Yohay Carmel

Identification of 100 fundamental ecological questions

Summary 1. Fundamental ecological research is both intrinsically interesting and provides the basic knowledge required to answer applied questions of importance to the management of the natural world. The 100th anniversary of the British Ecological Society in 2013 is an opportune moment to reflect on the current status of ecology as a science and look forward to high-light priorities for future work.

Sensitivity analysis for complex ecological models - A new approach

A strategy for global sensitivity analysis of a multi-parameter ecological model was developed and used for the hydrodynamic-ecological model (DYRESM-CAEDYM, DYnamic REservoir Simulation Model-Computational Aquatic Ecosystem Dynamics Model) applied to Lake Kinneret (Israel). Two different methods of sensitivity analysis, RPART (Recursive Partitioning And Regression Trees) and GLM (General Linear Model) were applied in order to screen a subset of significant parameters. All the parameters which were found significant by at least one of these methods were entered as input to a GBM (Generalized Boosted Modeling) analysis in order to provide a quantitative measure of the sensitivity of the model variables to these parameters. Although the GBM is a general and powerful machine learning algorithm, it has substantial computational costs in both storage requirements and CPU time. Employing the screening stage reduces this cost. The results of the analysis highlighted the role of particulate organic material in the lake ecosystem and its impact on the over all lake nutrient budget. The GBM analysis established, for example, that parameters such as particulate organic material diameter and density were particularly important to the model outcomes. The results were further explored by lumping together output variables that are associated with sub-components of the ecosystem. The variable lumping approach suggested that the phytoplankton group is most sensitive to parameters associated with the dominant phytoplankton group, dinoflagellates, and with nanoplankton (Chlorophyta), supporting the view of Lake Kinneret as a bottom-up system. The study demonstrates the effectiveness of such procedures for extracting useful information for model calibration and guiding further data collection.

Info‐Gap Robust‐Satisficing Model of Foraging Behavior: Do Foragers Optimize or Satisfice?

In this note we compare two mathematical models of foraging that reflect two competing theories of animal behavior: optimizing and robust satisficing. The optimal‐foraging model is based on the marginal value theorem (MVT). The robust‐satisficing model developed here is an application of info‐gap decision theory. The info‐gap robust‐satisficing model relates to the same circumstances described by the MVT. We show how these two alternatives translate into specific predictions that at some points are quite disparate. We test these alternative predictions against available data collected in numerous field studies with a large number of species from diverse taxonomic groups. We show that a large majority of studies appear to support the robust‐satisficing model and reject the optimal‐foraging model.

Monitoring post-wildfire vegetation response with remotely sensed time-series data in Spain, USA and Israel

Due to the challenges faced by resource managers in maintaining post-fire ecosystem health, there is a need for methods to assess the ecological consequences of disturbances. This research examines an approach for assessing changes in post-fire vegetation dynamics for sites in Spain, Israel and the USA that burned in 1998, 1999 and 2002 respectively. Moderate Resolution Imaging Spectroradiometer satellite Normalized Difference Vegetation Index (NDVI) time-series data (2000-07) are used for all sites to characterise and track the seasonal and spatial changes in vegetation response. Post-fire trends and metrics for burned areas are evaluated and compared with unburned reference sites to account for the influence of local environmental conditions. Time-series data interpretation provides insights into climatic influences on the post-fire vegetation. Although only two sites show increases in post-fire vegetation, all sites show declines in heterogeneity across the site. The evaluation of land surface phenological metrics, including the start and end of the season, the base and peak NDVI, and the integrated seasonal NDVI, show promising results, indicating trends in some measures of post-fire phenology. Results indicate that this monitoring approach, based on readily available satellite-based time-series vegetation data, provides a valuable tool for assessing post-fire vegetation response.

The evolution of the cultural Mediterranean landscape in Israel as affected by fire, grazing, and human activities.

The early evolution of the cultural Mediterranean landscape in Israel, with special reference to Mt. Carmel, is described with a holistic landscape-ecological systems approach as the coevolution of the paleolithic food gatherer-hunter and his landscapes. In addition to archeological findings and our research on fire ecology and the comparative dynamics of Mediterranean landscapes in Israel and California, we made use of new insights into the selforganization of living systems and landscapes and the theory of nonlinear general evolution. From the Middle Pleistocene onward, this process occurred in two major bifurcations; one in which the pristine forest landscape was converted by human land uses and by natural and intentional set fires into a more open subnatural landscape, and then from the Upper Pleistocene onward into a grass-rich, seminatural, landscape mosaic. The final stage of this coevolution was reached more than 10,000 years ago by the advanced epipaleolithic, preagricultural Natufians, whose rich culture and intensive land use have a striking resemblance with those of the pre-European central coastal California Indians. During the third major bifurcation of the Neolithic agricultural revolution, arable seminatural landscapes were converted into agropastoral ones. The coevolutionary symbiotic relationship was replaced by human dominance leading to intensive land uses including burning and grazing. This period is missing from Californian landscapes, ‘jumping’ almost directly into the agroindustrial age and, therefore, apparently also lacking the great regeneration capacities and adaptive resilience acquired by Mediterranean landscapes.

