Biological records are often the data of choice for training predictive species distribution models (SDMs), but spatial sampling bias is pervasive in biological records data at multiple spatial scales and is thought to impair the performance of SDMs. We simulated presences and absences of virtual species as well as the process of recording these species to evaluate the effect on species distribution model prediction performance of (1) spatial bias in training data, (2) sample size (the average number of observations per species), and (3) the choice of species distribution modelling method. Our approach is novel in quantifying and applying real-world spatial sampling biases to simulated data. Spatial bias in training data decreased species distribution model prediction performance, but sample size and the choice of modelling method were more important than spatial bias in determining the prediction performance of species distribution models.
To fully understand ecosystem functioning under global change, we need to be able to measure the stability of ecosystem functioning at multiple spatial scales. Although a number of stability components have been established at small spatial scales, there has been little progress in scaling these measures up to the landscape. Remote sensing data holds huge potential for studying processes at landscape scales but requires quantitative measures that are comparable from experimental field data to satellite remote sensing. Here we present a methodology to extract four components of ecosystem functioning stability from satellite-derived time series of Enhanced Vegetation Index (EVI) data. The four stability components are as follows: variability, resistance, recovery time and recovery rate in ecosystem functioning. We apply our method to the island of Ireland to demonstrate the use of remotely sensed data to identify large disturbance events in productivity. Our method uses stability measures that have been established at the field-plot scale to quantify the stability of ecosystem functioning. This makes our method consistent with previous small-scale stability research, whilst dealing with the unique challenges of using remotely sensed data including noise. We encourage the use of remotely-sensed data in assessing the stability of ecosystems at a scale that is relevant to conservation and management practices.
The impact of productivity on species diversity is often studied at small spatial scales and without taking additional environmental factors into account. Focusing on small spatial scales removes important regional scale effects, such as the role of land cover heterogeneity. Here, we use a regional spatial scale (10 km square) to establish the relationship between productivity and vascular plant species richness across the island of Ireland that takes into account variation in land cover. We used generalized additive mixed effects models to relate species richness, estimated from biological records, to plant productivity. Productivity was quantified by the satellite-derived enhanced vegetation index. The productivity-diversity relationship was fitted for three land cover types: pasture-dominated, heterogeneous, and non-pasture-dominated landscapes. We find that species richness decreases with increasing productivity, especially at higher productivity levels. This decreasing relationship appears to be driven by pasture-dominated areas. The relationship between species richness and heterogeneity in productivity (both spatial and temporal) varies with land cover. Our results suggest that the impact of pasture on species richness extends beyond field level. The effect of human modified landscapes, therefore, is important to consider when investigating classical ecological relationships, particularly at the wider landscape scale.
Warmer and drier conditions associated with ongoing climate change will increase abiotic stress for plants and mycorrhizal fungi in drylands worldwide, thereby potentially reducing vegetation cover and productivity and increasing the risk of land degradation and desertification. Rhizosphere microbial interactions and feedbacks are critical processes that could either mitigate or aggravate the vulnerability of dryland vegetation to forecasted climate change.We conducted a four-year manipulative study in a semiarid shrubland in the Iberian Peninsula to assess the effects of warming (~2.5ºC; W), rainfall reduction (~30%; RR) and their combination (W+RR) on the performance of native shrubs (Helianthemum squamatum) and their associated mycorrhizal fungi.Warming (W and W+RR) decreased the net photosynthetic rates of H. squamatum shrubs by ~31% despite concurrent increases in stomatal conductance (~33%), leading to sharp decreases (~50%) in water use efficiency. Warming also advanced growth phenology, decreased leaf nitrogen and phosphorus contents per unit area, reduced shoot biomass production by ~36% and decreased survival during a dry year in both W and W+RR plants. Plants under RR showed more moderate decreases (~10-20%) in photosynthesis, stomatal conductance and shoot growth.Warming, RR and W+RR altered ectomycorrhizal fungal (EMF) community structure and drastically reduced the relative abundance of EMF sequences obtained by high-throughput sequencing, a response associated with decreases in the leaf nitrogen, phosphorus and dry matter contents of their host plants. In contrast to EMF, the community structure and relative sequence abundances of other non-mycorrhizal fungal guilds were not significantly affected by the climate manipulation treatments.Synthesis: Our findings highlight the vulnerability of both native plants and their symbiotic mycorrhizal fungi to climate warming and drying in semiarid shrublands, and point to the importance of a deeper understanding of plant-soil feedbacks to predict dryland vegetation responses to forecasted aridification. The interdependent responses of plants and ectomycorrhizal fungi to warming and rainfall reduction may lead to a detrimental feedback loop on vegetation productivity and nutrient pool size, which could amplify the adverse impacts of forecasted climate change on ecosystem functioning in EMF-dominated drylands.
Whereas warming enhances plant nutrient status and photosynthesis in most terrestrial ecosystems, dryland vegetation is vulnerable to the likely increases in evapotranspiration and reductions in soil moisture caused by elevated temperatures. Any warming-induced declines in plant primary production and cover in drylands would increase erosion, land degradation, and desertification. We conducted a four-year manipulative experiment in a semi-arid Mediterranean ecosystem to evaluate the impacts of a ~2°C warming on the photosynthesis, transpiration, leaf nutrient status, chlorophyll content, isotopic composition, biomass growth, and postsummer survival of the native shrub Helianthemum squamatum. We predicted that warmed plants would show reduced photosynthetic activity and growth, primarily due to the greater stomatal limitation imposed by faster and more severe soil drying under warming. On average, warming reduced net photosynthetic rates by 36% across the study period. Despite this strong response, warming did not affect stomatal conductance and transpiration. The reduction of peak photosynthetic rates with warming was more pronounced in a drought year than in years with near-average rainfall (75% and 25-40% reductions relative to controls, respectively), with no indications of photosynthetic acclimation to warming through time. Warmed plants had lower leaf N and P contents, δ (13)C, and sparser and smaller leaves than control plants. Warming reduced shoot dry mass production by 31%. However, warmed plants were able to cope with large reductions in net photosynthesis, leaf area, and shoot biomass production without changes in postsummer survival rates. Our findings highlight the key role of nonstomatal factors (biochemical and/or nutritional) in reducing net carbon assimilation rates and growth under warming, which has important implications for projections of plant carbon balance under the warmer and drier climatic scenario predicted for drylands worldwide. Projected climate warming over the coming decades could reduce net primary production by about one-third in semi-arid gypsum shrublands dominated by H. squamatum.
