Forest Cover Research Articles

A machine learning approach for estimating snow depth across the European Alps from Sentinel-1 imagery

Seasonal snow plays a crucial role in society and understanding trends in snow depth and mass is essential for making informed decisions about water resources and adaptation to climate change. However, quantifying snow depth in remote, mountainous areas with complex topography remains a significant challenge. The increasing availability of high-resolution synthetic aperture radar (SAR) observations from active microwave satellites has prompted opportunistic use of the data to retrieve snow depth remotely across large spatial and frequent temporal scales and at a high spatial resolution. Nevertheless, these novel SAR-based snow depth retrieval methods face their own set of limitations, including challenges for shallow snowpacks, high vegetation cover, and wet snow conditions. In response, here we introduce a machine learning approach to enhance SAR-based snow depth estimation over the European Alps. By integrating Sentinel-1 SAR imagery, optical snow cover observations, and topographic, forest cover and snow class information, our machine learning retrieval method more accurately estimates snow depth at independent in-situ measurement sites than current methods. Further, our method provides estimates at 100 m horizontal resolution and is capable of better capturing local-scale topography-driven snow depth variability. Through detailed feature importance analysis, we identify optimal conditions for SAR data utilization, thereby providing insight into future use of C-band SAR for snow depth retrieval.

Changes in Land Use and Land Cover, Normalized Difference Vegetation Index and Land Surface Temperature in the Narsingdi District During 2001 to 2021

Rapid urbanization and industrialization cause land use changes, reduce green spaces, and increase the land surface temperature. Green spaces of a city area maintain environmental quality by absorbing air pollutants and reducing land surface temperature. The present study aimed to detect the changes in land use and land cover (LULC), normalized difference vegetation index (NDVI), and land surface temperature (LST) in the Narsingdi district including six Upazilas from 2001 to 2021. The Landsat 7- Enhanced Thematic Mapper Plus (ETM+), the Landsat 8- Operational Land Imager (OLI) imageries and the Moderate Resolution Imaging Spectroradiometer (MODIS) data were used to analyze the LULC, NDVI, and LST by using Google Earth Engine (GEE) and ArcGIS 10.8.2. The images were analyzed into four land use classifications – agricultural land, built-up area, forest vegetation, and water body. Among all the Upazilas, Narsingdi Sadar was the vulnerable area, where agricultural land, forest coverage, and water body decreased significantly by 6.67%, 2.2%, and 4.66%, respectively. The built-up area increased by a considerable amount of 13.53% during the last twenty years. The forest coverage of Narsingdi Sadar Upazila was calculated at only 8.91% in 2021 and decreased from 11.11% in 2001. The NDVI values surprisingly increased in all the Upazilas, but in Narsingdi Sadar, it is comparatively low (0.08) than in other Upazilas. The increasing trend in LST in the Narsingdi Sadar Upazila is alarming, 1.14oC from 2001 to 2021 (0.57oC/decade). The significant changes in LULC, NDVI, and LST made the Narsingdi Sadar a more critical area in the Narsingdi district. The findings of the study will be helpful to policymakers in making appropriate decisions in future city development. J. of Sci. and Tech. Res. 5(1): 93-118, 2023

Multi-Dimensional Landscape Connectivity Index for Prioritizing Forest Cover Change Scenarios: A Case Study of Southeast China

Predicting forest cover change (FCC) and screening development scenarios are crucial for ecological resilience. However, quantitative evaluations of prioritizing forest change scenarios are limited. Here, we took five shared socio-economic pathways (SSPs) representing potential global changes, namely SSP1: sustainability, SSP2: middle of the road, SSP3: regional rivalry, SSP4: inequality, and SSP5: fossil-fueled development, which were constructed by integrated assessment and climate models. We modeled them with the patch-generating land use simulation (PLUS) and constructed a multi-dimensional landscape connectivity index (MLCI) employing forest landscape connectivity (FLC) indices to assess forest development in Fujian Province, Southeast China. The MLCI visualized by radar charts was based on five metrics, including forest patch size (class area (CA), number (patch density (PD), isolation (landscape division index (DIVISION), aggregation (mean nearest-neighbor index (ENN_MN), and connectance index, (CONNECT). The results indicate that FC will remain above 61.4% until 2030, with growth observed in SSP1 and SSP4. Particularly, FC in SSP4 substantially increased, converted from cropland (1140.809 km2) and grassland (645.741 km2). SSP4 has the largest MLCI values and demonstrates significant enhancements in forest landscape integrity, with CA, ENN_MN and CONNECT increasing greatly. Our study offers valuable approaches to and insights into forest protection and restoration.

