Phosphorus export from catchments: a global view

16 pages, figures, and tables statistics.We reviewed global P export and its controlling factors from 685 world rivers. We used available continuous (runoff, rainfall, catchment area, % land use, and population density) and discrete (runoff type, soil type, biome, dominant land use, dominant type of forest, occurrence of stagnant water bodies in catchment, and Gross Product per Capita [GPC]) variables to predict export of P fractions. P export (kg P km22 y21) spanned 6 orders of magnitude worldwide. The distribution of all fractions of P export (total P [TP], soluble reactive P [SRP], and nonSRP [dissolved organic and particle-bound P]) was right skewed. Export of nonSRP had the highest coefficient of variability, and nonSRP was the dominant part of export. The available environmental variables predicted global P export fairly well (R2 = 0.73) if total N export was included in calculations. The unexplained variance in P export might be attributed to noise in the data set, inaccuracy of measurements of environmental variables at fine scales, lack of quantitative data on anthropogenic P sources, insufficient knowledge of P behavior in catchment soils, and nonlinearity of controlling processes. P exports were highly variable among catchment types, and runoff and population density were the predictors shared by most models. P export appeared to be controlled by different sets of environmental variables in different types of catchments. Quasi-empirical, mechanistic models of P export performed better than did empirical models. Our mechanistic understanding of P export could be improved by refining current analytical methods to obtain fast and reliable values of all P fractions in aquatic ecosystems and by incorporating better and more detailed data on catchment features, anthropogenic sources of P, and instream variables in a mechanistic modelling framework.Peer reviewe

Effects of shrimp-farm effluents on the food web structure in subtropical coastal lagoons

Received 4 October 2010, Revised 24 March 2011, Accepted 29 March 2011, Available online 19 April 2011Although numerous studies have reported the negative effects of shrimp aquaculture on water quality, little is known about the ecological effects of these practices in coastal lagoons and near-shore marine habitats. The impact of shrimp-farm effluents on the food webs of an impacted subtropical coastal lagoon in the Gulf of California was evaluated through measurements of isotopic (δ13C, δ15N) signatures in sediments, plants and animals, and compared with the results of a near-pristine reference site. Degradation was manifested in a strong reduction on fish diversity at the perturbed site. δ13C signatures provided ambiguous evidence of degradation while δ15N was a better descriptor of shrimp-farm effluent impact on coastal lagoon food webs. The site receiving nutrient-rich discharges showed significant enrichment of δ15N (≈ 5‰) in sediments, macroalgae, benthic algae, filterfeeders and omnivorous feeders, resulting in qualitative differences in foodweb structure between both lagoons. The food web in the perturbed site was sustained by sediment detritus and dominated by opportunistic species. The lowest influence on δ15N signatures by aquaculture discharges recorded in the upper trophic levels could be explained by the shift in the composition of biotic communities, and associated feeding strategies. While alterations in resource availability do not affect directly food chain length, trophic linkages between food web compartments can be reduced as a result of shrimp farm impacts. Our study demonstrates that nutrient-enriched discharges from shrimp-farm aquaculture generate changes in the availability of food sources, which reduce biodiversity and alter structural and functional food web characteristics.This research was supported by the Mexican Secretary of Natural Resources and Environment (SEMARNAT-CONACYT; contract SEMAR-NAT-2002-C01-0147) and by the Spanish Ministry of Environment (Organismo Autónomo Parques Nacionales; contracts 2008/001 DECA-MERON and 81/2005 CARBONDA.Peer reviewe

Tracking spatial regimes in animal communities: Implications for resilience-based management

