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Adaptive management of biological systems: A review
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Adaptive Management (AM) is widely considered to be the best available approach for managing biolog- ical systems in the presence of uncertainty. But AM has arguably only rarely succeeded in improving bio- diversity outcomes. There is therefore an urgent need for reflection regarding how practitioners might overcome key problems hindering greater implementation of AM. In this paper, we present the first structured review of the AM literature that relates to biodiversity and ecosystem management, with the aim of quantifying how rare AM projects actually are. We also investigated whether AM practitioners in terrestrial and aquatic systems described the same problems; the degree of consistency in how the term ‘adaptive management’ was applied; the extent to which AM projects were sustained over time; and whether articles describing AM projects were more highly cited than comparable non-AM articles. We found that despite the large number of articles identified through the ISI web of knowledge (n = 1336), only 61 articles (<5%) explicitly claimed to enact AM. These 61 articles cumulatively described 54 separate projects, but only 13 projects were supported by published monitoring data. The extent to which these 13 projects applied key aspects of the AM philosophy – such as referring to an underlying conceptual model, enacting ongoing monitoring, and comparing alternative management actions – varied enormously. Further, most AM projects were of short duration; terrestrial studies discussed biodiversity conservation significantly more frequently than aquatic studies; and empirical studies were no more highly cited than qualitative articles. Our review highlights that excessive use of the term ‘adaptive man- agement’ is rife in the peer-reviewed literature. However, a small but increasing number of projects have been able to effectively apply AM to complex problems. We suggest that attempts to apply AM may be improved by: (1) Better collaboration between scientists and representatives from resource-extracting industries. (2) Better communication of the risks of not doing AM. (3) Ensuring AM projects ‘‘pass the test of management relevance’’.
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Aeolian process effects on vegetation communities in an arid grassland ecosystem
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Many arid grassland communities are changing from grass dominance to shrub
dominance, but the mechanisms involved in this conversion process are not completely
understood. Aeolian processes likely contribute to this conversion from
grassland to shrubland. The purpose of this research is to provide information
regarding how vegetation changes occur in an arid grassland as a result of aeolian
sediment transport. The experimental design included three treatment blocks, each
with a 25 × 50 m area where all grasses, semi-shrubs, and perennial forbs were
hand removed, a 25 × 50 m control area with no manipulation of vegetation cover,
and two 10 × 25 m plots immediately downwind of the grass-removal and control
areas in the prevailing wind direction, 19◦ north of east, for measuring vegetation
cover. Aeolian sediment flux, soil nutrients, and soil seed bank were monitored on
each treatment area and downwind plot. Grass and shrub cover were measured on
each grass-removal, control, and downwind plot along continuous line transects as
well as on 5 × 10 m subplots within each downwind area over four years following
grass removal. On grass-removal areas, sediment flux increased significantly, soil
nutrients and seed bank were depleted, and Prosopis glandulosa shrub cover increased
compared to controls. Additionally, differential changes for grass and shrub
cover were observed for plots downwind of vegetation-removal and control areas.
Grass cover on plots downwind of vegetation-removal areas decreased over time
(2004–2007) despite above average rainfall throughout the period of observation,
while grass cover increased downwind of control areas; P. glandulosa cover increased
on plots downwind of vegetation-removal areas, while decreasing on plots downwind
of control areas. The relationships between vegetation changes and aeolian
sediment flux were significant and were best described by a logarithmic function,
with decreases in grass cover and increases in shrub cover occurring with small
increases in aeolian sediment flux
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All Downhill From Here?
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Biologists say climate change may already be affecting high-mountain ecosystems around the world, where plants and animals adapted to cold, barren conditions now face higher temperatures and a surge of predators and competitors
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Allometry of thermal variables in mammals: consequences of body size and phylogeny
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A large number of analyses have examined how basal metabolic rate (BMR) is affected by body mass in mammals. By contrast, the critical ambient temperatures that define the thermo-neutral zone (TNZ), in which BMR is measured, have received much less attention. We provide the first phylogenetic analyses on scaling of lower and upper critical temperatures and the breadth of the TNZ in 204 mammal species from diverse orders. The phylogenetic signal of thermal variables was strong for all variables analysed. Most allometric relationships between thermal variables and body mass were significant and regressions using phylogenetic analyses fitted the data better than conventional regressions. Allometric exponents for all mammals were 0.19 for the lower critical temperature (expressed as body temperature - lower critical temperature), −0.027 for the upper critical temperature, and 0.17 for the breadth of TNZ. The small exponents for the breadth of the TNZ compared to the large exponents for BMR suggest that BMR per se affects the influence of body mass on TNZ only marginally. However, the breadth of the TNZ is also related to the apparent thermal conductance and it is therefore possible that BMR at different body masses is a function of both the heat exchange in the TNZ and that encountered below and above the TNZ to permit effective homeothermic thermoregulation.
Keywords: allometry,lower critical temperature,mammals,marsupials,thermal neutral zone,upper critical temperature.
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Allowable carbon emissions lowered by multiple climate targets
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Climate targets are designed to inform policies that would limit the
magnitude and impacts of climate change caused by anthropogenic
emissions of greenhouse gases and other substances. The target
that is currently recognized by most world governments1 places a
limit of two degrees Celsius on the global mean warming since
preindustrial times. This would require large sustained reductions
in carbon dioxide emissions during the twenty-first century and
beyond2–4. Such a global temperature target, however, is not sufficient
to control many other quantities, such as transient sea level
rise5
, ocean acidification6,7 and net primary production on land8,9.