Mapping canopy cover for municipal forestry monitoring: Using free Landsat imagery and machine learning

Trees across the urban-rural continuum are recognized for their ecological importance and ecosystem services. Municipalities often utilize spatial canopy cover data for monitoring this resource. Monitoring frameworks typically rely on fine-scale maps derived from very high spatial resolution sensors, which are high quality but expensive and unwieldy for consistent wide-area monitoring. In this paper, we explore how free Landsat imagery, supported by very high-resolution imagery interpretation and/or digital hemispherical photographs, can be used to effectively map canopy cover at a scale appropriate for municipal monitoring. We compare linear models and random forest machine learning for predicting canopy cover across a landscape (general) and within specific land covers (specialized). We create 2018 canopy cover maps and track progress towards forestry objectives in a region of southern Ontario, Canada. Random forest models using all reference data perform best for general use (R2: 0.90, RMSE: 10.1 %), separating non-canopy vegetation (e.g., agricultural fields) from tree canopy. Specialized models are useful in forest land cover patches, where hemispherical photographs relate with Landsat at a moderate strength (R2: 0.67, RMSE: 2.73 %), and in residential areas, capturing the totality of canopy cover variation (R2: 0.85, RMSE: 5.66 %). Accuracy was assessed with standard cross-validation, which is useful given limited resources. However, following best practice, an independent reference sample was also leveraged to assess the best general model (R2: 0.86, RMSE: 11.4 %), indicating that cross-validation was slightly overoptimistic. Results show that Caledon, a rural-dominant municipality within the study area, is the greenest (34 % canopy cover). The two cities (Brampton and Mississauga) have 15.9 % and 17.5 % canopy cover. Residential canopy criteria indicate “Good” performance in Caledon, “Moderate” in Mississauga, and “Low” in Brampton based on our 2018 assessment. The methods described here can provide municipalities with a low-cost approach for tree canopy monitoring across complex landscapes. Data availabilityThe data used for this paper are available at: https://zenodo.org/records/12549244. The code created for this paper are available at: https://github.com/ZZMitch/PredictTreeCC_Landsat_1972to2020.

Quantifying the Potential of the Tropical Dry Region of the Gulf of Mexico to Provide Tree Species with Traditional Uses for Forest-Reliant Communities

The tropical dry regions in the Neotropics are under intense anthropogenic pressures, resulting in changes for local communities related with their life patterns, wellbeing, and their relationship with ecosystems. The region has a history of human occupation that has shaped the traditional use of resources. We evaluated the richness, redundancy, and divergence of traditional uses of tree species present in vegetation patches of the tropical dry region of the Gulf of Mexico using functional diversity indices. The most used species are Acacia cochliacantha, Cedrela odorata, Enterolobium cyclocarpum, Gliricidia sepium, and Guazuma ulmifolia, and the uses with the broadest distributions across the region are firewood and pasture management, while reforestation is the least common use. While distance to the nearest patch of the closest human settlement is the most predictive variable associated with inhabitants’ different uses or recognitions of the value of different plant species, the most recognized and valued species are widely distributed in Mexico. Even when the forest cover is greatly reduced, the inhabitants recognize numerous uses that can be obtained from the vegetation patches. The approach used in this work provides important baseline information, as well as a methodology that facilitates the identification of priority areas for conservation.

Complex stands in forested tropical landscapes harbor more endemic biodiversity and ecosystem functions

Transformation of forests into agricultural lands threatens biodiversity and ecosystem functions globally. In the biodiversity hotspot Madagascar, key ecosystem functions along with highly endemic flora and fauna are under threat. Comprehensive studies identifying determinants of biodiversity and ecosystem function losses are lacking, with no studies accounting for endemic species richness across multiple taxa. We assess how plot-scale stand structural attributes (basal area, leaf area index, diameter diversity, and tree species richness) and landscape-scale forest cover influence biodiversity (species richness of butterflies, ants, birds, reptiles, amphibians, herbaceous plants, and multidiversity) and ecosystem functions (soil organic carbon, predation rate, acoustic diversity, and multifunctionality) in the tropical mosaic landscape of northeastern Madagascar. Complexly structured stands with a larger basal area and/or a higher tree species richness promoted greater endemic multidiversity (R² = 0.70), soil organic carbon, and acoustic diversity. However, our models did not indicate significant explanatory variables for multidiversity (R² = 0.25) and multifunctionality (R² = 0.43). Landscape-scale forest cover significantly favored endemic bird species richness. Our findings highlight that a simplified stand structure, resulting from land-use change, substantially reduces endemic biodiversity and ecosystem functions in this historically forested region. Conservation actions should aim at maintaining complex stand structure in forests and agroforests, while restoration interventions should focus on re-building such structures.

