Socio-economic development drives solid waste management performance in cities: A global analysis using machine learning

Mismanaged municipal solid waste (MSW), the major source of plastics pollution and a key contributor to climate forcing, in Global South cities poses public health and environmental problems. This study analyses the first consistent and quality assured dataset available for cities distributed worldwide, featuring a comprehensive set of solid waste management performance indicators (Wasteaware Cities Benchmark Indicators - WABI). Machine learning (multivariate random forest) and univariate non-linear regression are applied, identifying best-fit converging models for a broad range of explanatory socioeconomic variables. These proxies describe in a variety of ways generic levels of progress, such as Gross Domestic Product - Purchasing Power per capita, Social Progress Index (SPI) and Corruption Perceptions Index. Specifically, the research tests and quantitatively confirms a long-standing, yet unverified, hypothesis: that variability in cities' performance on MSW can be accounted for by socioeconomic development indices. The results provide a baseline for measuring progress as cities report MSW performance for the sustainable development goal SDG11.6.1 indicator: median rates of controlled recovery and disposal are approximately at 45 % for cities in low-income countries, 75 % in lower-middle, and 100 % for both upper-middle and high-income. Casting light on aspects beyond the SDG metric, on the quality of MSW-related services, show that improvements in service quality often lag improvements in service coverage. Overall, the findings suggest that progress in collection coverage, and controlled recovery and disposal has already taken place in low- and middle-income cities. However, if cities aspire to perform better on MSW management than would have been anticipated by the average socioeconomic development in their country, they should identify ways to overcome systemic underlying failures associated with that socioeconomic level. Most alarmingly, 'business as usual' development would substantially increase their waste generation per capita unless new policies are found to promote decoupling.

Sampling and modelling rare species: Conceptual guidelines for the neglected majority

Biodiversity conservation faces a methodological conundrum: Biodiversity measurement often relies on species, most of which are rare at various scales, especially prone to extinction under global change, but also the most challenging to sample and model. Predicting the distribution change of rare species using conventional species distribution models is challenging because rare species are hardly captured by most survey systems. When enough data are available, predictions are usually spatially biased towards locations where the species is most likely to occur, violating the assumptions of many modelling frameworks. Workflows to predict and eventually map rare species distributions imply important trade-offs between data quantity, quality, representativeness and model complexity that need to be considered prior to survey and analysis. Our opinion is that study designs need to carefully integrate the different steps, from species sampling to modelling, in accordance with the different types of rarity and available data in order to improve our capacity for sound assessment and prediction of rare species distribution. In this article, we summarize and comment on how different categories of species rarity lead to different types of occurrence and distribution data depending on choices made during the survey process, namely the spatial distribution of samples (where to sample) and the sampling protocol in each selected location (how to sample). We then clarify which species distribution models are suitable depending on the different types of distribution data (how to model). Among others, for most rarity forms, we highlight the insights from systematic species-targeted sampling coupled with hierarchical models that allow correcting for overdispersion and spatial and sampling sources of bias. Our article provides scientists and practitioners with a much-needed guide through the ever-increasing diversity of methodological developments to improve the prediction of rare species distribution depending on rarity type and available data.

Scale dependency of conservation outcomes in a forest-offsetting scheme

Offset schemes help avoid or revert habitat loss through protection of existing habitat (avoided deforestation), through the restoration of degraded areas (natural regrowth), or both. The spatial scale of an offset scheme may influence which of these 2 outcomes is favored and is an important aspect of the scheme's design. However, how spatial scale influences the trade-offs between the preservation of existing habitat and restoration of degraded areas is poorly understood. We used the largest forest offset scheme in the world, which is part of the Brazilian Forest Code, to explore how implementation at different spatial scales may affect the outcome in terms of the area of avoided deforestation and area of regrowth. We employed a numerical simulation of trade between buyers (i.e., those who need to offset past deforestation) and sellers (i.e., landowners with exceeding native vegetation) in the Brazilian Amazon to estimate potential avoided deforestation and regrowth at different spatial scales of implementation. Allowing offsets over large spatial scales led to an area of avoided deforestation 12 times greater than regrowth, whereas restricting offsets to small spatial scales led to an area of regrowth twice as large as avoided deforestation. The greatest total area (avoided deforestation and regrowth combined) was conserved when the spatial scale of the scheme was small, especially in locations that were highly deforested. To maximize conservation gains from avoided deforestation and regrowth, the design of the Brazilian forest-offset scheme should focus on restricting the spatial scale in which offsets occur. Such a strategy could help ensure conservation benefits are localized and promote the recovery of degraded areas in the most threatened forest landscapes.

