National University of San Luis

Carbon sequestration strategies highlight tree plantations without considering their full environmental consequences. We combined field research, synthesis of more than 600 observations, and climate and economic modeling to document substantial losses in stream flow, and increased soil salinization and acidification, with afforestation. Plantations decreased stream flow by 227 millimeters per year globally (52%), with 13% of streams drying completely for at least 1 year. Regional modeling of U.S. plantation scenarios suggests that climate feedbacks are unlikely to offset such water losses and could exacerbate them. Plantations can help control groundwater recharge and upwelling but reduce stream flow and salinize and acidify some soils.

Plant rooting depth affects ecosystem resilience to environmental stress such as drought. Deep roots connect deep soil/groundwater to the atmosphere, thus influencing the hydrologic cycle and climate. Deep roots enhance bedrock weathering, thus regulating the long-term carbon cycle. However, we know little about how deep roots go and why. Here, we present a global synthesis of 2,200 root observations of >1,000 species along biotic (life form, genus) and abiotic (precipitation, soil, drainage) gradients. Results reveal strong sensitivities of rooting depth to local soil water profiles determined by precipitation infiltration depth from the top (reflecting climate and soil), and groundwater table depth from below (reflecting topography-driven land drainage). In well-drained uplands, rooting depth follows infiltration depth; in waterlogged lowlands, roots stay shallow, avoiding oxygen stress below the water table; in between, high productivity and drought can send roots many meters down to the groundwater capillary fringe. This framework explains the contrasting rooting depths observed under the same climate for the same species but at distinct topographic positions. We assess the global significance of these hydrologic mechanisms by estimating root water-uptake depths using an inverse model, based on observed productivity and atmosphere, at 30″ (∼1-km) global grids to capture the topography critical to soil hydrology. The resulting patterns of plant rooting depth bear a strong topographic and hydrologic signature at landscape to global scales. They underscore a fundamental plant-water feedback pathway that may be critical to understanding plant-mediated global change.

Abstract Carbon sequestration programs, including afforestation and reforestation, are gaining attention globally and will alter many ecosystem processes, including water yield. Some previous analyses have addressed deforestation and water yield, while the effects of afforestation on water yield have been considered for some regions. However, to our knowledge no systematic global analysis of the effects of afforestation on water yield has been undertaken. To assess and predict these effects globally, we analyzed 26 catchment data sets with 504 observations, including annual runoff and low flow. We examined changes in the context of several variables, including original vegetation type, plantation species, plantation age, and mean annual precipitation (MAP). All of these variables should be useful for understanding and modeling the effects of afforestation on water yield. We found that annual runoff was reduced on average by 44% (±3%) and 31% (±2%) when grasslands and shrublands were afforested, respectively. Eucalypts had a larger impact than other tree species in afforested grasslands ( P =0.002), reducing runoff (90) by 75% (±10%), compared with a 40% (±3%) average decrease with pines. Runoff losses increased significantly with plantation age for at least 20 years after planting, whether expressed as absolute changes (mm) or as a proportion of predicted runoff (%) ( P <0.001). For grasslands, absolute reductions in annual runoff were greatest at wetter sites, but proportional reductions were significantly larger in drier sites ( P <0.01 and P <0.001, respectively). Afforestation effects on low flow were similar to those on total annual flow, but proportional reductions were even larger for low flow ( P <0.001). These results clearly demonstrate that reductions in runoff can be expected following afforestation of grasslands and shrublands and may be most severe in drier regions. Our results suggest that, in a region where natural runoff is less than 10% of MAP, afforestation should result in a complete loss of runoff; where natural runoff is 30% of precipitation, it will likely be cut by half or more when trees are planted. The possibility that afforestation could cause or intensify water shortages in many locations is a tradeoff that should be explicitly addressed in carbon sequestration programs.