Potential Amplifiers of Hydrological Drought: A Deep Dive into the Seasonal Variations of New, Young, and Old Water Fractions in the Stream Discharge of a Pre-Alpine Catchment

This study examines runoff generation processes by focusing on new, young, and old water fractions in the stream discharge within the Swiss pre-Alpine Alp catchment and its smaller tributaries, Erlenbach and Vogelbach. Young water represents a contribution from the three most recent rainfall-runoff events. This research utilises a four-year time series of daily stable water isotope data from stream water and precipitation to investigate seasonal variations. An extended two-component hydrograph separation method is applied to analyse the catchment water and tracer mass balance across both the event and pre-event time axes. The calculated new, young and old water components in stream discharge help estimate time-varying backward travel time distributions. Factors such as air temperature, snow depth, and evapotranspiration data are considered to understand isotope fractionation because of phase changes. The results suggest that discharge generated in autumn and winter may have longer backward travel times compared with spring or summer discharge. Additionally, forest cover influences water fractions older than 40 days. The study identifies a nivo-pluvial runoff regime, with new water fractions peaking in August (Erlenbach, Vogelbach) and January (Alp). Young water fractions reach their highest levels at the start of winter and during snowmelt, while old water fractions peak towards the end of snowmelt and in mid-autumn. The Alp catchment and its tributaries exhibit higher new and young water components than old water following a month of low precipitation and high evapotranspiration in July. These findings are significant in light of the projected drier summers in Central Europe.

Integrating adult occurrence and reproduction data to identify conservation measures for amphibians.

Monitoring programs are pivotal to establishing sound management. Due to economic, logistic, and time limitations, monitoring programs often overlook differences among life-history stages. However, species occurrence does not necessarily mean population viability, and it is unclear to what extent monitoring programs that do not consider separately adult presence and reproduction provide effective management indications. Unfortunately, collecting data on certain life stages requires high sampling effort, leading to a trade-off between model reliability and resources needed for monitoring. We collected data on presence and reproduction of amphibians by monitoring 207 waterbodies in Lombardy (northern Italy) in 2017-2022. We then used multistate occupancy models to test whether certain environmental features, namely, pond area, hydroperiod, forest cover, shade, aquatic vegetation, and predators' presence, differentially affected adult occurrence and breeding probabilities of multiple amphibian species. To assess optimal sampling efforts, we modeled the detection probabilities of adults and reproduction across multiple species. Finally, we identified the optimal monitoring strategy under different scenarios of resource availability, comparing adult-only monitoring versus joint assessment of the occurrence of adults and reproduction. In many cases, the main drivers of adult occurrence and reproduction did not coincide because most investigated ecological variables affected one life stage or the other. Forest area, for instance, increased occurrence probabilities of adults of the endemic Rana latastei but showed no effect on their reproduction probabilities. Quantitative estimates of the sampling effort showed that occurrence of adults was easier to spot in 4 out of 7 species. Multicriteria decision analyses showed that when resources were scarce, monitoring adults was the optimal strategy for those 4 species. Conversely, with more resources, monitoring both adults and reproduction emerged as the best strategy for all the considered species. Integrated monitoring of adults and reproduction is essential to comprehensively identify effective conservation measures for amphibians.