Spatial regimes (the spatial extents of ecological states) exhibit strong spatiotemporal order as they expand or contract in response to retreating or encroaching adjacent spatial regimes (e.g., woody plant invasion of grasslands) and human management (e.g., fire treatments). New methods enable tracking spatial regime boundaries via vegetation landcover data, and this approach is being used for strategic management across biomes. A clear advancement would be incorporating animal community data to track spatial regime boundaries alongside vegetation data. In a 41,170-hectare grassland experiencing woody plant encroachment, we test the utility of using animal community data to track spatial regimes via two hypotheses. (H1) Spatial regime boundaries identified via independent vegetation and animal datasets will exhibit spatial synchrony; specifically, grassland:woodland bird community boundaries will synchronize with grass:woody vegetation boundaries. (H2) Negative feedbacks will stabilize spatial regimes identified via animal data; specifically, frequent fire treatments will stabilize grassland bird community boundaries. We used 26 years of bird community and vegetation data alongside 32 years of fire history data. We identified spatial regime boundaries with bird community data via a wombling approach. We identified spatial regime boundaries with vegetation data by calculating spatial covariance between remotely-sensed grass and woody plant cover per pixel. For fire history data, we calculated the cumulative number of fires per pixel. Setting bird boundary strength (wombling R2 values) as the response variable, we tested our hypotheses with a hierarchical generalized additive model (HGAM). Both hypotheses were supported: animal boundaries synchronized with vegetation boundaries in space and time, and grassland bird communities stabilized as fire frequency increased (HGAM explained 38% of deviance). We can now track spatial regimes via animal community data pixel-by-pixel and year-by-year. Alongside vegetation boundary tracking, tracking animal community boundaries can inform the scale of management necessary to maintain animal communities endemic to desirable ecological states. Our approach will be especially useful for conserving animal communities requiring large-scale, unfragmented landscapes—like grasslands and steppes

Tracking spatial regimes in animal communities: Implications for resilience-based management

Spatial regimes (the spatial extents of ecological states) exhibit strong spatiotemporal order as they expand or contract in response to retreating or encroaching adjacent spatial regimes (e.g., woody plant invasion of grasslands) and human management (e.g., fire treatments). New methods enable tracking spatial regime boundaries via vegetation landcover data, and this approach is being used for strategic management across biomes. A clear advancement would be incorporating animal community data to track spatial regime boundaries alongside vegetation data. In a 41,170-hectare grassland experiencing woody plant encroachment, we test the utility of using animal community data to track spatial regimes via two hypotheses. (H1) Spatial regime boundaries identified via independent vegetation and animal datasets will exhibit spatial synchrony; specifically, grassland:woodland bird community boundaries will synchronize with grass:woody vegetation boundaries. (H2) Negative feedbacks will stabilize spatial regimes identified via animal data; specifically, frequent fire treatments will stabilize grassland bird community boundaries. We used 26 years of bird community and vegetation data alongside 32 years of fire history data. We identified spatial regime boundaries with bird community data via a wombling approach. We identified spatial regime boundaries with vegetation data by calculating spatial covariance between remotely-sensed grass and woody plant cover per pixel. For fire history data, we calculated the cumulative number of fires per pixel. Setting bird boundary strength (wombling R2 values) as the response variable, we tested our hypotheses with a hierarchical generalized additive model (HGAM). Both hypotheses were supported: animal boundaries synchronized with vegetation boundaries in space and time, and grassland bird communities stabilized as fire frequency increased (HGAM explained 38% of deviance). We can now track spatial regimes via animal community data pixel-by-pixel and year-by-year. Alongside vegetation boundary tracking, tracking animal community boundaries can inform the scale of management necessary to maintain animal communities endemic to desirable ecological states. Our approach will be especially useful for conserving animal communities requiring large-scale, unfragmented landscapes—like grasslands and steppes

Enhancing quantitative approaches for assessing community resilience

Scholars from many different intellectual disciplines have attempted to measure, estimate, or quantify resilience. However, there is growing concern that lack of clarity on the operationalization of the concept will limit its application. In this paper, we discuss the theory, research development and quantitative approaches in ecological and community resilience. Upon noting the lack of methods that quantify the complexities of the linked human and natural aspects of community resilience, we identify several promising approaches within the ecological resilience tradition that may be useful in filling these gaps. Further, we discuss the challenges for consolidating these approaches into a more integrated perspective for managing social-ecological systems

A comparative analysis reveals weak relationships between ecological factors and beta diversity of stream insect metacommunities at two spatial levels

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