Modeling changes in the coastal ecosystem of the Pearl River Estuary from 1981 to 1998

The coastal ecosystem of the Pearl River Estuary (PRE) has been overfished and received a high level of combined pollution since the 1980s. Ecopath with Ecosim was used to construct two ecosystem models (for 1981 and 1998) to characterize the food web structure and functioning of the ecosystem. Pedigree work and simple sensitivity analysis were carried out to evaluate the quality of data and the uncertainty of the models. The two models seem reliable with regards to input data of good quality. Comparing the variations of outputs of these two models aimed to facilitate assessment of changes of the ecosystem during the past two decades.The trophic structure of the ecosystem has changed with an increase in the biomass proportion of lower trophic level (TL) organisms and a decrease in top predator biomass proportion. All the indices of ecosystem maturity examined show that the system was in a more mature condition in 1981 than in 1998, although the system has been in a condition of stress due to anthropogenic disturbances, such as environmental pollution and habitat destruction since 1981. The ecosystem was aggregated into six and seven integral TLs in 1981 and 1998, respectively, using the trophic aggregation routine of Ecopath. Most of the total system biomass and catch took place at TL II and III in both years. But the distribution of the total system biomass and catch at different TLs changed with decreasing proportions in higher TLs in 1998. The mean transfer efficiency was 9.1% and 10.2% in 1981 and 1998, respectively.Comparative network analysis allowed quantification of the importance of direct and indirect trophic interactions among functional groups. Moreover, a method derived from the mixed trophic impact (MTI) analysis allowed estimating importance of groups in terms of “keystoneness” and identifying the keystone species in the two models over the past two decades. The results indicate that there were no clear keystone species in 1998 but two keystone species at medium trophic levels were identified in 1981. Moreover, organisms located at low trophic levels such as phytoplankton, zooplankton and benthic invertebrates were identified to have relatively high keystoneness in the ecosystem.     

Bridging biogeochemical and food web models for an End-to-End representation of marine ecosystem dynamics: The Venice lagoon case study

The simultaneous accounting of effects of natural and anthropogenic changes within a common framework calls for the development of new comprehensive tools capable of integrating biological processes that span a huge range of scales, from viruses to fishes, in addition to their interactions with physical–chemical environmental properties, i.e. End-to-End models.     

A critical geography approach to land and water use in the tourism economy in Los Cabos,Baja California Sur,Mexico

ABSTRACT

This paper offers a critical assessment of how tourism development in the municipality of Los Cabos, Baja California Sur affects land and water use. Los Cabos is a seaside tourism Mecca located at the southern tip of the Baja California peninsula, in Mexico’s northwest. There, subsidised profits and a process of dispossession in the tourism sector have to do mainly with land and water appropriation in the form of restrictions to beach access by the local population, urban segregation and, in an arid region, privileging water provision for the tourism industry over the needs of the population. In order to sustain these claims, we map water and land use for tourism in Cabo San Lucas. We also analyse the expansion of the Los Cabos type of tourism to the small town of La Ribera, in the East Cape-Cabo Pulmo area, where marinas and high scale housing for residential tourism sprout along the coast. We argue that the seemingly ever-growing presence of tourism in the region carries with it an urgent call for the reappraisal of current approaches to land and water use, if local resources are to deliver quality of life for the population, and not only economic profitability for (mostly) foreign capital. Analytically, we address these issues by unpacking David Harvey’s concept of accumulation by dispossession, which – we argue – is for our purposes a broader tent than the (mostly Latin American) theorisations on extractivism, as we explain later in the relevant section of the paper.     

Using a fisheries ecosystem model with a water quality model to explore trophic and habitat impacts on a fisheries stock: A case study of the blue crab population in the Chesapeake Bay

Recent calls for the development of ecosystem-based fisheries management compel the development of resource management tools and linkages between existing fisheries management tools and other resource tools to enable assessment and management of multiple impacts on fisheries resources. In this paper, we describe the use of the Chesapeake Bay Fisheries Ecosystem Model (CBFEM), developed using the Ecopath with Ecosim (EwE) software, and the Chesapeake Bay Water Quality Model (WQM) to demonstrate how linkages between available modeling tools can be used to inform ecosystem-based natural resource management. The CBFEM was developed to provide strategic ecosystem information in support of fisheries management. The WQM was developed to assess impacts on water quality. The CBFEM was indirectly coupled with the WQM to assess the effects of water quality and submerged aquatic vegetation (SAV) on blue crabs. The output from two WQM scenarios (1985-1994), a baseline scenario representing actual nutrient inputs and another with reduced inputs based on a tributary management strategy, was incorporated into the CBFEM. The results suggested that blue crab biomass could be enhanced under management strategies (reduced nutrient input) when the effective search rate of blue crab young-of-the-year's (YOY's) predators or the vulnerability of blue crab YOY to its predators was adjusted by SAV. Such model linkages are important for incorporating physical and biological components of ecosystems in order to explore ecosystem-based fisheries management options.     