Landscape and insecticide use affecting the Leucoptera coffeella infestation and the natural parasitism spatiotemporal distribution in brazilian coffee agroecosystems

Monitoring the coffee leaf miner and natural parasitism is an important part of integrated pest management, and knowing the spatial distribution patterns of this pest can help improve sampling plans. This study aimed to determine spatial and temporal distributions of the coffee leaf miner infestation and natural parasitism in coffee plantations of different insecticide use and landscape configurations in the Planalto region, Bahia, Brazil. We monitored five coffee farms with different insecticide management practices in insecticide use and landscape features during two seasons, from December 2020 to November 2021. In each coffee farm, four regular grid plots of 30 points were established, for a total of 120 sample points per farm, that were georeferenced. Each point was a group of five coffee plants within 5 m of each other, 30 m in distance. Monthly collections of mined leaves were carried out at each sampling point to determine the L. coffeella infestation and natural parasitism rates. Geostatistical analysis was used to determine the spatial distribution of infestations and natural parasitism using semivariograms. Landscape metrics of each coffee plantation were surveyed in buffers ranging from 500 to 3000 m to assess their effects on population aggregation. Infestations of L. coffeella and natural parasitism of the pest occurred throughout the year and at varying intensities among farms. Leucoptera coffeella infestation and natural parasitism exhibited moderate aggregation patterns in most sampling months. The aggregation of L. coffeella infestations and natural parasitism were influenced by landscape and insecticide use. Forest cover, land cover use diversity, and insecticide use increased aggregation of L. coffeella infestations and natural parasitism, whereas edge density decreased aggregation of both. The study suggests that it may be beneficial to review the current sampling plans for the coffee leaf miner and the natural parasitism in coffee farms. This information can improve the integrated management of the pest in coffee farms and assist in decision-making regarding L. coffeella control strategies.

Protected area creation and its limited effect on deforestation: Insights from the Kiziba-Baluba hunting domain (DR Congo)

The study examines the spatiotemporal dynamics of landscape anthropization in the Kiziba-Baluba Hunting Domain (KBHD), near Lubumbashi in southeastern Democratic Republic of Congo, facing increasing human threats. It assesses these dynamics from 1989 to 2023 using remote sensing, Geographic Information Systems (GIS), and landscape ecology principles. The results reveal a significant decrease in forest cover, declining from 70.33 % in 1989 to 26.22 % in 2023, with an annual deforestation rate of -1.84 %. This deforestation has led to the expansion of savannas (63.93 %), agriculture (5.76 %), and built-up and bare soil (0.93 %) through patch creation and aggregation. The level of landscape disturbance has increased sixfold over 34 years, from 0.42 in 1989 to 2.81 in 2023. The reduction in the size of the largest forest patch and increased spatial isolation show rising fragmentation and dissection, often followed by the attrition of residual patches. These findings highlight the inefficiency of current conservation measures in KBHD, indicating a need for restructuring management, redefining protected area boundaries, developing a suitable management plan, implementing reforestation programs, strengthening enforcement of environmental laws, and actively involving local communities.

Comprehensive assessment of potential forestation land in China considering factors of vegetation resilience and top vegetation succession

China is currently the world’s largest carbon emitter and has pledged to achieve carbon neutrality by 2060, which requires significant reductions in emissions and the removal of carbon dioxide removal. Precise and efficient forestation has become a key strategy to increase carbon sequestration and mitigate the effects of climate change. In order to obtain a high-accuracy distribution area of potential forestation land, a variety of influencing factors on potential forestation land were selected in this study, including vegetation factors and environmental factors. Combining the two models “law of the minimum factors (LMF)” and “equal weight classification (EWC)” predicts the spatial distribution pattern of potential forestation land in China. And, we calculated the available forestation area in each province and predicted future forest coverage. The results showed that the potential forestation area using the LMF method reached approximately 5.65 × 105 km2, and the potential forestation area using the EMC method reached approximately 4.95 × 105 km2. Combining the two models, the final potential forestation area in China was approximately 6.29 × 105 km2, of which approximately 1.02 × 105 km2 was evaluated as a high-confidence area. If all potential forestation land obtained from the two models was successfully planted, China’s forest coverage rate would reach nearly 26 %. Two newly introduced vegetation factors, namely vegetation resilience and top vegetation succession, were considered in this study to make the prediction results of potential forestation distribution more accurate and reasonable. In addition, the results obtained in this study can provide certain assistance for the specific implementation of national forestation policies, and can provide a reference for promoting forestation actions and achieving the goal of carbon neutrality.

