Contribution of Home Gardens to Sustainable Development: Perspectives from A Supported Opinion Essay.

Home gardening has a long history that started when humans became sedentary, being traditionally considered an accessible source of food and medicinal plants to treat common illnesses. With trends towards urbanization and industrialization, particularly in the post-World War II period, the importance of home gardens as important spaces for growing food and medicinal plants reduced and they began to be increasingly seen as decorative and leisure spaces. However, the growing awareness of the negative impacts of agricultural intensification and urbanization for human health, food quality, ecosystem resilience, and biodiversity conservation motivated the emergence of new approaches concerning home gardens. Societies began to question the potential of nearby green infrastructures to human wellbeing, food provisioning, and the conservation of traditional varieties, as well as providers of important services, such as ecological corridors for wild species and carbon sinks. In this context. and to foster adaptive and resilient social-ecological systems, our supported viewpoint intends to be more than an exhaustive set of perceptions, but a reflection of ideas about the important contribution of home gardens to sustainable development. We envision these humble spaces strengthening social and ecological components, by providing a set of diversified and intermingled goods and services for an increasingly urban population.

Seasonal Variation in Selected Biochemical Traits in the Leaves of Co-Occurring Invasive and Native Plant Species under Mediterranean Conditions.

The success of invasive alien species (IAS) is often linked to differences in functional traits in relation to other, either native or non-invasive, species. Two of the most problematic IAS in the Mediterranean area belong to Hakea and Acacia genera that often invade pine plantations. Therefore, the aim of this study was to assess the seasonal variations in photosynthetic pigments, total phenolics, and non-structural carbohydrates (NSC), including total soluble sugars (SS) and starch (St), and lipid peroxidation, in terms of malondialdehyde (MDA) in the leaves of evergreen species, two IAS (Hakea sericea and Acacia melanoxylon) and one native (Pinus pinaster), throughout 2019. All parameters showed a pronounced seasonal variability while also differing across species. Generally, the lowest contents of photosynthetic pigments, phenolics and SS were noted in early spring, along with the highest St and NSC values. On the other hand, higher photosynthetic pigment and lower NSC contents were measured in early autumn and early winter. When these parameters were compared across the three species, the IAS had significantly higher content of photosynthetic pigments, mainly chlorophyll b and total chlorophyll, and lower total phenolics and MDA concentrations in their leaves than Pinus pinaster. Differences in seasonal patterns were also observed. Hakea sericea and Acacia melanoxylon had considerably higher chlorophyll, SS and NSC contents in the early autumn, while Pinus pinaster had higher St and MDA contents in early summer. Overall, the biochemical characteristics of leaves of the studied IAS can explain their success in the Mediterranean area, in terms of tolerance to stressful environmental conditions.

MAMMALS IN PORTUGAL: A data set of terrestrial, volant, and marine mammal occurrences in Portugal.

Mammals are threatened worldwide, with ~26% of all species being included in the IUCN threatened categories. This overall pattern is primarily associated with habitat loss or degradation, and human persecution for terrestrial mammals, and pollution, open net fishing, climate change, and prey depletion for marine mammals. Mammals play a key role in maintaining ecosystems functionality and resilience, and therefore information on their distribution is crucial to delineate and support conservation actions. MAMMALS IN PORTUGAL is a publicly available data set compiling unpublished georeferenced occurrence records of 92 terrestrial, volant, and marine mammals in mainland Portugal and archipelagos of the Azores and Madeira that includes 105,026 data entries between 1873 and 2021 (72% of the data occurring in 2000 and 2021). The methods used to collect the data were: live observations/captures (43%), sign surveys (35%), camera trapping (16%), bioacoustics surveys (4%) and radiotracking, and inquiries that represent less than 1% of the records. The data set includes 13 types of records: (1) burrows | soil mounds | tunnel, (2) capture, (3) colony, (4) dead animal | hair | skulls | jaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8), observation in shelters, (9) photo trapping | video, (10) predators diet | pellets | pine cones/nuts, (11) scat | track | ditch, (12) telemetry and (13) vocalization | echolocation. The spatial uncertainty of most records ranges between 0 and 100 m (76%). Rodentia (n =31,573) has the highest number of records followed by Chiroptera (n = 18,857), Carnivora (n = 18,594), Lagomorpha (n = 17,496), Cetartiodactyla (n = 11,568) and Eulipotyphla (n = 7008). The data set includes records of species classified by the IUCN as threatened (e.g., Oryctolagus cuniculus [n = 12,159], Monachus monachus [n = 1,512], and Lynx pardinus [n = 197]). We believe that this data set may stimulate the publication of other European countries data sets that would certainly contribute to ecology and conservation-related research, and therefore assisting on the development of more accurate and tailored conservation management strategies for each species. There are no copyright restrictions; please cite this data paper when the data are used in publications.