New Internet of Things (IoT) technologies such as Long Range (LoRa) are emerging which enable power efficient wireless communication over very long distances. Devices typically communicate directly to a sink node which removes the need of constructing and maintaining a complex multi-hop network. Given the fact that a wide area is covered and that all devices communicate directly to a few sink nodes a large number of nodes have to share the communication medium. LoRa provides for this reason a range of communication options (centre frequency, spreading factor, bandwidth, coding rates) from which a transmitter can choose. Many combination settings are orthogonal and provide simultaneous collision free communications. Nevertheless, there is a limit regarding the number of transmitters a LoRa system can support. In this paper we investigate the capacity limits of LoRa networks. Using experiments we develop models describing LoRa communication behaviour. We use these models to parameterise a LoRa simulation to study scalability. Our experiments show that a typical smart city deployment can support 120 nodes per 3.8 ha, which is not sufficient for future IoT deployments. LoRa networks can scale quite well, however, if they use dynamic communication parameter selection and/or multiple sinks.

PyMC is a probabilistic programming library for Python that provides tools for constructing and fitting Bayesian models. It offers an intuitive, readable syntax that is close to the natural syntax statisticians use to describe models. PyMC leverages the symbolic computation library PyTensor, allowing it to be compiled into a variety of computational backends, such as C, JAX, and Numba, which in turn offer access to different computational architectures including CPU, GPU, and TPU. Being a general modeling framework, PyMC supports a variety of models including generalized hierarchical linear regression and classification, time series, ordinary differential equations (ODEs), and non-parametric models such as Gaussian processes (GPs). We demonstrate PyMC's versatility and ease of use with examples spanning a range of common statistical models. Additionally, we discuss the positive role of PyMC in the development of the open-source ecosystem for probabilistic programming.

While conceptually simple, Bayesian methods can be mathematically and numerically challenging. Probabilistic programming languages (PPLs) implement functions to easily build Bayesian models together with efficient automatic inference methods. This helps separate the model building from the inference, allowing practitioners to focus on their specific problems and leaving PPLs to handle the computational details for them The inference process generates a posterior distribution -which has a central role in Bayesian statistics -together with other distributions like the posterior predictive distribution and the prior predictive distribution. The correct visualization, analysis, and interpretation of these distributions is key to properly answer the questions that motivate the inference process.

Variability of above-ground net primary production (ANPP) of arid to sub-humid ecosystems displays a closer association with precipitation when considered across space (based on multiyear averages for different locations) than through time (based on year-to-year change at single locations). Here, we propose a theory of controls of ANPP based on four hypotheses about legacies of wet and dry years that explains space versus time differences in ANPP-precipitation relationships. We tested the hypotheses using 16 long-term series of ANPP. We found that legacies revealed by the association of current- versus previous-year conditions through the temporal series occur across all ecosystem types from deserts to mesic grasslands. Therefore, previous-year precipitation and ANPP control a significant fraction of current-year production. We developed unified models for the controls of ANPP through space and time. The relative importance of current-versus previous-year precipitation changes along a gradient of mean annual precipitation with the importance of current-year PPT decreasing, whereas the importance of previous-year PPT remains constant as mean annual precipitation increases. Finally, our results suggest that ANPP will respond to climate-change-driven alterations in water availability and, more importantly, that the magnitude of the response will increase with time.

