Which records are returned? | Use the app | Local installation | Adding new taxa | Adapt infinitylists for other countries | Why did I get disconnected from the server?

One surface, two consumers | Terms | The three calls | The solve path, and the eight kinds | Why the implicit function theorem | Why the kind is recorded, not inferred | Inside the surface | Extending it | What is tested | Deliberately not built

Simulated data, so the answer is known | The objective, and the loop that makes it affordable | Using the gradients | Faster or slower depends on which parameter count you mean | What reverses it is more fitted parameters per model parameter | Where the intercept goes | Fitting a different collection of parameters | Cost does not depend on the collection | A stem gradient means something different at a boundary | Not everything is reachable | What a new study actually has to write | Where a gradient-based fit goes wrong | Fitting to real data

What this model does differently | What is on this page | One solve | A drought response | The same sweep on a familiar scale | Light and VPD together | Traits and numerical settings are separate | Water potentials are positive magnitudes | Two supply paths, two routes | Multiple soil layers | The stateful interface | Trait gradients, and where they stop working | Choosing which gradients to compute | A collar potential you supply | A faster method: the closed form | When it applies, and when it refuses | What it costs, and what it buys | Accuracy, and one failure that is not a tolerance | The caveat that would stop you using this in a demographic model | What the model assumes | Where to go next

How to read this page | A leaf choosing where to operate | The problem being solved | The two supply paths | One problem, several coordinates | Solving for the optimum by its first-order condition | The scan, which does not run by default | When the answer is a bound, not a stationary point | The benefit, and the root-find inside it | The cost curves | The benefit link, and the proof it costs nothing | The wet-end price, and the one curve that has one | Pricing the drop is not pricing the potential | λ is the common currency | λ is not water use efficiency | λ is a common currency only across difference objectives | The two gates | Thermal damage | When the leaf cannot transpire | The variants, under one roof | Comparable at their defaults | The biological components | 1. Photosynthetic demand | 2. Temperature responses | 3. Diffusive supply | 4. Closing the loop: supply equals demand | 5. Hydraulic supply, and why the problem is non-trivial | 6. Optionally, energy balance and thermal damage | What the models disagree about | What the model assumes | Glossary | Where to go next | Appendix A — the (P50, c) parameterisation | Why not (P50, b) | Why c is not a constant | Converting from published numbers | psi_crit is a quantile, not a parameter | Three consequences for gradients | Appendix B — gradients | The implicit function theorem | The link makes one derivative serve every model | The envelope theorem, and where it stops | Prescribed versus optimised | A partial is not always a total | The energy-balance term | Appendix C — numerical practice | The maximum is flat, so its location is the delicate quantity | A finite difference through a solve has a noise floor, so sweep the step | A scan's argmax cannot feed a parameter gradient | References

The two umbrella headers, and why the extension matters | Building | A solve | Trait gradients from C++ | What is fast, and what is not | The golden file is the contract

1. Build a multiband image from single-band TIFs | 2. Choose areas of interest | 3. Calculate spectral metrics | 4. Compute on-the-ground taxonomic diversity | 5. Comparing the two

Generate a reference trajectory | Register the calibration target | Optimise | Check the recovered parameters

The core abstractions | Define the system | Solve the system | Plot the attractor | Controlling the solver | Choosing an integration method | Solving a system written in R | Where next

Installation | Retrieve taxonomic resources | Align and update plant taxon names | Plant established status across states/territories | Closer look at name standardisation with 'APCalign' | Aligning names to APC and APNI | Configuring matching precision and aligned output | Updating to APC-accepted names | Taxonomic resources used for updating names | Name updates at different taxonomic levels | Taxonomic splits | Generating lists of synonyms

One sample analyses | Testing for significance | Multiple sample analyses

An example community | Running the model | Rate of spread per stratum | Flame summaries per stratum | The result object | Building inputs yourself | Under the hood: the mechanistic primitives | Where this is going

Provenance: everything traces to original FRaME | The check | A concrete comparison | Beyond the golden references

References

Overview | Load dependencies | Priors | Simulate data | Visualise data | SUSTAIN trout data | Transform data | Visualise raw data | Fit model using | Inspect estimates | $R^2$ | Individual growth functions ($\beta$) | Population hyper-parameters | References

Load dependencies | The model | Simulating data | Implementing models and collecting posterior estimates | Step size data | Analysis | Second cluster analysis | Where to from here?

Getting started with | The Theory | The Maths | The Stats | Integration of time series | Demonstration: Canham Growth - Multiple Individuals

Load dependencies | Overview | Priors | Visualise model | Lizard size data | Implementation | References

Aligning taxon names with taxon concepts/names in APC and APNI | Updating taxonomy | Outputs of APCalign

Getting started

Installation | Overview | Notation | hmde supported growth functions | Workflow | References

Install and load austraits | Retrieve AusTraits database | Descriptive summaries of traits and taxa | Quickly look up data | Extracting data | Extracting by dataset | Extracting by taxonomy | Extracting by trait | Extracting from other tables | Extracting from a single table | Join data from other tables | Visualising data by site | Visualising data distribution and variance | Reshaping the traits table | Pivot wider | Binding trait values

Load dependencies | Configure galah | Submit data request | Pre-download check | Upload your own KML | Launch infinitylist and explore! | Open downloaded data

Goal of package | Installation | {bmsma} supported models | Linear model

Scope | Background | How datastorr works | The package interface | Worked example | Access control | Semantic versioning of data | Beyond GitHub | How it actually works