A commentary on climate change, stone decay dynamics and the ‘greening’ of natural stone buildings: new perspectives on ‘deep wetting’

Environmental controls on stone decay processes are rapidly changing as a result of changing climate. UKCP09 projections for the 2020s (2010–2039) indicate that over much of the UK seasonality of precipitation will increase. Summer dryness and winter wetness are both set to increase, the latter linked to projected precipitation increases in autumn and spring months. If so, this could increase the time that stone structures remain wet and possibly the depth of moisture penetration, and it appears that building stone in Northern Ireland has already responded through an increased incidence of algal ‘greening’.This paper highlights the need for understanding the effects of climate change through a series of studies of largely sandstone structures. Current and projected climatic trends are therefore considered to have aesthetic, physical and chemical implications that are not currently built into our models of sandstone decay, especially with respect to the role played by deep-seated wetness on sandstone deterioration and decay progression and the feedbacks associated with, for example surface algal growth. In particular,it is proposed that algal biofilms will aid moisture retention and further facilitate moisture and dissolved salt penetration to depth. Thus, whilst the outer surface of stone may continue to experience frequent wetting and drying associated with individual precipitation events, the latter is less likely to be complete, and the interiors of building blocks may only experience wetting/drying in response to seasonal cycling. A possible consequence of deeper salt penetration could be a delay in the onset of surface deterioration,but more rapid and effective retreat once it commences as decay mechanisms ‘tap into a reservoir of deep salt’.

Isolation basin records of late Quaternary sea-level change, central mainland British Columbia, Canada.

Isolation basin records from the Seymour-Belize Inlet Complex, a remote area of central mainland British Columbia, Canada are used to constrain post-glacial sea-level changes and provide a preliminary basis for testing geophysical model predictions of relative sea-level (RSL) change. Sedimentological and diatom data from three low-lying (<4 m elevation) basins record falling RSLs in late-glacial times and isolation from the sea by ~11,800–11,200 14C BP. A subsequent RSL rise during the early Holocene (~8000 14C BP) breached the 2.13 m sill of the lowest basin (Woods Lake), but the two more elevated basins (sill elevations of ~3.6 m) remained isolated. At ~2400 14C BP, RSL stood at 1.49 ± 0.34 m above present MTL. Falling RSLs in the late Holocene led to the final emergence of the Woods Lake basin by 1604 ± 36 14C BP. Model predictions generated using the ICE-5G model partnered with a small number of different Earth viscosity models generally show poor agreement with the observational data, indicating that the ice model and/or Earth models considered can be improved upon. The best data-model fits were achieved with relatively low values of upper mantle viscosity (5 × 1019 Pa s), which is consistent with previous modelling results from the region. The RSL data align more closely with observational records from the southeast of the region (eastern Vancouver Island, central Strait of Georgia), than the immediate north (Bella Bella–Bella Coola and Prince Rupert-Kitimat) and areas to the north-west (Queen Charlotte Sound, Hecate Strait), underlining the complexity of the regional response to glacio-isostatic recovery.

How do grazers achieve their distribution? A continuum of models from random diffusion to the ideal free distribution using biased random walks

A conceptual model is described for generating distributions of grazing animals, according to their searching behavior, to investigate the mechanisms animals may use to achieve their distributions. The model simulates behaviors ranging from random diffusion, through taxis and cognitively aided navigation (i.e., using memory), to the optimization extreme of the Ideal Free Distribution. These behaviors are generated from simulation of biased diffusion that operates at multiple scales simultaneously, formalizing ideas of multiple-scale foraging behavior. It uses probabilistic bias to represent decisions, allowing multiple search goals to be combined (e.g., foraging and social goals) and the representation of suboptimal behavior. By allowing bias to arise at multiple scales within the environment, each weighted relative to the others, the model can represent different scales of simultaneous decision-making and scale-dependent behavior. The model also allows different constraints to be applied to the animal's ability (e.g., applying food-patch accessibility and information limits). Simulations show that foraging-decision randomness and spatial scale of decision bias have potentially profound effects on both animal intake rate and the distribution of resources in the environment. Spatial variograms show that foraging strategies can differentially change the spatial pattern of resource abundance in the environment to one characteristic of the foraging strategy.</

A millennial record of environmental change in peat deposits from the Misten bog (East Belgium)

