Benchmarking inference methods for water quality monitoring and status classification

River water quality monitoring at limited temporal resolution can lead to imprecise and inaccurate classification of physicochemical status due to sampling error. Bayesian inference allows for the quantification of this uncertainty, which can assist decision-making. However, implicit assumptions of Bayesian methods can cause further uncertainty in the uncertainty quantification, so-called second-order uncertainty. In this study, and for the first time, we rigorously assessed this second-order uncertainty for inference of common water quality statistics (mean and 95th percentile) based on sub-sampling high-frequency (hourly) total reactive phosphorus (TRP) concentration data from three watersheds. The statistics were inferred with the low-resolution sub-samples using the Bayesian lognormal distribution and bootstrap, frequentist t test, and face-value approach and were compared with those of the high-frequency data as benchmarks. The t test exhibited a high risk of bias in estimating the water quality statistics of interest and corresponding physicochemical status (up to 99% of sub-samples). The Bayesian lognormal model provided a good fit to the high-frequency TRP concentration data and the least biased classification of physicochemical status (< 5% of sub-samples). Our results suggest wide applicability of Bayesian inference for water quality status classification, a new approach for regulatory practice that provides uncertainty information about water quality monitoring and regulatory classification with reduced bias compared to frequentist approaches. Furthermore, the study elucidates sizeable second-order uncertainty due to the choice of statistical model, which could be quantified based on the high-frequency data.Peer Reviewe

The effects of forest cover and disturbance on torrential hazards

Global human population growth, limited space for settlements and a booming tourism industry have led to a strong increase of human infrastructure in mountain regions. As this infrastructure is highly exposed to natural hazards, a main role of mountain forests is to regulate the environment and reduce hazard probability. However, canopy disturbances are increasing in many parts of the world, potentially threatening the protection function of forests. Yet, large-scale quantitative evidence on the influence of forest cover and disturbance on natural hazards remains scarce to date. Here we quantified the effects of forest cover and disturbance on the probability and frequency of torrential hazards for 10 885 watersheds in the Eastern Alps. Torrential hazard occurrences were derived from a comprehensive database documenting 3768 individual debris flow and flood events between 1986 and 2018. Forest disturbances were mapped from Landsat satellite time series analysis. We found evidence that forests reduce the probability of natural hazards, with a 25 percentage point increase in forest cover decreasing the probability of torrential hazards by 8.7%± 1.2%. Canopy disturbances generally increased the probability of torrential hazard events, with the regular occurrence of large disturbance events being the most detrimental disturbance regime for natural hazards. Disturbances had a bigger effect on debris flows than on flood events, and press disturbances were more detrimental than pulse disturbances. We here present the first large scale quantification of forest cover and disturbance effects on torrential hazards. Our findings highlight that forests constitute important green infrastructure in mountain landscapes, efficiently reducing the probability of natural hazards, but that increasing forest disturbances can weaken the protective function of forests.Austrian Climate Research ProgramAustrian Science Fund https://doi.org/10.13039/501100002428Peer Reviewe