Legal analysis of the functioning, organisation and management of modern health resorts and medical spa care

On the surface, it would seem that the operation of a health resort commune does not differ from the majority of local authorities in Poland that do not have health resorts in their area and its activities can be subordinated to the market law of supply and demand. It would seem that it is the health resort gminas that are particularly privileged entities, endowed by nature with unique therapeutic raw materials, unique landscape, clean air and high forest cover, and being the proverbial apple of the sovereign's (the State's) eye, they have versatile development opportunities. A health resort municipality is a municipality whose area or part thereof has been granted the status of a health resort in accordance with the procedure set out in the Act on Health Resort Treatment, Health Resorts and Areas of Health Resort Protection and on Health Resort Municipalities of 28 July 2005. A health resort is an area where spa treatment is carried out, separated for the purpose of utilising and protecting the natural medicinal resources located in its area, which has been granted the status of a health resort. It follows from these definitions that a health resort is a limited area of the territory of a municipality, carrying out a specific activity such as spa treatment.

Interpretation of Soil Characteristics and Preferential Water Flow in Different Forest Covers of Karst Areas of China

Soil hydrology seriously affects the prevention of desertification in karst areas. However, water infiltration in the different soil layers of secondary forests and artificial forests in karst areas remains uncertain. This lack of clarity is also the factor that constrains local vegetation restoration. Therefore, monitoring and simulating the priority transport of soil moisture will help us understand the shallow soil moisture transport patterns after artificial vegetation restoration in the local area, providing a reference for more scientific restoration of the ecological environment and enhancement of carbon storage in karst areas. The integration of soil physical property assessments, computed tomography (CT) scanning, dye tracing studies, and HYDRUS-2D modeling was utilized to evaluate and contrast the attributes of soil macropores and the phenomenon of preferential flow across various forestland categories. This approach allowed for a comprehensive analysis of how the soil structure and water movement are influenced by different forest ecosystems and infiltration head simulations (5 mm, 15 mm, 35 mm, and 55 mm) to elucidate the dynamics of water movement across diverse soil types within karst regions, to identify the causes of water leakage due to preferential flow in secondary forests, and to understand the mechanisms of water conservation and reduction in artificial forests adopting a multifaceted approach. This study demonstrated that (1) the soil hydrological capacity of a plantation forest was 20% higher than a natural forest, which may be promoted by the clay content and distribution. (2) Afforestation-enhanced soils in karst regions demonstrate a significant capacity to mitigate the loss of clay particles during episodes of preferential flow and then improve the soil erosion resistance by about 5 times, which can effectively control desertification in karst area. (3) The uniform distribution of macropores in plantation forest soil was conducive to prevent water leakage more effectively than the secondary forest but was incapable of hindering the occurrence of preferential flow. The secondary forest had a very developed preferential flow phenomenon, and soil clay deposition occurred with an increase in depth. (4) Moreover, the results for preferential flow showed that the matrix flow depth did not increase with the increase in water quantity. Short-term and high-intensity heavy rainfall events facilitated the occurrence of preferential flow. Infiltration along the horizontal and vertical directions occurred simultaneously. These results could facilitate a further understanding of the contribution of the plantation to soil amelioration and the prevention of desertification in karst areas, and provide some suggestions for the sustainable development of forestry in karst areas where plantation restoration is an important ingredient.

Landscape properties and density dependence shape the movement patterns of three threatened butterflies

ContextConservation of endangered species necessitates an in-depth understanding of their ecological requirements. Particularly in landscape ecology, the behavioural tendencies of threatened butterfly species in Gotland, a biodiversity-rich island in the Baltic Sea, become crucial.ObjectivesThe primary aim of this study was to elucidate the movement patterns of three threatened butterfly species—Euphydryas aurinia, Parnassius apollo, and Phengaris arion—in Gotland and to identify the influence of specific land characteristics on these patterns.MethodsOur study, conducted from 2017 to 2020 across 60 km2 in Gotland, involved detailed capture-mark-recapture (CMR) efforts of 29,584 captures including 16,223 unique butterflies. We investigate the departure and arrival events of butterflies, specifically focusing on the associations between movements when individuals leave or enter a hectare grid different from their previously recorded location and key landscape features: open vegetated land, ground moisture, and forest cover. We model landscape features to examine the interplay between these and butterfly movement patterns, providing insights into preferred landscape features and conservation strategies.ResultsAmong the 4821 arrivals and 5083 departures documented, the species exhibited differential responses to the evaluated habitat features. Both E. aurinia and P. apollo displayed a positive density-dependent dispersal, while P. arion’s movements were not significantly associated with any of the examined habitat features. Landscape properties like open vegetated land and ground moisture index statistically influenced the likelihood of arrival and departure.ConclusionsThe study accentuates the relationship between land cover and the behavioural tendencies of the subject butterfly species. It has broader implications for the targeted habitat management strategies that would benefit threatened butterfly populations in Gotland.

