How to make ecological models useful for environmental management

Understanding and predicting the ecological consequences of different management alternatives is becoming increasingly important to support environmental management decisions. Ecological models could contribute to such predictions, but in the past this was often not the case. Ecological models are often developed within research projects but are rarely used for practical applications. In this synthesis paper, we discuss how to strengthen the role of ecological modeling in supporting environmental management decisions with a focus on methodological aspects. We address mainly ecological modellers but also potential users of modeling results. Various modeling approaches can be used to predict the response of ecosystems to anthropogenic interventions, including mechanistic models, statistical models, and machine learning approaches. Regardless of the chosen approach, we outline how to better align the modeling to the decision making process, and identify six requirements that we believe are important to increase the usefulness of ecological models for management support, especially if management decisions need to be justified to the public. These cover: (i) a mechanistic understanding regarding causality, (ii) alignment of model input and output with the management decision, (iii) appropriate spatial and temporal resolutions, (iv) uncertainty quantification, (v) sufficient predictive performance, and (vi) transparent communication. We discuss challenges and synthesize suggestions for addressing these points. © 2019 The Author(s)This paper was initialized during a special session on Ecological Modelling at the 10th Symposium for European Freshwater Science 2017 ( http://www.sefs10.cz/ ) and further developed during the AQUACROSS project, funded by European Union's Horizon 2020 research and innovation programme (Grant agreement No. 642317 ). SD, SDL and MF were partly funded by the “GLANCE” project (Global Change Effects in River Ecosystems; 01 LN1320A) through the German Federal Ministry of Education and Research ( BMBF ). SDL has received additional funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 748625 . JML acknowledges the support of the Spanish Government through María de Maeztu excellence accreditation 2018–2021 (Ref. MDM-2017-0714 )

Accounting for biotic interactions through alpha-diversity constraints in stacked species distribution models

1. Species Distribution Models (SDM) are widely used to predict occupancy patterns at fine resolution over wide extents. However, SDMs generally ignore the effect of biotic interactions and tend to overpredict the number of species that can coexist at a given location and time (hereafter, the alpha-capacity). We developed an extension of SDMs that integrates species-level and community-level modelling to account for the above drivers. 2. The alpha-adjusted SDM takes the Probabilities of Occurrence (PoO) for all species of a community and the site’s alpha-capacity and adjusts the PoO, such that: a. their sum will equal the alpha-capacity as predicted by probability theory; and b. the adjusted PoO are dependent upon the relative suitability of each species for that site. The new method was tested using community data comprising 87 freshwater invertebrate species in an LTER watershed in Germany. We explored the ability of the method to predict alpha and beta-diversity patterns. We further focused on the effect on model performance at the species-level of the error associated with modelling alpha-capacity, of differences in gamma diversity (the size of the community) and of the type of community (random or guild-based). 3. The models that predicted alpha-capacity contained considerable error, and thus adjusting the PoO according to the modelled alpha-capacity resulted with decreased performance at the species level. However, when using the observed alpha-capacity to mimic a good alpha-capacity model, the alpha-adjusted SDMs usually resulted in increased performance. We further found that the alpha-adjusted SDM was better than the original SDM at predicting beta-diversity patterns, especially when using similarity indices that are sensitive to double absences. 4. Using the alpha-adjusted SDM approach may increase the predictive performance at the species and community levels if alpha-capacity can be assessed or modelled with sufficient accuracy, especially in relatively small communities of closely interacting species. With better models to predict alpha-capacity being developed, alpha-adjusted SDM has considerable potential to provide more realistic predictions of species-distribution patterns

SDM profiling: A tool for assessing the information-content of sampled and unsampled locations for species distribution models

Species distribution models (SDMs) are key tools in biodiversity and conservation, but assessing their reliability in unsampled locations is difficult, especially where there are sampling biases. We present a spatially-explicit sensitivity analysis for SDMs – SDM profiling – which assesses the leverage that unsampled locations have on the overall model by exploring the interaction between the effect on the variable response curves and the prevalence of the affected environmental conditions. The method adds a ‘pseudo-presence’ and ‘pseudo-absence’ to unsampled locations, re-running the SDM for each, and measuring the difference between the probability surfaces of the original and new SDMs. When the standardised difference values are plotted against each other (a ‘profile plot’), each point's location can be summarized by four leverage measures, calculated as the distances to each corner. We explore several applications: visualization of model certainty; identification of optimal new sampling locations and redundant existing locations; and flagging potentially erroneous occurrence records

Combining eight research areas to foster the uptake of ecosystem-based management in fresh waters

Freshwater ecosystems are under a constant risk of being irreversibly damaged by human pressures that threaten their biodiversity, the sustainability of ecosystem services (ESs), and human well-being. Despite the implementation of various environmental regulations, the challenges of safeguarding freshwater assets have so far not been tackled successfully. A promising way forward to stop the loss of freshwater biodiversity and to sustain freshwater-based ESs is by implementing ecosystem-based management (EBM), an environmental planning and adaptive management approach that jointly considers social and ecological needs. Responsible for considerable recent success in sustainably managing and conserving marine ecosystems, EBM has not yet been championed for fresh waters. A major reason for the delayed uptake of EBM in fresh waters is likely to be its complexity, requiring planners to be familiar with the latest developments in a range of different research areas. EBM would therefore benefit from becoming more tangible to receive attention on the ground. To facilitate uptake, eight core research areas for EBM and their innovations are introduced, and the way in which they feed into the workflow that guides the EBM planning stage is explained. The workflow links biodiversity distributions with ES supply-and-demand modelling and SMART (specific, measurable, attainable, relevant, and timely) target planning, including scenario- and cross-realm perspectives, the prioritization of management alternatives, spatial prioritization of biodiversity conservation and ES areas, and the quantification of uncertainties. Given the extensive resources, time, and technical capacity required to implement the full workflow, a light and an ultralight version of the workflow are also provided. Applied in concert, the eight well-known research areas allow for better planning and operationalizing, and eventually for implementing EBM in freshwater ecosystems. EBM has great potential to increase public acceptance by introducing the consideration of human needs and aspirations into typically biodiversity-driven conservation and management approaches. This will ultimately improve the integrity of freshwater ecosystems. © 2019 John Wiley & Sons, Ltd.German Federal Ministry of Education and Research, Grant/Award Number: 01 LN1320A; Horizon 2020 Framework Programme, Grant/Award Number: 642317; Marie Sklodowska‐Curie Global Fellowship, Grant/Award Number: 748625; Ramón y Cajal, Grant/Award Number: RYC‐2013‐1397