Patterns and drivers of recent disturbances across the temperate forest biome

Increasing evidence indicates that forest disturbances are changing in response to global change, yet local variability in disturbance remains high. We quantified this considerable variability and analyzed whether recent disturbance episodes around the globe were consistently driven by climate, and if human influence modulates patterns of forest disturbance. We combined remote sensing data on recent (2001-2014) disturbances with in-depth local information for 50 protected landscapes and their surroundings across the temperate biome. Disturbance patterns are highly variable, and shaped by variation in disturbance agents and traits of prevailing tree species. However, high disturbance activity is consistently linked to warmer and drier than average conditions across the globe. Disturbances in protected areas are smaller and more complex in shape compared to their surroundings affected by human land use. This signal disappears in areas with high recent natural disturbance activity, underlining the potential of climate-mediated disturbance to transform forest landscapes.A.S. and R.S. acknowledge support from the Austrian Science Fund (FWF) through START grant Y895-B25. C.S. acknowledges funding from the German Academic Exchange Service (DAAD) with funds from the German Federal Ministry of Education and Research (BMBF) and the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007–2013) under REA grant agreement Nr. 605728 (P.R.I.M.E.—Postdoctoral Researchers International Mobility Experience). T. D. acknowledges funding from the Fonds institutionnel de recherche de l’Universitédu Quebec en Abitibi-Te ́ miscamingue, the Natural Sciences and Engineering Research ́ Council of Canada (NSERC), Tembec, and EACOM Timber Corporation. Á.G.G. was supported by FONDECYT 11150835. S.J.H. and T.T.V. acknowledge NSF Award 1262687. A.H. was partially supported by NSF (award #1738104). D.K. acknowledges support from the US NSF. D.L. was supported by an Australian Research Council Laureate Fellowship. A.S.M. was supported by the Environment Research and Technology Development Fund (S-14) of the Japanese Ministry of the Environment and by the Grants-in-Aid for Scientific Research of the Japan Society for the Promotion of Science (15KK0022). G.L.W.P. acknowledges support from a Royal Society of New Zealand Marsden Fund grant. S.L.S. acknowledges funds from the US Joint Fire Sciences Program (project number 14-1-06-22) and UC ANR competitive grants. M.S. and T.H. acknowledges support from the institutional project MSMT CZ.02.1.01/0.0/0.0/16_019/ 0000803. M.G.T. acknowledges funding from the University of Wisconsin-Madison Vilas Trust and the US Joint Fire Science Program (project numbers 09-1-06-3, 12-3-01-3, and 16-3-01-4). The study used data from the TRY initiative on plant traits (http://www.trydb.org). The TRY initiative and database is hosted, developed and maintained by J. Kattge and G. Boenisch (Max Planck Institute for Biogeochemistry, Jena, Germany). TRY is currently supported by Future Earth/bioDISCOVERY and the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzi

Tree canopy extent and height change in Europe, 2001-2021, quantified using Landsat data archive

European forests are among the most extensively studied ecosystems in the world, yet there are still debates about their recent dynamics. We modeled the changes in tree canopy height across Europe from 2001 to 2021 using the multidecadal spectral data from the Landsat archive and calibration data from Airborne Laser Scanning (ALS) and spaceborne Global Ecosystem Dynamics Investigation (GEDI) lidars. Annual tree canopy height was modeled using regression tree ensembles and integrated with annual tree canopy removal maps to produce harmonized tree height map time series. From these time series, we derived annual tree canopy extent maps using a >= 5 m tree height threshold. The root-mean-square error (RMSE) for both ALS-calibrated and GEDI-calibrated tree canopy height maps was = 94% for the tree canopy extent maps and >= 80% for the annual tree canopy removal maps. Analyzing the map time series, we found that the European tree canopy extent area increased by nearly 1% overall during the past two decades, with the largest increase observed in Eastern Europe, Southern Europe, and the British Isles. However, after the year 2016, the tree canopy extent in Europe declined. Some regions reduced their tree canopy extent between 2001 and 2021, with the highest reduction observed in Fennoscandia (3.5% net decrease). The continental extent of tall tree canopy forests (>= 15 m height) decreased by 3% from 2001 to 2021. The recent decline in tree canopy extent agrees with the FAO statistics on timber harvesting intensification and with the increasing extent and severity of natural disturbances. The observed decreasing tree canopy height indicates a reduction in forest carbon storage capacity in Europe

Globally consistent climate sensitivity of natural disturbances across boreal and temperate forest ecosystems