Oceans of stimuli: an individual-based model to assess the role of olfactory cues and local enhancement in seabirds' foraging behaviour.

Oceans are extremely dynamic environments, which poses challenges for top-predators such as seabirds to find food resources. Yet, seabirds evolved sensorial abilities (olfactory senses) along with complex behaviours (social information transfer through local enhancement) to improve foraging efficiency. Using the Cory's shearwater (Calonectris borealis) as a model species, we developed an individual-based model to explore the complementary role of different searching mechanisms (olfactory foraging and local enhancement) for the optimal foraging behaviour of pelagic seabirds during 1-day foraging trips around breeding colonies. Model outputs were compared with observed patterns of Cory's shearwaters distribution during local foraging trips. Also, the foraging efficiency of virtual individuals was analysed considering hypothetical scenarios of foraging conditions and densities of foraging individuals around breeding colonies. The results support the use of a combination of searching strategies by Cory's shearwaters, which produced representative patterns of space use from tracked individuals, including spatial foraging segregation of neighbouring sub-colonies. Furthermore, while the mechanisms underpinning local enhancement played a key role in mitigating sub-optimal foraging conditions, the use of olfactory senses conferred great adaptive foraging advantages over a wide range of environmental conditions. Our results also indicate a synergistic effect between the two strategies, which suggests that a multimodal foraging strategy is useful to forage in extremely dynamic environments. The developed model provides a basis for further investigation regarding the role of foraging mechanisms in the population dynamics of colonial animals, including the adaptive foraging behaviour of marine top predators to dynamic environmental conditions.

Are data-mining techniques useful for selecting ecological indicators in biodiverse regions? Bridges between market basket analysis and indicator value analysis from a case study in the neotropics

Ecological monitoring research relies heavily on signals to detect ecosystem changes, making the selection of indicators a crucial methodological requirement. Over the years, individual species and species assemblages have been widely used, thereby, giving rise to reference methods that support the detection of ecological indicators. One such method, the Indicator Value Analysis (IndVal), has been adapted to identify not only species but also combinations of species, assuming collective responses to environmental factors. However, the IndVal method requires a pre-selection of species before performing the analysis, especially in the case of large datasets (e.g. high species richness), when it becomes ineffective. Species pre-selection might introduce subjectivity and a bias into the database, which can cause possible impacts on the final set of indicators. To address these issues, the authors propose the use of Market Basket Analysis (MBA) – a data mining method – which is mathematically similar to IndVal but designed to handle large amounts of data. Both methods were applied to select indicators from gradually larger datasets of Soil Surface Dwelling Arthropods from the Brazilian Amazon, using threshold-dependent indices to assess concordance between results. In general, the results obtained by applying both methods were found to be similar, with an average Jaccard's distance of 0.432 (±0.346) and an average True Skill Statistic of 0.991 (±0.012). As expected, MBA was able to select ecological indicators without species pre-selection as well as from datasets where IndVal had been unsuccessful. In such cases, and by means of objective association rules, the authors demonstrate that MBA could be used to pre-select ecological indicators, which can then be further processed and summarized with the IndVal method. In this study, the authors briefly outline the potential of MBA to complement IndVal and discuss advantages and disadvantages of using MBA for ecological indicators (pre-) selection.

Is wind energy increasing the impact of socio-ecological change on Mediterranean mountain ecosystems? Insights from a modelling study relating wind power boost options with a declining species.

The growing concern about future challenges of energy security and climate change has led to the expansion of renewable energy production, with a special emphasis on wind power. Despite the environmental advantages of wind power, it's important to assess the impacts caused by the presence of wind farms on wildlife, particularly on species also affected by habitat loss and degradation. In Mediterranean Europe, the skylark (Alauda arvensis) is a declining passerine that breeds in mountain habitats vulnerable to the abandonment of traditional management practices and climate change. We have created a spatially explicit agent-based model (ABM) in order to replicate the selection of territories, evaluating the effect of wind farms on the mortality rate of breeding males. We were especially interested in assessing the mortality rates related with the interplay between habitat loss due to socio-ecological change and increasing wind power using alternative strategies: adding wind turbines or substituting existing wind turbines by more powerful ones, i.e. repowering. Several known aspects related with the risk of collision of A. arvensis with wind turbines were considered, particularly regarding the male habitat selection and behaviour displayed throughout the breeding season. By simulating a sequential contraction of suitable habitat for the species, we found a substantial increase in the breeding territories superimposed to the wind farm influence zone. In these conditions males' relative mortality was predicted to suffer significant increases. For equivalent wind power, adding wind turbines produced significant increases in the males' relative mortality, whereas repowering didn't. Based on our findings we propose repowering as a defensible strategy to increase wind energy production without increasing A. arvensis collision risk. We highlight that this strategy might also benefit other vulnerable bird and bat species associated with declining habitats of mountain ridges in the Mediterranean region.