FragSAD: A database of diversity and species abundance distributions from habitat fragments

Habitat destruction is the single greatest anthropogenic threat to biodiversity. Decades of research on this issue have led to the accumulation of hundreds of data sets comparing species assemblages in larger, intact, habitats to smaller, more fragmented, habitats. Despite this, little synthesis or consensus has been achieved, primarily because of non-standardized sampling methodology and analyses of notoriously scale-dependent response variables (i.e., species richness). To be able to compare and contrast the results of habitat fragmentation on species' assemblages, it is necessary to have the underlying data on species abundances and sampling intensity, so that standardization can be achieved. To accomplish this, we systematically searched the literature for studies where abundances of species in assemblages (of any taxa) were sampled from many habitat patches that varied in size. From these, we extracted data from several studies, and contacted authors of studies where appropriate data were collected but not published, giving us 117 studies that compared species assemblages among habitat fragments that varied in area. Less than one-half (41) of studies came from tropical forests of Central and South America, but there were many studies from temperate forests and grasslands from all continents except Antarctica. Fifty-four of the studies were on invertebrates (mostly insects), but there were several studies on plants (15), birds (16), mammals (19), and reptiles and amphibians (13). We also collected qualitative information on the length of time since fragmentation. With data on total and relative abundances (and identities) of species, sampling effort, and affiliated meta-data about the study sites, these data can be used to more definitively test hypotheses about the role of habitat fragmentation in altering patterns of biodiversity. There are no copyright restrictions. Please cite this data paper and the associated Dryad data set if the data are used in publications.

Cascading ecological effects from local extirpation of an ecosystem engineer in the Arava desert

The extinction of a single species from a local community may carry little cost in terms of species diversity, yet its loss eliminates its biotic and abiotic interactions. We describe such a scenario in the Arava desert, where different cultural and law enforcement practices exclude Dorcas gazelles (Gazella dorcas (Linnaeus, 1758)) from the Jordanian side of the border while protecting their populations on the Israeli side. We found that gazelles break the soil crust, formed in desert systems after annual flooding, thereby creating patches of loose and cooler sand that are used by pit-building antlions (Neuroptera: Myrmeleontidae). When we artificially broke the soil crust on both sides of the border, we found a significant increase in antlion density in these patches, but only on the Israeli side. On the Jordanian side, where no gazelles have been observed since the early 1980s, no antlions colonized either control or manipulated plots. Additional choice/no-choice feeding experiments, in which we offered antlions to lizards and birds, revealed that the effect of humans on gazelles cascades farther, as antlions serve as a palatable food source for both groups. Thus, the human-mediated loss of nontrophic interactions between gazelles and antlions cascades to the loss of trophic interactions between antlions and their predators.

From endosymbionts to host communities: factors determining the reproductive success of arthropod vectors

Elucidating the factors determining reproductive success has challenged scientists since Darwin, but the exact pathways that shape the evolution of life history traits by connecting extrinsic (e.g., landscape structure) and intrinsic (e.g., female's age and endosymbionts) factors and reproductive success have rarely been studied. Here we collected female fleas from wild rodents in plots differing in their densities and proportions of the most dominant rodent species. We then combined path analysis and model selection approaches to explore the network of effects, ranging from micro to macroscales, determining the reproductive success of these fleas. Our results suggest that female reproductive success is directly and positively associated with their infection by Mycoplasma bacteria and their own body mass, and with the rodent species size and total density. In addition, we found evidence for indirect effects of rodent sex and rodent community diversity on female reproductive success. These results highlight the importance of exploring interrelated factors across organization scales while studying the reproductive success of wild organisms, and they have implications for the control of vector-borne diseases.

Joint Effect of Habitat Identity and Spatial Distance on Spiders' Community Similarity in a Fragmented Transition Zone

Understanding the main processes that affect community similarity have been the focus of much ecological research. However, the relative effects of environmental and spatial aspects in structuring ecological communities is still unresolved and is probably scale-dependent. Here, we examine the effect of habitat identity and spatial distance on fine-grained community similarity within a biogeographic transition zone. We compared four hypotheses: i) habitat identity alone, ii) spatial proximity alone, iii) non-interactive effects of both habitat identity and spatial proximity, and iv) interactive effect of habitat identity and spatial proximity. We explored these hypotheses for spiders in three fragmented landscapes located along the sharp climatic gradient of Southern Judea Lowlands (SJL), Israel. We sampled 14,854 spiders (from 199 species or morphospecies) in 644 samples, taken in 35 patches and stratified to nine different habitats. We calculated the Bray-Curtis similarity between all samples-pairs. We divided the pairwise values to four functional distance categories (same patch, different patches from the same landscape, adjacent landscapes and distant landscapes) and two habitat categories (same or different habitats) and compared them using non-parametric MANOVA. A significant interaction between habitat identity and spatial distance was found, such that the difference in mean similarity between same-habitat pairs and different-habitat pairs decreases with spatial distance. Additionally, community similarity decayed with spatial distance. Furthermore, at all distances, same-habitat pairs had higher similarity than different-habitats pairs. Our results support the fourth hypothesis of interactive effect of habitat identity and spatial proximity. We suggest that the environmental complexity of habitats or increased habitat specificity of species near the edge of their distribution range may explain this pattern. Thus, in transitions zones care should be taken when using habitats as surrogate of community composition in conservation planning since similar habitats in different locations are more likely to support different communities.