Afforestation, the conversion of non-forested lands to forest plantations, can sequester atmospheric carbon dioxide, but the rapid growth and harvesting of biomass may deplete nutrients and degrade soils if managed improperly. The goal of this study is to evaluate how afforestation affects mineral soil quality, including pH, sodium, exchangeable cations, organic carbon, and nitrogen, and to examine the magnitude of these changes regionally where afforestation rates are high. We also examine potential mechanisms to reduce the impacts of afforestation on soils and to maintain long-term productivity. Across diverse plantation types (153 sites) to a depth of 30 cm of mineral soil, we observed significant decreases in nutrient cations (Ca, K, Mg), increases in sodium (Na), or both with afforestation. Across the data set, afforestation reduced soil concentrations of the macronutrient Ca by 29% on average (P < 0.05). Afforestation by Pinus alone decreased soil K by 23% (P < 0.05). Overall, plantations of all genera also led to a mean 71% increase of soil Na (P < 0.05). Mean pH decreased 0.3 units (P < 0.05) with afforestation. Afforestation caused a 6.7% and 15% (P < 0.05) decrease in soil C and N content respectively, though the effect was driven principally by Pinus plantations (15% and 20% decrease, P < 0.05). Carbon to nitrogen ratios in soils under plantations were 5.7-11.6% higher (P < 0.05). In several regions with high rates of afforestation, cumulative losses of N, Ca, and Mg are likely in the range of tens of millions of metric tons. The decreases indicate that trees take up considerable amounts of nutrients from soils; harvesting this biomass repeatedly could impair long-term soil fertility and productivity in some locations. Based on this study and a review of other literature, we suggest that proper site preparation and sustainable harvest practices, such as avoiding the removal or burning of harvest residue, could minimize the impact of afforestation on soils. These sustainable practices would in turn slow soil compaction, erosion, and organic matter loss, maintaining soil fertility to the greatest extent possible.

Soil biota influence plant performance through plant-soil feedback, but it is unclear whether the strength of such feedback depends on plant traits and whether plant-soil feedback drives local plant diversity. We grew 16 co-occurring plant species with contrasting nutrient-acquisition strategies from hyperdiverse Australian shrublands and exposed them to soil biota from under their own or other plant species. Plant responses to soil biota varied according to their nutrient-acquisition strategy, including positive feedback for ectomycorrhizal plants and negative feedback for nitrogen-fixing and nonmycorrhizal plants. Simulations revealed that such strategy-dependent feedback is sufficient to maintain the high taxonomic and functional diversity characterizing these Mediterranean-climate shrublands. Our study identifies nutrient-acquisition strategy as a key trait explaining how different plant responses to soil biota promote local plant diversity.

Policies for climate mitigation on land rarely acknowledge biophysical factors, such as reflectivity, evaporation, and surface roughness. Yet such factors can alter temperatures much more than carbon sequestration does, and often in a conflicting way. We outline a framework for examining biophysical factors in mitigation policies and provide some best-practice recommendations based on that framework. Tropical projects—avoided deforestation, forest restoration, and afforestation—provide the greatest climate value, because carbon storage and biophysics align to cool the Earth. In contrast, the climate benefits of carbon storage are often counteracted in boreal and other snow-covered regions, where darker trees trap more heat than snow does. Managers can increase the climate benefit of some forest projects by using more reflective and deciduous species and through urban forestry projects that reduce energy use. Ignoring biophysical interactions could result in millions of dollars being invested in some mitigation projects that provide little climate benefit or, worse, are counter-productive.

Land use is central to addressing sustainability issues, including biodiversity conservation, climate change, food security, poverty alleviation, and sustainable energy. In this paper, we synthesize knowledge accumulated in land system science, the integrated study of terrestrial social-ecological systems, into 10 hard truths that have strong, general, empirical support. These facts help to explain the challenges of achieving sustainability in land use and thus also point toward solutions. The 10 facts are as follows: 1) Meanings and values of land are socially constructed and contested; 2) land systems exhibit complex behaviors with abrupt, hard-to-predict changes; 3) irreversible changes and path dependence are common features of land systems; 4) some land uses have a small footprint but very large impacts; 5) drivers and impacts of land-use change are globally interconnected and spill over to distant locations; 6) humanity lives on a used planet where all land provides benefits to societies; 7) land-use change usually entails trade-offs between different benefits-"win-wins" are thus rare; 8) land tenure and land-use claims are often unclear, overlapping, and contested; 9) the benefits and burdens from land are unequally distributed; and 10) land users have multiple, sometimes conflicting, ideas of what social and environmental justice entails. The facts have implications for governance, but do not provide fixed answers. Instead they constitute a set of core principles which can guide scientists, policy makers, and practitioners toward meeting sustainability challenges in land use.

