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Ecosystem services are essential for human survival and wellbeing, and the quantity and quality of the services delivered by an ecosystem are dependent on its underlying condition. With many ecosystems degraded or in poor condition, the capacity to deliver key ecosystem services can be affected. The System of Environmental Economic Accounting – Ecosystem Accounting (SEEA EA) is the international statistical framework developed to estimate and monitor changes in ecosystem extent, condition, and flow of ecosystem services. Although the condition of ecosystems underpins their capacity to supply a service, the connection between ecosystem condition and ecosystem services accounts is underdeveloped. This is because condition is usually assessed relative to an ideal reference state, whereas capacity to supply ecosystem services depends on both the condition of the ecosystem and the ecosystem service being considered. For example, a forest in one condition may have very different capacities to supply ecosystem services such as timber provisioning and recreational services. We propose a methodology to better integrate condition and ecosystem services accounts through development of an ecosystem capacity index. Building on condition accounts, we derived a capacity index and related capacity accounts, reflecting the capacity of each ecosystem asset to support the delivery of selected ecosystem services. We show that an ecosystem with a particular condition profile may have different capacity index values depending on the ecosystem service that is expected to be delivered. We provide case studies from two sites in the Republic of Ireland to illustrate the integration of capacity indices into ecosystem services accounts. This approach is an extension to ecosystem accounting that enables more rigorous connection of condition to ecosystem service supply by accounting for capacity.

Abstract Eutrophication usually impacts grassland biodiversity, community composition, and biomass production, but its impact on the stability of these community aspects is unclear. One challenge is that stability has many facets that can be tightly correlated (low dimensionality) or highly disparate (high dimensionality). Using standardized experiments in 55 grassland sites from a globally distributed experiment (NutNet), we quantify the effects of nutrient addition on five facets of stability (temporal invariability, resistance during dry and wet growing seasons, recovery after dry and wet growing seasons), measured on three community aspects (aboveground biomass, community composition, and species richness). Nutrient addition reduces the temporal invariability and resistance of species richness and community composition during dry and wet growing seasons, but does not affect those of biomass. Different stability measures are largely uncorrelated under both ambient and eutrophic conditions, indicating consistently high dimensionality. Harnessing the dimensionality of ecological stability provides insights for predicting grassland responses to global environmental change.

Abstract Human activities are altering ecological communities around the globe. Understanding the implications of these changes requires that we consider the composition of those communities. However, composition can be summarized by many metrics which in turn are influenced by different ecological processes. For example, incidence‐based metrics strongly reflect species gains or losses, while abundance‐based metrics are minimally affected by changes in the abundance of small or uncommon species. Furthermore, metrics might be correlated with different predictors. We used a globally distributed experiment to examine variation in species composition within 60 grasslands on six continents. Each site had an identical experimental and sampling design: 24 plots × 4 years. We expressed compositional variation within each site—not across sites—using abundance‐ and incidence‐based metrics of the magnitude of dissimilarity (Bray–Curtis and Sorensen, respectively), abundance‐ and incidence‐based measures of the relative importance of replacement (balanced variation and species turnover, respectively), and species richness at two scales (per plot‐year [alpha] and per site [gamma]). Average compositional variation among all plot‐years at a site was high and similar to spatial variation among plots in the pretreatment year, but lower among years in untreated plots. For both types of metrics, most variation was due to replacement rather than nestedness. Differences among sites in overall within‐site compositional variation were related to several predictors. Environmental heterogeneity (expressed as the CV of total aboveground plant biomass in unfertilized plots of the site) was an important predictor for most metrics. Biomass production was a predictor of species turnover and of alpha diversity but not of other metrics. Continentality (measured as annual temperature range) was a strong predictor of Sorensen dissimilarity. Metrics of compositional variation are moderately correlated: knowing the magnitude of dissimilarity at a site provides little insight into whether the variation is driven by replacement processes. Overall, our understanding of compositional variation at a site is enhanced by considering multiple metrics simultaneously. Monitoring programs that explicitly incorporate these implications, both when designing sampling strategies and analyzing data, will have a stronger ability to understand the compositional variation of systems and to quantify the impacts of human activities.