Deforestation-induced runoff changes dominated by forest-climate feedbacks.

Large-scale deforestation alters water availability through its direct effect on runoff generation and indirect effect through forest-climate feedbacks. However, these direct and indirect effects and their spatial variations are difficult to separate and poorly understood. Here, we develop an attribution framework that combines the Budyko theory and deforestation experiments with climate models, showing that widespread runoff reductions caused by the indirect effect of forest-climate feedbacks can largely offset the direct effect of reduced forest cover on runoff increases. The indirect effect dominates the hydrological responses to deforestation over 63% of deforested areas worldwide. This indirect effect arises from deforestation-induced reductions in precipitation and potential evapotranspiration, which decrease and increase runoff, respectively, leading to complex patterns of runoff responses. Our findings underscore the importance of forest-climate feedbacks for improved understanding and prediction of climate and hydrological changes caused by deforestation, with profound implications for sustainable management of forests and water resources.

Monthly new water fractions and their relationships with climate and catchment properties across Alpine rivers

Abstract. The Alps are a key water resource for central Europe, providing water for drinking, agriculture, and hydropower production. Thus, understanding runoff generation processes of Alpine streams is important for sustainable water management. It is currently unclear how much streamflow is derived from old water stored in the subsurface and how much stems from more recent precipitation that reaches the stream via near-surface quick flow processes. It is also unclear how this partitioning varies across different Alpine catchments in response to hydroclimatic forcing and catchment characteristics. Here, we use stable water isotope time series in precipitation and streamflow to quantify the young water fractions (Fyw; i.e., the fraction of water younger than approximately 2–3 months) and new water fractions (Fnew; here, the fraction of water younger than 1 month) in streamflow from 32 Alpine catchments. We contrast these measures of water age between summer and winter and between wet and dry periods and then correlate them with hydroclimatic variables and physical catchment properties. New water fractions varied between 3.5 % and 9.6 %, with values of 9.2 % in rainfall-dominated catchments, 9.6 % in hybrid catchments, and 3.5 % in snow-dominated catchments (mean across all catchments of 7.1 %). Young water fractions were approximately twice as large (reflecting their longer timescale) and ranged between 10.1 % and 17.6 %, with values of 17.6 % in rainfall-dominated catchments, 16.6 % in hybrid catchments, and 10.1 % in snow-dominated catchments (mean across all catchments of 14.3 %). New water fractions were negatively correlated with catchment size (Spearman rank correlation, rS, of −0.38), q95 baseflow (rS=-0.36), catchment elevation (rS=-0.37), total catchment relief (rS=-0.59), and the fraction of slopes steeper than 40° (rS=-0.48). Large new water fractions, implying faster transmission of precipitation to streamflow, are more prevalent in small catchments, at low elevations, with small elevation differences, and with large fractions of forest cover (rS=0.36). New water fractions averaged 3.3 % following dry antecedent conditions, compared with 9.3 % after wet antecedent conditions. Our results quantify how hydroclimatic and physical drivers shape the partitioning of old and new waters across the Alps, thus indicating which landscapes transmit recent precipitation more readily to streamflow and which landscapes tend to retain water over longer periods. Our results further illustrate how new water fractions may find relationships that remained invisible with young water fractions.

Forest Cover Type Prediction Based Linear Regression

Forest Cover Type Prediction Based Linear Regression

Evidence for adaptation of colourful truffle-like fungi for birds in Aotearoa-New Zealand

Propagule dispersal is a crucial aspect of the survival and reproduction of sessile organisms, such as plants and fungi. As such, the colours of fleshy fruits serve as a visual cue for animal dispersers. However, little is known about how, or whether, specific traits of fungal fruiting bodies, such as colour or shape, attract animal dispersers, and additionally the identities of fungal dispersers are poorly understood. Globally, most truffle-like fungi are dull-coloured, subterranean, and likely have scents that are attractive to mammalian dispersers. In Aotearoa-New Zealand, however, brightly coloured truffle-like fungi that emerge from the forest floor have seemingly proliferated. This proliferation has prompted the hypothesis that they are adapted to dispersal by a bird-dominated fauna. In our study, we used the literature and citizen science data (GBIF) to explore whether colourful species occur at a higher proportion of the total truffle-like fungi flora in Aotearoa-New Zealand than elsewhere in the world. In addition, we tested for a relationship between biotic factors (avian frugivory and forest cover) and abiotic factors (precipitation, radiation, and temperature) and the prevalence of brightly coloured truffle-like fungi across the world. The most colourful truffle-like fungi are in three defined regions: Australia, South and Central America and the Caribbean, and Aotearoa-NZ. Potential dispersers and the environment both relate to the distribution of truffle-like fungi: we found that increasing levels of frugivory were associated with higher proportions of colourful truffle-like fungi. This finding provides new insights into drivers of certain fungal traits, and their interactions between birds and fungi. Unique ecosystems, such as Aotearoa-NZ’s bird-dominated biota, provide fascinating opportunities to explore how plants and fungi interact with the sensory systems of animals.