The morphological and functional design of gastrointestinal tracts of many vertebrates and invertebrates can be explained largely by the interaction between diet chemical constituents and principles of economic design, both of which are embodied in chemical reactor models of gut function. Natural selection seems to have led to the expression of digestive features that approximately match digestive capacities with dietary loads while exhibiting relatively modest excess. Mechanisms explaining differences in hydrolase activity between populations and species include gene copy number variations and single-nucleotide polymorphisms. In many animals, both transcriptional adjustment and posttranscriptional adjustment mediate phenotypic flexibility in the expression of intestinal hydrolases and transporters in response to dietary signals. Digestive performance of animals depends also on their gastrointestinal microbiome. The microbiome seems to be characterized by large beta diversity among hosts and by a common core metagenome and seems to differ flexibly among animals with different diets.

Abstract Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1‐km 2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1‐km 2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse‐grained air temperature estimates from ERA5‐Land (an atmospheric reanalysis by the European Centre for Medium‐Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome‐specific offsets emphasize that the projected impacts of climate and climate change on near‐surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil‐related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

This paper introduces a particle swarm optimization algorithm to solve constrained engineering optimization problems. The proposed approach uses a relatively simple method to handle constraints and a different mechanism to update the velocity and position of each particle. The algorithm is validated using four standard engineering design problems reported in the specialized literature and it is compared with respect to algorithms representative of the state-of-the-art in the area. Our results indicate that the proposed scheme is a promising alternative to solve this sort of problems because it obtains good results with a low number of objective function evaluations.

Abstract International agreements aim to conserve 17% of Earth's land area by 2020 but include no area‐based conservation targets within the working landscapes that support human needs through farming, ranching, and forestry. Through a review of country‐level legislation, we found that just 38% of countries have minimum area requirements for conserving native habitats within working landscapes. We argue for increasing native habitats to at least 20% of working landscape area where it is below this minimum. Such target has benefits for food security, nature's contributions to people, and the connectivity and effectiveness of protected area networks in biomes in which protected areas are underrepresented. We also argue for maintaining native habitat at higher levels where it currently exceeds the 20% minimum, and performed a literature review that shows that even more than 50% native habitat restoration is needed in particular landscapes. The post‐2020 Global Biodiversity Framework is an opportune moment to include a minimum habitat restoration target for working landscapes that contributes to, but does not compete with, initiatives for expanding protected areas, the UN Decade on Ecosystem Restoration (2021–2030) and the UN Sustainable Development Goals.

A series of bio-compatible metal-organic frameworks (MOFs) have been studied as potential carriers for drug delivery applications. Grand canonical Monte Carlo (GCMC) simulations were performed to study the adsorption of the model drug ibuprofen. Simulations were first validated with available experimental data for ibuprofen adsorption and release in MIL-53, MIL-100 and MIL-101. In the second stage, the study was extended to three additional MOFs with interesting properties in terms of bio-compatibility and porosity: CDMOF-1, based on edible precursors; MOF-74 containing a highly biocompatible metal (Mg); and BioMOF-100, a mesoporous MOF with extremely high pore volume. By comparing with experimental data, we show how GCMC simulation is able to predict the macroscopic performance of new porous MOFs in drug delivery applications, providing useful molecular-level insights and giving thermodynamic and structural details of the process. Adsorption isotherms, snapshots, energy of adsorption and radial distribution functions were used to analyse the drug delivery process.

Animals maintain complex associations with a diverse microbiota living in their guts. Our understanding of the ecology of these associations is extremely limited in reptiles. Here, we report an in-depth study into the microbial ecology of gut communities in three syntopic and viviparous lizard species (two omnivores: Liolaemus parvus and Liolaemus ruibali and an herbivore: Phymaturus williamsi). Using 16S rRNA gene sequencing to inventory various bacterial communities, we elucidate four major findings: (i) closely related lizard species harbour distinct gut bacterial microbiota that remain distinguishable in captivity; a considerable portion of gut bacterial diversity (39.1%) in nature overlap with that found on plant material, (ii) captivity changes bacterial community composition, although host-specific communities are retained, (iii) faecal samples are largely representative of the hindgut bacterial community and thus represent acceptable sources for nondestructive sampling, and (iv) lizards born in captivity and separated from their mothers within 24 h shared 34.3% of their gut bacterial diversity with their mothers, suggestive of maternal or environmental transmission. Each of these findings represents the first time such a topic has been investigated in lizard hosts. Taken together, our findings provide a foundation for comparative analyses of the faecal and gastrointestinal microbiota of reptile hosts.

