A general framework for quantifying the effects of land-use history on ecosystem dynamics

Land-use legacies are important for explaining present-day ecological patterns and processes. However, an overarching approach to quantify land-use history effects on ecosystem properties is lacking, mainly due to the scarcity of high-quality, complete and detailed data on past land use. We propose a general framework for quantifying the effects of land-use history on ecosystem properties, which is applicable (i) to different ecological processes in various ecosystem types and across trophic levels; and (ii) when historical data are incomplete or of variable quality. The conceptual foundation of our framework is that past land use affects current (and future) ecosystem properties through altering the past values of resources and conditions that are the driving variables of ecosystem responses. We describe and illustrate how Markov chains can be applied to derive past time series of driving variables, and how these time series can be used to improve our understanding of present-day ecosystem properties. We present our framework in a stepwise manner, elucidating its general nature. We illustrate its application through a case study on the importance of past light levels for the contemporary understorey composition of temperate deciduous forest. We found that the understorey shows legacies of past forest management: high past light availability lead to a low proportion of typical forest species in the understorey. Our framework can be a useful tool for quantifying the effect of past land use on ecological patterns and processes and enhancing our understanding of ecosystem dynamics by including legacy effects which have often been ignored

Seasonal drivers of understorey temperature buffering in temperate deciduous forests across Europe.

Aim:Forest understorey microclimates are often buffered against extreme heat or cold, with important implications for the organisms living in these environments. We quantified seasonal effects of understorey microclimate predictors describing canopy structure, canopy composition and topography (i.e., local factors) and the forest patch size and distance to the coast (i.e., landscape factors). Location:Temperate forests in Europe. Time period:2017-2018. Major taxa studied:Woody plants. Methods:We combined data from a microclimate sensor network with weather-station records to calculate the difference, or offset, between temperatures measured inside and outside forests. We used regression analysis to study the effects of local and landscape factors on the seasonal offset of minimum, mean and maximum temperatures. Results:The maximum temperature during the summer was on average cooler by 2.1 °C inside than outside forests, and the minimum temperatures during the winter and spring were 0.4 and 0.9 °C warmer. The local canopy cover was a strong nonlinear driver of the maximum temperature offset during summer, and we found increased cooling beneath tree species that cast the deepest shade. Seasonal offsets of minimum temperature were mainly regulated by landscape and topographic features, such as the distance to the coast and topographic position. Main conclusions:Forest organisms experience less severe temperature extremes than suggested by currently available macroclimate data; therefore, climate-species relationships and the responses of species to anthropogenic global warming cannot be modelled accurately in forests using macroclimate data alone. Changes in canopy cover and composition will strongly modulate the warming of maximum temperatures in forest understories, with important implications for understanding the responses of forest biodiversity and functioning to the combined threats of land-use change and climate change. Our predictive models are generally applicable across lowland temperate deciduous forests, providing ecologically important microclimate data for forest understories

Responses of competitive understorey species to spatial environmental gradients inaccurately explain temporal changes

Understorey plant communities play a key role in the functioning of forest ecosystems. Under favourable environmental conditions, competitive understorey species may develop high abundances and influence important ecosystem processes such as tree regeneration. Thus, understanding and predicting the response of competitive understorey species as a function of changing environmental conditions is important for forest managers. In the absence of sufficient temporal data to quantify actual vegetation changes, space-for-time (SFT) substitution is often used, i.e. studies that use environmental gradients across space to infer vegetation responses to environmental change over time. Here we assess the validity of such SFT approaches and analysed 36 resurvey studies from ancient forests with low levels of recent disturbances across temperate Europe to assess how six competitive understorey plant species respond to gradients of overstorey cover, soil conditions, atmospheric N deposition and climatic conditions over space and time. The combination of historical and contemporary surveys allows (i) to test if observed contemporary patterns across space are consistent at the time of the historical survey, and, crucially, (ii) to assess whether changes in abundance over time given recorded environmental change match expectations from patterns recorded along environmental gradients in space. We found consistent spatial relationships at the two periods: local variation in soil variables and overstorey cover were the best predictors of individual species’ cover while interregional variation in coarse-scale variables, i.e. N deposition and climate, was less important. However, we found that our SFT approach could not accurately explain the large variation in abundance changes over time. We thus recommend to be cautious when using SFT substitution to infer species responses to temporal changes.</p

Forest microclimate dynamics drive plant responses to warming

Climate warming is causing a shift in biological communities in favor of warm-affinity species (i.e., thermophilization). Species responses often lag behind climate warming, but the reasons for such lags remain largely unknown. Here, we analyzed multidecadal understory microclimate dynamics in European forests and show that thermophilization and the climatic lag in forest plant communities are primarily controlled by microclimate. Increasing tree canopy cover reduces warming rates inside forests, but loss of canopy cover leads to increased local heat that exacerbates the disequilibrium between community responses and climate change. Reciprocal effects between plants and microclimates are key to understanding the response of forest biodiversity and functioning to climate and land-use changes

Combining biodiversity resurveys across regions to advance global change research