Land use history and landscape forest cover determine tropical forest recovery

Abstract To conserve biodiversity and combat climate change it is vital to restore forest ecosystems. Natural forest regrowth is a nature‐based solution to restore forests, but it has rarely been evaluated how this is affected by the combination of previous land use intensity and surrounding forest cover, and how this varies between the two main tropical forest types; dry and wet forests. Thirty‐three plots were established on abandoned agricultural fields in a dry (13 plots) and wet (20 plots) tropical forest in Mexico and monitored 3 years for the following tree community attributes: structure, diversity, regeneration mode, potential symbioses with N fixing bacteria and mycorrhizal fungi. Previous land use intensity was described using interviews, and landscape forest cover and fragmentation within a 1000 m radius surrounding the plots were quantified using satellite images. Variable importance analyses indicated that land use intensity was more important than forest cover and fragmentation for the state of the tree community attributes after 3 years. This suggests that previous land use impacts the start of succession and leaves important legacies on the vegetation. Land use intensity, forest cover and fragmentation were equally important in determining the change in tree community attributes over time, indicating that both management practices and dispersal shape subsequently community assembly. A higher land use intensity decreases tree richness recovery, while size of the largest forest patch decreases tree density and connectivity of these patches increases tree density. The dry forest had a faster increase in tree density recovery compared to the wet forest through a high initial resprouting capacity and abiotically dispersed trees. Synthesis and applications: Both a higher land use intensity and fragmented forest landscape decreases the speed of forest recovery, indicating that human actions and landscape transformation shape the course of succession. Restoration in fragmented forest landscapes through natural regeneration is more suitable in areas with low previous land use intensity, higher forest connectivity and abiotically dispersed species. Effective restoration should therefore consider both land use history and landscape forest cover and be tailored to local socio‐ecological conditions.

Spatiotemporal and Environmental Completeness of eBird Data in Taiwan

Recent developments in citizen science have significantly enhanced the public availability of biodiversity data (Chandler et al. 2017, Kelling et al. 2019). Associated open data platforms, such as eBird, have become the major data source supporting scientific research and biodiversity conservation (Tsai et al. 2021, Meehan et al. 2022, Walker and Taylor 2017). However, the increasing availabililty of data does not resolve, but rather exacerbates, data bias issues (Escribano et al. 2019, La Sorte and Somveille 2020, Troia and McManamay 2016). While over 11.2 million bird observation records from Taiwan, including historical data spanning 40 years, are currently available on the eBird platform, their usefulness for characterizing the spatiotemporal patterns of bird communities remains unclear. To address this gap, we evaluated the data’s completeness in representing species richness across spatial and temporal scales and examined the representativeness of the data along several environmental gradients. Using the iNEXT package in R, we found an increase in data completeness with increasing spatial scales Fig. 1, with the mean proportion of bird species represented being increased from 14.0% at the 1 km scale to 68.0 and 82.9% at the 5 and 10 km scales, respectively, across Taiwan. We also found an exponential improvement of data completeness over time. At the 5 km scale, the represented species proportion increased from 6.78 and 32.14% in the 1980s and 1990s to 36.86 and 63.56% in the 2000s and 2010s Fig. 2, with the data in the last decade alone achieving similar completeness to the entire four-decade data. We also found that the areas with good data completeness (i.e., over 80%) adequately represented the full gradient of annual precipitation across Taiwan, but showed a bias toward areas at lower elevations and with lower forest coverage. These results indicate overall good data completeness of the eBird dataset for representing bird species richness in Taiwan. However, this study also highlights some data gaps, especially at finer scales, which need attention when using the dataset. This information is crucial for shaping future research designs and survey plans, aiming to enhance the applications of biodiversity data.