Disturbance regimes are changing in forests across the world in response to global climate change. Despite the profound impacts of disturbances on ecosystem services and biodiversity, assessments of disturbances at the global scale remain scarce. Here, we analyzed natural disturbances in boreal and temperate forest ecosystems for the period 2001-2014, aiming to 1) quantify their within- and between-biome variation and 2) compare the climate sensitivity of disturbances across biomes. We studied 103 unmanaged forest landscapes with a total land area of 28.2 x 10(6) ha, distributed across five continents. A consistent and comprehensive quantification of disturbances was derived by combining satellite-based disturbance maps with local expert knowledge of disturbance agents. We used Gaussian finite mixture models to identify clusters of landscapes with similar disturbance activity as indicated by the percent forest area disturbed as well as the size, edge density and perimeter-area-ratio of disturbed patches. The climate sensitivity of disturbances was analyzed using Bayesian generalized linear mixed effect models and a globally consistent climate dataset. Within-biome variation in natural disturbances was high in both boreal and temperate biomes, and disturbance patterns did not vary systematically with latitude or biome. The emergent clusters of disturbance activity in the boreal zone were similar to those in the temperate zone, but boreal landscapes were more likely to experience high disturbance activity than their temperate counterparts. Across both biomes high disturbance activity was particularly associated with wildfire, and was consistently linked to years with warmer and drier than average conditions. Natural disturbances are a key driver of variability in boreal and temperate forest ecosystems, with high similarity in the disturbance patterns between both biomes. The universally high climate sensitivity of disturbances across boreal and temperate ecosystems indicates that future climate change could substantially increase disturbance activity.Peer reviewe

Landscape to regional scale patterns and drivers of forest insect disturbances

Insekten spielen eine bedeutende Rolle im Erhalt von Waldökosystemen, haben aber auch eine nicht zu vernachlässigende ökonomische Bedeutung. Obwohl die ökologische sowie ökonomische Bedeutung von Insekten bekannt ist, gibt es bisher wenig Forschung zu den Dynamiken von herbivoren Insekten in der westamerikanischen Nadelholzzone, insbesondere durch die Art Choristoneura occidentalis. Der Mangel an Studien kann durch ein Fehlen von geeigneten Methoden zur Quantifizierung von Insektenausbrüchen auf der Landschafts- und Regionalskala erklärt werden. Die Nutzung von Fernerkundung vermag diese Wissenslücke zu schließen. Das übergeordnete Ziel dieser Dissertation ist daher, anhand von Fernerkundung ein besseres Verständnis der raumzeitlichen Muster von Insektenausbrüchen in der nord-west amerikanischen Nadelholzzone zu erlangen. Die spezifischen Forschungsfragen der Dissertation sind: (1) Inwieweit kann Fernerkundung die Kartierung und Quantifizierung von Insektenausbrüchen, insbesondere durch Herbivoren, unterstützen? (2) Was sind die raumzeitlichen Muster und Prozesse von Ausbrüchen des Choristoneura occidentalis in der west-nord-amerikanischen Nadelholzzone? Anhand des rezenten Ausbruches in Britisch Kolumbien, Kanada, wurde gezeigt, dass Fernerkundung ein geeigneter Weg ist um die raumzeitlichen Muster von Choristoneura occidentalis zu rekonstruieren. Mit dieser Erkenntnis konnten die hauptsächlichen Triebkräfte hinter diesen raumzeitlichen Mustern erklärt werden. So zeigte sich, dass sich die Dynamiken durch Ausbreitung adulter Motten, eine hohe Abundanz von Wirtsbäumen, Wetter, sowie deren Interaktion erklärt werden konnte. Aus den Ergebnissen kann geschlossen werden, dass Ausbrüche herbivorer Insekten in der westamerikanischen Nadelholzzone durch Prozesse welche über ein Management auf Standesebene hinausgehen bestimmt werden. Ein nachhaltiges Waldmanagement sollte daher neben Standfaktoren auch Faktoren auf Landschafts- und Regionalebene berücksichtigen.Insect disturbances play a key role for maintaining healthy forest ecosystems, though they are also important for the timber industry, reducing yields and wood quality during major outbreaks. Despite the ecological and economic importance of insect disturbances, the outbreak dynamics of defoliating insects of the coniferous forests of western North America -- in particular the western spruce budworm Choristoneura occidentalis - are yet poorly understood. This is partly caused by a lack of suitable methods for quantifying landscape to regional scale outbreak patterns. Remote sensing time series analysis can help overcoming this challenge. Consequently, the overall goal of this dissertation was to increase the understanding of landscape to regional scale patterns and processes of insect defoliator disturbances in the coniferous forests of western North America with the help of Landsat remote sensing. Precisely, the research questions of the dissertation were: (1) How can Landsat remote sensing be used to map and quantify insect defoliator outbreaks? (2) What are the spatiotemporal patterns and processes of outbreaks of western spruce budworm in the coniferous forests of western North America? Using the current outbreak in British Columbia as example, it could be demonstrated that Landsat time series can be used to map and quantify the spatial and temporal dynamics of budworm outbreaks at the landscape and regional scale. The outbreak dynamics were mainly driven by direct effects and interactions of moth dispersal, host abundance, and weather patterns. Concluding from my results, it is suggested that outbreaks of forest defoliators in the coniferous forests of western North America are governed by factors that go beyond stand level management. Forest management thus should consider those factors in their operational planning, as well as in their models of future forest change