Abstract The shape of mortality, or how mortality is spread across an organism's life course, is fundamental to a range of biological processes, with attempts to quantify it rooted in ecology, evolution, and demography. One approach to quantify the distribution of mortality over an organism's life is the use of entropy metrics whose values are interpreted within the classical framework of survivorship curves ranging from type I distributions, with mortality concentrated in late life stages, to type III survivorship curves associated with high early stage mortality. However, entropy metrics were originally developed using restricted taxonomic groups and the behavior of entropy metrics over larger scales of variation may make them unsuitable for wider‐ranging contemporary comparative studies. Here, we revisit the classic survivorship framework and, using a combination of simulations and comparative analysis of demography data spanning the animal and plant kingdoms, we show that commonly used entropy metrics cannot distinguish between the most extreme survivorship curves, which in turn can mask important macroecological patterns. We show how using H entropy masks a macroecological pattern of how parental care is associated with type I and type II species and for macroecological studies recommend the use of metrics, such as measures of area under the curve. Using frameworks and metrics that capture the full range of variation of survivorship curves will aid in our understanding of the links between the shape of mortality, population dynamics, and life history traits.

Abstract The invasive grass–fire cycle is a widely documented feedback phenomenon in which invasive grasses increase vegetation flammability and fire frequency, resulting in further invasion and compounded effects on fire regimes. Few studies have examined the role of short‐term adaptation in driving the invasive grass–fire cycle, despite invasive species often thriving after introduction to new environments. We used a replicated (nine locations), paired sampling design (burn vs unburnt sites) to test the hypothesis that roadside burning increases genetic diversity and thus adaptive potential in the invasive, high‐biomass grass Cenchrus ciliaris. Between four and five samples per site (n = 93) were genotyped using the DArTseq platform, and we filtered the data to produce panels of 15,965 neutral and 5030 non‐neutral single nucleotide polymorphism (SNP) markers. Using fastSTRUCTURE, we detected three distinct genetic clusters with extremely high FST values among them (0.94–0.97) suggesting three different cultivars. We found high rates of asexual reproduction, possibly related to clonality or apomixis common in this species. At three locations, burnt and unburnt sites were genetically different, but genetic structure was not consistently related to fire management across the study region. Burning was associated with high genetic diversity and sexual reproduction in one genetic cluster, but with low genetic diversity and clonality in another. Individual SNPs were associated with longitude and genetic clustering, but not with recent fire management. Overall, we found limited evidence that roadside burning consistently increased genetic diversity and adaptive potential in C. ciliaris; evolutionary and breeding history more strongly shaped genetic structure. Roadside burning could therefore continue to be used for managing biomass in this species, with continued monitoring. Our study provides a framework for detecting fire‐related changes on a genetic level–a process that could be used as an early warning system to detect the invasive grass–fire cycle in future.

Abstract Increasing demand for access to nature has the potential to increase environmental impacts. Identifying links between increased visitor intensity and habitat damage in context‐specific studies is an oversimplification which does not account for visitor demographics or activity characteristics. We compared the prevalence of tourism‐related threats/pressures across protected areas in Europe, Ireland, and in sites close to the Wild Atlantic Way (WAW) tourism route along the west coast of Ireland. To better understand the drivers of tourism‐related impacts, we analysed impact occurrence (IO) and impact severity (IS) at 43 sites along the WAW using a database of over 6000 visitor movement, demographic and behaviour records gathered by a national tourism agency (Fáilte Ireland). Threats/pressures related to tourism and recreation are prevalent and widespread across protected sites in Europe (49% of sites) with significantly higher (p

Experiments comparing diploids with polyploids and in single grassland sites show that nitrogen and/or phosphorus availability influences plant growth and community composition dependent on genome size; specifically, plants with larger genomes grow faster under nutrient enrichments relative to those with smaller genomes. However, it is unknown if these effects are specific to particular site localities with speciifc plant assemblages, climates, and historical contingencies. To determine the generality of genome size-dependent growth responses to nitrogen and phosphorus fertilization, we combined genome size and species abundance data from 27 coordinated grassland nutrient addition experiments in the Nutrient Network that occur in the Northern Hemisphere across a range of climates and grassland communities. We found that after nitrogen treatment, species with larger genomes generally increased more in cover compared to those with smaller genomes, potentially due to a release from nutrient limitation. Responses were strongest for C3 grasses and in less seasonal, low precipitation environments, indicating that genome size effects on water-use-efficiency modulates genome size-nutrient interactions. Cumulatively, the data suggest that genome size is informative and improves predictions of species' success in grassland communities.