Abstract Vegetation changes, particularly those involving transitions between tree‐ and grass‐dominated covers, often modify evaporative water losses as a result of plant‐mediated shifts in moisture access and demand. Massive afforestation of native grasslands, particularly important in the Southern Hemisphere, may have strong yet poorly quantified effects on the hydrological cycle. We explored water use patterns in Eucalyptus grandis plantations and the native humid grasslands that they replace in Central Argentina. In order to uncover the interactive effects that land cover type, soil texture and climate variability may have on evaporative water losses and water use efficiency, we estimated daily evapotranspiration (ET) in 117 tree plantations and grasslands plots across a soil textural gradient (clay‐textured Vertisols to sandy‐textured Entisols) using radiometric information from seven Landsat scenes, existing timber productions records, and 13 C measurements in tree stems. Tree plantations had cooler surface temperatures (−5°C on average) and evaporated more water (+80% on average) than grasslands at all times and across all sites. Absolute ET differences between grasslands and plantations ranged from ∼0.6 to 2 mm day −1 and annual up‐scaling suggested values of ∼630 and ∼1150 mm yr −1 for each vegetation type, respectively. The temporal variability of ET was significantly lower in plantations compared with grasslands (coefficient of variation 36% vs. 49%). Daily ET increased as the water balance became more positive (accumulated balance for previous 18 days) with a saturation response in grassland vs. a continuous linear increase in plantations, suggesting lower ecophysiological limits to water loss in tree canopies compared with the native vegetation. Plantation ET was more strongly affected by soil texture than grassland ET and peaked in coarse textured sites followed by medium and fine textured sites. Timber productivity as well as 13 C concentration in stems peaked in medium textured sites, indicating lower water use efficiency on extreme textures and suggesting that water limitation was not responsible for productivity declines towards finer and coarser soils. Our study highlighted the key role that vegetation type plays on evapotranspiration and, therefore, in the hydrological cycle. Considering that tree plantations may continue their expansion over grasslands, problematic changes in water management and, perhaps, in local climate can develop from the higher evaporative water losses of tree plantations.

The impacts of a 40 ha stand of Eucalyptus camaldulensis in the Pampas grasslands of Argentina were explored for 2 years using a novel combination of sap flow, groundwater data, soil moisture measurements, and modeling. Sap flow measurements showed transpiration rates of 2–3.7 mm d −1 , lowering groundwater levels by more than 0.5 m with respect to the surrounding grassland. This hydraulic gradient induced flow from the grassland areas into the plantation and resulted in a rising of the plantation water table at night. Groundwater use estimated from diurnal water table fluctuations correlated well with sap flow (p &lt; 0.001, r 2 = 0.78). Differences between daily sap flow and the estimates of groundwater use were proportional to changes in surface soil moisture content (p &lt; 0.001, r 2 = 0.75). E. camaldulensis therefore used both groundwater and vadose zone moisture sources, depending on soil water availability. Model results suggest that groundwater sources represented ∼67% of total annual water use.

An algorithm to calculate the density of states, based on the well-known Wang-Landau method, is introduced. Independent random walks are performed in different restricted ranges of energy, and the resultant density of states is modified by a function of time, F(t) proportional to t-1, for large time. As a consequence, the calculated density of state, gm(E,t) , approaches asymptotically the exact value g(ex)(E) as proportional to t-1/2, avoiding the saturation of the error. It is also shown that the growth of the interface of the energy histogram belongs to the random deposition universality class.