scholarly journals Macrosystems ecology: understanding ecological patterns and processes at continental scales

2014 ◽  
Vol 12 (1) ◽  
pp. 5-14 ◽  
Author(s):  
James B Heffernan ◽  
Patricia A Soranno ◽  
Michael J Angilletta ◽  
Lauren B Buckley ◽  
Daniel S Gruner ◽  
...  
Keyword(s):  
Ecological Patterns ◽  
Macrosystems Ecology ◽  
Patterns And Processes

scholarly journals Fragmented Landscape, Fragmented Knowledge: A Synthesis of Renosterveld Ecology and Conservation

2019 ◽  
Vol 46 (2) ◽  
pp. 171-179 ◽  
Author(s):  
Emmeline N Topp ◽  
Jacqueline Loos
Keyword(s):  
Cape Floristic Region ◽  
Fragmented Landscape ◽  
Biodiversity Hotspots ◽  
Current State ◽  
Ecological Patterns ◽  
Local Patch ◽  
Populated Region ◽  
Patterns And Processes ◽  
First Time ◽  
Effective Conservation

SummaryKnowledge of ecological patterns and processes is key to effective conservation of biodiversity hotspots under threat. Renosterveld is one of the most critically endangered habitats in the biologically unique Cape Floristic Region, South Africa. For the first time, we map and synthesize the current state of knowledge on renosterveld ecology and conservation. We investigated 132 studies for the themes, locations and taxa of renosterveld research and the fragmentation, threats, recommendations and barriers to renosterveld conservation. More studies focused on plants than any other taxa (48% of articles) and are conducted mostly in larger, intact renosterveld fragments. The most commonly identified threat to renosterveld was agricultural intensification; conservation recommendations spanned improved farming practices, formal protection and local patch management. Conservation implementation has been piecemeal and has depended largely on the goodwill of landowners, which can be constrained by costs of conservation measures and a lack of suitable restoration means. Citizen science is a promising potential solution to some barriers. Fragmented knowledge in such a transformed and relatively densely populated region highlights the scale of knowledge gaps for other biodiversity hotspots and has implications for ongoing conservation work.

Hydrologic dynamics and ecosystem structure

2003 ◽  
Vol 47 (6) ◽  
pp. 17-24 ◽  
Author(s):  
I. Rodríguez-Iturbe
Keyword(s):  
Hydrological Cycle ◽  
Limiting Factor ◽  
Ecosystem Structure ◽  
Nutrient Cycles ◽  
Stochastic Fluctuation ◽  
Ecological Patterns ◽  
Probabilistic Structure ◽  
Patterns And Processes ◽  
Hydrologic Inputs ◽  
Soil Climate

Ecohydrology is the science that studies the mutual interaction between the hydrological cycle and ecosystems. Such an interaction is especially intense in water-controlled ecosystems, where water may be a limiting factor, not only because of its scarcity, but also because of its intermittent and unpredictable appearance. Hydrologic dynamics is shown to be a crucial factor for ecological patterns and processes. The probabilistic structure of soil moisture in time and space is presented as the key linkage between soil, climate and vegetation dynamics. Nutrient cycles, vegetation coexistence and plant response to environmental conditions are all intimately linked to the stochastic fluctuation of the hydrologic inputs driving an ecosystem.

Landscape allometry: from tidal channel hydraulic geometry to benthic ecology

2002 ◽  
Vol 59 (8) ◽  
pp. 1418-1427 ◽  
Author(s):  
W Gregory Hood
Keyword(s):  
Exit Time ◽  
Surface Velocity ◽  
Hydraulic Geometry ◽  
Tidal Channel ◽  
Tidal Channels ◽  
Surface Deposit ◽  
Channel Size ◽  
Channel Form ◽  
Ecological Patterns ◽  
Patterns And Processes

The use of hydraulic geometry and other geomorphic indices has been recommended for habitat restoration and creation of estuarine tidal channels. Although such an approach provides design guidance for tidal channel form, it does not provide guidance for the ecological consequences of channel form. This study investigates the potential linkage of the scaling of tidal channel form with ecological patterns and processes in estuarine tidal channels of the lower Chehalis River, Washington, U.S.A. Ebb tide surface velocity was related to channel size, as was exit time and export probability of tiny drogues, which mimic floating allochthonous detritus. Consequently, the amount of organic material in channel sediments scaled negatively with channel size as did the abundance of benthic surface deposit feeders. These observations suggest that the highest concentrations of fish feeding in estuarine tidal channels may be in smaller channels or in the smaller and more distal portions of large channels. Scaling of ecological patterns and processes with tidal channel size may be an example of a more general ecological scaling with landscape form, i.e., landscape allometry.

scholarly journals Water quality in two Australian dryland rivers: spatial and temporal variability and the role of flow

2010 ◽  
Vol 61 (8) ◽  
pp. 864 ◽  
Author(s):  
Fran Sheldon ◽  
Christine S. Fellows
Keyword(s):  
Water Quality ◽  
Temporal Variability ◽  
Temporal Dynamics ◽  
Spatial And Temporal Variability ◽  
Quality Guidelines ◽  
Spatial And Temporal Dynamics ◽  
Flow Phase ◽  
Ecological Patterns ◽  
Patterns And Processes ◽  
Dryland Rivers

Water quality, along with hydrology, plays an important role in the spatial and temporal dynamics of a range of ecological patterns and processes in large rivers and is also often a key component of river health assessments. Geology and land use are significant drivers of water quality during flow periods while during periods of no-flow, local-scale factors such as evaporation, groundwater influence and the concentration and precipitation of compounds are important. This study explored the water quality changes in two Australian dryland rivers, the Cooper Creek (Lake Eyre Basin) and the Warrego River (Murray–Darling Basin), across different hydrological phases over several years. Water quality varied both spatially and temporally; the greatest spatial variability occurred during the no-flow phase, with temporal changes driven by flow. Concentrations of major anions and cations also varied spatially and temporally, with an overall cation dominance of calcium and magnesium and an anion dominance of bicarbonate. This bicarbonate dominance contrasts with previous data from inland lentic systems where sodium chloride was found to dominate. Such extreme spatial and temporal variability hampers successful derivation of water quality guidelines for these variable rivers and suggests such guidelines would need to be developed with respect to ‘flow phase’.

scholarly journals A simulation study of the use of temporal occupancy for identifying core and transient species

2020 ◽  
Author(s):  
Sara Snell Taylor ◽  
Jessica R. Coyle ◽  
Ethan P. White ◽  
Allen H. Hurlbert
Keyword(s):  
Transient Species ◽  
Imperfect Detection ◽  
Heterogeneous Landscapes ◽  
Core Species ◽  
Simulation Based ◽  
Ecological Patterns ◽  
Misclassification Rates ◽  
Patterns And Processes ◽  
Source Sink

AbstractTransient species, which do not maintain self-sustaining populations in a system where they are observed, are ubiquitous in nature and their presence often impacts the interpretation of ecological patterns and processes. Identifying transient species from temporal occupancy, the proportion of time a species is observed at a given site over a time series, is subject to classification errors as a result of imperfect detection and source-sink dynamics. We use a simulation-based approach to assess how often errors in detection or classification occur in order to validate the use of temporal occupancy as a metric for inferring whether a species is a core or transient member of a community. We found that low detection increases error in the classification of core species, while high habitat heterogeneity and high detection increase error in classification of transient species. These findings confirm that temporal occupancy is a valid metric for inferring whether a species can maintain a self-sustaining population, but imperfect detection, low abundance, and highly heterogeneous landscapes may yield high misclassification rates.

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