In this study, palaeoenvironmental changes recorded in the top metre of a peat profile (Misten bog, East Belgium) were investigated using a multiproxy approach. Proxies include bulk density, Ti and Si content, pollen, macrofossils, d13C on specific Sphagnum stems, and d13C–d18O on Sphagnum leaves. A high-resolution chronology was generated using 210Pb measurements and 22 14C AMS dates on carefully selected Sphagnum macrofossils. d13C only records large change in mire surface wetness. This is partly due to the fact that the core was taken from the edge of a hummock, which may make it difficult to track small isotopic changes. The d13C signal seems to be dependent upon the Sphagnum species composition. For example, a change between Sphagnum section Cuspidata towards Sphagnum imbricatum causes a significant drop in the d13C values. On the whole, the C and O isotopes record two shallow pool phases during the 8th–9th and the 13th centuries. Pollen and atmospheric soil dust (ASD) fluxes records increased human occupation in the area. There may be some climatic signals in the ASD flux, but they are difficult to decipher from the increasing human impact (land clearance, agriculture) during the last millennium. The variations in the proxies are not always synchronous, suggesting different triggering factors (temperature, wetness, windiness) for each proxy. This study also emphasizes that, compared to studies dealing with pollution using geochemical proxies, palaeoclimatic inferences from peat bogs need as many proxies as possible, together with highly accurate and precise age-models, in order to better understand climate variability and their consequences during the Holocene.

Hierarchical Bayesian models in ecology: Reconstructing species interaction networks from non-homogeneous species abundance data

The relationships among organisms and their surroundings can be of immense complexity. To describe and understand an ecosystem as a tangled bank, multiple ways of interaction and their effects have to be considered, such as predation, competition, mutualism and facilitation. Understanding the resulting interaction networks is a challenge in changing environments, e.g. to predict knock-on effects of invasive species and to understand how climate change impacts biodiversity. The elucidation of complex ecological systems with their interactions will benefit enormously from the development of new machine learning tools that aim to infer the structure of interaction networks from field data. In the present study, we propose a novel Bayesian regression and multiple changepoint model (BRAM) for reconstructing species interaction networks from observed species distributions. The model has been devised to allow robust inference in the presence of spatial autocorrelation and distributional heterogeneity. We have evaluated the model on simulated data that combines a trophic niche model with a stochastic population model on a 2-dimensional lattice, and we have compared the performance of our model with L1-penalized sparse regression (LASSO) and non-linear Bayesian networks with the BDe scoring scheme. In addition, we have applied our method to plant ground coverage data from the western shore of the Outer Hebrides with the objective to infer the ecological interactions. (C) 2012 Elsevier B.V. All rights reserved.

Refining Risk Estimates Using Models (Chapter 4)

In 2004 nineteen scientists from fourteen institutions in seven countries
collaborated in the landmark study described in chapter 2 (Thomas et al., 2004a). This chapter provides an overview of results of studies published subsequently and assesses how much, and why, new results differ from those of Thomas et al.
Some species distribution modeling (SDM) studies are directly comparable to the Thomas et al. estimates. Others using somewhat different methods nonetheless illuminate whether the original estimates were of the right order of magnitude. Climate similarity models (Williams et al., 2007; Williams and Jackson, 2007), biome, and vegetation dynamic models (Perry and Enright, 2006) have also been
applied in the context of climate change, providing interesting opportunities
for comparison and cross-validation with results from SDMs.
This chapter concludes with an assessment of whether the range of extinction risk estimates presented in 2004 can be narrowed, and whether the mean estimate should be revised upward or downward. To set the stage for these analyses, the chapter begins with brief reviews of advances in climate modeling and species modeling since 2004.