How informative is the response of Ground Beetles' (Coleoptera: Carabidae) assemblages to anthropogenic land use changes? Insights for ecological status assessments from a case study in the Neotropics.

Ground Beetles (Carabidae) have been suggested to be used as indicators of ecological status under the effects of anthropogenic land use and land cover changes in highly biodiverse regions such as the Neotropics. In this study Ground Beetles' assemblages from a region in the Brazilian Amazon were investigated for evaluating their applicability as disturbance indicators. Differences in assemblages between ecosystems, discriminated by complimentary methodologies, demonstrate a sensitive reaction from the most pristine forests to increasingly disturbed systems. Besides capturing the influence of different prevailing conditions between ecosystems, Ground Beetles are easy to communicate and to link with the other components of the system, being effortless and routinely measurable using standard methodologies. This study represents a step forward in using Ground Beetles for the purposes of planning, management and public reporting on the ecological status of Neotropical ecosystems. Additionally, the methods depicted could support projections for trends of relevant ecosystem attributes under realistic social-ecological change scenarios, which can be used to guide effective conservation planning.

A modelling framework to predict bat activity patterns on wind farms: An outline of possible applications on mountain ridges of North Portugal.

Worldwide ecological impact assessments of wind farms have gathered relevant information on bat activity patterns. Since conventional bat study methods require intensive field work, the prediction of bat activity might prove useful by anticipating activity patterns and estimating attractiveness concomitant with the wind farm location. A novel framework was developed, based on the stochastic dynamic methodology (StDM) principles, to predict bat activity on mountain ridges with wind farms. We illustrate the framework application using regional data from North Portugal by merging information from several environmental monitoring programmes associated with diverse wind energy facilities that enable integrating the multifactorial influences of meteorological conditions, land cover and geographical variables on bat activity patterns. Output from this innovative methodology can anticipate episodes of exceptional bat activity, which, if correlated with collision probability, can be used to guide wind farm management strategy such as halting wind turbines during hazardous periods. If properly calibrated with regional gradients of environmental variables from mountain ridges with windfarms, the proposed methodology can be used as a complementary tool in environmental impact assessments and ecological monitoring, using predicted bat activity to assist decision making concerning the future location of wind farms and the implementation of effective mitigation measures.

A stochastic dynamic model to assess land use change scenarios on the ecological status of fluvial water bodies under the Water Framework Directive.

This method development paper outlines an integrative stochastic dynamic methodology (StDM) framework to anticipate land use (LU) change effects on the ecological status of monitored and non-monitored lotic surface waters under the Water Framework Directive (WFD). Tested in the Alto Minho River Basin District in North West Portugal, the model is an innovative step towards developing a decision-making and planning tool to assess the influence impacts such as LU change and climate change on these complex systems. Comprising a series of sequential steps, a Generalized Linear Model based, competing model Multi Model Inference (MMI) approach was used for parameter estimation to identify principal land use types (distal factors) driving change in biological and physicochemical support elements (proximal factors) in monitored water bodies. The framework integrated MMI constants and coefficients of selected LU categories in the StDM simulations and spatial projections to simulate the ecological status of monitored and non-monitored lotic waterbodies in the test area under 2 scenarios of (1) LU intensification and (2) LU extensification. A total of 100 simulations were run for a 50year period for each scenario. Spatially dynamic projections of WFD metrics were obtained, taking into account the occurrence of stochastic wildfire events which typically occur in the study region and are exacerbated by LU change. A marked projected decline to "Moderate" ecological status for most waterbodies was detected under intensification but little change under extensification; only a few waterbodies fell to "moderate" status. The latter scenario describes the actual regional socio-economic situation of agricultural abandonment due to rural poverty, partly explaining the projected lack of change in ecological status. Based on the WFD "one out all out" criterion, projected downward shifts in ecological status were due to physicochemical support elements, namely increased phosphorus levels. Little or no change in status was driven by Intercalibrated Biological Quality Elements, indicating innate resilience and raising questions concerning uncertainty, the effect of pressures other than land use and metric redundancy and the WFD classification process.

Predicting trends of invasive plants richness using local socio-economic data: an application in North Portugal.

This study assesses the potential of an integrated methodology for predicting local trends in invasive exotic plant species (invasive richness) using indirect, regional information on human disturbance. The distribution of invasive plants was assessed in North Portugal using herbarium collections and local environmental, geophysical and socio-economic characteristics. Invasive richness response to anthropogenic disturbance was predicted using a dynamic model based on a sequential modeling process (stochastic dynamic methodology-StDM). Derived scenarios showed that invasive richness trends were clearly associated with ongoing socio-economic change. Simulations including scenarios of growing urbanization showed an increase in invasive richness while simulations in municipalities with decreasing populations showed stable or decreasing levels of invasive richness. The model simulations demonstrate the interest and feasibility of using this methodology in disturbance ecology.