Importance of jumbo squid Dosidicus gigas (Orbigny, 1835) in the pelagic ecosystem of the central Gulf of California

The Humboldt squid is an important predator in the pelagic ecosystem of the central Gulf of California and the commercial catch of this species has increased over the past decade, probable due to a decrease of several top predators (sharks, large pelagic fish and the marine mammals) and the optimal feeding conditions in this area. Its high abundance and important position in the pelagic food web was quantified through two trophic models of the pelagic ecosystem of the central Gulf of California. Models represented conditions in 1980 and 2002, to document the decadal changes in ecosystem structure and function. The models were composed of 18 functional groups, including marine mammals, birds, fish, mollusks, crustaceans, and primary producers. Model results show direct negative effects on principal prey groups such as myctophids and pelagic red crab and positive effects on sharks, marine mammals and specifically sperm whales. It thus appears that the jumbo squid has an important role in the ecosystem and plays a central part in the overall energy flow as main food item for most top predators, and due to its predation of organisms on lower tropic levels.     

Invasion, Disturbance, and Competition: Modeling the Fate of Coastal Plant Populations

Abstract:  Wetland habitats are besieged by biotic and abiotic disturbances such as invasive species, hurricanes, habitat fragmentation, and salinization. Predicting how these factors will alter local population dynamics and community structure is a monumental challenge. By examining ecologically similar congeners, such as Iris hexagona and I. pseudacorus (which reproduce clonally and sexually and tolerate a wide range of environmental conditions), one can identify life-history traits that are most influential to population growth and viability. We combined empirical data and stage-structured matrix models to investigate the demographic responses of native ( I. hexagona ) and invasive ( I. pseudacorus ) plant populations to hurricanes and salinity stress in freshwater and brackish wetlands. In our models I. hexagona and I. pseudacorus responded differently to salinity stress, and species coexistence was rare. In 82% of computer simulations of freshwater marsh, invasive iris populations excluded the native species within 50 years, whereas native populations excluded the invasive species in 99% of the simulations in brackish marsh. The occurrence of hurricanes allowed the species to coexist, and species persistence was determined by the length of time it took the ecosystem to recover. Rapid recovery (2 years) favored the invasive species, whereas gradual recovery (30 years) favored the native species. Little is known about the effects of hurricanes on competitive interactions between native and invasive plant species in marsh ecosystems. Our models contribute new insight into the relationship between environmental disturbance and invasion and demonstrate how influential abiotic factors such as climate change will be in determining interspecific interactions.     

Sea-level rise and coastal vulnerability: an assessment of Andhra Pradesh coast,India through remote sensing and GIS

The eustatic sea-level rise due to global warming is predicted to be about 18 to 59 cm by the 2100 (IPCC 2007), which necessitates identification and protection of vulnerable sections of coasts. Assessment of vulnerability level of Andhra Pradesh (AP) coast as an example is demonstrated in this study using five physical variables, namely coastal geomorphology, coastal slope, shoreline change, mean spring tide range, and significant wave height. A coastal vulnerability index was prepared by integrating the differentially weighted rank values of the five variables, based on which the coastline is segmented into low-, moderate-, high-, and very high risk categories. About 43% of the 1,030-km-long AP coast is under very high-risk, followed by another 35% under high-risk if the sea level rises by ~0.6 m displacing more than 1.29 million people living within 2.0 m elevation in 282 villages in the region.     

Predicting tree distributions in an East African biodiversity hotspot: model selection, data bias and envelope uncertainty

The Eastern Arc Mountains (EAMs) of Tanzania and Kenya support some of the most ancient tropical rainforest on Earth. The forests are a global priority for biodiversity conservation and provide vital resources to the Tanzanian population. Here, we make a first attempt to predict the spatial distribution of 40 EAM tree species, using generalised additive models, plot data and environmental predictor maps at sub 1 km resolution. The results of three modelling experiments are presented, investigating predictions obtained by (1) two different procedures for the stepwise selection of predictors, (2) down-weighting absence data, and (3) incorporating an autocovariate term to describe fine-scale spatial aggregation. In response to recent concerns regarding the extrapolation of model predictions beyond the restricted environmental range of training data, we also demonstrate a novel graphical tool for quantifying envelope uncertainty in restricted range niche-based models (envelope uncertainty maps). We find that even for species with very few documented occurrences useful estimates of distribution can be achieved. Initiating selection with a null model is found to be useful for explanatory purposes, while beginning with a full predictor set can over-fit the data. We show that a simple multimodel average of these two best-model predictions yields a superior compromise between generality and precision (parsimony). Down-weighting absences shifts the balance of errors in favour of higher sensitivity, reducing the number of serious mistakes (i.e., falsely predicted absences); however, response functions are more complex, exacerbating uncertainty in larger models. Spatial autocovariates help describe fine-scale patterns of occurrence and significantly improve explained deviance, though if important environmental constraints are omitted then model stability and explanatory power can be compromised. We conclude that the best modelling practice is contingent both on the intentions of the analyst (explanation or prediction) and on the quality of distribution data; generalised additive models have potential to provide valuable information for conservation in the EAMs, but methods must be carefully considered, particularly if occurrence data are scarce. Full results and details of all species models are supplied in an online Appendix.