Bayesian Hierarchical Modeling of Nitrate Concentration in a Forest Stream Affected by Large‐Scale Forest Dieback

The ecosystem function of vegetation to attenuate export of nutrients is of substantial importance for securing water quality. This ecosystem function is at risk of deterioration due to an increasing risk of large-scale forest dieback under climate change. The present study explores the response of the nitrogen (N) cycle of a forest catchment in the Bavarian Forest National Park, Germany, in the face of a severe bark beetle (Ips typographus Linnaeus) outbreak and resulting large-scale forest dieback using top-down statistical-mechanistic modeling. Outbreaks of bark beetle killed the dominant tree species Norway spruce (Picea abies (L.) H.Karst.) in stands accounting for 55% of the catchment area. A Bayesian hierarchical model that predicts daily stream NO3 concentration (C) over three decades with discharge (Q) and temperature (T) (C-Q-T relationship) outperformed alternative statistical models. A catchment model was subsequently developed to explain the C-Q-T relationship in top-down fashion. Annually varying parameter estimates provide mechanistic interpretations of the catchment processes. Release of NO3 from decaying litter after the dieback was tracked by an increase of the nutrient input parameter cs0. The slope of C-T relation was near zero during this period, suggesting that the nutrient release was beyond the regulating capacity of the vegetation and soils. Within a decade after the dieback, the released N was flushed out and nutrient retention capacity was restored with the regrowth of the vegetation.Peer Reviewe

sgdm: An R Package for Performing Sparse Generalized Dissimilarity Modelling with Tools for gdm

Global biodiversity change creates a need for standardized monitoring methods. Modelling and mapping spatial patterns of community composition using high-dimensional remotely sensed data requires adapted methods adequate to such datasets. Sparse generalized dissimilarity modelling is designed to deal with high dimensional datasets, such as time series or hyperspectral remote sensing data. In this manuscript we present sgdm, an R package for performing sparse generalized dissimilarity modelling (SGDM). The package includes some general tools that add functionality to both generalized dissimilarity modelling and sparse generalized dissimilarity modelling. It also includes an exemplary dataset that allows for the application of SGDM for mapping the spatial patterns of tree communities in a region of natural vegetation in the Brazilian Cerrado.Peer Reviewe

Characterizing spring phenology of temperate broadleaf forests using Landsat and Sentinel-2 time series

