Climate-driven range extension of Amphistegina (protista, foraminiferida) : models of current and predicted future ranges

© The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in PLoS ONE 8 (2013): e54443, doi:10.1371/journal.pone.0054443.Species-range expansions are a predicted and realized consequence of global climate change. Climate warming and the poleward widening of the tropical belt have induced range shifts in a variety of marine and terrestrial species. Range expansions may have broad implications on native biota and ecosystem functioning as shifting species may perturb recipient communities. Larger symbiont-bearing foraminifera constitute ubiquitous and prominent components of shallow water ecosystems, and range shifts of these important protists are likely to trigger changes in ecosystem functioning. We have used historical and newly acquired occurrence records to compute current range shifts of Amphistegina spp., a larger symbiont-bearing foraminifera, along the eastern coastline of Africa and compare them to analogous range shifts currently observed in the Mediterranean Sea. The study provides new evidence that amphisteginid foraminifera are rapidly progressing southwestward, closely approaching Port Edward (South Africa) at 31°S. To project future species distributions, we applied a species distribution model (SDM) based on ecological niche constraints of current distribution ranges. Our model indicates that further warming is likely to cause a continued range extension, and predicts dispersal along nearly the entire southeastern coast of Africa. The average rates of amphisteginid range shift were computed between 8 and 2.7 km year−1, and are projected to lead to a total southward range expansion of 267 km, or 2.4° latitude, in the year 2100. Our results corroborate findings from the fossil record that some larger symbiont-bearing foraminifera cope well with rising water temperatures and are beneficiaries of global climate change.This work was supported by grants from the German Science Foundation (DFG; www.dfg.de) to ML and SL (LA 884/10-1, LA 884/5-1)

Modelling historical landscape changes

Context: Historical maps of land use/land cover (LULC) enable detection of landscape changes, and help to assess drivers and potential future trajectories. However, historical maps are often limited in their spatial and temporal coverage. There is a need to develop and test methods to improve re-construction of historical landscape change. Objectives: To implement a modelling method to accurately identify key land use changes over a rural landscape at multiple time points. Methods: We used existing LULC maps at two time points for 1930 and 2015, along with a habitat time-series dataset, to construct two new, modelled LULC maps for Dorset in 1950 and 1980 to produce a four-step time-series. We used the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Scenario Generator tool to model new LULC maps. Results: The modelled 1950 and 1980 LULC maps were cross-validated against habitat survey data and demonstrated a high level of accuracy (87% and 84%, respectively) and low levels of model uncertainty. The LULC time-series revealed the timing of LULC changes in detail, with the greatest losses in neutral and calcareous grassland having occurred by 1950, the period when arable land expanded the most, whilst the expansion in agriculturally-improved grassland was greatest over the period 1950–1980. Conclusions: We show that the modelling approach is a viable methodology for re-constructing historical landscapes. The time-series output can be useful for assessing patterns and changes in the landscape, such as fragmentation and ecosystem service delivery, which is important for informing future land management and conservation strategies

Man and the Last Great Wilderness: Human Impact on the Deep Sea

The deep sea, the largest ecosystem on Earth and one of the least studied, harbours high biodiversity and provides a wealth of resources. Although humans have used the oceans for millennia, technological developments now allow exploitation of fisheries resources, hydrocarbons and minerals below 2000 m depth. The remoteness of the deep seafloor has promoted the disposal of residues and litter. Ocean acidification and climate change now bring a new dimension of global effects. Thus the challenges facing the deep sea are large and accelerating, providing a new imperative for the science community, industry and national and international organizations to work together to develop successful exploitation management and conservation of the deep-sea ecosystem. This paper provides scientific expert judgement and a semi-quantitative analysis of past, present and future impacts of human-related activities on global deep-sea habitats within three categories: disposal, exploitation and climate change. The analysis is the result of a Census of Marine Life – SYNDEEP workshop (September 2008). A detailed review of known impacts and their effects is provided. The analysis shows how, in recent decades, the most significant anthropogenic activities that affect the deep sea have evolved from mainly disposal (past) to exploitation (present). We predict that from now and into the future, increases in atmospheric CO2 and facets and consequences of climate change will have the most impact on deep-sea habitats and their fauna. Synergies between different anthropogenic pressures and associated effects are discussed, indicating that most synergies are related to increased atmospheric CO2 and climate change effects. We identify deep-sea ecosystems we believe are at higher risk from human impacts in the near future: benthic communities on sedimentary upper slopes, cold-water corals, canyon benthic communities and seamount pelagic and benthic communities. We finalise this review with a short discussion on protection and management methods

Antimicrobial resistance: The complex challenge of measurement to inform policy and the public

Didier Wernli and colleagues discuss the role of monitoring in countering antimicrobial resistance

Large-ccale prediction of seagrass distribution integrating landscape metrics and environmental factors: The case of cymodocea nodosa (Mediterranean-Atlantic)

Understanding the factors that affect seagrass meadows encompassing their entire range of distribution is challenging yet important for their conservation. Here, we predict the realized and potential distribution for the species Cymodocea nodosa modelling its environmental niche in the Mediterranean and adjacent Atlantic coastlines. We use a combination of environmental variables and landscape metrics to perform a suite of predictive algorithms which enables examination of the niche and find suitable habitats for the species. The most relevant environmental variables defining the distribution of C. nodosa were sea surface temperature (SST) and salinity. We found suitable habitats at SST from 5.8 A degrees C to 26.4 A degrees C and salinity ranging from 17.5 to 39.3. Optimal values of mean winter wave height ranged between 1.2 and 1.5 m, while waves higher than 2.5 m seemed to limit the presence of the species. The influence of nutrients and pH, despite having weight on the models, was not so clear in terms of ranges that confine the distribution of the species. Landscape metrics able to capture variation in the coastline enhanced significantly the accuracy of the models, despite the limitations caused by the scale of the study. We found potential suitable areas not occupied by the seagrass mainly in coastal regions of North Africa and the Adriatic coast of Italy. The present study describes the realized and potential distribution of a seagrass species, providing the first global model of the factors that can be shaping the environmental niche of C. nodosa throughout its range. We identified the variables constraining its distribution as well as thresholds delineating its environmental niche. Landscape metrics showed promising prospects for the prediction of coastal species dependent on the shape of the coast. By contrasting predictive approaches, we defined the variables affecting the distributional areas that seem unsuitable for C. nodosa as well as those suitable habitats not occupied by the species. These findings are encouraging for its use in future studies on climate-related marine range shifts and meadow restoration projects of these fragile ecosystems