Monitoring biodiversity loss in rapidly changing Afrotropical ecosystems: an emerging imperative for governance and research.

Africa is experiencing extensive biodiversity loss due to rapid changes in the environment, where natural resources constitute the main instrument for socioeconomic development and a mainstay source of livelihoods for an increasing population. Lack of data and information deficiency on biodiversity, but also budget constraints and insufficient financial and technical capacity, impede sound policy design and effective implementation of conservation and management measures. The problem is further exacerbated by the lack of harmonized indicators and databases to assess conservation needs and monitor biodiversity losses. We review challenges with biodiversity data (availability, quality, usability and database access) as a key limiting factor that impacts funding and governance. We also evaluate the drivers of both ecosystems change and biodiversity loss as a central piece of knowledge to develop and implement effective policies. While the continent focuses more on the latter, we argue that the two are complementary in shaping restoration and management solutions. We thus underscore the importance of establishing monitoring programmes focusing on biodiversity-ecosystem linkages in order to inform evidence-based decisions in ecosystem conservation and restoration in Africa. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

Technical note: Bayesian calibration of dynamic ruminant nutrition models.

Mechanistic models of ruminant digestion and metabolism have advanced our understanding of the processes underlying ruminant animal physiology. Deterministic modeling practices ignore the inherent variation within and among individual animals and thus have no way to assess how sources of error influence model outputs. We introduce Bayesian calibration of mathematical models to address the need for robust mechanistic modeling tools that can accommodate error analysis by remaining within the bounds of data-based parameter estimation. For the purpose of prediction, the Bayesian approach generates a posterior predictive distribution that represents the current estimate of the value of the response variable, taking into account both the uncertainty about the parameters and model residual variability. Predictions are expressed as probability distributions, thereby conveying significantly more information than point estimates in regard to uncertainty. Our study illustrates some of the technical advantages of Bayesian calibration and discusses the future perspectives in the context of animal nutrition modeling.

Phosphorus retention in a mesotrophic lake under transient loading conditions: insights from a sediment phosphorus binding form study.

Phosphorus retention in sediments has been estimated for three basins in Lake Simcoe, a mesotrophic lake in Ontario, Canada. Total phosphorous (TP) fractionation was used to examine the concentration of phosphorus (P) binding forms in the sediments of Cook's Bay, Kempenfelt Bay, and the Main Basin. The extended sequential extractions allowed us to differentiate between organic-, inorganic-, carbonate-bounded and redox-sensitive phosphorus. Our results showed different mechanisms of P release in each of the three investigated basins, which may be linked to their distinct loading histories, present land-uses and morphology of the sampling sites. In the deep Main Basin, where moderate changes in P loading have been induced by deforestation, sediments are not an important long-term source of diagenetically mobile P, as almost 75% of P is released within a short time scale. P release is predominantly generated by a continuous epilimnetic P flux, rather than a large inventory of temporary P stored in the sediments. Diagenesis in the upper sediment layers is fast enough to prevent a large accumulation of temporary P. In the much deeper glacially formed Kempenfelt Bay with a highly urbanized catchment, P release from the sediments is dominated by the redox-sensitive P fraction, representing up to 40% and 57% of long- and short-term sediment P release, respectively. In the shallow and agriculturally-impacted Cook's Bay, the main P binding form that can be mobilized through diagenesis is carbonate-bound P. This fraction contributes 40.1% and 37.6% to the long- and short-term P sediment release, respectively. Although different mechanisms of P release have been revealed for the three basins in Lake Simcoe, the vertical profiles indicate that the sediments throughout the system are still able to bind deposited P.

Examination of the uncertainty in contaminant fate and transport modeling: a case study in the Venice Lagoon.