Predicting the impacts of climate change on the distribution of threatened forest-restricted birds in Madagascar

The greatest common threat to birds in Madagascar has historically been from anthropogenic deforestation. During recent decades, global climate change is now also regarded as a significant threat to biodiversity. This study uses Maximum Entropy species distribution modeling to explore how potential climate change could affect the distribution of 17 threatened forest endemic bird species, using a range of climate variables from the Hadley Center's HadCM3 climate change model, for IPCC scenario B2a, for 2050. We explore the importance of forest cover as a modeling variable and we test the use of pseudo-presences drawn from extent of occurrence distributions. Inclusion of the forest cover variable improves the models and models derived from real-presence data with forest layer are better predictors than those from pseudo-presence data. Using real-presence data, we analyzed the impacts of climate change on the distribution of nine species. We could not predict the impact of climate change on eight species because of low numbers of occurrences. All nine species were predicted to experience reductions in their total range areas, and their maximum modeled probabilities of occurrence. In general, species range and altitudinal contractions follow the reductive trend of the Maximum presence probability. Only two species (Tyto soumagnei and Newtonia fanovanae) are expected to expand their altitude range. These results indicate that future availability of suitable habitat at different elevations is likely to be critical for species persistence through climate change. Five species (Eutriorchis astur, Neodrepanis hypoxantha, Mesitornis unicolor, Euryceros prevostii, and Oriola bernieri) are probably the most vulnerable to climate change. Four of them (E. astur, M. unicolor, E. prevostii, and O. bernieri) were found vulnerable to the forest fragmentation during previous research. Combination of these two threats in the future could negatively affect these species in a drastic way. Climate change is expected to act differently on each species and it is important to incorporate complex ecological variables into species distribution models.

Patterns of Holocene relative sea level change in the North of Britain and Ireland

Temporal and spatial patterns of relative sea level (RSL) change in the North of Britain and Ireland during the Holocene are examined. Four episodes, each defined by marked changes in the RSL trend, are identified. Each episode is marked by a rise to a culminating shoreline followed by a fall. Episode HRSL-1 dates from the Younger Dryas to early in the Holocene; HRSL-2 to HRSL-4 occurred later in the Holocene. There is extensive evidence for each episode, and on this basis the spatial distribution of the altitude data for three culminating shorelines and a shoreline formed at the time of the Holocene Storegga Slide tsunami (ca 8110 ± 100 cal. BP) is analysed. Ordinary Kriging is used to determine the general pattern, following which Gaussian Trend Surface Analysis is employed. Recognising that empirical measurements of RSL change can be unevenly distributed spatially, a new approach is introduced which enables the developing pattern to be identified. The patterns for the most widely occurring shorelines were analysed and found to be similar and common centre and axis models were developed for all shorelines. The analyses described provide models of the spatial pattern of Holocene RSL change in the area between ca 8100 cal. BP and ca 1000 cal. BP based on 2262 high resolution shoreline altitude measurements. These models fit the data closely, no shoreline altitude measurement lying more than −1.70 m or +1.82 m from the predicted value. The models disclose a similar pattern to a recently published Glacial Isostatic Adjustment model for present RSL change across the area, indicating that the overall spatial pattern of RSL change may not have varied greatly during the last ca 8000 years.

Protected area networks and savannah bird biodiversity in the face of climate change and land degradation

The extent to which climate change might diminish the efficacy of protected areas is one of the most pressing conservation questions. Many projections suggest that climate-driven species distribution shifts will leave protected areas impoverished and species inadequately protected while other evidence suggests that intact ecosystems within protected areas will be resilient to change. Here, we tackle this problem empirically. We show how recent changes in distribution of 139 Tanzanian savannah bird species are linked to climate change, protected area status and land degradation. We provide the first evidence of climate-driven range shifts for an African bird community. Our results suggest that the continued maintenance of existing protected areas is an appropriate conservation response to the challenge of climate and environmental change.

Determining the response of African biota to climate change: using the past to model the future

Prediction of biotic responses to future climate change in tropical Africa tends to be based on two modelling approaches: bioclimatic species envelope models and dynamic vegetation models. Another complementary but underused approach is to examine biotic responses to similar climatic changes in the past as evidenced in fossil and historical records. This paper reviews these records and highlights the information that they provide in terms of understanding the local- and regional-scale responses of African vegetation to future climate change. A key point that emerges is that a move to warmer and wetter conditions in the past resulted in a large increase in biomass and a range distribution of woody plants up to 400–500 km north of its present location, the so-called greening of the Sahara. By contrast, a transition to warmer and drier conditions resulted in a reduction in woody vegetation in many regions and an increase in grass/savanna-dominated landscapes. The rapid rate of climate warming coming into the current interglacial resulted in a dramatic increase in community turnover, but there is little evidence for widespread extinctions. However, huge variation in biotic response in both space and time is apparent with, in some cases, totally different responses to the same climatic driver. This highlights the importance of local features such as soils, topography and also internal biotic factors in determining responses and resilience of the African biota to climate change, information that is difficult to obtain from modelling but is abundant in palaeoecological records.