Spatial analysis of air pollution and cancer incidence rates in Haifa Bay, Israel

The Israel National Cancer Registry reported in 2001 that cancer incidence rates in the Haifa area are roughly 20% above the national average. Since Haifa has been the major industrial center in Israel since 1930, concern has been raised that the elevated cancer rates may be associated with historically high air pollution levels. This work tests whether persistent spatial patterns of metrics of chronic exposure to air pollutants are associated with the observed patterns of cancer incidence rates. Risk metrics of chronic exposure to PM(10), emitted both by industry and traffic, and to SO(2), a marker of industrial emissions, was developed. Ward-based maps of standardized incidence rates of three prevalent cancers: Non-Hodgkins lymphoma, lung cancer and bladder cancer were also produced. Global clustering tests were employed to filter out those cancers that show sufficiently random spatial distribution to have a nil probability of being related to the spatial non-random risk maps. A Bayesian method was employed to assess possible associations between the morbidity and risk patterns, accounting for the ward-based socioeconomic status ranking. Lung cancer in males and bladder cancer in both genders showed non-random spatial patterns. No significant associations between the SO(2)-based risk maps and any of the cancers were found. Lung cancer in males was found to be associated with PM(10), with the relative risk associated with an increase of 1 microg/m(3) of PM(10) being 12%. Special consideration of wards with expected rates <1 improved the results by decreasing the variance of the spatially correlated residual log-relative risk.

Comparing landscape scale vegetation dynamics following recent disturbance in climatically similar sites in California and the Mediterranean basin

A long line of inquiry on the notion of ecological convergence has compared ecosystem structure and function between areas that are evolutionarily unrelated but under the same climate regime. Much of this literature has focused on quantifying the degree to which animal morphology or plant physiognomy is alike between disjunct areas. An important property of ecosystems is their behavior following disturbance. Yet, this aspect of ecosystems has not been investigated in a comparative study of convergence. If different ecosystems are under similar environmental controls, then one would predict that the rates and patterns of response to disturbance would also be similar. The objective of this study is to compare landscape dynamics following disturbance using spatiotemporal models to quantify vegetation change in Mediterranean ecosystems found in California and Israel. We model the process of tree and shrub regeneration at the landscape scale in two similar study sites in Israel (Mount Meron) and California (Hasting Nature Reserve). During the periods studied (1964-1992 for Israel and 1971-1995 for California), average annual change in tree cover was 5 times larger in Israel than in California. Based on multiple regression models, differences were found in the relative importance of specific variables predicting vegetation change. In Hastings (California), initial tree cover accounted for most of the explained variability in 1995 tree cover (partial R2 = 0.71), while in Meron (Israel), grazing type and intensity, topography indices, and initial vegetation each accounted for about a third of the explained variability. These findings support the notion that traits such as regeneration pattern and rate, both at the individual level and at the landscape level, were largely affected by the human land use history of the region.

Trends in Ecological Research during the Last Three Decades – A Systematic Review

It is thought that the science of ecology has experienced conceptual shifts in recent decades, chiefly from viewing nature as static and balanced to a conception of constantly changing, unpredictable, complex ecosystems. Here, we ask if these changes are reflected in actual ecological research over the last 30 years. We surveyed 750 articles from the entire pool of ecological literature and 750 articles from eight leading journals. Each article was characterized according to its type, ecological domain, and applicability, and major topics. We found that, in contrast to its common image, ecology is still mostly a study of single species (70% of the studies); while ecosystem and community studies together comprise only a quarter of ecological research. Ecological science is somewhat conservative in its topics of research (about a third of all topics changed significantly through time), as well as in its basic methodologies and approaches. However, the growing proportion of problem-solving studies (from 9% in the 1980s to 20% in the 2000 s) may represent a major transition in ecological science in the long run.

Automated segmentation of vegetation structure units in a Mediterranean landscape

In Mediterranean regions, the combination of disturbances, life histories, plant regeneration traits, and microhabitat variability form highly heterogeneous vegetation mosaics which shift in space and time. Consequently, structure-based forest management is emerging as a superior alternative to management of vegetation formations in such areas. Delineation of management units in these areas is often based on manual interpretation of aerial imagery coupled with field surveys. Here, we propose an alternative approach that is based on segmentation of remotely sensed height and cover maps derived from light detection and ranging (LiDAR) imagery. A large suite of alternative segmentation maps was generated using multiresolution segmentation (MS) with different parameters, and an area-fit approach used to select the map that most successfully captured a reference set of structural units delineated manually. We assessed the feasibility of this approach in a nature reserve in northern Israel, compared the resulting map with a traditional vegetation formations map, and explored the performance of the segmentation algorithm under various parameter combinations. Pronounced differences between the structure and formation maps highlight the suitability of this approach as an alternative to the existing methods of delineating vegetation units in Mediterranean systems, and possibly in other systems as well.

Performance of a spatio-temporal error model for raster datasets under complex error patterns

The CLC (Combined Location Classification) error model provides indices for overall data uncertainty in thematic spatio-temporal datasets. It accounts for the two major sources of error in such datasets, location error and classification error. The model assumes independence between error components, while recent studies revealed various degrees of correlation between error components in actual datasets. The goal of this study is to determine if the likely violation of model assumptions biases model predictions. A comprehensive algorithm was devised to simulate the entire process of error formation and propagation. Time series thematic maps were constructed, and modified maps were derived as realizations of underlying error patterns. Error rate and pattern (positive autocorrelation) were controlled for location error and for classification error. The magnitude of correlation between errors from different sources and correlation between error at different time steps was also controlled. A very good agreement between model predictions and simulation results was found in the absence of correlation in error between time steps and between error types, while the inclusion of such correlations was shown to affect model fit slightly. Given our current knowledge of spatio-temporal error patterns in real data, the CLC error model can be used reliably to assess the overall uncertainty in thematic change detection analyses.