More and more ecologists have started to resurvey communities sampled in earlier decades to determine long-term shifts in community composition and infer the likely drivers of the ecological changes observed. However, to assess the relative importance of and interactions among multiple drivers, joint analyses of resurvey data from many regions spanning large environmental gradients are needed. In this article, we illustrate how combining resurvey data from multiple regions can increase the likelihood of driver orthogonality within the design and show that repeatedly surveying across multiple regions provides higher representativeness and comprehensiveness, allowing us to answer more completely a broader range of questions. We provide general guidelines to aid the implementation of multiregion resurvey databases. In so doing, we aim to encourage resurvey database development across other community types and biomes to advance global environmental change research

Replacements of small- by large-ranged species scale up to diversity loss in Europe’s temperate forest biome

The loss of biodiversity at the global scale has been difficult to reconcile with observations of no net loss at local scales. Vegetation surveys across European temperate forests show that this may be explained by the replacement of small-ranged species with large-ranged ones, driven by nitrogen deposition. Biodiversity time series reveal global losses and accelerated redistributions of species, but no net loss in local species richness. To better understand how these patterns are linked, we quantify how individual species trajectories scale up to diversity changes using data from 68 vegetation resurvey studies of seminatural forests in Europe. Herb-layer species with small geographic ranges are being replaced by more widely distributed species, and our results suggest that this is due less to species abundances than to species nitrogen niches. Nitrogen deposition accelerates the extinctions of small-ranged, nitrogen-efficient plants and colonization by broadly distributed, nitrogen-demanding plants (including non-natives). Despite no net change in species richness at the spatial scale of a study site, the losses of small-ranged species reduce biome-scale (gamma) diversity. These results provide one mechanism to explain the directional replacement of small-ranged species within sites and thus explain patterns of biodiversity change across spatial scales

Observer and relocation errors matter in resurveys of historical vegetation plots

Aim: Revisits of non-permanent, relocatable plots first surveyed several decades ago offer a direct way to observe vegetation change and form a unique and increasingly used source of information for global change research. Despite the important insights that can be obtained from resurveying these quasi-permanent vegetation plots, their use is prone to both observer and relocation errors. Studying the combined effects of both error types is important since they will play out together in practice and it is yet unknown to what extent observed vegetation changes are influenced by these errors. Methods: We designed a study that mimicked all steps in a resurvey study and that allowed determination of the magnitude of observer errors only vs the joint observer and relocation errors. Communities of vascular plants growing in the understorey of temperate forests were selected as study system. Ten regions in Europe were covered to explore generality across contexts and 50 observers were involved, which deliberately differed in their experience in making vegetation records. Results: The mean geographic distance between plots in the observer+relocation error data set was 24m. The mean relative difference in species richness in the observer error and the observer+relocation data set was 15% and 21%, respectively. The mean pseudo-turnover between the five records at a quasi-permanent plot location was on average 0.21 and 0.35 for the observer error and observer+relocation error data sets, respectively. More detailed analyses of the compositional variation showed that the nestedness and turnover components were of equal importance in the observer data set, whereas turnover was much more important than nestedness in the observer+relocation data set. Interestingly, the differences between the observer and the observer+relocation data sets largely disappeared when looking at temporal change: both the changes in species richness and species composition over time were very similar in these data sets. Conclusions: Our results demonstrate that observer and relocation errors are non-negligible when resurveying quasi-permanent plots. A careful interpretation of the results of resurvey studies is warranted, especially when changes are assessed based on a low number of plots. We conclude by listing measures that should be taken to maximally increase the precision and the strength of the inferences drawn from vegetation resurveys

Evaluating structural and compositional canopy characteristics to predict the light‐demand signature of the forest understorey in mixed, semi‐natural temperate forests

Questions: Light availability at the forest floor affects many forest ecosystem processes, and is often quantified indirectly through easy‐to‐measure stand characteristics. We investigated how three such characteristics, basal area, canopy cover and canopy closure, were related to each other in structurally complex mixed forests. We also asked how well they can predict the light‐demand signature of the forest understorey (estimated as the mean Ellenberg indicator value for light [“EIVLIGHT”] and the proportion of “forest specialists” [“%FS”] within the plots). Furthermore, we asked whether accounting for the shade‐casting ability of individual canopy species could improve predictions of EIVLIGHT and %FS. Location: A total of 192 study plots from nineteen temperate forest regions across Europe. Methods: In each plot, we measured stand basal area (all stems >7.5 cm diameter), canopy closure (with a densiometer) and visually estimated the percentage cover of all plant species in the herb (7 m). We used linear mixed‐effect models to assess the relationships between basal area, canopy cover and canopy closure. We performed model comparisons, based on R2 and the Akaike Information Criterion (AIC), to assess which stand characteristics can predict EIVLIGHT and %FS best, and to assess whether canopy shade‐casting ability can significantly improve model fit. Results: Canopy closure and cover were weakly related to each other, but showed no relation with basal area. For both EIVLIGHT and %FS, canopy cover was the best predictor. Including the share of high‐shade‐casting species in both the basal‐area and cover models improved the model fit for EIVLIGHT, but not for %FS. Conclusions: The typically expected relationships between basal area, canopy cover and canopy closure were weak or even absent in structurally complex mixed forests. In these forests, easy‐to‐measure structural canopy characteristics were poor predictors of the understorey light‐demand signature, but accounting for compositional characteristics could improve predictions