A global agenda for advancing freshwater biodiversity research

This manuscript is a contribution of the Alliance for Freshwater Life (www.allianceforfreshwaterlife.org). We thank Nick Bond, Lisa Bossenbroek, Lekima Copeland, Dean Jacobsen, Maria Cecilia Londo?o, David Lopez, Jaime Ricardo Garcia Marquez, Ketlhatlogile Mosepele, Nunia Thomas-Moko, Qiwei Wei and the authors of Living Waters: A Research Agenda for the Biodiversity of Inland and Coastal Waters for their contributions. We also thank Peter Thrall, Ian Harrison and two anonymous referees for their valuable comments that helped improve the manuscript. Open access funding enabled and organised by Projekt DEAL

A global agenda for advancing freshwater biodiversity research

Global freshwater biodiversity is declining dramatically, and meeting the challenges of this crisis requires bold goals and the mobilisation of substantial resources. While the reasons are varied, investments in both research and conservation of freshwater biodiversity lag far behind those in the terrestrial and marine realms. Inspired by a global consultation, we identify 15 pressing priority needs, grouped into five research areas, in an effort to support informed stewardship of freshwater biodiversity. The proposed agenda aims to advance freshwater biodiversity research globally as a critical step in improving coordinated actions towards its sustainable management and conservation

A global agenda for advancing freshwater biodiversity research

Global freshwater biodiversity is declining dramatically, and meeting the challenges of this crisis requires bold goals and the mobilisation of substantial resources. While the reasons are varied, investments in both research and conservation of freshwater biodiversity lag far behind those in the terrestrial and marine realms. Inspired by a global consultation, we identify 15 pressing priority needs, grouped into five research areas, in an effort to support informed stewardship of freshwater biodiversity. The proposed agenda aims to advance freshwater biodiversity research globally as a critical step in improving coordinated actions towards its sustainable management and conservation.Peer reviewe

Integrating catchment properties in small scale species distribution models of stream macroinvertebrates

Species distribution models are increasingly applied to freshwater ecosystems. Most applications use large scales, coarse resolutions and anthropocentric modelling extents, thus not being able to consider important environmental predictors and ecological processes detectable within a catchment and at finer scales. Moreover, high resolution predictions of species distribution in streams can help improve our understanding of how environmental variables within a catchment affect the distribution of stream macroinvertebrates. We built models at a resolution of 25 m x 25 m for a 488 km(2) catchment in northern Germany to determine whether the spatial approach in which environmental predictors are implemented in the model affects the overall performance. We used predictors from four different categories relevant to freshwater ecosystems: bioclimatic, topographic, hydrologic and land use. Two spatial approaches were tested: a local one, or grid based and a cumulative for the upstream area, or subcatchment specific. Models were evaluated in terms of model performance and accuracy in order to identify the approach best suited for each category, as well as the most important predictor in each. In the case of the land use category, the subcatchment approach made a significant difference, increasing performance. A final model, calibrated with the selected predictors, resulted in the highest model performance and accuracy. Our results indicate that species distribution models perform well and are accurate at high resolutions, within small catchments. We conclude that catchment wide models, especially when using predictors from multiple categories, have the potential to significantly improve modelling framework of species distribution in freshwater ecosystems. The information produced by accurate, small scale, species distribution models can guide managers and conservation practitioners, by predicting the effects of management decisions within a catchment. We suggest that highly resolved predictors be applied in models using the catchment approach. (C) 2014 Elsevier B.V. All rights reserved.Species distribution models are increasingly applied to freshwater ecosystems. Most applications use large scales, coarse resolutions and anthropocentric modelling extents, thus not being able to consider important environmental predictors and ecological processes detectable within a catchment and at finer scales. Moreover, high resolution predictions of species distribution in streams can help improve our understanding of how environmental variables within a catchment affect the distribution of stream macroinvertebrates. We built models at a resolution of 25 m x 25 m for a 488 km(2) catchment in northern Germany to determine whether the spatial approach in which environmental predictors are implemented in the model affects the overall performance. We used predictors from four different categories relevant to freshwater ecosystems: bioclimatic, topographic, hydrologic and land use. Two spatial approaches were tested: a local one, or grid based and a cumulative for the upstream area, or subcatchment specific. Models were evaluated in terms of model performance and accuracy in order to identify the approach best suited for each category, as well as the most important predictor in each. In the case of the land use category, the subcatchment approach made a significant difference, increasing performance. A final model, calibrated with the selected predictors, resulted in the highest model performance and accuracy. Our results indicate that species distribution models perform well and are accurate at high resolutions, within small catchments. We conclude that catchment wide models, especially when using predictors from multiple categories, have the potential to significantly improve modelling framework of species distribution in freshwater ecosystems. The information produced by accurate, small scale, species distribution models can guide managers and conservation practitioners, by predicting the effects of management decisions within a catchment. We suggest that highly resolved predictors be applied in models using the catchment approach. (C) 2014 Elsevier B.V. All rights reserved