Here, using an Earth system model of intermediate complexity
(EMIC) in an observation-informed Bayesian approach, we show
that allowable carbon emissions are substantially reduced whenmultiple
climate targets are set. We take into account uncertainties in
physical and carbon cycle model parameters, radiative efficiencies10,
climate sensitivity11 and carbon cycle feedbacks12,13 along with a
large set of observational constraints. Within this framework, we
explore a broad range of economically feasible greenhouse gas scenarios
from the integrated assessment community14–17 to determine
the likelihood of meeting a combination of specific global
and regional targets under various assumptions. For any given
likelihood of meeting a set of such targets, the allowable cumulative
emissions are greatly reduced from those inferred from the temperature
target alone. Therefore, temperature targets alone are unable
to comprehensively limit the risks from anthropogenic emissions.
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Amazon Basin climate under global warming: the role of the sea surface temperature
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The Hadley Centre coupled climate–carbon cycle model (HadCM3LC) predicts loss of the Amazon
rainforest in response to future anthropogenic greenhouse gas emissions. In this study, the
atmospheric component of HadCM3LC is used to assess the role of simulated changes in midtwenty-first
century sea surface temperature (SST) in Amazon Basin climate change. When the full HadCM3LC SST anomalies (SSTAs) are used, the atmosphere model reproduces the Amazon Basin climate change exhibited by HadCM3LC, including much of the reduction in Amazon Basin rainfall. This rainfall change is shown to be the combined effect of SSTAs in both thetropical Atlantic and the Pacific, with roughly equal contributions from each basin. The greatest rainfall reduction occurs from May to October, outside of the mature South American monsoon (SAM) season. This dry season response is the combined effect of a more rapid warming of the tropical North Atlantic relative to the south, and warm SSTAs in the tropical east Pacific. Conversely,
a weak enhancement of mature SAM season rainfall in response to Atlantic SST change is suppressed
by the atmospheric response to Pacific SST. This net wet season response is sufficient to prevent dry
season soil moisture deficits from being recharged through the SAM season, leading to a perennial
soil moisture reduction and an associated 30% reduction in annual Amazon Basin net primary
productivity (NPP). A further 23% NPP reduction occurs in response to a 3.58C warmer air
temperature associated with a global mean SST warming.
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An extreme climatic event alters marine ecosystem structure in a global biodiversity hotspot
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Extreme climatic events, such as heat waves, are predicted to increase in frequency and magnitude as a consequence of global warming but their ecological effects are poorly understood, particularly in marine ecosystems1–3. In early 2011, the marine ecosystems along the west coast of Australia -- a global hotspot of biodiversity and endemism 4,5 -- experienced the highest-magnitude warming event on record. Sea temperatures soared to unprecedented levels and warming anomalies of 2–4 ◦ C persisted for more than ten weeks along >2,000 km of coastline. We show that biodiversity patterns of temperate seaweeds, sessile invertebrates and demersal fish were significantly different after the warming event, which led to a reduction in the abundance of habitat-forming seaweeds and a subsequent shift in community structure towards a depauperate state and a tropicalization of fish communities. We conclude that extreme climatic events are key drivers of biodiversity patterns and that the frequency and intensity of such episodes have major implications for predictive models of species distribution and ecosystem structure, which are largely based on gradual warming trends.
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An Uncertain Future for Soil Carbon
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Predictions of how rapidly the large amounts of carbon stored as soil organic matter will respond to warming
are highly uncertain (1). Organic matter plays a key role in determining the physical and chemical properties of soils and is a major reservoir for plant nutrients. Understanding how fast organic matter in soils can be built up and lost is thus critical not just for its net effect on the atmospheric CO2 concentration but for
sustaining other soil functions, such as soil fertility, on which societies and ecosystems rely. Recent analytic advances are rapidly improving our understanding of the complex and interacting factors that control the age
and form of organic matter in soils, but the processes that destabilize organic matter in response to disturbances (such as warming or land use change) are poorly understood
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Analysing fossil-fuel displacement
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It is commonly assumed that fossil fuels can be replaced by alternative forms of energy. Now research challenges this assumption, and highlights the role of non-technological solutions to reduce fossil-fuel consumption.
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Analysis of monotonic greening and browning trends from global NDVI time-series
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Remotely sensed vegetation indices are widely used to detect greening and browning trends; especially the global coverage of time-series normalized difference vegetation index (NDVI) data which are available from 1981. Seasonality and serial auto-correlation in the data have previously been dealt with by integrating the data to annual values; as an alternative to reducing the temporal resolution, we apply harmonic analyses and non-parametric trend tests to the GIMMS NDVI dataset (1981–2006). Using the complete dataset, greening and browning trends were analyzed using a linear model corrected for seasonality by subtracting the seasonal component, and a seasonal non-parametric model. In a third approach, phenological shift and variation in length of growing season were accounted for by analyzing the time-series using vegetation development stages rather than calendar days. Results differed substantially between the models, even though the input data were the same. Prominent regional greening trends identified by several other studies were confirmed but the models were inconsistent in areas with weak trends. The linear model using data corrected for seasonality showed similar trend slopes to those described in previous work using linear models on yearly mean values. The non-parametric models demonstrated the significant influence of variations in phenology; accounting for these variations should yield more robust trend analyses and better understanding of vegetation trends.
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