A Monte Carlo analysis is used to quantify environmental parametric uncertainty in a multi-segment, multi-chemical model of the Venice Lagoon. Scientific knowledge, expert judgment and observational data are used to formulate prior probability distributions that characterize the uncertainty pertaining to 43 environmental system parameters. The propagation of this uncertainty through the model is then assessed by a comparative analysis of the moments (central tendency, dispersion) of the model output distributions. We also apply principal component analysis in combination with correlation analysis to identify the most influential parameters, thereby gaining mechanistic insights into the ecosystem functioning. We found that modeled concentrations of Cu, Pb, OCDD/F and PCB-180 varied by up to an order of magnitude, exhibiting both contaminant- and site-specific variability. These distributions generally overlapped with the measured concentration ranges. We also found that the uncertainty of the contaminant concentrations in the Venice Lagoon was characterized by two modes of spatial variability, mainly driven by the local hydrodynamic regime, which separate the northern and central parts of the lagoon and the more isolated southern basin. While spatial contaminant gradients in the lagoon were primarily shaped by hydrology, our analysis also shows that the interplay amongst the in-place historical pollution in the central lagoon, the local suspended sediment concentrations and the sediment burial rates exerts significant control on the variability of the contaminant concentrations. We conclude that the probabilistic analysis presented herein is valuable for quantifying uncertainty and probing its cause in over-parameterized models, while some of our results can be used to dictate where additional data collection efforts should focus on and the directions that future model refinement should follow.

A predictive approach to nutrient criteria.

Violation of a water quality standard triggers the need for a total maximum daily load (TMDL); this should result in actions that improve water quality, but sometimes at significant cost. If the standard is well-conceived, a designated-use statement characterizes societal values, and a criterion provides a measurable surrogate for designated use. This latter provision means that scientists measure the criterion and view violations of the criterion as equivalent to noncompliance with the designated use. However, if a criterion is not a good indicator of designated use, it is apt to result in misallocation of the limited resources for water quality improvement through the TMDL process. This concern provides the basis for our assessment of the national nutrient criteria strategy recently proposed by the U.S. EPA. We acquired data sets for four case studies (Lake Washington, Neuse River Estuary, San Francisco Bay, and Lake Mendota) and then used expert elicitation to quantify designated-use attainment for each case. Applying structural equation modeling, we identified good water quality criteria as the best predictors of the designated use elicited response variable. Further, we used the model to relate the level (concentration) of each criterion to the probability of compliance with the designated use; this provides decision-makers with an estimate of risk associated with the criterion level, facilitating the selection of appropriate water quality criteria.

Eutrophication risk assessment in coastal embayments using simple statistical models.

A statistical methodology is proposed for assessing the risk of eutrophication in marine coastal embayments. The procedure followed was the development of regression models relating the levels of chlorophyll a (Chl) with the concentration of the limiting nutrient--usually nitrogen--and the renewal rate of the systems. The method was applied in the Gulf of Gera, Island of Lesvos, Aegean Sea and a surrogate for renewal rate was created using the Canberra metric as a measure of the resemblance between the Gulf and the oligotrophic waters of the open sea in terms of their physical, chemical and biological properties. The Chl-total dissolved nitrogen-renewal rate regression model was the most significant, accounting for 60% of the variation observed in Chl. Predicted distributions of Chl for various combinations of the independent variables, based on Bayesian analysis of the models, enabled comparison of the outcomes of specific scenarios of interest as well as further analysis of the system dynamics. The present statistical approach can be used as a methodological tool for testing the resilience of coastal ecosystems under alternative managerial schemes and levels of exogenous nutrient loading.

Environmental control and limnological impacts of a large recurrent spring bloom in Lake Washington, USA.

A series of statistical analyses were used to identify temporal and spatial patterns in the phytoplankton and nutrient dynamics of Lake Washington, an mesotrophic lake in Washington State (USA). These analyses were based on fortnightly or monthly samples of water temperature, Secchi transparency, ammonium (NH(4)), nitrate (NO(3)), inorganic phosphorus (IP), total nitrogen (TN), total phosphorus (TP), dissolved oxygen (DO), pH and chlorophyll a (chl a) collected during 1995-2000 from 12 stations. Lake Washington has a very consistent and pronounced annual spring diatom bloom which occurs from March to May. During this bloom, epilimnetic chl a concentrations peak on average at 10 microg/L, which is 3 times higher than chl a concentrations typically seen during summer stratified conditions. The spring bloom on average comprised 62% diatoms, 21% chlorophytes and 8% cyanobacteria. During summer stratification, diatoms comprised 26% of the phytoplankton community, chlorophytes 37% and cyanobacteria 25%. Cryptophytes comprised approximately 8% of the community throughout the year. Overall, 6 phytoplankton genera (i.e., Aulacoseira, Fragilaria, Cryptomonas, Asterionella, Stephanodiscus, and Ankistrodesmus) cumulatively accounted for over 50% of the community. These analyses also suggest that the phytoplankton community strongly influences the seasonality of NO(3), IP, DO, pH and water clarity. According to a MANOVA, seasonal fluctuations explained 40% of the total variability for the major parameters, spatial heterogeneity explained 10% of variability, and the seasonal-spatial interaction explained 10% of variability. Distinctive patterns were identified between offshore and inshore sampling stations. The results of our analyses also suggest that spatial variability was substantial, but much smaller than temporal variability.