Behavioural context of multi-scale species distribution models assessed by radio-tracking

Incorporating ecological processes and animal behaviour into Species Distribution Models (SDMs) is difficult. In species with a central resting or breeding place, there can be conflict between the environmental requirements of the 'central place' and foraging habitat. We apply a multi-scale SDM to examine habitat trade-offs between the central place, roost sites, and foraging habitat in . Myotis nattereri. We validate these derived associations using habitat selection from behavioural observations of radio-tracked bats. A Generalised Linear Model (GLM) of roost occurrence using land cover variables with mixed spatial scales indicated roost occurrence was positively associated with woodland on a fine scale and pasture on a broad scale. Habitat selection of radio-tracked bats mirrored the SDM with bats selecting for woodland in the immediate vicinity of individual roosts but avoiding this habitat in foraging areas, whilst pasture was significantly positively selected for in foraging areas. Using habitat selection derived from radio-tracking enables a multi-scale SDM to be interpreted in a behavioural context. We suggest that the multi-scale SDM of . M. nattereri describes a trade-off between the central place and foraging habitat. Multi-scale methods provide a greater understanding of the ecological processes which determine where species occur and allow integration of behavioural processes into SDMs. The findings have implications when assessing the resource use of a species at a single point in time. Doing so could lead to misinterpretation of habitat requirements as these can change within a short time period depending on specific behaviour, particularly if detectability changes depending on behaviour. © 2011 Gesellschaft für ökologie.

Care and Management of Ancient Stone Monuments During Environmental Change

Ancient stone monuments (ASMs), such as standing stones and rock art panels, are powerful and iconic expressions of Britain’s rich prehistoric past that have major economic and tourism value. However, ASMs are under pressure due to increasing anthropogenic exposure and changing climatic conditions, which accelerate their rates of disrepair. Although scientific data exists on the integrity of stone monuments, most applies to “built” systems; therefore, additional work specific to ASMs in the countryside is needed to develop better-informed safeguarding strategies. Here, we use Neolithic and Bronze Age rock art panels across Northern England as a case study for delineating ASM management actions required to enhance monument preservation. The state of the rock art is described first, including factors that led to current conditions. Rock art management approaches then are described within the context of future environments, which models suggest to be more dynamic and locally variable. Finally, a Condition Assessment and Risk Evaluation (CARE) scheme is proposed to help prioritise interventions; an example of which is provided based on stone deterioration at Petra in Jordon. We conclude that more focused scientific and behavioural data, specific to deterioration mechanisms, are required for an ASM CARE scheme to be successful.

Parasites that change predator or prey behaviour can have keystone effects on community composition

Parasites play pivotal roles in structuring communities, often via indirect interactions with non-host species. These effects can be density-mediated (through mortality) or trait-mediated (behavioural, physiological and developmental), and may be crucial to population interactions, including biological invasions. For instance, parasitism can alter intraguild predation (IGP) between native and invasive crustaceans, reversing invasion outcomes. Here, we use mathematical models to examine how parasite-induced trait changes influence the population dynamics of hosts that interact via IGP. We show that trait-mediated indirect interactions impart keystone effects, promoting or inhibiting host coexistence. Parasites can thus have strong ecological impacts, even if they have negligible virulence, underscoring the need to consider trait-mediated effects when predicting effects of parasites on community structure in general and biological invasions in particular.

Did children’s perceptions of an after-school social learning program predict change in their behavior?

This research explored the influence of children’s perceptions of a pro-social behavior after-school program on actual change in the children’s behavioral outcomes over the program’s duration. Children’s perceptions of three program processes were collected as well as self-reported pro-social and anti-social behavior before and after the program. Statistical models showed that: Positive perceptions of the program facilitators’ dispositions significantly predicted reductions in anti-social behavior; and positive perceptions with the program activities significantly predicted gains in pro-social behavior. The children’s perceptions of their peers’ behavior in the sessions were not found to a significant predictor of behavioral change. The two significant perceptual indicators predicted a small percentage of the change in the behavioral outcomes. However, as after-school social learning programs have a research history of problematic implementation children’s perceptions should be considered in future program design, evaluation and monitoring.