Association of host and microbial species diversity across spatial scales in desert rodent communities

Relationships between host and microbial diversity have important ecological and applied implications. Theory predicts that these relationships will depend on the spatio-temporal scale of the analysis and the niche breadth of the organisms in question, but representative data on host-microbial community assemblage in nature is lacking. We employed a natural gradient of rodent species richness and quantified bacterial communities in rodent blood at several hierarchical spatial scales to test the hypothesis that associations between host and microbial species diversity will be positive in communities dominated by organisms with broad niches sampled at large scales. Following pyrosequencing of rodent blood samples, bacterial communities were found to be comprised primarily of broad niche lineages. These communities exhibited positive correlations between host diversity, microbial diversity and the likelihood for rare pathogens at the regional scale but not at finer scales. These findings demonstrate how microbial diversity is affected by host diversity at different spatial scales and suggest that the relationships between host diversity and overall disease risk are not always negative, as the dilution hypothesis predicts.

Decoupling fragmentation from habitat loss for spiders in patchy agricultural landscapes

Habitat loss reduces species diversity, but the effect of habitat fragmentation on number of species is less clear because fragmentation generally accompanies loss of habitat. We compared four methods that aim to decouple the effects of fragmentation from the effects of habitat loss. Two methods are based on species-area relations, one on Fisher's alpha index of diversity, and one on plots of cumulative number of species detected against cumulative area sampled. We used these methods to analyze the species diversity of spiders in 2, 3.2 × 4 km agricultural landscapes in Southern Judea Lowlands, Israel. Spider diversity increased as fragmentation increased with all four methods, probably not because of the additive within-patch processes, such as edge effect and heterogeneity. The positive relation between fragmentation and species diversity might reflect that most species can disperse through the fields during the wheat-growing season. We suggest that if a given area was designated for the conservation of spiders in Southern Judea Lowlands, Israel, a set of several small patches may maximize species diversity over time.

Holy or Not, Israel is a Palaearctic Biodiversity Hotspot

In their rebuttal to my comment, Roll et al. (2011) defend their original conclusion, by questioning the theoretical framework on which I based my analysis. They stress the importance of the statistical prediction limits and the treatment of latitudinal location as a covariate. They also add an additional grid-cell-based analysis. Here, I claim that even if provincial species-area relationships (SPAR) are not parallel, they are still different. While relying on Roll et al.'s (2011) analyses, I show that for each taxon there is at least one other provincial SPAR that lies considerably above the Palaearctic SPAR, making Palaearctic countries less favorable to be identified as a global biodiversity hotspot. I further claim that prediction limits should not be used to answer the question in focus and that adding latitude as a covariate does not alter the results. Finally, I address the grid-cell analyses of Roll et al. (2011), claiming that Israel's diversity lies mainly in the species turnover between cells (i.e., β diversity) and not on the average species richness within cells (α diversity). Therefore I hold on to my former conclusion that at least for three taxa—birds, mammals, and reptiles—Israel is indeed a Palaearctic provincial hotspot.

Questioning Israel's Great Biodiversity—Relative to Whom? A Comment on Roll et al., 2009

Each evolutionary-independent province has its own mainland species area relationship (SPAR). When using the power law SPAR (S = cAz), separate mainland SPARs are parallel in a log-log space (similar z value), yet they differ in species density per unit area (c value). This implies that there are two main SPAR-based strategies to identify biodiversity hotspots. The first treats all mainland SPARs of all provinces as if they form one global SPAR. This is the strategy employed by Roll et al. (2009) when questioning Israel's high biodiversity. They concluded that Israel is not a global biodiversity hotspot. Their results may arise from the fact that Israel's province, the Palaearctic, is relatively poor. Therefore, countries from richer provinces, whose mainland SPAR lies above the Palaearctic SPAR, are identified as global hotspots. The second strategy is to construct different mainland SPARs for each province and identify the provincial hotspots. In this manuscript I ask whether Israel's biodiversity is high relative to other countries within its province. For six different taxa, I analyzed data for Palaearctic countries. For each taxon, I conducted a linear regression of species richness against the country's area, both log transformed. The studentized residuals were used to explore Israel's rank relative to all other Palaearctic countries. I found that Israel lies above the 95th percentile for reptiles and mammals and above the 90th percentile for birds. Therefore, within the Palaearctic province, Israel is indeed a biodiversity hotspot.