Analysis of phytoplankton community structure using similarity indices: a new methodology for discriminating among eutrophication levels in coastal marine ecosystems.

Nine similarity indices based on phytoplankton community structure were examined for their sensitivity to assess different levels of eutrophication. Two phytoplankton data sets, one from an open coastal system and one from a semi-enclosed gulf, associated with different nutrient dynamics and circulation patterns were used for evaluating the indices. The results have shown that similarity indices, measuring interspecific association and resemblance of phytoplankton communities between enriched areas and control sites, were effective for detecting spatial and temporal dissimilarities in coastal marine ecosystems. The structure of the oligotrophic habitat as a potential source of ambiguity for the results was discussed, whereas the validity ranges and the potential applicability of this method were deemed to be dependent on the size of the fraction of the common species among the samples, and the similarity of the classification patterns resulted from this subcategory and those extracted from the overall community data. Furthermore, the study provides a new technique based on the use of the "Box and Whisker Plot" designed to distinguish opportunistic and rare phytoplanktonic species. The similarity indices, applied solely to the dominant species abundance, were more sensitive to resolve eutrophic, mesotrophic and oligotrophic conditions. This procedure can be proposed as an effective methodology for water characterization and can also be used as a qualitative tracer for detecting renewal processes of coastal marine ecosystems.

Quantitative assessment of agricultural runoff and soil erosion using mathematical modeling: applications in the Mediterranean region.

Three mathematical models, the runoff curve number equation, the universal soil loss equation, and the mass response functions, were evaluated for predicting nonpoint source nutrient loading from agricultural watersheds of the Mediterranean region. These methodologies were applied to a catchment, the gulf of Gera Basin, that is a typical terrestrial ecosystem of the islands of the Aegean archipelago. The calibration of the model parameters was based on data from experimental plots from which edge-of-field losses of sediment, water runoff, and nutrients were measured. Special emphasis was given to the transport of dissolved and solid-phase nutrients from their sources in the farmers' fields to the outlet of the watershed in order to estimate respective attenuation rates. It was found that nonpoint nutrient loading due to surface losses was high during winter, the contribution being between 50% and 80% of the total annual nutrient losses from the terrestrial ecosystem. The good fit between simulated and experimental data supports the view that these modeling procedures should be considered as reliable and effective methodological tools in Mediterranean areas for evaluating potential control measures, such as management practices for soil and water conservation and changes in land uses, aimed at diminishing soil loss and nutrient delivery to surface waters. Furthermore, the modifications of the general mathematical formulations and the experimental values of the model parameters provided by the study can be used in further application of these methodologies in watersheds with similar characteristics.

Ecological patterns and comparative nutrient dynamics of natural and agricultural mediterranean-type ecosystems.

An agricultural watershed, situated on an island of the Aegean archipelago, was studied in order to gain insight into the structure and the design of a typical terrestrial ecosystem of the Mediterranean region. Fieldwork was focused on the comparative study of seasonal patterns of inorganic nutrients, organic nitrogen, and erosion over the most abundant vegetation types of the area, such as olive groves, maquis, and wetlands. Nutrient losses via the pathway of erosion were provided by the determination of nutrient concentrations in runoff sediments. Results showed that nutrient levels are higher and more susceptible to rapid changes in the zones that host agricultural activities and animal husbandry. The behavior of nitrogen and phosphorus showed remarkable stability in the maquis, where dynamic processes were mainly affected by soil erosion, which led gradually to land degradation, especially on sloping terrains. The aim of this study was to form the basis for the quantification of the interconnections within the Mediterranean-type ecosystems and to conceptualize their operational properties.