Eremocene: the Age of Loneliness; the "miserable future" into which we are accelerating as a species, characterised by the existential & material isolation that comes from having calamitously extinguished other forms of life on Earth. 

Eremoceno: la Era de la Soledad; el "futuro miserable" hacia el que estamos acelerando como especie, caracterizado por el aislamiento existencial y material que proviene de haber extinguido calamitosamente otras formas de vida en la Tierra.

 

E.O. Wilson

Complex agricultural landscapes host more biodiversity than simple ones: A global meta-analysis 

Estrada-Carmona et al., 2022

Significance

Agricultural land, the world’s largest human-managed ecosystem, forms the matrix that connects remnant and fragmented patches of natural vegetation where nondomesticated biodiversity struggles to survive. Increasing the resources that this matrix can offer to biodiversity is critical to halting biodiversity loss. Our comprehensive meta-analysis demonstrates the positive and significant effect on biodiversity of increasing landscape complexity in agricultural lands. We found more biodiversity in complex landscapes, potentially contributing to agriculture production, ecosystem resilience, and human well-being. Current biodiversity conservation strategies tend to focus on natural ecosystems, often ignoring opportunities to boost biodiversity in agricultural landscapes. Our findings provide a strong scientific evidence base for managing agriculture at the landscape level for biodiversity synergistically conservation and sustainable production.

Abstract

Managing agricultural landscapes to support biodiversity conservation requires profound structural changes worldwide. Often, discussions are centered on management at the field level. However, a wide and growing body of evidence calls for zooming out and targeting agricultural policies, research, and interventions at the landscape level to halt and reverse the decline in biodiversity, increase biodiversity-mediated ecosystem services in agricultural landscapes, and improve the resilience and adaptability of these ecosystems. We conducted the most comprehensive assessment to date on landscape complexity effects on nondomesticated terrestrial biodiversity through a meta-analysis of 1,134 effect sizes from 157 peer-reviewed articles. Increasing landscape complexity through changes in composition, configuration, or heterogeneity significatively and positively affects biodiversity. More complex landscapes host more biodiversity (richness, abundance, and evenness) with potential benefits to sustainable agricultural production and conservation, and effects are likely underestimated. The few articles that assessed the combined contribution of linear (e.g., hedgerows) and areal (e.g., woodlots) elements resulted in a near-doubling of the effect sizes (i.e., biodiversity level) compared to the dominant number of studies measuring these elements separately. Similarly, positive effects on biodiversity are stronger in articles monitoring biodiversity for at least 2 y compared to the dominant 1-y monitoring efforts. Besides, positive and stronger effects exist when monitoring occurs in nonoverlapping landscapes, highlighting the need for long-term and robustly designed monitoring efforts. Living in harmony with nature will require shifting paradigms toward valuing and promoting multifunctional agriculture at the farm and landscape levels with a research agenda that untangles complex agricultural landscapes’ contributions to people and nature under current and future conditions.

https://bit.ly/3LjOlbL

.

Global Warming 

John Harte

 

Global Warming John Harte, PhD from Central Colorado Humanists on Vimeo.

All of the rivers and waterways in South America, with coastlines, coloured according to the major hydrological basins they are part of and scaled by their size.

Via: PythonMaps

Community structure determines the predictability of population collapse 

Baruah et al., 2022.

1. Early warning signals (EWS) are phenomenological tools that have been proposed as predictors of the collapse of biological systems. Although a growing body of work has shown the utility of EWS based on either statistics derived from abundance data or shifts in phenotypic traits such as body size, so far this work has largely focused on single species populations.
2. However, to predict reliably the future state of ecological systems, which inherently could consist of multiple species, understanding how reliable such signals are in a community context is critical.
3. Here, reconciling quantitative trait evolution and Lotka–Volterra equations, which allow us to track both abundance and mean traits, we simulate the collapse of populations embedded in mutualistic and multi-trophic predator–prey communities. Using these simulations and warning signals derived from both population- and community-level data, we showed the utility of abundance-based EWS, as well as metrics derived from stability-landscape theory (e.g. width and depth of the basin of attraction), were fundamentally linked. Thus, the depth and width of such stability-landscape curves could be used to identify which species should exhibit the strongest EWS of collapse.
4. The probability a species displays both trait and abundance-based EWS was dependent on its position in a community, with some species able to act as indicator species. In addition, our results also demonstrated that in general trait-based EWS were less reliable in comparison with abundance-based EWS in forecasting species collapses in our simulated communities. Furthermore, community-level abundance-based EWS were fairly reliable in comparison with their species-level counterparts in forecasting species-level collapses.
5. Our study suggests a holistic framework that combines abundance-based EWS and metrics derived from stability-landscape theory that may help in forecasting species loss in a community context.

https://bit.ly/3BjTBZM