plant traits were explained only moderately for some traits (e.g. 33% for leaf N concentrations) but largely for others (e.g. 66% for whole-canopy P concentration). The moderate relationships were probably due to complex regulation mechanisms of fertility on traits, rather than to a wrong choice of fertility measures. We identified both mutual (i.e. shared) and divergent (i.e. element-specific and stoichiometric) effects of soil N and P on traits, implying the importance of explicitly considering the roles of different elements to properly interpret fertility–trait relationships.

Predicting leaf traits of herbaceous species from their spectral characteristics

Trait predictions from leaf spectral properties are mainly applied to tree species, while herbaceous systems received little attention in this topic. Whether similar trait–spectrum relations can be derived for herbaceous plants that differ strongly in growing strategy and environmental constraints is therefore unknown. We used partial least squares regression to relate key traits to leaf spectra (reflectance, transmittance, and absorbance) for 35 herbaceous species, sampled from a wide range of environmental conditions. Specific Leaf Area and nutrient-related traits (N and P content) were poorly predicted from any spectrum, although N prediction improved when expressed on a per area basis (mg/m2 leaf surface) instead of mass basis (mg/g dry matter). Leaf dry matter content was moderately to good correlated with spectra. We explain our results by the range of environmental constraints encountered by herbaceous species; both N and P limitations as well as a range of light and water availabilities occurred. This weakened the relation between the measured response traits and the leaf constituents that are truly responsible for leaf spectral behavior. Indeed, N predictions improve considering solely upper or under canopy species. Therefore, trait predictions in herbaceous systems should focus on traits relating to dry matter content and the true, underlying drivers of spectral properties.

Incorporating microbial ecology concepts into global soil mineralization models to improve predictions of carbon and nitrogen fluxes

Global models of soil carbon (C) and nitrogen (N) fluxes become increasingly needed to describe climate change impacts, yet they typically have limited ability to reflect microbial activities that may affect global-scale soil dynamics. Benefiting from recent advances in microbial knowledge, we evaluated critical assumptions on microbial processes to be applied in global models. We conducted a sensitivity analysis of soil respiration rates (Cmin) and N mineralization rates (Nmin) for different model structures and parameters regarding microbial processes and validated them with laboratory incubation data of diverse soils. Predicted Cmin was sensitive to microbial biomass, and the model fit to observed Cmin improved when using site-specific microbial biomass. Cmin was less affected by the approach of microbial substrate consumption (i.e., linear, multiplicative, or Michaelis-Menten kinetics). The sensitivity of Cmin to increasing soil N fertility was idiosyncratic and depended on the assumed mechanism of microbial C:N stoichiometry effects: a C overflow mechanism upon N limitation (with decreased microbial growth efficiency) led to the best model fit. Altogether, inclusion of microbial processes reduced prediction errors by 26% (for Cmin) and 7% (for Nmin) in our validation data set. Our study identified two important aspects to incorporate into global models: site-specific microbial biomass and microbial C:N stoichiometry effects. The former requires better understandings of spatial patterns of microbial biomass and its drivers, while the latter urges for further conceptual progress on C-N interactions. With such advancements, we envision improved predictions of global C and N fluxes for a current and projected climate.

Mapping ecosystem types by means of ecological species groups

Abstract A method is presented to deduce nation-wide maps of ecosystem types from FLORBASE. This national database contains data, per km 2 , on the presence of indigenous plant species that grow in the wild. The ecosystem types on the maps are defined on the basis of abiotic factors that determine the plant species composition of the vegetation in the Netherlands: salinity, moisture regime, nutrient availability, acidity. Water management measures may cause changes in these four factors and, as a result, change the species composition of the vegetation. For the construction of the maps, species of the Dutch flora are first allotted to the ecosystem types. Then, on the basis of both the number and the indicative value of species, a botanical quality class of each km 2 is assessed for each ecosystem map. The boundaries of the quality classes are obtained by expert judgement. It is possible, however, to compute class boundaries with a mathematical procedure, also for grid cells larger than 1 km 2 . The maps are corrected for regional differences in the detail of the plant inventories.