Vegetation phenology has a great impact on land-atmosphere interactions like carbon cycling, albedo, and water and energy exchanges. To understand and predict these critical land-atmosphere feedbacks, it is crucial to measure and quantify phenological responses to climate variability, and ultimately climate change. Coarse-resolution sensors such as MODIS and AVHRR have been useful to study vegetation phenology from regional to global scales. These sensors are, however, not capable of discerning phenological variation at moderate spatial scales. By offering increased observation density and higher spatial resolution, the combination of Landsat and Sentinel-2 time series might provide the opportunity to overcome this limitation. In this study, we analyzed the potential of combined Sentinel-2 and Landsat time series for estimating start of season (SOS) of broadleaf forests across Germany for the year 2018. We tested two common statistical modeling approaches (logistic and generalized additive models using thin plate splines) and the two most commonly used vegetation indices, the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). We found strong agreement between SOS estimates from logistic and spline models (rEVI = 0.86; rNDVI = 0.65), whereas agreement was higher for EVI than for NDVI (RMSDEVI = 3.07, RMSDNDVI = 5.26 days). The choice of vegetation index thus had a higher impact on the results than the fitting method. The EVI-based SOS also showed higher correlation with ground observations compared to NDVI (rEVI = 0.51, rNDVI = 0.42). Data density played an important role in estimating land surface phenology. Models combining Sentinel-2A/B, with an average cloud-free observation frequency of 12 days, were largely consistent with the combined Landsat and Sentinel-2 models, suggesting that Sentinel-2A/B may be sufficient to capture SOS for most areas in Germany in 2018. However, in non-overlapping swath areas and mountain areas, observation frequency was significantly lower, underlining the need to combine Landsat and Sentinel-2 for consistent SOS estimates over large areas. Our study demonstrates that estimating SOS of temperate broadleaf forests at medium spatial resolution has become feasible with combined Landsat and Sentinel-2 time series.Peer Reviewe

Satellite‐based habitat monitoring reveals long‐term dynamics of deer habitat in response to forest disturbances

Disturbances play a key role in driving forest ecosystem dynamics, but how disturbances shape wildlife habitat across space and time often remains unclear. A major reason for this is a lack of information about changes in habitat suitability across large areas and longer time periods. Here, we use a novel approach based on Landsat satellite image time series to map seasonal habitat suitability annually from 1986 to 2017. Our approach involves characterizing forest disturbance dynamics using Landsat‐based metrics, harmonizing these metrics through a temporal segmentation algorithm, and then using them together with GPS telemetry data in habitat models. We apply this framework to assess how natural forest disturbances and post‐disturbance salvage logging affect habitat suitability for two ungulates, roe deer (Capreolus capreolus) and red deer (Cervus elaphus), over 32 yr in a Central European forest landscape. We found that red and roe deer differed in their response to forest disturbances. Habitat suitability for red deer consistently improved after disturbances, whereas the suitability of disturbed sites was more variable for roe deer depending on season (lower during winter than summer) and disturbance agent (lower in windthrow vs. bark‐beetle‐affected stands). Salvage logging altered the suitability of bark beetle‐affected stands for deer, having negative effects on red deer and mixed effects on roe deer, but generally did not have clear effects on habitat suitability in windthrows. Our results highlight long‐lasting legacy effects of forest disturbances on deer habitat. For example, bark beetle disturbances improved red deer habitat suitability for at least 25 yr. The duration of disturbance impacts generally increased with elevation. Methodologically, our approach proved effective for improving the robustness of habitat reconstructions from Landsat time series: integrating multiyear telemetry data into single, multi‐temporal habitat models improved model transferability in time. Likewise, temporally segmenting the Landsat‐based metrics increased the temporal consistency of our habitat suitability maps. As the frequency of natural forest disturbances is increasing across the globe, their impacts on wildlife habitat should be considered in wildlife and forest management. Our approach offers a widely applicable method for monitoring habitat suitability changes caused by landscape dynamics such as forest disturbance.Federal State of BerlinEuropean Commission http://dx.doi.org/10.13039/501100000780Peer Reviewe